Table of Contents
Glue.Client¶A low-level client representing AWS Glue
Defines the public endpoint for the Glue service.
import boto3
client = boto3.client('glue')
These are the available methods:
batch_create_partition()batch_delete_connection()batch_delete_partition()batch_delete_table()batch_delete_table_version()batch_get_blueprints()batch_get_crawlers()batch_get_custom_entity_types()batch_get_data_quality_result()batch_get_dev_endpoints()batch_get_jobs()batch_get_partition()batch_get_triggers()batch_get_workflows()batch_stop_job_run()batch_update_partition()can_paginate()cancel_data_quality_rule_recommendation_run()cancel_data_quality_ruleset_evaluation_run()cancel_ml_task_run()cancel_statement()check_schema_version_validity()close()create_blueprint()create_classifier()create_connection()create_crawler()create_custom_entity_type()create_data_quality_ruleset()create_database()create_dev_endpoint()create_job()create_ml_transform()create_partition()create_partition_index()create_registry()create_schema()create_script()create_security_configuration()create_session()create_table()create_trigger()create_user_defined_function()create_workflow()delete_blueprint()delete_classifier()delete_column_statistics_for_partition()delete_column_statistics_for_table()delete_connection()delete_crawler()delete_custom_entity_type()delete_data_quality_ruleset()delete_database()delete_dev_endpoint()delete_job()delete_ml_transform()delete_partition()delete_partition_index()delete_registry()delete_resource_policy()delete_schema()delete_schema_versions()delete_security_configuration()delete_session()delete_table()delete_table_version()delete_trigger()delete_user_defined_function()delete_workflow()get_blueprint()get_blueprint_run()get_blueprint_runs()get_catalog_import_status()get_classifier()get_classifiers()get_column_statistics_for_partition()get_column_statistics_for_table()get_connection()get_connections()get_crawler()get_crawler_metrics()get_crawlers()get_custom_entity_type()get_data_catalog_encryption_settings()get_data_quality_result()get_data_quality_rule_recommendation_run()get_data_quality_ruleset()get_data_quality_ruleset_evaluation_run()get_database()get_databases()get_dataflow_graph()get_dev_endpoint()get_dev_endpoints()get_job()get_job_bookmark()get_job_run()get_job_runs()get_jobs()get_mapping()get_ml_task_run()get_ml_task_runs()get_ml_transform()get_ml_transforms()get_paginator()get_partition()get_partition_indexes()get_partitions()get_plan()get_registry()get_resource_policies()get_resource_policy()get_schema()get_schema_by_definition()get_schema_version()get_schema_versions_diff()get_security_configuration()get_security_configurations()get_session()get_statement()get_table()get_table_version()get_table_versions()get_tables()get_tags()get_trigger()get_triggers()get_unfiltered_partition_metadata()get_unfiltered_partitions_metadata()get_unfiltered_table_metadata()get_user_defined_function()get_user_defined_functions()get_waiter()get_workflow()get_workflow_run()get_workflow_run_properties()get_workflow_runs()import_catalog_to_glue()list_blueprints()list_crawlers()list_crawls()list_custom_entity_types()list_data_quality_results()list_data_quality_rule_recommendation_runs()list_data_quality_ruleset_evaluation_runs()list_data_quality_rulesets()list_dev_endpoints()list_jobs()list_ml_transforms()list_registries()list_schema_versions()list_schemas()list_sessions()list_statements()list_triggers()list_workflows()put_data_catalog_encryption_settings()put_resource_policy()put_schema_version_metadata()put_workflow_run_properties()query_schema_version_metadata()register_schema_version()remove_schema_version_metadata()reset_job_bookmark()resume_workflow_run()run_statement()search_tables()start_blueprint_run()start_crawler()start_crawler_schedule()start_data_quality_rule_recommendation_run()start_data_quality_ruleset_evaluation_run()start_export_labels_task_run()start_import_labels_task_run()start_job_run()start_ml_evaluation_task_run()start_ml_labeling_set_generation_task_run()start_trigger()start_workflow_run()stop_crawler()stop_crawler_schedule()stop_session()stop_trigger()stop_workflow_run()tag_resource()untag_resource()update_blueprint()update_classifier()update_column_statistics_for_partition()update_column_statistics_for_table()update_connection()update_crawler()update_crawler_schedule()update_data_quality_ruleset()update_database()update_dev_endpoint()update_job()update_job_from_source_control()update_ml_transform()update_partition()update_registry()update_schema()update_source_control_from_job()update_table()update_trigger()update_user_defined_function()update_workflow()batch_create_partition(**kwargs)¶Creates one or more partitions in a batch operation.
See also: AWS API Documentation
Request Syntax
response = client.batch_create_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionInputList=[
{
'Values': [
'string',
],
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1)
},
]
)
[REQUIRED]
The name of the metadata database in which the partition is to be created.
[REQUIRED]
The name of the metadata table in which the partition is to be created.
[REQUIRED]
A list of PartitionInput structures that define the partitions to be created.
The structure used to create and update a partition.
The values of the partition. Although this parameter is not required by the SDK, you must specify this parameter for a valid input.
The values for the keys for the new partition must be passed as an array of String objects that must be ordered in the same order as the partition keys appearing in the Amazon S3 prefix. Otherwise Glue will add the values to the wrong keys.
The last time at which the partition was accessed.
Provides information about the physical location where the partition is stored.
A list of the Columns in the table.
A column in a Table .
The name of the Column .
The data type of the Column .
A free-form text comment.
These key-value pairs define properties associated with the column.
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
A list of locations that point to the path where a Delta table is located.
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Trueif the data in the table is compressed, orFalseif not.
Must be specified if the table contains any dimension columns.
The serialization/deserialization (SerDe) information.
Name of the SerDe.
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
These key-value pairs define initialization parameters for the SerDe.
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
A list specifying the sort order of each bucket in the table.
Specifies the sort order of a sorted column.
The name of the column.
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
The user-supplied properties in key-value form.
The information about values that appear frequently in a column (skewed values).
A list of names of columns that contain skewed values.
A list of values that appear so frequently as to be considered skewed.
A mapping of skewed values to the columns that contain them.
Trueif the table data is stored in subdirectories, orFalseif not.
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
The version number of the schema.
These key-value pairs define partition parameters.
The last time at which column statistics were computed for this partition.
dict
Response Syntax
{
'Errors': [
{
'PartitionValues': [
'string',
],
'ErrorDetail': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
Errors (list) --
The errors encountered when trying to create the requested partitions.
(dict) --
Contains information about a partition error.
PartitionValues (list) --
The values that define the partition.
ErrorDetail (dict) --
The details about the partition error.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionbatch_delete_connection(**kwargs)¶Deletes a list of connection definitions from the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.batch_delete_connection(
CatalogId='string',
ConnectionNameList=[
'string',
]
)
[REQUIRED]
A list of names of the connections to delete.
dict
Response Syntax
{
'Succeeded': [
'string',
],
'Errors': {
'string': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
}
}
Response Structure
(dict) --
Succeeded (list) --
A list of names of the connection definitions that were successfully deleted.
Errors (dict) --
A map of the names of connections that were not successfully deleted to error details.
(string) --
(dict) --
Contains details about an error.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionbatch_delete_partition(**kwargs)¶Deletes one or more partitions in a batch operation.
See also: AWS API Documentation
Request Syntax
response = client.batch_delete_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionsToDelete=[
{
'Values': [
'string',
]
},
]
)
[REQUIRED]
The name of the catalog database in which the table in question resides.
[REQUIRED]
The name of the table that contains the partitions to be deleted.
[REQUIRED]
A list of PartitionInput structures that define the partitions to be deleted.
Contains a list of values defining partitions.
The list of values.
dict
Response Syntax
{
'Errors': [
{
'PartitionValues': [
'string',
],
'ErrorDetail': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
Errors (list) --
The errors encountered when trying to delete the requested partitions.
(dict) --
Contains information about a partition error.
PartitionValues (list) --
The values that define the partition.
ErrorDetail (dict) --
The details about the partition error.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionbatch_delete_table(**kwargs)¶Deletes multiple tables at once.
Note
After completing this operation, you no longer have access to the table versions and partitions that belong to the deleted table. Glue deletes these "orphaned" resources asynchronously in a timely manner, at the discretion of the service.
To ensure the immediate deletion of all related resources, before calling BatchDeleteTable , use DeleteTableVersion or BatchDeleteTableVersion , and DeletePartition or BatchDeletePartition , to delete any resources that belong to the table.
See also: AWS API Documentation
Request Syntax
response = client.batch_delete_table(
CatalogId='string',
DatabaseName='string',
TablesToDelete=[
'string',
],
TransactionId='string'
)
[REQUIRED]
The name of the catalog database in which the tables to delete reside. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
A list of the table to delete.
dict
Response Syntax
{
'Errors': [
{
'TableName': 'string',
'ErrorDetail': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
Errors (list) --
A list of errors encountered in attempting to delete the specified tables.
(dict) --
An error record for table operations.
TableName (string) --
The name of the table. For Hive compatibility, this must be entirely lowercase.
ErrorDetail (dict) --
The details about the error.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.ResourceNotReadyExceptionbatch_delete_table_version(**kwargs)¶Deletes a specified batch of versions of a table.
See also: AWS API Documentation
Request Syntax
response = client.batch_delete_table_version(
CatalogId='string',
DatabaseName='string',
TableName='string',
VersionIds=[
'string',
]
)
[REQUIRED]
The database in the catalog in which the table resides. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The name of the table. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
A list of the IDs of versions to be deleted. A VersionId is a string representation of an integer. Each version is incremented by 1.
dict
Response Syntax
{
'Errors': [
{
'TableName': 'string',
'VersionId': 'string',
'ErrorDetail': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
Errors (list) --
A list of errors encountered while trying to delete the specified table versions.
(dict) --
An error record for table-version operations.
TableName (string) --
The name of the table in question.
VersionId (string) --
The ID value of the version in question. A VersionID is a string representation of an integer. Each version is incremented by 1.
ErrorDetail (dict) --
The details about the error.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionbatch_get_blueprints(**kwargs)¶Retrieves information about a list of blueprints.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_blueprints(
Names=[
'string',
],
IncludeBlueprint=True|False,
IncludeParameterSpec=True|False
)
[REQUIRED]
A list of blueprint names.
dict
Response Syntax
{
'Blueprints': [
{
'Name': 'string',
'Description': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ParameterSpec': 'string',
'BlueprintLocation': 'string',
'BlueprintServiceLocation': 'string',
'Status': 'CREATING'|'ACTIVE'|'UPDATING'|'FAILED',
'ErrorMessage': 'string',
'LastActiveDefinition': {
'Description': 'string',
'LastModifiedOn': datetime(2015, 1, 1),
'ParameterSpec': 'string',
'BlueprintLocation': 'string',
'BlueprintServiceLocation': 'string'
}
},
],
'MissingBlueprints': [
'string',
]
}
Response Structure
(dict) --
Blueprints (list) --
Returns a list of blueprint as a Blueprints object.
(dict) --
The details of a blueprint.
Name (string) --
The name of the blueprint.
Description (string) --
The description of the blueprint.
CreatedOn (datetime) --
The date and time the blueprint was registered.
LastModifiedOn (datetime) --
The date and time the blueprint was last modified.
ParameterSpec (string) --
A JSON string that indicates the list of parameter specifications for the blueprint.
BlueprintLocation (string) --
Specifies the path in Amazon S3 where the blueprint is published.
BlueprintServiceLocation (string) --
Specifies a path in Amazon S3 where the blueprint is copied when you call CreateBlueprint/UpdateBlueprint to register the blueprint in Glue.
Status (string) --
The status of the blueprint registration.
ErrorMessage (string) --
An error message.
LastActiveDefinition (dict) --
When there are multiple versions of a blueprint and the latest version has some errors, this attribute indicates the last successful blueprint definition that is available with the service.
Description (string) --
The description of the blueprint.
LastModifiedOn (datetime) --
The date and time the blueprint was last modified.
ParameterSpec (string) --
A JSON string specifying the parameters for the blueprint.
BlueprintLocation (string) --
Specifies a path in Amazon S3 where the blueprint is published by the Glue developer.
BlueprintServiceLocation (string) --
Specifies a path in Amazon S3 where the blueprint is copied when you create or update the blueprint.
MissingBlueprints (list) --
Returns a list of BlueprintNames that were not found.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionbatch_get_crawlers(**kwargs)¶Returns a list of resource metadata for a given list of crawler names. After calling the ListCrawlers operation, you can call this operation to access the data to which you have been granted permissions. This operation supports all IAM permissions, including permission conditions that uses tags.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_crawlers(
CrawlerNames=[
'string',
]
)
[REQUIRED]
A list of crawler names, which might be the names returned from the ListCrawlers operation.
{
'Crawlers': [
{
'Name': 'string',
'Role': 'string',
'Targets': {
'S3Targets': [
{
'Path': 'string',
'Exclusions': [
'string',
],
'ConnectionName': 'string',
'SampleSize': 123,
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'JdbcTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'Exclusions': [
'string',
],
'EnableAdditionalMetadata': [
'COMMENTS'|'RAWTYPES',
]
},
],
'MongoDBTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'ScanAll': True|False
},
],
'DynamoDBTargets': [
{
'Path': 'string',
'scanAll': True|False,
'scanRate': 123.0
},
],
'CatalogTargets': [
{
'DatabaseName': 'string',
'Tables': [
'string',
],
'ConnectionName': 'string',
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'DeltaTargets': [
{
'DeltaTables': [
'string',
],
'ConnectionName': 'string',
'WriteManifest': True|False,
'CreateNativeDeltaTable': True|False
},
]
},
'DatabaseName': 'string',
'Description': 'string',
'Classifiers': [
'string',
],
'RecrawlPolicy': {
'RecrawlBehavior': 'CRAWL_EVERYTHING'|'CRAWL_NEW_FOLDERS_ONLY'|'CRAWL_EVENT_MODE'
},
'SchemaChangePolicy': {
'UpdateBehavior': 'LOG'|'UPDATE_IN_DATABASE',
'DeleteBehavior': 'LOG'|'DELETE_FROM_DATABASE'|'DEPRECATE_IN_DATABASE'
},
'LineageConfiguration': {
'CrawlerLineageSettings': 'ENABLE'|'DISABLE'
},
'State': 'READY'|'RUNNING'|'STOPPING',
'TablePrefix': 'string',
'Schedule': {
'ScheduleExpression': 'string',
'State': 'SCHEDULED'|'NOT_SCHEDULED'|'TRANSITIONING'
},
'CrawlElapsedTime': 123,
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'LastCrawl': {
'Status': 'SUCCEEDED'|'CANCELLED'|'FAILED',
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string',
'MessagePrefix': 'string',
'StartTime': datetime(2015, 1, 1)
},
'Version': 123,
'Configuration': 'string',
'CrawlerSecurityConfiguration': 'string',
'LakeFormationConfiguration': {
'UseLakeFormationCredentials': True|False,
'AccountId': 'string'
}
},
],
'CrawlersNotFound': [
'string',
]
}
Response Structure
A list of crawler definitions.
Specifies a crawler program that examines a data source and uses classifiers to try to determine its schema. If successful, the crawler records metadata concerning the data source in the Glue Data Catalog.
The name of the crawler.
The Amazon Resource Name (ARN) of an IAM role that's used to access customer resources, such as Amazon Simple Storage Service (Amazon S3) data.
A collection of targets to crawl.
Specifies Amazon Simple Storage Service (Amazon S3) targets.
Specifies a data store in Amazon Simple Storage Service (Amazon S3).
The path to the Amazon S3 target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
The name of a connection which allows a job or crawler to access data in Amazon S3 within an Amazon Virtual Private Cloud environment (Amazon VPC).
Sets the number of files in each leaf folder to be crawled when crawling sample files in a dataset. If not set, all the files are crawled. A valid value is an integer between 1 and 249.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies JDBC targets.
Specifies a JDBC data store to crawl.
The name of the connection to use to connect to the JDBC target.
The path of the JDBC target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
Specify a value of RAWTYPES or COMMENTS to enable additional metadata in table responses. RAWTYPES provides the native-level datatype. COMMENTS provides comments associated with a column or table in the database.
If you do not need additional metadata, keep the field empty.
Specifies Amazon DocumentDB or MongoDB targets.
Specifies an Amazon DocumentDB or MongoDB data store to crawl.
The name of the connection to use to connect to the Amazon DocumentDB or MongoDB target.
The path of the Amazon DocumentDB or MongoDB target (database/collection).
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
Specifies Amazon DynamoDB targets.
Specifies an Amazon DynamoDB table to crawl.
The name of the DynamoDB table to crawl.
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
The percentage of the configured read capacity units to use by the Glue crawler. Read capacity units is a term defined by DynamoDB, and is a numeric value that acts as rate limiter for the number of reads that can be performed on that table per second.
The valid values are null or a value between 0.1 to 1.5. A null value is used when user does not provide a value, and defaults to 0.5 of the configured Read Capacity Unit (for provisioned tables), or 0.25 of the max configured Read Capacity Unit (for tables using on-demand mode).
Specifies Glue Data Catalog targets.
Specifies an Glue Data Catalog target.
The name of the database to be synchronized.
A list of the tables to be synchronized.
The name of the connection for an Amazon S3-backed Data Catalog table to be a target of the crawl when using a Catalog connection type paired with a NETWORK Connection type.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies Delta data store targets.
Specifies a Delta data store to crawl one or more Delta tables.
A list of the Amazon S3 paths to the Delta tables.
The name of the connection to use to connect to the Delta table target.
Specifies whether to write the manifest files to the Delta table path.
Specifies whether the crawler will create native tables, to allow integration with query engines that support querying of the Delta transaction log directly.
The name of the database in which the crawler's output is stored.
A description of the crawler.
A list of UTF-8 strings that specify the custom classifiers that are associated with the crawler.
A policy that specifies whether to crawl the entire dataset again, or to crawl only folders that were added since the last crawler run.
Specifies whether to crawl the entire dataset again or to crawl only folders that were added since the last crawler run.
A value of CRAWL_EVERYTHING specifies crawling the entire dataset again.
A value of CRAWL_NEW_FOLDERS_ONLY specifies crawling only folders that were added since the last crawler run.
A value of CRAWL_EVENT_MODE specifies crawling only the changes identified by Amazon S3 events.
The policy that specifies update and delete behaviors for the crawler.
The update behavior when the crawler finds a changed schema.
The deletion behavior when the crawler finds a deleted object.
A configuration that specifies whether data lineage is enabled for the crawler.
Specifies whether data lineage is enabled for the crawler. Valid values are:
Indicates whether the crawler is running, or whether a run is pending.
The prefix added to the names of tables that are created.
For scheduled crawlers, the schedule when the crawler runs.
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
The state of the schedule.
If the crawler is running, contains the total time elapsed since the last crawl began.
The time that the crawler was created.
The time that the crawler was last updated.
The status of the last crawl, and potentially error information if an error occurred.
Status of the last crawl.
If an error occurred, the error information about the last crawl.
The log group for the last crawl.
The log stream for the last crawl.
The prefix for a message about this crawl.
The time at which the crawl started.
The version of the crawler.
Crawler configuration information. This versioned JSON string allows users to specify aspects of a crawler's behavior. For more information, see Setting crawler configuration options.
The name of the SecurityConfiguration structure to be used by this crawler.
Specifies whether the crawler should use Lake Formation credentials for the crawler instead of the IAM role credentials.
Specifies whether to use Lake Formation credentials for the crawler instead of the IAM role credentials.
Required for cross account crawls. For same account crawls as the target data, this can be left as null.
A list of names of crawlers that were not found.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionbatch_get_custom_entity_types(**kwargs)¶Retrieves the details for the custom patterns specified by a list of names.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_custom_entity_types(
Names=[
'string',
]
)
[REQUIRED]
A list of names of the custom patterns that you want to retrieve.
{
'CustomEntityTypes': [
{
'Name': 'string',
'RegexString': 'string',
'ContextWords': [
'string',
]
},
],
'CustomEntityTypesNotFound': [
'string',
]
}
Response Structure
A list of CustomEntityType objects representing the custom patterns that have been created.
An object representing a custom pattern for detecting sensitive data across the columns and rows of your structured data.
A name for the custom pattern that allows it to be retrieved or deleted later. This name must be unique per Amazon Web Services account.
A regular expression string that is used for detecting sensitive data in a custom pattern.
A list of context words. If none of these context words are found within the vicinity of the regular expression the data will not be detected as sensitive data.
If no context words are passed only a regular expression is checked.
A list of the names of custom patterns that were not found.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionbatch_get_data_quality_result(**kwargs)¶Retrieves a list of data quality results for the specified result IDs.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_data_quality_result(
ResultIds=[
'string',
]
)
[REQUIRED]
A list of unique result IDs for the data quality results.
{
'Results': [
{
'ResultId': 'string',
'Score': 123.0,
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'RulesetName': 'string',
'EvaluationContext': 'string',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobName': 'string',
'JobRunId': 'string',
'RulesetEvaluationRunId': 'string',
'RuleResults': [
{
'Name': 'string',
'Description': 'string',
'EvaluationMessage': 'string',
'Result': 'PASS'|'FAIL'|'ERROR'
},
]
},
],
'ResultsNotFound': [
'string',
]
}
Response Structure
A list of DataQualityResult objects representing the data quality results.
Describes a data quality result.
A unique result ID for the data quality result.
An aggregate data quality score. Represents the ratio of rules that passed to the total number of rules.
The table associated with the data quality result, if any.
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.The name of the ruleset associated with the data quality result.
In the context of a job in Glue Studio, each node in the canvas is typically assigned some sort of name and data quality nodes will have names. In the case of multiple nodes, the evaluationContext can differentiate the nodes.
The date and time when this data quality run started.
The date and time when this data quality run completed.
The job name associated with the data quality result, if any.
The job run ID associated with the data quality result, if any.
The unique run ID for the ruleset evaluation for this data quality result.
A list of DataQualityRuleResult objects representing the results for each rule.
Describes the result of the evaluation of a data quality rule.
The name of the data quality rule.
A description of the data quality rule.
An evaluation message.
A pass or fail status for the rule.
A list of result IDs for which results were not found.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionbatch_get_dev_endpoints(**kwargs)¶Returns a list of resource metadata for a given list of development endpoint names. After calling the ListDevEndpoints operation, you can call this operation to access the data to which you have been granted permissions. This operation supports all IAM permissions, including permission conditions that uses tags.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_dev_endpoints(
DevEndpointNames=[
'string',
]
)
[REQUIRED]
The list of DevEndpoint names, which might be the names returned from the ListDevEndpoint operation.
{
'DevEndpoints': [
{
'EndpointName': 'string',
'RoleArn': 'string',
'SecurityGroupIds': [
'string',
],
'SubnetId': 'string',
'YarnEndpointAddress': 'string',
'PrivateAddress': 'string',
'ZeppelinRemoteSparkInterpreterPort': 123,
'PublicAddress': 'string',
'Status': 'string',
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'GlueVersion': 'string',
'NumberOfWorkers': 123,
'NumberOfNodes': 123,
'AvailabilityZone': 'string',
'VpcId': 'string',
'ExtraPythonLibsS3Path': 'string',
'ExtraJarsS3Path': 'string',
'FailureReason': 'string',
'LastUpdateStatus': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'LastModifiedTimestamp': datetime(2015, 1, 1),
'PublicKey': 'string',
'PublicKeys': [
'string',
],
'SecurityConfiguration': 'string',
'Arguments': {
'string': 'string'
}
},
],
'DevEndpointsNotFound': [
'string',
]
}
Response Structure
A list of DevEndpoint definitions.
A development endpoint where a developer can remotely debug extract, transform, and load (ETL) scripts.
The name of the DevEndpoint .
The Amazon Resource Name (ARN) of the IAM role used in this DevEndpoint .
A list of security group identifiers used in this DevEndpoint .
The subnet ID for this DevEndpoint .
The YARN endpoint address used by this DevEndpoint .
A private IP address to access the DevEndpoint within a VPC if the DevEndpoint is created within one. The PrivateAddress field is present only when you create the DevEndpoint within your VPC.
The Apache Zeppelin port for the remote Apache Spark interpreter.
The public IP address used by this DevEndpoint . The PublicAddress field is present only when you create a non-virtual private cloud (VPC) DevEndpoint .
The current status of this DevEndpoint .
The type of predefined worker that is allocated to the development endpoint. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.Known issue: when a development endpoint is created with the G.2X WorkerType configuration, the Spark drivers for the development endpoint will run on 4 vCPU, 16 GB of memory, and a 64 GB disk.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for running your ETL scripts on development endpoints.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Development endpoints that are created without specifying a Glue version default to Glue 0.9.
You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
The number of workers of a defined workerType that are allocated to the development endpoint.
The maximum number of workers you can define are 299 for G.1X , and 149 for G.2X .
The number of Glue Data Processing Units (DPUs) allocated to this DevEndpoint .
The Amazon Web Services Availability Zone where this DevEndpoint is located.
The ID of the virtual private cloud (VPC) used by this DevEndpoint .
The paths to one or more Python libraries in an Amazon S3 bucket that should be loaded in your DevEndpoint . Multiple values must be complete paths separated by a comma.
Note
You can only use pure Python libraries with a DevEndpoint . Libraries that rely on C extensions, such as the pandas Python data analysis library, are not currently supported.
The path to one or more Java .jar files in an S3 bucket that should be loaded in your DevEndpoint .
Note
You can only use pure Java/Scala libraries with a DevEndpoint .
The reason for a current failure in this DevEndpoint .
The status of the last update.
The point in time at which this DevEndpoint was created.
The point in time at which this DevEndpoint was last modified.
The public key to be used by this DevEndpoint for authentication. This attribute is provided for backward compatibility because the recommended attribute to use is public keys.
A list of public keys to be used by the DevEndpoints for authentication. Using this attribute is preferred over a single public key because the public keys allow you to have a different private key per client.
Note
If you previously created an endpoint with a public key, you must remove that key to be able to set a list of public keys. Call the UpdateDevEndpoint API operation with the public key content in the deletePublicKeys attribute, and the list of new keys in the addPublicKeys attribute.
The name of the SecurityConfiguration structure to be used with this DevEndpoint .
A map of arguments used to configure the DevEndpoint .
Valid arguments are:
"--enable-glue-datacatalog": ""You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
A list of DevEndpoints not found.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionbatch_get_jobs(**kwargs)¶Returns a list of resource metadata for a given list of job names. After calling the ListJobs operation, you can call this operation to access the data to which you have been granted permissions. This operation supports all IAM permissions, including permission conditions that uses tags.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_jobs(
JobNames=[
'string',
]
)
[REQUIRED]
A list of job names, which might be the names returned from the ListJobs operation.
{
'Jobs': [
{
'Name': 'string',
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
},
],
'JobsNotFound': [
'string',
]
}
Response Structure
A list of job definitions.
Specifies a job definition.
The name you assign to this job definition.
A description of the job.
This field is reserved for future use.
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
The time and date that this job definition was created.
The last point in time when this job definition was modified.
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
The JobCommand that runs this job.
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
The default arguments for this job, specified as name-value pairs.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Non-overridable arguments for this job, specified as name-value pairs.
The connections used for this job.
A list of connections used by the job.
The maximum number of times to retry this job after a JobRun fails.
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to runs of this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.The number of workers of a defined workerType that are allocated when a job runs.
The name of the SecurityConfiguration structure to be used with this job.
Specifies configuration properties of a job notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
CodeGenConfigurationNodeenumerates all valid Node types. One and only one of its member variables can be populated.
Specifies a connector to an Amazon Athena data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
The name of the table in the data source.
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
Specifies the data schema for the custom Athena source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to a JDBC data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
Additional connection options for the connector.
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
The minimum value of partitionColumn that is used to decide partition stride.
The maximum value of partitionColumn that is used to decide partition stride.
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
The name of the job bookmark keys on which to sort.
Specifies an ascending or descending sort order.
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
The name of the table in the data source.
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
Specifies the data schema for the custom JDBC source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to an Apache Spark data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies data schema for the custom spark source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a data store in the Glue Data Catalog.
The name of the data store.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Amazon Redshift data store.
The name of the Amazon Redshift data store.
The database to read from.
The database table to read from.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
Specifies an Amazon S3 data store in the Glue Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a command-separated value (CSV) data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
A Boolean value that specifies whether to write the header to output. The default value is True .
A Boolean value that specifies whether to skip the first data line. The default value is False .
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
Specifies the data schema for the S3 CSV source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a JSON data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
A JsonPath string defining the JSON data.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
Specifies the data schema for the S3 JSON source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies an Apache Parquet data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the data schema for the S3 Parquet source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a Relational database data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a DynamoDB data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
The name of the connection that is associated with the connector.
The name of the table in the data target.
The name of a connector that will be used.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
Additional connection options for the connector.
Specifies the data schema for the JDBC target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses an Apache Spark connector.
The name of the data target.
The nodes that are inputs to the data target.
The name of a connection for an Apache Spark connector.
The name of an Apache Spark connector.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies the data schema for the custom spark target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses a Glue Data Catalog table.
The name of your data target.
The nodes that are inputs to the data target.
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
Specifies a target that uses Amazon Redshift.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
The set of options to configure an upsert operation when writing to a Redshift target.
The physical location of the Redshift table.
The name of the connection to use to write to Redshift.
The keys used to determine whether to perform an update or insert.
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a data target that writes to Amazon S3.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Specifies the data output format for the target.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
The name of the transform node.
The data inputs identified by their node names.
Specifies the mapping of data property keys in the data source to data property keys in the data target.
Specifies the mapping of data property keys.
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
The table or column to be modified.
The type of the data to be modified.
The data type that the data is to be modified to.
If true, then the column is removed.
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
Specifies a transform that chooses the data property keys that you want to keep.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses the data property keys that you want to drop.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that renames a single data property key.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the source data.
A JSON path to a variable in the data structure for the target data.
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
The name of the transform node.
The data inputs identified by their node names.
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Specifies a number of records to write starting from the beginning of the dataset.
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
The name of the transform node.
The data inputs identified by their node names.
Specifies the type of join to be performed on the datasets.
A list of the two columns to be joined.
Specifies a column to be joined.
The column to be joined.
The key of the column to be joined.
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
The name of the transform node.
The data inputs identified by their node names.
The index for the DynamicFrame to be selected.
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the dataset that is imputed.
A JSON path to a variable in the data structure for the dataset that is filled.
Specifies a transform that splits a dataset into two, based on a filter condition.
The name of the transform node.
The data inputs identified by their node names.
The operator used to filter rows by comparing the key value to a specified value.
Specifies a filter expression.
Specifies a filter expression.
The type of operation to perform in the expression.
Whether the expression is to be negated.
A list of filter values.
Represents a single entry in the list of values for a FilterExpression .
The type of filter value.
The value to be associated.
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
The name of the transform node.
The data inputs identified by their node names.
The custom code that is used to perform the data transformation.
The name defined for the custom code node class.
Specifies the data schema for the custom code transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
The name of the transform node.
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
A SQL query that must use Spark SQL syntax and return a single data set.
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
Represents a single entry in the list of values for SqlAliases .
A table, or a column in a table.
A temporary name given to a table, or a column in a table.
Specifies the data schema for the SparkSQL transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a direct Amazon Kinesis data source.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store.
The name of the data store.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a Kinesis data source in the Glue Data Catalog.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store in the Data Catalog.
The name of the data store.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
The name of the transform node.
The data inputs identified by their node names.
A structure that represents whether certain values are recognized as null values for removal.
Specifies that an empty string is considered as a null value.
Specifies that a value spelling out the word 'null' is considered as a null value.
Specifies that an integer value of -1 is considered as a null value.
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
The value of the null placeholder.
The datatype of the value.
The datatype of the value.
A label assigned to the datatype.
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
The name of the transform node.
The data inputs identified by their node names.
The source DynamicFrame that will be merged with a staging DynamicFrame .
The list of primary key fields to match records from the source and staging dynamic frames.
Specifies a transform that combines the rows from two or more datasets into a single result.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
Specifies a transform that identifies, removes or masks PII data.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of PIIDetection transform.
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
Indicates the output column name that will contain any entity type detected in that row.
Indicates the fraction of the data to sample when scanning for PII entities.
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
Indicates the value that will replace the detected entity.
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
The name of the transform node.
Specifies the fields and rows to use as inputs for the aggregate transform.
Specifies the fields to group by.
Specifies the aggregate functions to be performed on specified fields.
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Specifies the column on the data set on which the aggregation function will be applied.
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
Specifies a transform that removes rows of repeating data from a data set.
The name of the transform node.
The data inputs identified by their node names.
The name of the columns to be merged or removed if repeating.
Specifies a data target that writes to a goverened catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the governed catalog.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data source in a goverened Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a MySQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Oracle data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a PostgresSQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a target that uses Microsoft SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses MySQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Oracle SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Postgres SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a custom visual transform created by a user.
Specifies the name of the dynamic transform.
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Specifies the inputs for the dynamic transform that are required.
Specifies the parameters of the dynamic transform.
Specifies the parameters in the config file of the dynamic transform.
Specifies the name of the parameter in the config file of the dynamic transform.
Specifies the parameter type in the config file of the dynamic transform.
Specifies the validation rule in the config file of the dynamic transform.
Specifies the validation message in the config file of the dynamic transform.
Specifies the value of the parameter in the config file of the dynamic transform.
Specifies the list type of the parameter in the config file of the dynamic transform.
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
Specifies the name of the function of the dynamic transform.
Specifies the path of the dynamic transform source and config files.
This field is not used and will be deprecated in future release.
Specifies your data quality evaluation criteria.
The name of the data quality evaluation.
The inputs of your data quality evaluation.
The ruleset for your data quality evaluation.
The output of your data quality evaluation.
Options to configure how your results are published.
The context of the evaluation.
The Amazon S3 prefix prepended to the results.
Enable metrics for your data quality results.
Enable publishing for your data quality results.
Options to configure how your job will stop if your data quality evaluation fails.
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
Indicates whether the job is run with a standard or flexible execution class. The standard execution class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
The provider for the remote repository.
The name of the remote repository that contains the job artifacts.
The owner of the remote repository that contains the job artifacts.
An optional branch in the remote repository.
An optional folder in the remote repository.
The last commit ID for a commit in the remote repository.
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
The value of an authorization token.
A list of names of jobs not found.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionbatch_get_partition(**kwargs)¶Retrieves partitions in a batch request.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionsToGet=[
{
'Values': [
'string',
]
},
]
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
[REQUIRED]
A list of partition values identifying the partitions to retrieve.
Contains a list of values defining partitions.
The list of values.
dict
Response Syntax
{
'Partitions': [
{
'Values': [
'string',
],
'DatabaseName': 'string',
'TableName': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1),
'CatalogId': 'string'
},
],
'UnprocessedKeys': [
{
'Values': [
'string',
]
},
]
}
Response Structure
(dict) --
Partitions (list) --
A list of the requested partitions.
(dict) --
Represents a slice of table data.
Values (list) --
The values of the partition.
DatabaseName (string) --
The name of the catalog database in which to create the partition.
TableName (string) --
The name of the database table in which to create the partition.
CreationTime (datetime) --
The time at which the partition was created.
LastAccessTime (datetime) --
The last time at which the partition was accessed.
StorageDescriptor (dict) --
Provides information about the physical location where the partition is stored.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
Parameters (dict) --
These key-value pairs define partition parameters.
LastAnalyzedTime (datetime) --
The last time at which column statistics were computed for this partition.
CatalogId (string) --
The ID of the Data Catalog in which the partition resides.
UnprocessedKeys (list) --
A list of the partition values in the request for which partitions were not returned.
(dict) --
Contains a list of values defining partitions.
Values (list) --
The list of values.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.InvalidStateExceptionbatch_get_triggers(**kwargs)¶Returns a list of resource metadata for a given list of trigger names. After calling the ListTriggers operation, you can call this operation to access the data to which you have been granted permissions. This operation supports all IAM permissions, including permission conditions that uses tags.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_triggers(
TriggerNames=[
'string',
]
)
[REQUIRED]
A list of trigger names, which may be the names returned from the ListTriggers operation.
{
'Triggers': [
{
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
},
],
'TriggersNotFound': [
'string',
]
}
Response Structure
A list of trigger definitions.
Information about a specific trigger.
The name of the trigger.
The name of the workflow associated with the trigger.
Reserved for future use.
The type of trigger that this is.
The current state of the trigger.
A description of this trigger.
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
The actions initiated by this trigger.
Defines an action to be initiated by a trigger.
The name of a job to be run.
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
The name of the SecurityConfiguration structure to be used with this action.
Specifies configuration properties of a job run notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
The name of the crawler to be used with this action.
The predicate of this trigger, which defines when it will fire.
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
A list of the conditions that determine when the trigger will fire.
Defines a condition under which a trigger fires.
A logical operator.
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
The name of the crawler to which this condition applies.
The state of the crawler to which this condition applies.
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
A list of names of triggers not found.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionbatch_get_workflows(**kwargs)¶Returns a list of resource metadata for a given list of workflow names. After calling the ListWorkflows operation, you can call this operation to access the data to which you have been granted permissions. This operation supports all IAM permissions, including permission conditions that uses tags.
See also: AWS API Documentation
Request Syntax
response = client.batch_get_workflows(
Names=[
'string',
],
IncludeGraph=True|False
)
[REQUIRED]
A list of workflow names, which may be the names returned from the ListWorkflows operation.
dict
Response Syntax
{
'Workflows': [
{
'Name': 'string',
'Description': 'string',
'DefaultRunProperties': {
'string': 'string'
},
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'LastRun': {
'Name': 'string',
'WorkflowRunId': 'string',
'PreviousRunId': 'string',
'WorkflowRunProperties': {
'string': 'string'
},
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'Status': 'RUNNING'|'COMPLETED'|'STOPPING'|'STOPPED'|'ERROR',
'ErrorMessage': 'string',
'Statistics': {
'TotalActions': 123,
'TimeoutActions': 123,
'FailedActions': 123,
'StoppedActions': 123,
'SucceededActions': 123,
'RunningActions': 123,
'ErroredActions': 123,
'WaitingActions': 123
},
'Graph': {
'Nodes': [
{
'Type': 'CRAWLER'|'JOB'|'TRIGGER',
'Name': 'string',
'UniqueId': 'string',
'TriggerDetails': {
'Trigger': {
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
},
'JobDetails': {
'JobRuns': [
{
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
},
]
},
'CrawlerDetails': {
'Crawls': [
{
'State': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string'
},
]
}
},
],
'Edges': [
{
'SourceId': 'string',
'DestinationId': 'string'
},
]
},
'StartingEventBatchCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
},
'Graph': {
'Nodes': [
{
'Type': 'CRAWLER'|'JOB'|'TRIGGER',
'Name': 'string',
'UniqueId': 'string',
'TriggerDetails': {
'Trigger': {
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
},
'JobDetails': {
'JobRuns': [
{
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
},
]
},
'CrawlerDetails': {
'Crawls': [
{
'State': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string'
},
]
}
},
],
'Edges': [
{
'SourceId': 'string',
'DestinationId': 'string'
},
]
},
'MaxConcurrentRuns': 123,
'BlueprintDetails': {
'BlueprintName': 'string',
'RunId': 'string'
}
},
],
'MissingWorkflows': [
'string',
]
}
Response Structure
(dict) --
Workflows (list) --
A list of workflow resource metadata.
(dict) --
A workflow is a collection of multiple dependent Glue jobs and crawlers that are run to complete a complex ETL task. A workflow manages the execution and monitoring of all its jobs and crawlers.
Name (string) --
The name of the workflow.
Description (string) --
A description of the workflow.
DefaultRunProperties (dict) --
A collection of properties to be used as part of each execution of the workflow. The run properties are made available to each job in the workflow. A job can modify the properties for the next jobs in the flow.
CreatedOn (datetime) --
The date and time when the workflow was created.
LastModifiedOn (datetime) --
The date and time when the workflow was last modified.
LastRun (dict) --
The information about the last execution of the workflow.
Name (string) --
Name of the workflow that was run.
WorkflowRunId (string) --
The ID of this workflow run.
PreviousRunId (string) --
The ID of the previous workflow run.
WorkflowRunProperties (dict) --
The workflow run properties which were set during the run.
StartedOn (datetime) --
The date and time when the workflow run was started.
CompletedOn (datetime) --
The date and time when the workflow run completed.
Status (string) --
The status of the workflow run.
ErrorMessage (string) --
This error message describes any error that may have occurred in starting the workflow run. Currently the only error message is "Concurrent runs exceeded for workflow: foo ."
Statistics (dict) --
The statistics of the run.
TotalActions (integer) --
Total number of Actions in the workflow run.
TimeoutActions (integer) --
Total number of Actions that timed out.
FailedActions (integer) --
Total number of Actions that have failed.
StoppedActions (integer) --
Total number of Actions that have stopped.
SucceededActions (integer) --
Total number of Actions that have succeeded.
RunningActions (integer) --
Total number Actions in running state.
ErroredActions (integer) --
Indicates the count of job runs in the ERROR state in the workflow run.
WaitingActions (integer) --
Indicates the count of job runs in WAITING state in the workflow run.
Graph (dict) --
The graph representing all the Glue components that belong to the workflow as nodes and directed connections between them as edges.
Nodes (list) --
A list of the the Glue components belong to the workflow represented as nodes.
(dict) --
A node represents an Glue component (trigger, crawler, or job) on a workflow graph.
Type (string) --
The type of Glue component represented by the node.
Name (string) --
The name of the Glue component represented by the node.
UniqueId (string) --
The unique Id assigned to the node within the workflow.
TriggerDetails (dict) --
Details of the Trigger when the node represents a Trigger.
Trigger (dict) --
The information of the trigger represented by the trigger node.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
JobDetails (dict) --
Details of the Job when the node represents a Job.
JobRuns (list) --
The information for the job runs represented by the job node.
(dict) --
Contains information about a job run.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
CrawlerDetails (dict) --
Details of the crawler when the node represents a crawler.
Crawls (list) --
A list of crawls represented by the crawl node.
(dict) --
The details of a crawl in the workflow.
State (string) --
The state of the crawler.
StartedOn (datetime) --
The date and time on which the crawl started.
CompletedOn (datetime) --
The date and time on which the crawl completed.
ErrorMessage (string) --
The error message associated with the crawl.
LogGroup (string) --
The log group associated with the crawl.
LogStream (string) --
The log stream associated with the crawl.
Edges (list) --
A list of all the directed connections between the nodes belonging to the workflow.
(dict) --
An edge represents a directed connection between two Glue components that are part of the workflow the edge belongs to.
SourceId (string) --
The unique of the node within the workflow where the edge starts.
DestinationId (string) --
The unique of the node within the workflow where the edge ends.
StartingEventBatchCondition (dict) --
The batch condition that started the workflow run.
BatchSize (integer) --
Number of events in the batch.
BatchWindow (integer) --
Duration of the batch window in seconds.
Graph (dict) --
The graph representing all the Glue components that belong to the workflow as nodes and directed connections between them as edges.
Nodes (list) --
A list of the the Glue components belong to the workflow represented as nodes.
(dict) --
A node represents an Glue component (trigger, crawler, or job) on a workflow graph.
Type (string) --
The type of Glue component represented by the node.
Name (string) --
The name of the Glue component represented by the node.
UniqueId (string) --
The unique Id assigned to the node within the workflow.
TriggerDetails (dict) --
Details of the Trigger when the node represents a Trigger.
Trigger (dict) --
The information of the trigger represented by the trigger node.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
JobDetails (dict) --
Details of the Job when the node represents a Job.
JobRuns (list) --
The information for the job runs represented by the job node.
(dict) --
Contains information about a job run.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
CrawlerDetails (dict) --
Details of the crawler when the node represents a crawler.
Crawls (list) --
A list of crawls represented by the crawl node.
(dict) --
The details of a crawl in the workflow.
State (string) --
The state of the crawler.
StartedOn (datetime) --
The date and time on which the crawl started.
CompletedOn (datetime) --
The date and time on which the crawl completed.
ErrorMessage (string) --
The error message associated with the crawl.
LogGroup (string) --
The log group associated with the crawl.
LogStream (string) --
The log stream associated with the crawl.
Edges (list) --
A list of all the directed connections between the nodes belonging to the workflow.
(dict) --
An edge represents a directed connection between two Glue components that are part of the workflow the edge belongs to.
SourceId (string) --
The unique of the node within the workflow where the edge starts.
DestinationId (string) --
The unique of the node within the workflow where the edge ends.
MaxConcurrentRuns (integer) --
You can use this parameter to prevent unwanted multiple updates to data, to control costs, or in some cases, to prevent exceeding the maximum number of concurrent runs of any of the component jobs. If you leave this parameter blank, there is no limit to the number of concurrent workflow runs.
BlueprintDetails (dict) --
This structure indicates the details of the blueprint that this particular workflow is created from.
BlueprintName (string) --
The name of the blueprint.
RunId (string) --
The run ID for this blueprint.
MissingWorkflows (list) --
A list of names of workflows not found.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionbatch_stop_job_run(**kwargs)¶Stops one or more job runs for a specified job definition.
See also: AWS API Documentation
Request Syntax
response = client.batch_stop_job_run(
JobName='string',
JobRunIds=[
'string',
]
)
[REQUIRED]
The name of the job definition for which to stop job runs.
[REQUIRED]
A list of the JobRunIds that should be stopped for that job definition.
dict
Response Syntax
{
'SuccessfulSubmissions': [
{
'JobName': 'string',
'JobRunId': 'string'
},
],
'Errors': [
{
'JobName': 'string',
'JobRunId': 'string',
'ErrorDetail': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
SuccessfulSubmissions (list) --
A list of the JobRuns that were successfully submitted for stopping.
(dict) --
Records a successful request to stop a specified JobRun .
JobName (string) --
The name of the job definition used in the job run that was stopped.
JobRunId (string) --
The JobRunId of the job run that was stopped.
Errors (list) --
A list of the errors that were encountered in trying to stop JobRuns , including the JobRunId for which each error was encountered and details about the error.
(dict) --
Records an error that occurred when attempting to stop a specified job run.
JobName (string) --
The name of the job definition that is used in the job run in question.
JobRunId (string) --
The JobRunId of the job run in question.
ErrorDetail (dict) --
Specifies details about the error that was encountered.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionbatch_update_partition(**kwargs)¶Updates one or more partitions in a batch operation.
See also: AWS API Documentation
Request Syntax
response = client.batch_update_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
Entries=[
{
'PartitionValueList': [
'string',
],
'PartitionInput': {
'Values': [
'string',
],
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1)
}
},
]
)
[REQUIRED]
The name of the metadata database in which the partition is to be updated.
[REQUIRED]
The name of the metadata table in which the partition is to be updated.
[REQUIRED]
A list of up to 100 BatchUpdatePartitionRequestEntry objects to update.
A structure that contains the values and structure used to update a partition.
A list of values defining the partitions.
The structure used to update a partition.
The values of the partition. Although this parameter is not required by the SDK, you must specify this parameter for a valid input.
The values for the keys for the new partition must be passed as an array of String objects that must be ordered in the same order as the partition keys appearing in the Amazon S3 prefix. Otherwise Glue will add the values to the wrong keys.
The last time at which the partition was accessed.
Provides information about the physical location where the partition is stored.
A list of the Columns in the table.
A column in a Table .
The name of the Column .
The data type of the Column .
A free-form text comment.
These key-value pairs define properties associated with the column.
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
A list of locations that point to the path where a Delta table is located.
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Trueif the data in the table is compressed, orFalseif not.
Must be specified if the table contains any dimension columns.
The serialization/deserialization (SerDe) information.
Name of the SerDe.
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
These key-value pairs define initialization parameters for the SerDe.
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
A list specifying the sort order of each bucket in the table.
Specifies the sort order of a sorted column.
The name of the column.
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
The user-supplied properties in key-value form.
The information about values that appear frequently in a column (skewed values).
A list of names of columns that contain skewed values.
A list of values that appear so frequently as to be considered skewed.
A mapping of skewed values to the columns that contain them.
Trueif the table data is stored in subdirectories, orFalseif not.
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
The version number of the schema.
These key-value pairs define partition parameters.
The last time at which column statistics were computed for this partition.
dict
Response Syntax
{
'Errors': [
{
'PartitionValueList': [
'string',
],
'ErrorDetail': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
Errors (list) --
The errors encountered when trying to update the requested partitions. A list of BatchUpdatePartitionFailureEntry objects.
(dict) --
Contains information about a batch update partition error.
PartitionValueList (list) --
A list of values defining the partitions.
ErrorDetail (dict) --
The details about the batch update partition error.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.GlueEncryptionExceptioncan_paginate(operation_name)¶Check if an operation can be paginated.
create_foo, and you'd normally invoke the
operation as client.create_foo(**kwargs), if the
create_foo operation can be paginated, you can use the
call client.get_paginator("create_foo").True if the operation can be paginated,
False otherwise.cancel_data_quality_rule_recommendation_run(**kwargs)¶Cancels the specified recommendation run that was being used to generate rules.
See also: AWS API Documentation
Request Syntax
response = client.cancel_data_quality_rule_recommendation_run(
RunId='string'
)
[REQUIRED]
The unique run identifier associated with this run.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptioncancel_data_quality_ruleset_evaluation_run(**kwargs)¶Cancels a run where a ruleset is being evaluated against a data source.
See also: AWS API Documentation
Request Syntax
response = client.cancel_data_quality_ruleset_evaluation_run(
RunId='string'
)
[REQUIRED]
The unique run identifier associated with this run.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptioncancel_ml_task_run(**kwargs)¶Cancels (stops) a task run. Machine learning task runs are asynchronous tasks that Glue runs on your behalf as part of various machine learning workflows. You can cancel a machine learning task run at any time by calling CancelMLTaskRun with a task run's parent transform's TransformID and the task run's TaskRunId .
See also: AWS API Documentation
Request Syntax
response = client.cancel_ml_task_run(
TransformId='string',
TaskRunId='string'
)
[REQUIRED]
The unique identifier of the machine learning transform.
[REQUIRED]
A unique identifier for the task run.
dict
Response Syntax
{
'TransformId': 'string',
'TaskRunId': 'string',
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'
}
Response Structure
(dict) --
TransformId (string) --
The unique identifier of the machine learning transform.
TaskRunId (string) --
The unique identifier for the task run.
Status (string) --
The status for this run.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptioncancel_statement(**kwargs)¶Cancels the statement.
See also: AWS API Documentation
Request Syntax
response = client.cancel_statement(
SessionId='string',
Id=123,
RequestOrigin='string'
)
[REQUIRED]
The Session ID of the statement to be cancelled.
[REQUIRED]
The ID of the statement to be cancelled.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.IllegalSessionStateExceptioncheck_schema_version_validity(**kwargs)¶Validates the supplied schema. This call has no side effects, it simply validates using the supplied schema using DataFormat as the format. Since it does not take a schema set name, no compatibility checks are performed.
See also: AWS API Documentation
Request Syntax
response = client.check_schema_version_validity(
DataFormat='AVRO'|'JSON'|'PROTOBUF',
SchemaDefinition='string'
)
[REQUIRED]
The data format of the schema definition. Currently AVRO , JSON and PROTOBUF are supported.
[REQUIRED]
The definition of the schema that has to be validated.
dict
Response Syntax
{
'Valid': True|False,
'Error': 'string'
}
Response Structure
(dict) --
Valid (boolean) --
Return true, if the schema is valid and false otherwise.
Error (string) --
A validation failure error message.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionclose()¶Closes underlying endpoint connections.
create_blueprint(**kwargs)¶Registers a blueprint with Glue.
See also: AWS API Documentation
Request Syntax
response = client.create_blueprint(
Name='string',
Description='string',
BlueprintLocation='string',
Tags={
'string': 'string'
}
)
[REQUIRED]
The name of the blueprint.
[REQUIRED]
Specifies a path in Amazon S3 where the blueprint is published.
The tags to be applied to this blueprint.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
Returns the name of the blueprint that was registered.
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptioncreate_classifier(**kwargs)¶Creates a classifier in the user's account. This can be a GrokClassifier , an XMLClassifier , a JsonClassifier , or a CsvClassifier , depending on which field of the request is present.
See also: AWS API Documentation
Request Syntax
response = client.create_classifier(
GrokClassifier={
'Classification': 'string',
'Name': 'string',
'GrokPattern': 'string',
'CustomPatterns': 'string'
},
XMLClassifier={
'Classification': 'string',
'Name': 'string',
'RowTag': 'string'
},
JsonClassifier={
'Name': 'string',
'JsonPath': 'string'
},
CsvClassifier={
'Name': 'string',
'Delimiter': 'string',
'QuoteSymbol': 'string',
'ContainsHeader': 'UNKNOWN'|'PRESENT'|'ABSENT',
'Header': [
'string',
],
'DisableValueTrimming': True|False,
'AllowSingleColumn': True|False,
'CustomDatatypeConfigured': True|False,
'CustomDatatypes': [
'string',
]
}
)
A GrokClassifier object specifying the classifier to create.
An identifier of the data format that the classifier matches, such as Twitter, JSON, Omniture logs, Amazon CloudWatch Logs, and so on.
The name of the new classifier.
The grok pattern used by this classifier.
Optional custom grok patterns used by this classifier.
An XMLClassifier object specifying the classifier to create.
An identifier of the data format that the classifier matches.
The name of the classifier.
The XML tag designating the element that contains each record in an XML document being parsed. This can't identify a self-closing element (closed by /> ). An empty row element that contains only attributes can be parsed as long as it ends with a closing tag (for example, <row item_a="A" item_b="B"></row> is okay, but <row item_a="A" item_b="B" /> is not).
A JsonClassifier object specifying the classifier to create.
The name of the classifier.
A JsonPath string defining the JSON data for the classifier to classify. Glue supports a subset of JsonPath, as described in Writing JsonPath Custom Classifiers.
A CsvClassifier object specifying the classifier to create.
The name of the classifier.
A custom symbol to denote what separates each column entry in the row.
A custom symbol to denote what combines content into a single column value. Must be different from the column delimiter.
Indicates whether the CSV file contains a header.
A list of strings representing column names.
Specifies not to trim values before identifying the type of column values. The default value is true.
Enables the processing of files that contain only one column.
Enables the configuration of custom datatypes.
Creates a list of supported custom datatypes.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptioncreate_connection(**kwargs)¶Creates a connection definition in the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.create_connection(
CatalogId='string',
ConnectionInput={
'Name': 'string',
'Description': 'string',
'ConnectionType': 'JDBC'|'SFTP'|'MONGODB'|'KAFKA'|'NETWORK'|'MARKETPLACE'|'CUSTOM',
'MatchCriteria': [
'string',
],
'ConnectionProperties': {
'string': 'string'
},
'PhysicalConnectionRequirements': {
'SubnetId': 'string',
'SecurityGroupIdList': [
'string',
],
'AvailabilityZone': 'string'
}
},
Tags={
'string': 'string'
}
)
[REQUIRED]
A ConnectionInput object defining the connection to create.
The name of the connection.
The description of the connection.
The type of the connection. Currently, these types are supported:
JDBC - Designates a connection to a database through Java Database Connectivity (JDBC).KAFKA - Designates a connection to an Apache Kafka streaming platform.MONGODB - Designates a connection to a MongoDB document database.NETWORK - Designates a network connection to a data source within an Amazon Virtual Private Cloud environment (Amazon VPC).MARKETPLACE - Uses configuration settings contained in a connector purchased from Amazon Web Services Marketplace to read from and write to data stores that are not natively supported by Glue.CUSTOM - Uses configuration settings contained in a custom connector to read from and write to data stores that are not natively supported by Glue.SFTP is not supported.
A list of criteria that can be used in selecting this connection.
These key-value pairs define parameters for the connection.
A map of physical connection requirements, such as virtual private cloud (VPC) and SecurityGroup , that are needed to successfully make this connection.
The subnet ID used by the connection.
The security group ID list used by the connection.
The connection's Availability Zone. This field is redundant because the specified subnet implies the Availability Zone to be used. Currently the field must be populated, but it will be deprecated in the future.
The tags you assign to the connection.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.GlueEncryptionExceptioncreate_crawler(**kwargs)¶Creates a new crawler with specified targets, role, configuration, and optional schedule. At least one crawl target must be specified, in the s3Targets field, the jdbcTargets field, or the DynamoDBTargets field.
See also: AWS API Documentation
Request Syntax
response = client.create_crawler(
Name='string',
Role='string',
DatabaseName='string',
Description='string',
Targets={
'S3Targets': [
{
'Path': 'string',
'Exclusions': [
'string',
],
'ConnectionName': 'string',
'SampleSize': 123,
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'JdbcTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'Exclusions': [
'string',
],
'EnableAdditionalMetadata': [
'COMMENTS'|'RAWTYPES',
]
},
],
'MongoDBTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'ScanAll': True|False
},
],
'DynamoDBTargets': [
{
'Path': 'string',
'scanAll': True|False,
'scanRate': 123.0
},
],
'CatalogTargets': [
{
'DatabaseName': 'string',
'Tables': [
'string',
],
'ConnectionName': 'string',
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'DeltaTargets': [
{
'DeltaTables': [
'string',
],
'ConnectionName': 'string',
'WriteManifest': True|False,
'CreateNativeDeltaTable': True|False
},
]
},
Schedule='string',
Classifiers=[
'string',
],
TablePrefix='string',
SchemaChangePolicy={
'UpdateBehavior': 'LOG'|'UPDATE_IN_DATABASE',
'DeleteBehavior': 'LOG'|'DELETE_FROM_DATABASE'|'DEPRECATE_IN_DATABASE'
},
RecrawlPolicy={
'RecrawlBehavior': 'CRAWL_EVERYTHING'|'CRAWL_NEW_FOLDERS_ONLY'|'CRAWL_EVENT_MODE'
},
LineageConfiguration={
'CrawlerLineageSettings': 'ENABLE'|'DISABLE'
},
LakeFormationConfiguration={
'UseLakeFormationCredentials': True|False,
'AccountId': 'string'
},
Configuration='string',
CrawlerSecurityConfiguration='string',
Tags={
'string': 'string'
}
)
[REQUIRED]
Name of the new crawler.
[REQUIRED]
The IAM role or Amazon Resource Name (ARN) of an IAM role used by the new crawler to access customer resources.
arn:aws:daylight:us-east-1::database/sometable/* .[REQUIRED]
A list of collection of targets to crawl.
Specifies Amazon Simple Storage Service (Amazon S3) targets.
Specifies a data store in Amazon Simple Storage Service (Amazon S3).
The path to the Amazon S3 target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
The name of a connection which allows a job or crawler to access data in Amazon S3 within an Amazon Virtual Private Cloud environment (Amazon VPC).
Sets the number of files in each leaf folder to be crawled when crawling sample files in a dataset. If not set, all the files are crawled. A valid value is an integer between 1 and 249.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies JDBC targets.
Specifies a JDBC data store to crawl.
The name of the connection to use to connect to the JDBC target.
The path of the JDBC target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
Specify a value of RAWTYPES or COMMENTS to enable additional metadata in table responses. RAWTYPES provides the native-level datatype. COMMENTS provides comments associated with a column or table in the database.
If you do not need additional metadata, keep the field empty.
Specifies Amazon DocumentDB or MongoDB targets.
Specifies an Amazon DocumentDB or MongoDB data store to crawl.
The name of the connection to use to connect to the Amazon DocumentDB or MongoDB target.
The path of the Amazon DocumentDB or MongoDB target (database/collection).
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
Specifies Amazon DynamoDB targets.
Specifies an Amazon DynamoDB table to crawl.
The name of the DynamoDB table to crawl.
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
The percentage of the configured read capacity units to use by the Glue crawler. Read capacity units is a term defined by DynamoDB, and is a numeric value that acts as rate limiter for the number of reads that can be performed on that table per second.
The valid values are null or a value between 0.1 to 1.5. A null value is used when user does not provide a value, and defaults to 0.5 of the configured Read Capacity Unit (for provisioned tables), or 0.25 of the max configured Read Capacity Unit (for tables using on-demand mode).
Specifies Glue Data Catalog targets.
Specifies an Glue Data Catalog target.
The name of the database to be synchronized.
A list of the tables to be synchronized.
The name of the connection for an Amazon S3-backed Data Catalog table to be a target of the crawl when using a Catalog connection type paired with a NETWORK Connection type.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies Delta data store targets.
Specifies a Delta data store to crawl one or more Delta tables.
A list of the Amazon S3 paths to the Delta tables.
The name of the connection to use to connect to the Delta table target.
Specifies whether to write the manifest files to the Delta table path.
Specifies whether the crawler will create native tables, to allow integration with query engines that support querying of the Delta transaction log directly.
cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .A list of custom classifiers that the user has registered. By default, all built-in classifiers are included in a crawl, but these custom classifiers always override the default classifiers for a given classification.
The policy for the crawler's update and deletion behavior.
The update behavior when the crawler finds a changed schema.
The deletion behavior when the crawler finds a deleted object.
A policy that specifies whether to crawl the entire dataset again, or to crawl only folders that were added since the last crawler run.
Specifies whether to crawl the entire dataset again or to crawl only folders that were added since the last crawler run.
A value of CRAWL_EVERYTHING specifies crawling the entire dataset again.
A value of CRAWL_NEW_FOLDERS_ONLY specifies crawling only folders that were added since the last crawler run.
A value of CRAWL_EVENT_MODE specifies crawling only the changes identified by Amazon S3 events.
Specifies data lineage configuration settings for the crawler.
Specifies whether data lineage is enabled for the crawler. Valid values are:
Specifies Lake Formation configuration settings for the crawler.
Specifies whether to use Lake Formation credentials for the crawler instead of the IAM role credentials.
Required for cross account crawls. For same account crawls as the target data, this can be left as null.
SecurityConfiguration structure to be used by this crawler.The tags to use with this crawler request. You may use tags to limit access to the crawler. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptioncreate_custom_entity_type(**kwargs)¶Creates a custom pattern that is used to detect sensitive data across the columns and rows of your structured data.
Each custom pattern you create specifies a regular expression and an optional list of context words. If no context words are passed only a regular expression is checked.
See also: AWS API Documentation
Request Syntax
response = client.create_custom_entity_type(
Name='string',
RegexString='string',
ContextWords=[
'string',
]
)
[REQUIRED]
A name for the custom pattern that allows it to be retrieved or deleted later. This name must be unique per Amazon Web Services account.
[REQUIRED]
A regular expression string that is used for detecting sensitive data in a custom pattern.
A list of context words. If none of these context words are found within the vicinity of the regular expression the data will not be detected as sensitive data.
If no context words are passed only a regular expression is checked.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
The name of the custom pattern you created.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.IdempotentParameterMismatchExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptioncreate_data_quality_ruleset(**kwargs)¶Creates a data quality ruleset with DQDL rules applied to a specified Glue table.
You create the ruleset using the Data Quality Definition Language (DQDL). For more information, see the Glue developer guide.
See also: AWS API Documentation
Request Syntax
response = client.create_data_quality_ruleset(
Name='string',
Description='string',
Ruleset='string',
Tags={
'string': 'string'
},
TargetTable={
'TableName': 'string',
'DatabaseName': 'string'
},
ClientToken='string'
)
[REQUIRED]
A unique name for the data quality ruleset.
[REQUIRED]
A Data Quality Definition Language (DQDL) ruleset. For more information, see the Glue developer guide.
A list of tags applied to the data quality ruleset.
A target table associated with the data quality ruleset.
The name of the Glue table.
The name of the database where the Glue table exists.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
A unique name for the data quality ruleset.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptioncreate_database(**kwargs)¶Creates a new database in a Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.create_database(
CatalogId='string',
DatabaseInput={
'Name': 'string',
'Description': 'string',
'LocationUri': 'string',
'Parameters': {
'string': 'string'
},
'CreateTableDefaultPermissions': [
{
'Principal': {
'DataLakePrincipalIdentifier': 'string'
},
'Permissions': [
'ALL'|'SELECT'|'ALTER'|'DROP'|'DELETE'|'INSERT'|'CREATE_DATABASE'|'CREATE_TABLE'|'DATA_LOCATION_ACCESS',
]
},
],
'TargetDatabase': {
'CatalogId': 'string',
'DatabaseName': 'string'
}
},
Tags={
'string': 'string'
}
)
[REQUIRED]
The metadata for the database.
The name of the database. For Hive compatibility, this is folded to lowercase when it is stored.
A description of the database.
The location of the database (for example, an HDFS path).
These key-value pairs define parameters and properties of the database.
These key-value pairs define parameters and properties of the database.
Creates a set of default permissions on the table for principals.
Permissions granted to a principal.
The principal who is granted permissions.
An identifier for the Lake Formation principal.
The permissions that are granted to the principal.
A DatabaseIdentifier structure that describes a target database for resource linking.
The ID of the Data Catalog in which the database resides.
The name of the catalog database.
The tags you assign to the database.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.ConcurrentModificationExceptioncreate_dev_endpoint(**kwargs)¶Creates a new development endpoint.
See also: AWS API Documentation
Request Syntax
response = client.create_dev_endpoint(
EndpointName='string',
RoleArn='string',
SecurityGroupIds=[
'string',
],
SubnetId='string',
PublicKey='string',
PublicKeys=[
'string',
],
NumberOfNodes=123,
WorkerType='Standard'|'G.1X'|'G.2X'|'G.025X',
GlueVersion='string',
NumberOfWorkers=123,
ExtraPythonLibsS3Path='string',
ExtraJarsS3Path='string',
SecurityConfiguration='string',
Tags={
'string': 'string'
},
Arguments={
'string': 'string'
}
)
[REQUIRED]
The name to be assigned to the new DevEndpoint .
[REQUIRED]
The IAM role for the DevEndpoint .
Security group IDs for the security groups to be used by the new DevEndpoint .
DevEndpoint to use.DevEndpoint for authentication. This attribute is provided for backward compatibility because the recommended attribute to use is public keys.A list of public keys to be used by the development endpoints for authentication. The use of this attribute is preferred over a single public key because the public keys allow you to have a different private key per client.
Note
If you previously created an endpoint with a public key, you must remove that key to be able to set a list of public keys. Call the UpdateDevEndpoint API with the public key content in the deletePublicKeys attribute, and the list of new keys in the addPublicKeys attribute.
DevEndpoint .The type of predefined worker that is allocated to the development endpoint. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.Known issue: when a development endpoint is created with the G.2X WorkerType configuration, the Spark drivers for the development endpoint will run on 4 vCPU, 16 GB of memory, and a 64 GB disk.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for running your ETL scripts on development endpoints.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Development endpoints that are created without specifying a Glue version default to Glue 0.9.
You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
The number of workers of a defined workerType that are allocated to the development endpoint.
The maximum number of workers you can define are 299 for G.1X , and 149 for G.2X .
The paths to one or more Python libraries in an Amazon S3 bucket that should be loaded in your DevEndpoint . Multiple values must be complete paths separated by a comma.
Note
You can only use pure Python libraries with a DevEndpoint . Libraries that rely on C extensions, such as the pandas Python data analysis library, are not yet supported.
.jar files in an S3 bucket that should be loaded in your DevEndpoint .SecurityConfiguration structure to be used with this DevEndpoint .The tags to use with this DevEndpoint. You may use tags to limit access to the DevEndpoint. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
A map of arguments used to configure the DevEndpoint .
dict
Response Syntax
{
'EndpointName': 'string',
'Status': 'string',
'SecurityGroupIds': [
'string',
],
'SubnetId': 'string',
'RoleArn': 'string',
'YarnEndpointAddress': 'string',
'ZeppelinRemoteSparkInterpreterPort': 123,
'NumberOfNodes': 123,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'GlueVersion': 'string',
'NumberOfWorkers': 123,
'AvailabilityZone': 'string',
'VpcId': 'string',
'ExtraPythonLibsS3Path': 'string',
'ExtraJarsS3Path': 'string',
'FailureReason': 'string',
'SecurityConfiguration': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'Arguments': {
'string': 'string'
}
}
Response Structure
(dict) --
EndpointName (string) --
The name assigned to the new DevEndpoint .
Status (string) --
The current status of the new DevEndpoint .
SecurityGroupIds (list) --
The security groups assigned to the new DevEndpoint .
SubnetId (string) --
The subnet ID assigned to the new DevEndpoint .
RoleArn (string) --
The Amazon Resource Name (ARN) of the role assigned to the new DevEndpoint .
YarnEndpointAddress (string) --
The address of the YARN endpoint used by this DevEndpoint .
ZeppelinRemoteSparkInterpreterPort (integer) --
The Apache Zeppelin port for the remote Apache Spark interpreter.
NumberOfNodes (integer) --
The number of Glue Data Processing Units (DPUs) allocated to this DevEndpoint.
WorkerType (string) --
The type of predefined worker that is allocated to the development endpoint. May be a value of Standard, G.1X, or G.2X.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for running your ETL scripts on development endpoints.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated to the development endpoint.
AvailabilityZone (string) --
The Amazon Web Services Availability Zone where this DevEndpoint is located.
VpcId (string) --
The ID of the virtual private cloud (VPC) used by this DevEndpoint .
ExtraPythonLibsS3Path (string) --
The paths to one or more Python libraries in an S3 bucket that will be loaded in your DevEndpoint .
ExtraJarsS3Path (string) --
Path to one or more Java .jar files in an S3 bucket that will be loaded in your DevEndpoint .
FailureReason (string) --
The reason for a current failure in this DevEndpoint .
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure being used with this DevEndpoint .
CreatedTimestamp (datetime) --
The point in time at which this DevEndpoint was created.
Arguments (dict) --
The map of arguments used to configure this DevEndpoint .
Valid arguments are:
"--enable-glue-datacatalog": ""You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.IdempotentParameterMismatchExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.ValidationExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptioncreate_job(**kwargs)¶Creates a new job definition.
See also: AWS API Documentation
Request Syntax
response = client.create_job(
Name='string',
Description='string',
LogUri='string',
Role='string',
ExecutionProperty={
'MaxConcurrentRuns': 123
},
Command={
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
DefaultArguments={
'string': 'string'
},
NonOverridableArguments={
'string': 'string'
},
Connections={
'Connections': [
'string',
]
},
MaxRetries=123,
AllocatedCapacity=123,
Timeout=123,
MaxCapacity=123.0,
SecurityConfiguration='string',
Tags={
'string': 'string'
},
NotificationProperty={
'NotifyDelayAfter': 123
},
GlueVersion='string',
NumberOfWorkers=123,
WorkerType='Standard'|'G.1X'|'G.2X'|'G.025X',
CodeGenConfigurationNodes={
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
ExecutionClass='FLEX'|'STANDARD',
SourceControlDetails={
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
)
[REQUIRED]
The name you assign to this job definition. It must be unique in your account.
[REQUIRED]
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
[REQUIRED]
The JobCommand that runs this job.
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
The default arguments for this job.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Non-overridable arguments for this job, specified as name-value pairs.
The connections used for this job.
A list of connections used by the job.
This parameter is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) to allocate to this Job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
TIMEOUT status. The default is 2,880 minutes (48 hours).For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
SecurityConfiguration structure to be used with this job.The tags to use with this job. You may use tags to limit access to the job. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
Specifies configuration properties of a job notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
workerType that are allocated when a job runs.The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
CodeGenConfigurationNodeenumerates all valid Node types. One and only one of its member variables can be populated.
Specifies a connector to an Amazon Athena data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
The name of the table in the data source.
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
Specifies the data schema for the custom Athena source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to a JDBC data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
Additional connection options for the connector.
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
The minimum value of partitionColumn that is used to decide partition stride.
The maximum value of partitionColumn that is used to decide partition stride.
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
The name of the job bookmark keys on which to sort.
Specifies an ascending or descending sort order.
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
The name of the table in the data source.
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
Specifies the data schema for the custom JDBC source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to an Apache Spark data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies data schema for the custom spark source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a data store in the Glue Data Catalog.
The name of the data store.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Amazon Redshift data store.
The name of the Amazon Redshift data store.
The database to read from.
The database table to read from.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
Specifies an Amazon S3 data store in the Glue Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a command-separated value (CSV) data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
A Boolean value that specifies whether to write the header to output. The default value is True .
A Boolean value that specifies whether to skip the first data line. The default value is False .
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
Specifies the data schema for the S3 CSV source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a JSON data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
A JsonPath string defining the JSON data.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
Specifies the data schema for the S3 JSON source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies an Apache Parquet data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the data schema for the S3 Parquet source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a Relational database data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a DynamoDB data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
The name of the connection that is associated with the connector.
The name of the table in the data target.
The name of a connector that will be used.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
Additional connection options for the connector.
Specifies the data schema for the JDBC target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses an Apache Spark connector.
The name of the data target.
The nodes that are inputs to the data target.
The name of a connection for an Apache Spark connector.
The name of an Apache Spark connector.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies the data schema for the custom spark target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses a Glue Data Catalog table.
The name of your data target.
The nodes that are inputs to the data target.
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
Specifies a target that uses Amazon Redshift.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
The set of options to configure an upsert operation when writing to a Redshift target.
The physical location of the Redshift table.
The name of the connection to use to write to Redshift.
The keys used to determine whether to perform an update or insert.
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a data target that writes to Amazon S3.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Specifies the data output format for the target.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
The name of the transform node.
The data inputs identified by their node names.
Specifies the mapping of data property keys in the data source to data property keys in the data target.
Specifies the mapping of data property keys.
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
The table or column to be modified.
The type of the data to be modified.
The data type that the data is to be modified to.
If true, then the column is removed.
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
Specifies a transform that chooses the data property keys that you want to keep.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses the data property keys that you want to drop.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that renames a single data property key.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the source data.
A JSON path to a variable in the data structure for the target data.
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
The name of the transform node.
The data inputs identified by their node names.
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Specifies a number of records to write starting from the beginning of the dataset.
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
The name of the transform node.
The data inputs identified by their node names.
Specifies the type of join to be performed on the datasets.
A list of the two columns to be joined.
Specifies a column to be joined.
The column to be joined.
The key of the column to be joined.
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
The name of the transform node.
The data inputs identified by their node names.
The index for the DynamicFrame to be selected.
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the dataset that is imputed.
A JSON path to a variable in the data structure for the dataset that is filled.
Specifies a transform that splits a dataset into two, based on a filter condition.
The name of the transform node.
The data inputs identified by their node names.
The operator used to filter rows by comparing the key value to a specified value.
Specifies a filter expression.
Specifies a filter expression.
The type of operation to perform in the expression.
Whether the expression is to be negated.
A list of filter values.
Represents a single entry in the list of values for a FilterExpression .
The type of filter value.
The value to be associated.
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
The name of the transform node.
The data inputs identified by their node names.
The custom code that is used to perform the data transformation.
The name defined for the custom code node class.
Specifies the data schema for the custom code transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
The name of the transform node.
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
A SQL query that must use Spark SQL syntax and return a single data set.
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
Represents a single entry in the list of values for SqlAliases .
A table, or a column in a table.
A temporary name given to a table, or a column in a table.
Specifies the data schema for the SparkSQL transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a direct Amazon Kinesis data source.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store.
The name of the data store.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a Kinesis data source in the Glue Data Catalog.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store in the Data Catalog.
The name of the data store.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
The name of the transform node.
The data inputs identified by their node names.
A structure that represents whether certain values are recognized as null values for removal.
Specifies that an empty string is considered as a null value.
Specifies that a value spelling out the word 'null' is considered as a null value.
Specifies that an integer value of -1 is considered as a null value.
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
The value of the null placeholder.
The datatype of the value.
The datatype of the value.
A label assigned to the datatype.
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
The name of the transform node.
The data inputs identified by their node names.
The source DynamicFrame that will be merged with a staging DynamicFrame .
The list of primary key fields to match records from the source and staging dynamic frames.
Specifies a transform that combines the rows from two or more datasets into a single result.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
Specifies a transform that identifies, removes or masks PII data.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of PIIDetection transform.
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
Indicates the output column name that will contain any entity type detected in that row.
Indicates the fraction of the data to sample when scanning for PII entities.
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
Indicates the value that will replace the detected entity.
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
The name of the transform node.
Specifies the fields and rows to use as inputs for the aggregate transform.
Specifies the fields to group by.
Specifies the aggregate functions to be performed on specified fields.
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Specifies the column on the data set on which the aggregation function will be applied.
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
Specifies a transform that removes rows of repeating data from a data set.
The name of the transform node.
The data inputs identified by their node names.
The name of the columns to be merged or removed if repeating.
Specifies a data target that writes to a goverened catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the governed catalog.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data source in a goverened Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a MySQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Oracle data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a PostgresSQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a target that uses Microsoft SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses MySQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Oracle SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Postgres SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a custom visual transform created by a user.
Specifies the name of the dynamic transform.
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Specifies the inputs for the dynamic transform that are required.
Specifies the parameters of the dynamic transform.
Specifies the parameters in the config file of the dynamic transform.
Specifies the name of the parameter in the config file of the dynamic transform.
Specifies the parameter type in the config file of the dynamic transform.
Specifies the validation rule in the config file of the dynamic transform.
Specifies the validation message in the config file of the dynamic transform.
Specifies the value of the parameter in the config file of the dynamic transform.
Specifies the list type of the parameter in the config file of the dynamic transform.
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
Specifies the name of the function of the dynamic transform.
Specifies the path of the dynamic transform source and config files.
This field is not used and will be deprecated in future release.
Specifies your data quality evaluation criteria.
The name of the data quality evaluation.
The inputs of your data quality evaluation.
The ruleset for your data quality evaluation.
The output of your data quality evaluation.
Options to configure how your results are published.
The context of the evaluation.
The Amazon S3 prefix prepended to the results.
Enable metrics for your data quality results.
Enable publishing for your data quality results.
Options to configure how your job will stop if your data quality evaluation fails.
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
The provider for the remote repository.
The name of the remote repository that contains the job artifacts.
The owner of the remote repository that contains the job artifacts.
An optional branch in the remote repository.
An optional folder in the remote repository.
The last commit ID for a commit in the remote repository.
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
The value of an authorization token.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
The unique name that was provided for this job definition.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.IdempotentParameterMismatchExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentModificationExceptioncreate_ml_transform(**kwargs)¶Creates an Glue machine learning transform. This operation creates the transform and all the necessary parameters to train it.
Call this operation as the first step in the process of using a machine learning transform (such as the FindMatches transform) for deduplicating data. You can provide an optional Description , in addition to the parameters that you want to use for your algorithm.
You must also specify certain parameters for the tasks that Glue runs on your behalf as part of learning from your data and creating a high-quality machine learning transform. These parameters include Role , and optionally, AllocatedCapacity , Timeout , and MaxRetries . For more information, see Jobs.
See also: AWS API Documentation
Request Syntax
response = client.create_ml_transform(
Name='string',
Description='string',
InputRecordTables=[
{
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
},
],
Parameters={
'TransformType': 'FIND_MATCHES',
'FindMatchesParameters': {
'PrimaryKeyColumnName': 'string',
'PrecisionRecallTradeoff': 123.0,
'AccuracyCostTradeoff': 123.0,
'EnforceProvidedLabels': True|False
}
},
Role='string',
GlueVersion='string',
MaxCapacity=123.0,
WorkerType='Standard'|'G.1X'|'G.2X'|'G.025X',
NumberOfWorkers=123,
Timeout=123,
MaxRetries=123,
Tags={
'string': 'string'
},
TransformEncryption={
'MlUserDataEncryption': {
'MlUserDataEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyId': 'string'
},
'TaskRunSecurityConfigurationName': 'string'
}
)
[REQUIRED]
The unique name that you give the transform when you create it.
[REQUIRED]
A list of Glue table definitions used by the transform.
The database and table in the Glue Data Catalog that is used for input or output data.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.[REQUIRED]
The algorithmic parameters that are specific to the transform type used. Conditionally dependent on the transform type.
The type of machine learning transform.
For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
The parameters for the find matches algorithm.
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
The value selected when tuning your transform for a balance between precision and recall. A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.
The precision metric indicates how often your model is correct when it predicts a match.
The recall metric indicates that for an actual match, how often your model predicts the match.
The value that is selected when tuning your transform for a balance between accuracy and cost. A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate FindMatches transform, sometimes with unacceptable accuracy.
Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall.
Cost measures how many compute resources, and thus money, are consumed to run the transform.
The value to switch on or off to force the output to match the provided labels from users. If the value is True , the find matches transform forces the output to match the provided labels. The results override the normal conflation results. If the value is False , the find matches transform does not ensure all the labels provided are respected, and the results rely on the trained model.
Note that setting this value to true may increase the conflation execution time.
[REQUIRED]
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions. The required permissions include both Glue service role permissions to Glue resources, and Amazon S3 permissions required by the transform.
The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
MaxCapacityis a mutually exclusive option withNumberOfWorkersandWorkerType.
NumberOfWorkers or WorkerType is set, then MaxCapacity cannot be set.MaxCapacity is set then neither NumberOfWorkers or WorkerType can be set.WorkerType is set, then NumberOfWorkers is required (and vice versa).MaxCapacity and NumberOfWorkers must both be at least 1.When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
The type of predefined worker that is allocated when this task runs. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.MaxCapacityis a mutually exclusive option withNumberOfWorkersandWorkerType.
NumberOfWorkers or WorkerType is set, then MaxCapacity cannot be set.MaxCapacity is set then neither NumberOfWorkers or WorkerType can be set.WorkerType is set, then NumberOfWorkers is required (and vice versa).MaxCapacity and NumberOfWorkers must both be at least 1.The number of workers of a defined workerType that are allocated when this task runs.
If WorkerType is set, then NumberOfWorkers is required (and vice versa).
TIMEOUT status. The default is 2,880 minutes (48 hours).The tags to use with this machine learning transform. You may use tags to limit access to the machine learning transform. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
An MLUserDataEncryption object containing the encryption mode and customer-provided KMS key ID.
The encryption mode applied to user data. Valid values are:
The ID for the customer-provided KMS key.
The name of the security configuration.
dict
Response Syntax
{
'TransformId': 'string'
}
Response Structure
(dict) --
TransformId (string) --
A unique identifier that is generated for the transform.
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.IdempotentParameterMismatchExceptioncreate_partition(**kwargs)¶Creates a new partition.
See also: AWS API Documentation
Request Syntax
response = client.create_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionInput={
'Values': [
'string',
],
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1)
}
)
[REQUIRED]
The name of the metadata database in which the partition is to be created.
[REQUIRED]
The name of the metadata table in which the partition is to be created.
[REQUIRED]
A PartitionInput structure defining the partition to be created.
The values of the partition. Although this parameter is not required by the SDK, you must specify this parameter for a valid input.
The values for the keys for the new partition must be passed as an array of String objects that must be ordered in the same order as the partition keys appearing in the Amazon S3 prefix. Otherwise Glue will add the values to the wrong keys.
The last time at which the partition was accessed.
Provides information about the physical location where the partition is stored.
A list of the Columns in the table.
A column in a Table .
The name of the Column .
The data type of the Column .
A free-form text comment.
These key-value pairs define properties associated with the column.
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
A list of locations that point to the path where a Delta table is located.
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Trueif the data in the table is compressed, orFalseif not.
Must be specified if the table contains any dimension columns.
The serialization/deserialization (SerDe) information.
Name of the SerDe.
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
These key-value pairs define initialization parameters for the SerDe.
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
A list specifying the sort order of each bucket in the table.
Specifies the sort order of a sorted column.
The name of the column.
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
The user-supplied properties in key-value form.
The information about values that appear frequently in a column (skewed values).
A list of names of columns that contain skewed values.
A list of values that appear so frequently as to be considered skewed.
A mapping of skewed values to the columns that contain them.
Trueif the table data is stored in subdirectories, orFalseif not.
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
The version number of the schema.
These key-value pairs define partition parameters.
The last time at which column statistics were computed for this partition.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptioncreate_partition_index(**kwargs)¶Creates a specified partition index in an existing table.
See also: AWS API Documentation
Request Syntax
response = client.create_partition_index(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionIndex={
'Keys': [
'string',
],
'IndexName': 'string'
}
)
[REQUIRED]
Specifies the name of a database in which you want to create a partition index.
[REQUIRED]
Specifies the name of a table in which you want to create a partition index.
[REQUIRED]
Specifies a PartitionIndex structure to create a partition index in an existing table.
The keys for the partition index.
The name of the partition index.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptioncreate_registry(**kwargs)¶Creates a new registry which may be used to hold a collection of schemas.
See also: AWS API Documentation
Request Syntax
response = client.create_registry(
RegistryName='string',
Description='string',
Tags={
'string': 'string'
}
)
[REQUIRED]
Name of the registry to be created of max length of 255, and may only contain letters, numbers, hyphen, underscore, dollar sign, or hash mark. No whitespace.
Amazon Web Services tags that contain a key value pair and may be searched by console, command line, or API.
dict
Response Syntax
{
'RegistryArn': 'string',
'RegistryName': 'string',
'Description': 'string',
'Tags': {
'string': 'string'
}
}
Response Structure
(dict) --
RegistryArn (string) --
The Amazon Resource Name (ARN) of the newly created registry.
RegistryName (string) --
The name of the registry.
Description (string) --
A description of the registry.
Tags (dict) --
The tags for the registry.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.InternalServiceExceptioncreate_schema(**kwargs)¶Creates a new schema set and registers the schema definition. Returns an error if the schema set already exists without actually registering the version.
When the schema set is created, a version checkpoint will be set to the first version. Compatibility mode "DISABLED" restricts any additional schema versions from being added after the first schema version. For all other compatibility modes, validation of compatibility settings will be applied only from the second version onwards when the RegisterSchemaVersion API is used.
When this API is called without a RegistryId , this will create an entry for a "default-registry" in the registry database tables, if it is not already present.
See also: AWS API Documentation
Request Syntax
response = client.create_schema(
RegistryId={
'RegistryName': 'string',
'RegistryArn': 'string'
},
SchemaName='string',
DataFormat='AVRO'|'JSON'|'PROTOBUF',
Compatibility='NONE'|'DISABLED'|'BACKWARD'|'BACKWARD_ALL'|'FORWARD'|'FORWARD_ALL'|'FULL'|'FULL_ALL',
Description='string',
Tags={
'string': 'string'
},
SchemaDefinition='string'
)
This is a wrapper shape to contain the registry identity fields. If this is not provided, the default registry will be used. The ARN format for the same will be: arn:aws:glue:us-east-2:<customer id>:registry/default-registry:random-5-letter-id .
Name of the registry. Used only for lookup. One of RegistryArn or RegistryName has to be provided.
Arn of the registry to be updated. One of RegistryArn or RegistryName has to be provided.
[REQUIRED]
Name of the schema to be created of max length of 255, and may only contain letters, numbers, hyphen, underscore, dollar sign, or hash mark. No whitespace.
[REQUIRED]
The data format of the schema definition. Currently AVRO , JSON and PROTOBUF are supported.
The compatibility mode of the schema. The possible values are:
Amazon Web Services tags that contain a key value pair and may be searched by console, command line, or API. If specified, follows the Amazon Web Services tags-on-create pattern.
DataFormat setting for SchemaName .dict
Response Syntax
{
'RegistryName': 'string',
'RegistryArn': 'string',
'SchemaName': 'string',
'SchemaArn': 'string',
'Description': 'string',
'DataFormat': 'AVRO'|'JSON'|'PROTOBUF',
'Compatibility': 'NONE'|'DISABLED'|'BACKWARD'|'BACKWARD_ALL'|'FORWARD'|'FORWARD_ALL'|'FULL'|'FULL_ALL',
'SchemaCheckpoint': 123,
'LatestSchemaVersion': 123,
'NextSchemaVersion': 123,
'SchemaStatus': 'AVAILABLE'|'PENDING'|'DELETING',
'Tags': {
'string': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionStatus': 'AVAILABLE'|'PENDING'|'FAILURE'|'DELETING'
}
Response Structure
(dict) --
RegistryName (string) --
The name of the registry.
RegistryArn (string) --
The Amazon Resource Name (ARN) of the registry.
SchemaName (string) --
The name of the schema.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema.
Description (string) --
A description of the schema if specified when created.
DataFormat (string) --
The data format of the schema definition. Currently AVRO , JSON and PROTOBUF are supported.
Compatibility (string) --
The schema compatibility mode.
SchemaCheckpoint (integer) --
The version number of the checkpoint (the last time the compatibility mode was changed).
LatestSchemaVersion (integer) --
The latest version of the schema associated with the returned schema definition.
NextSchemaVersion (integer) --
The next version of the schema associated with the returned schema definition.
SchemaStatus (string) --
The status of the schema.
Tags (dict) --
The tags for the schema.
SchemaVersionId (string) --
The unique identifier of the first schema version.
SchemaVersionStatus (string) --
The status of the first schema version created.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.InternalServiceExceptioncreate_script(**kwargs)¶Transforms a directed acyclic graph (DAG) into code.
See also: AWS API Documentation
Request Syntax
response = client.create_script(
DagNodes=[
{
'Id': 'string',
'NodeType': 'string',
'Args': [
{
'Name': 'string',
'Value': 'string',
'Param': True|False
},
],
'LineNumber': 123
},
],
DagEdges=[
{
'Source': 'string',
'Target': 'string',
'TargetParameter': 'string'
},
],
Language='PYTHON'|'SCALA'
)
A list of the nodes in the DAG.
Represents a node in a directed acyclic graph (DAG)
A node identifier that is unique within the node's graph.
The type of node that this is.
Properties of the node, in the form of name-value pairs.
An argument or property of a node.
The name of the argument or property.
The value of the argument or property.
True if the value is used as a parameter.
The line number of the node.
A list of the edges in the DAG.
Represents a directional edge in a directed acyclic graph (DAG).
The ID of the node at which the edge starts.
The ID of the node at which the edge ends.
The target of the edge.
dict
Response Syntax
{
'PythonScript': 'string',
'ScalaCode': 'string'
}
Response Structure
(dict) --
PythonScript (string) --
The Python script generated from the DAG.
ScalaCode (string) --
The Scala code generated from the DAG.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptioncreate_security_configuration(**kwargs)¶Creates a new security configuration. A security configuration is a set of security properties that can be used by Glue. You can use a security configuration to encrypt data at rest. For information about using security configurations in Glue, see Encrypting Data Written by Crawlers, Jobs, and Development Endpoints.
See also: AWS API Documentation
Request Syntax
response = client.create_security_configuration(
Name='string',
EncryptionConfiguration={
'S3Encryption': [
{
'S3EncryptionMode': 'DISABLED'|'SSE-KMS'|'SSE-S3',
'KmsKeyArn': 'string'
},
],
'CloudWatchEncryption': {
'CloudWatchEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyArn': 'string'
},
'JobBookmarksEncryption': {
'JobBookmarksEncryptionMode': 'DISABLED'|'CSE-KMS',
'KmsKeyArn': 'string'
}
}
)
[REQUIRED]
The name for the new security configuration.
[REQUIRED]
The encryption configuration for the new security configuration.
The encryption configuration for Amazon Simple Storage Service (Amazon S3) data.
Specifies how Amazon Simple Storage Service (Amazon S3) data should be encrypted.
The encryption mode to use for Amazon S3 data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
The encryption configuration for Amazon CloudWatch.
The encryption mode to use for CloudWatch data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
The encryption configuration for job bookmarks.
The encryption mode to use for job bookmarks data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
dict
Response Syntax
{
'Name': 'string',
'CreatedTimestamp': datetime(2015, 1, 1)
}
Response Structure
(dict) --
Name (string) --
The name assigned to the new security configuration.
CreatedTimestamp (datetime) --
The time at which the new security configuration was created.
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptioncreate_session(**kwargs)¶Creates a new session.
See also: AWS API Documentation
Request Syntax
response = client.create_session(
Id='string',
Description='string',
Role='string',
Command={
'Name': 'string',
'PythonVersion': 'string'
},
Timeout=123,
IdleTimeout=123,
DefaultArguments={
'string': 'string'
},
Connections={
'Connections': [
'string',
]
},
MaxCapacity=123.0,
NumberOfWorkers=123,
WorkerType='Standard'|'G.1X'|'G.2X'|'G.025X',
SecurityConfiguration='string',
GlueVersion='string',
Tags={
'string': 'string'
},
RequestOrigin='string'
)
[REQUIRED]
The ID of the session request.
[REQUIRED]
The IAM Role ARN
[REQUIRED]
The SessionCommand that runs the job.
Specifies the name of the SessionCommand. Can be 'glueetl' or 'gluestreaming'.
Specifies the Python version. The Python version indicates the version supported for jobs of type Spark.
A map array of key-value pairs. Max is 75 pairs.
The number of connections to use for the session.
A list of connections used by the job.
WorkerType to use for the session.The type of predefined worker that is allocated to use for the session. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.The map of key value pairs (tags) belonging to the session.
dict
Response Syntax
{
'Session': {
'Id': 'string',
'CreatedOn': datetime(2015, 1, 1),
'Status': 'PROVISIONING'|'READY'|'FAILED'|'TIMEOUT'|'STOPPING'|'STOPPED',
'ErrorMessage': 'string',
'Description': 'string',
'Role': 'string',
'Command': {
'Name': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'Progress': 123.0,
'MaxCapacity': 123.0,
'SecurityConfiguration': 'string',
'GlueVersion': 'string'
}
}
Response Structure
(dict) --
Session (dict) --
Returns the session object in the response.
Id (string) --
The ID of the session.
CreatedOn (datetime) --
The time and date when the session was created.
Status (string) --
The session status.
ErrorMessage (string) --
The error message displayed during the session.
Description (string) --
The description of the session.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role associated with the Session.
Command (dict) --
The command object.See SessionCommand.
Name (string) --
Specifies the name of the SessionCommand. Can be 'glueetl' or 'gluestreaming'.
PythonVersion (string) --
Specifies the Python version. The Python version indicates the version supported for jobs of type Spark.
DefaultArguments (dict) --
A map array of key-value pairs. Max is 75 pairs.
Connections (dict) --
The number of connections used for the session.
Connections (list) --
A list of connections used by the job.
Progress (float) --
The code execution progress of the session.
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when the job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB memory.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with the session.
GlueVersion (string) --
The Glue version determines the versions of Apache Spark and Python that Glue supports. The GlueVersion must be greater than 2.0.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.IdempotentParameterMismatchExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.ValidationExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptioncreate_table(**kwargs)¶Creates a new table definition in the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.create_table(
CatalogId='string',
DatabaseName='string',
TableInput={
'Name': 'string',
'Description': 'string',
'Owner': 'string',
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
}
},
PartitionIndexes=[
{
'Keys': [
'string',
],
'IndexName': 'string'
},
],
TransactionId='string'
)
Table . If none is supplied, the Amazon Web Services account ID is used by default.[REQUIRED]
The catalog database in which to create the new table. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The TableInput object that defines the metadata table to create in the catalog.
The table name. For Hive compatibility, this is folded to lowercase when it is stored.
A description of the table.
The table owner.
The last time that the table was accessed.
The last time that column statistics were computed for this table.
The retention time for this table.
A storage descriptor containing information about the physical storage of this table.
A list of the Columns in the table.
A column in a Table .
The name of the Column .
The data type of the Column .
A free-form text comment.
These key-value pairs define properties associated with the column.
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
A list of locations that point to the path where a Delta table is located.
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Trueif the data in the table is compressed, orFalseif not.
Must be specified if the table contains any dimension columns.
The serialization/deserialization (SerDe) information.
Name of the SerDe.
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
These key-value pairs define initialization parameters for the SerDe.
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
A list specifying the sort order of each bucket in the table.
Specifies the sort order of a sorted column.
The name of the column.
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
The user-supplied properties in key-value form.
The information about values that appear frequently in a column (skewed values).
A list of names of columns that contain skewed values.
A list of values that appear so frequently as to be considered skewed.
A mapping of skewed values to the columns that contain them.
Trueif the table data is stored in subdirectories, orFalseif not.
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
The version number of the schema.
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
A column in a Table .
The name of the Column .
The data type of the Column .
A free-form text comment.
These key-value pairs define properties associated with the column.
If the table is a view, the original text of the view; otherwise null .
If the table is a view, the expanded text of the view; otherwise null .
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
These key-value pairs define properties associated with the table.
A TableIdentifier structure that describes a target table for resource linking.
The ID of the Data Catalog in which the table resides.
The name of the catalog database that contains the target table.
The name of the target table.
A list of partition indexes, PartitionIndex structures, to create in the table.
A structure for a partition index.
The keys for the partition index.
The name of the partition index.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.ResourceNotReadyExceptioncreate_trigger(**kwargs)¶Creates a new trigger.
See also: AWS API Documentation
Request Syntax
response = client.create_trigger(
Name='string',
WorkflowName='string',
Type='SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
Schedule='string',
Predicate={
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
Actions=[
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
Description='string',
StartOnCreation=True|False,
Tags={
'string': 'string'
},
EventBatchingCondition={
'BatchSize': 123,
'BatchWindow': 123
}
)
[REQUIRED]
The name of the trigger.
[REQUIRED]
The type of the new trigger.
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
This field is required when the trigger type is SCHEDULED.
A predicate to specify when the new trigger should fire.
This field is required when the trigger type is CONDITIONAL .
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
A list of the conditions that determine when the trigger will fire.
Defines a condition under which a trigger fires.
A logical operator.
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
The name of the crawler to which this condition applies.
The state of the crawler to which this condition applies.
[REQUIRED]
The actions initiated by this trigger when it fires.
Defines an action to be initiated by a trigger.
The name of a job to be run.
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
The name of the SecurityConfiguration structure to be used with this action.
Specifies configuration properties of a job run notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
The name of the crawler to be used with this action.
true to start SCHEDULED and CONDITIONAL triggers when created. True is not supported for ON_DEMAND triggers.The tags to use with this trigger. You may use tags to limit access to the trigger. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
The name of the trigger.
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.IdempotentParameterMismatchExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentModificationExceptioncreate_user_defined_function(**kwargs)¶Creates a new function definition in the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.create_user_defined_function(
CatalogId='string',
DatabaseName='string',
FunctionInput={
'FunctionName': 'string',
'ClassName': 'string',
'OwnerName': 'string',
'OwnerType': 'USER'|'ROLE'|'GROUP',
'ResourceUris': [
{
'ResourceType': 'JAR'|'FILE'|'ARCHIVE',
'Uri': 'string'
},
]
}
)
[REQUIRED]
The name of the catalog database in which to create the function.
[REQUIRED]
A FunctionInput object that defines the function to create in the Data Catalog.
The name of the function.
The Java class that contains the function code.
The owner of the function.
The owner type.
The resource URIs for the function.
The URIs for function resources.
The type of the resource.
The URI for accessing the resource.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.GlueEncryptionExceptioncreate_workflow(**kwargs)¶Creates a new workflow.
See also: AWS API Documentation
Request Syntax
response = client.create_workflow(
Name='string',
Description='string',
DefaultRunProperties={
'string': 'string'
},
Tags={
'string': 'string'
},
MaxConcurrentRuns=123
)
[REQUIRED]
The name to be assigned to the workflow. It should be unique within your account.
A collection of properties to be used as part of each execution of the workflow.
The tags to be used with this workflow.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
The name of the workflow which was provided as part of the request.
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentModificationExceptiondelete_blueprint(**kwargs)¶Deletes an existing blueprint.
See also: AWS API Documentation
Request Syntax
response = client.delete_blueprint(
Name='string'
)
[REQUIRED]
The name of the blueprint to delete.
{
'Name': 'string'
}
Response Structure
Returns the name of the blueprint that was deleted.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptiondelete_classifier(**kwargs)¶Removes a classifier from the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.delete_classifier(
Name='string'
)
[REQUIRED]
Name of the classifier to remove.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_column_statistics_for_partition(**kwargs)¶Delete the partition column statistics of a column.
The Identity and Access Management (IAM) permission required for this operation is DeletePartition .
See also: AWS API Documentation
Request Syntax
response = client.delete_column_statistics_for_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionValues=[
'string',
],
ColumnName='string'
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
[REQUIRED]
A list of partition values identifying the partition.
[REQUIRED]
Name of the column.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptiondelete_column_statistics_for_table(**kwargs)¶Retrieves table statistics of columns.
The Identity and Access Management (IAM) permission required for this operation is DeleteTable .
See also: AWS API Documentation
Request Syntax
response = client.delete_column_statistics_for_table(
CatalogId='string',
DatabaseName='string',
TableName='string',
ColumnName='string'
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
[REQUIRED]
The name of the column.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptiondelete_connection(**kwargs)¶Deletes a connection from the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.delete_connection(
CatalogId='string',
ConnectionName='string'
)
[REQUIRED]
The name of the connection to delete.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_crawler(**kwargs)¶Removes a specified crawler from the Glue Data Catalog, unless the crawler state is RUNNING .
See also: AWS API Documentation
Request Syntax
response = client.delete_crawler(
Name='string'
)
[REQUIRED]
The name of the crawler to remove.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.CrawlerRunningExceptionGlue.Client.exceptions.SchedulerTransitioningExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_custom_entity_type(**kwargs)¶Deletes a custom pattern by specifying its name.
See also: AWS API Documentation
Request Syntax
response = client.delete_custom_entity_type(
Name='string'
)
[REQUIRED]
The name of the custom pattern that you want to delete.
{
'Name': 'string'
}
Response Structure
The name of the custom pattern you deleted.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_data_quality_ruleset(**kwargs)¶Deletes a data quality ruleset.
See also: AWS API Documentation
Request Syntax
response = client.delete_data_quality_ruleset(
Name='string'
)
[REQUIRED]
A name for the data quality ruleset.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptiondelete_database(**kwargs)¶Removes a specified database from a Data Catalog.
Note
After completing this operation, you no longer have access to the tables (and all table versions and partitions that might belong to the tables) and the user-defined functions in the deleted database. Glue deletes these "orphaned" resources asynchronously in a timely manner, at the discretion of the service.
To ensure the immediate deletion of all related resources, before calling DeleteDatabase , use DeleteTableVersion or BatchDeleteTableVersion , DeletePartition or BatchDeletePartition , DeleteUserDefinedFunction , and DeleteTable or BatchDeleteTable , to delete any resources that belong to the database.
See also: AWS API Documentation
Request Syntax
response = client.delete_database(
CatalogId='string',
Name='string'
)
[REQUIRED]
The name of the database to delete. For Hive compatibility, this must be all lowercase.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptiondelete_dev_endpoint(**kwargs)¶Deletes a specified development endpoint.
See also: AWS API Documentation
Request Syntax
response = client.delete_dev_endpoint(
EndpointName='string'
)
[REQUIRED]
The name of the DevEndpoint .
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptiondelete_job(**kwargs)¶Deletes a specified job definition. If the job definition is not found, no exception is thrown.
See also: AWS API Documentation
Request Syntax
response = client.delete_job(
JobName='string'
)
[REQUIRED]
The name of the job definition to delete.
{
'JobName': 'string'
}
Response Structure
The name of the job definition that was deleted.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_ml_transform(**kwargs)¶Deletes an Glue machine learning transform. Machine learning transforms are a special type of transform that use machine learning to learn the details of the transformation to be performed by learning from examples provided by humans. These transformations are then saved by Glue. If you no longer need a transform, you can delete it by calling DeleteMLTransforms . However, any Glue jobs that still reference the deleted transform will no longer succeed.
See also: AWS API Documentation
Request Syntax
response = client.delete_ml_transform(
TransformId='string'
)
[REQUIRED]
The unique identifier of the transform to delete.
{
'TransformId': 'string'
}
Response Structure
The unique identifier of the transform that was deleted.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptiondelete_partition(**kwargs)¶Deletes a specified partition.
See also: AWS API Documentation
Request Syntax
response = client.delete_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionValues=[
'string',
]
)
[REQUIRED]
The name of the catalog database in which the table in question resides.
[REQUIRED]
The name of the table that contains the partition to be deleted.
[REQUIRED]
The values that define the partition.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_partition_index(**kwargs)¶Deletes a specified partition index from an existing table.
See also: AWS API Documentation
Request Syntax
response = client.delete_partition_index(
CatalogId='string',
DatabaseName='string',
TableName='string',
IndexName='string'
)
[REQUIRED]
Specifies the name of a database from which you want to delete a partition index.
[REQUIRED]
Specifies the name of a table from which you want to delete a partition index.
[REQUIRED]
The name of the partition index to be deleted.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ConflictExceptionGlue.Client.exceptions.GlueEncryptionExceptiondelete_registry(**kwargs)¶Delete the entire registry including schema and all of its versions. To get the status of the delete operation, you can call the GetRegistry API after the asynchronous call. Deleting a registry will deactivate all online operations for the registry such as the UpdateRegistry , CreateSchema , UpdateSchema , and RegisterSchemaVersion APIs.
See also: AWS API Documentation
Request Syntax
response = client.delete_registry(
RegistryId={
'RegistryName': 'string',
'RegistryArn': 'string'
}
)
[REQUIRED]
This is a wrapper structure that may contain the registry name and Amazon Resource Name (ARN).
Name of the registry. Used only for lookup. One of RegistryArn or RegistryName has to be provided.
Arn of the registry to be updated. One of RegistryArn or RegistryName has to be provided.
{
'RegistryName': 'string',
'RegistryArn': 'string',
'Status': 'AVAILABLE'|'DELETING'
}
Response Structure
The name of the registry being deleted.
The Amazon Resource Name (ARN) of the registry being deleted.
The status of the registry. A successful operation will return the Deleting status.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.ConcurrentModificationExceptiondelete_resource_policy(**kwargs)¶Deletes a specified policy.
See also: AWS API Documentation
Request Syntax
response = client.delete_resource_policy(
PolicyHashCondition='string',
ResourceArn='string'
)
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.ConditionCheckFailureExceptiondelete_schema(**kwargs)¶Deletes the entire schema set, including the schema set and all of its versions. To get the status of the delete operation, you can call GetSchema API after the asynchronous call. Deleting a registry will deactivate all online operations for the schema, such as the GetSchemaByDefinition , and RegisterSchemaVersion APIs.
See also: AWS API Documentation
Request Syntax
response = client.delete_schema(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
}
)
[REQUIRED]
This is a wrapper structure that may contain the schema name and Amazon Resource Name (ARN).
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
{
'SchemaArn': 'string',
'SchemaName': 'string',
'Status': 'AVAILABLE'|'PENDING'|'DELETING'
}
Response Structure
The Amazon Resource Name (ARN) of the schema being deleted.
The name of the schema being deleted.
The status of the schema.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.ConcurrentModificationExceptiondelete_schema_versions(**kwargs)¶Remove versions from the specified schema. A version number or range may be supplied. If the compatibility mode forbids deleting of a version that is necessary, such as BACKWARDS_FULL, an error is returned. Calling the GetSchemaVersions API after this call will list the status of the deleted versions.
When the range of version numbers contain check pointed version, the API will return a 409 conflict and will not proceed with the deletion. You have to remove the checkpoint first using the DeleteSchemaCheckpoint API before using this API.
You cannot use the DeleteSchemaVersions API to delete the first schema version in the schema set. The first schema version can only be deleted by the DeleteSchema API. This operation will also delete the attached SchemaVersionMetadata under the schema versions. Hard deletes will be enforced on the database.
If the compatibility mode forbids deleting of a version that is necessary, such as BACKWARDS_FULL, an error is returned.
See also: AWS API Documentation
Request Syntax
response = client.delete_schema_versions(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
Versions='string'
)
[REQUIRED]
This is a wrapper structure that may contain the schema name and Amazon Resource Name (ARN).
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
[REQUIRED]
A version range may be supplied which may be of the format:
dict
Response Syntax
{
'SchemaVersionErrors': [
{
'VersionNumber': 123,
'ErrorDetails': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
SchemaVersionErrors (list) --
A list of SchemaVersionErrorItem objects, each containing an error and schema version.
(dict) --
An object that contains the error details for an operation on a schema version.
VersionNumber (integer) --
The version number of the schema.
ErrorDetails (dict) --
The details of the error for the schema version.
ErrorCode (string) --
The error code for an error.
ErrorMessage (string) --
The error message for an error.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.ConcurrentModificationExceptiondelete_security_configuration(**kwargs)¶Deletes a specified security configuration.
See also: AWS API Documentation
Request Syntax
response = client.delete_security_configuration(
Name='string'
)
[REQUIRED]
The name of the security configuration to delete.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_session(**kwargs)¶Deletes the session.
See also: AWS API Documentation
Request Syntax
response = client.delete_session(
Id='string',
RequestOrigin='string'
)
[REQUIRED]
The ID of the session to be deleted.
dict
Response Syntax
{
'Id': 'string'
}
Response Structure
(dict) --
Id (string) --
Returns the ID of the deleted session.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.IllegalSessionStateExceptionGlue.Client.exceptions.ConcurrentModificationExceptiondelete_table(**kwargs)¶Removes a table definition from the Data Catalog.
Note
After completing this operation, you no longer have access to the table versions and partitions that belong to the deleted table. Glue deletes these "orphaned" resources asynchronously in a timely manner, at the discretion of the service.
To ensure the immediate deletion of all related resources, before calling DeleteTable , use DeleteTableVersion or BatchDeleteTableVersion , and DeletePartition or BatchDeletePartition , to delete any resources that belong to the table.
See also: AWS API Documentation
Request Syntax
response = client.delete_table(
CatalogId='string',
DatabaseName='string',
Name='string',
TransactionId='string'
)
[REQUIRED]
The name of the catalog database in which the table resides. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The name of the table to be deleted. For Hive compatibility, this name is entirely lowercase.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.ResourceNotReadyExceptiondelete_table_version(**kwargs)¶Deletes a specified version of a table.
See also: AWS API Documentation
Request Syntax
response = client.delete_table_version(
CatalogId='string',
DatabaseName='string',
TableName='string',
VersionId='string'
)
[REQUIRED]
The database in the catalog in which the table resides. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The name of the table. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The ID of the table version to be deleted. A VersionID is a string representation of an integer. Each version is incremented by 1.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_trigger(**kwargs)¶Deletes a specified trigger. If the trigger is not found, no exception is thrown.
See also: AWS API Documentation
Request Syntax
response = client.delete_trigger(
Name='string'
)
[REQUIRED]
The name of the trigger to delete.
{
'Name': 'string'
}
Response Structure
The name of the trigger that was deleted.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptiondelete_user_defined_function(**kwargs)¶Deletes an existing function definition from the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.delete_user_defined_function(
CatalogId='string',
DatabaseName='string',
FunctionName='string'
)
[REQUIRED]
The name of the catalog database where the function is located.
[REQUIRED]
The name of the function definition to be deleted.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptiondelete_workflow(**kwargs)¶Deletes a workflow.
See also: AWS API Documentation
Request Syntax
response = client.delete_workflow(
Name='string'
)
[REQUIRED]
Name of the workflow to be deleted.
{
'Name': 'string'
}
Response Structure
Name of the workflow specified in input.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptionget_blueprint(**kwargs)¶Retrieves the details of a blueprint.
See also: AWS API Documentation
Request Syntax
response = client.get_blueprint(
Name='string',
IncludeBlueprint=True|False,
IncludeParameterSpec=True|False
)
[REQUIRED]
The name of the blueprint.
dict
Response Syntax
{
'Blueprint': {
'Name': 'string',
'Description': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ParameterSpec': 'string',
'BlueprintLocation': 'string',
'BlueprintServiceLocation': 'string',
'Status': 'CREATING'|'ACTIVE'|'UPDATING'|'FAILED',
'ErrorMessage': 'string',
'LastActiveDefinition': {
'Description': 'string',
'LastModifiedOn': datetime(2015, 1, 1),
'ParameterSpec': 'string',
'BlueprintLocation': 'string',
'BlueprintServiceLocation': 'string'
}
}
}
Response Structure
(dict) --
Blueprint (dict) --
Returns a Blueprint object.
Name (string) --
The name of the blueprint.
Description (string) --
The description of the blueprint.
CreatedOn (datetime) --
The date and time the blueprint was registered.
LastModifiedOn (datetime) --
The date and time the blueprint was last modified.
ParameterSpec (string) --
A JSON string that indicates the list of parameter specifications for the blueprint.
BlueprintLocation (string) --
Specifies the path in Amazon S3 where the blueprint is published.
BlueprintServiceLocation (string) --
Specifies a path in Amazon S3 where the blueprint is copied when you call CreateBlueprint/UpdateBlueprint to register the blueprint in Glue.
Status (string) --
The status of the blueprint registration.
ErrorMessage (string) --
An error message.
LastActiveDefinition (dict) --
When there are multiple versions of a blueprint and the latest version has some errors, this attribute indicates the last successful blueprint definition that is available with the service.
Description (string) --
The description of the blueprint.
LastModifiedOn (datetime) --
The date and time the blueprint was last modified.
ParameterSpec (string) --
A JSON string specifying the parameters for the blueprint.
BlueprintLocation (string) --
Specifies a path in Amazon S3 where the blueprint is published by the Glue developer.
BlueprintServiceLocation (string) --
Specifies a path in Amazon S3 where the blueprint is copied when you create or update the blueprint.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionget_blueprint_run(**kwargs)¶Retrieves the details of a blueprint run.
See also: AWS API Documentation
Request Syntax
response = client.get_blueprint_run(
BlueprintName='string',
RunId='string'
)
[REQUIRED]
The name of the blueprint.
[REQUIRED]
The run ID for the blueprint run you want to retrieve.
dict
Response Syntax
{
'BlueprintRun': {
'BlueprintName': 'string',
'RunId': 'string',
'WorkflowName': 'string',
'State': 'RUNNING'|'SUCCEEDED'|'FAILED'|'ROLLING_BACK',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ErrorMessage': 'string',
'RollbackErrorMessage': 'string',
'Parameters': 'string',
'RoleArn': 'string'
}
}
Response Structure
(dict) --
BlueprintRun (dict) --
Returns a BlueprintRun object.
BlueprintName (string) --
The name of the blueprint.
RunId (string) --
The run ID for this blueprint run.
WorkflowName (string) --
The name of a workflow that is created as a result of a successful blueprint run. If a blueprint run has an error, there will not be a workflow created.
State (string) --
The state of the blueprint run. Possible values are:
StartedOn (datetime) --
The date and time that the blueprint run started.
CompletedOn (datetime) --
The date and time that the blueprint run completed.
ErrorMessage (string) --
Indicates any errors that are seen while running the blueprint.
RollbackErrorMessage (string) --
If there are any errors while creating the entities of a workflow, we try to roll back the created entities until that point and delete them. This attribute indicates the errors seen while trying to delete the entities that are created.
Parameters (string) --
The blueprint parameters as a string. You will have to provide a value for each key that is required from the parameter spec that is defined in the Blueprint$ParameterSpec .
RoleArn (string) --
The role ARN. This role will be assumed by the Glue service and will be used to create the workflow and other entities of a workflow.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_blueprint_runs(**kwargs)¶Retrieves the details of blueprint runs for a specified blueprint.
See also: AWS API Documentation
Request Syntax
response = client.get_blueprint_runs(
BlueprintName='string',
NextToken='string',
MaxResults=123
)
[REQUIRED]
The name of the blueprint.
dict
Response Syntax
{
'BlueprintRuns': [
{
'BlueprintName': 'string',
'RunId': 'string',
'WorkflowName': 'string',
'State': 'RUNNING'|'SUCCEEDED'|'FAILED'|'ROLLING_BACK',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ErrorMessage': 'string',
'RollbackErrorMessage': 'string',
'Parameters': 'string',
'RoleArn': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
BlueprintRuns (list) --
Returns a list of BlueprintRun objects.
(dict) --
The details of a blueprint run.
BlueprintName (string) --
The name of the blueprint.
RunId (string) --
The run ID for this blueprint run.
WorkflowName (string) --
The name of a workflow that is created as a result of a successful blueprint run. If a blueprint run has an error, there will not be a workflow created.
State (string) --
The state of the blueprint run. Possible values are:
StartedOn (datetime) --
The date and time that the blueprint run started.
CompletedOn (datetime) --
The date and time that the blueprint run completed.
ErrorMessage (string) --
Indicates any errors that are seen while running the blueprint.
RollbackErrorMessage (string) --
If there are any errors while creating the entities of a workflow, we try to roll back the created entities until that point and delete them. This attribute indicates the errors seen while trying to delete the entities that are created.
Parameters (string) --
The blueprint parameters as a string. You will have to provide a value for each key that is required from the parameter spec that is defined in the Blueprint$ParameterSpec .
RoleArn (string) --
The role ARN. This role will be assumed by the Glue service and will be used to create the workflow and other entities of a workflow.
NextToken (string) --
A continuation token, if not all blueprint runs have been returned.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionget_catalog_import_status(**kwargs)¶Retrieves the status of a migration operation.
See also: AWS API Documentation
Request Syntax
response = client.get_catalog_import_status(
CatalogId='string'
)
{
'ImportStatus': {
'ImportCompleted': True|False,
'ImportTime': datetime(2015, 1, 1),
'ImportedBy': 'string'
}
}
Response Structure
The status of the specified catalog migration.
Trueif the migration has completed, orFalseotherwise.
The time that the migration was started.
The name of the person who initiated the migration.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_classifier(**kwargs)¶Retrieve a classifier by name.
See also: AWS API Documentation
Request Syntax
response = client.get_classifier(
Name='string'
)
[REQUIRED]
Name of the classifier to retrieve.
{
'Classifier': {
'GrokClassifier': {
'Name': 'string',
'Classification': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'GrokPattern': 'string',
'CustomPatterns': 'string'
},
'XMLClassifier': {
'Name': 'string',
'Classification': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'RowTag': 'string'
},
'JsonClassifier': {
'Name': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'JsonPath': 'string'
},
'CsvClassifier': {
'Name': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'Delimiter': 'string',
'QuoteSymbol': 'string',
'ContainsHeader': 'UNKNOWN'|'PRESENT'|'ABSENT',
'Header': [
'string',
],
'DisableValueTrimming': True|False,
'AllowSingleColumn': True|False,
'CustomDatatypeConfigured': True|False,
'CustomDatatypes': [
'string',
]
}
}
}
Response Structure
The requested classifier.
A classifier that uses grok .
The name of the classifier.
An identifier of the data format that the classifier matches, such as Twitter, JSON, Omniture logs, and so on.
The time that this classifier was registered.
The time that this classifier was last updated.
The version of this classifier.
The grok pattern applied to a data store by this classifier. For more information, see built-in patterns in Writing Custom Classifiers.
Optional custom grok patterns defined by this classifier. For more information, see custom patterns in Writing Custom Classifiers.
A classifier for XML content.
The name of the classifier.
An identifier of the data format that the classifier matches.
The time that this classifier was registered.
The time that this classifier was last updated.
The version of this classifier.
The XML tag designating the element that contains each record in an XML document being parsed. This can't identify a self-closing element (closed by /> ). An empty row element that contains only attributes can be parsed as long as it ends with a closing tag (for example, <row item_a="A" item_b="B"></row> is okay, but <row item_a="A" item_b="B" /> is not).
A classifier for JSON content.
The name of the classifier.
The time that this classifier was registered.
The time that this classifier was last updated.
The version of this classifier.
A JsonPath string defining the JSON data for the classifier to classify. Glue supports a subset of JsonPath, as described in Writing JsonPath Custom Classifiers.
A classifier for comma-separated values (CSV).
The name of the classifier.
The time that this classifier was registered.
The time that this classifier was last updated.
The version of this classifier.
A custom symbol to denote what separates each column entry in the row.
A custom symbol to denote what combines content into a single column value. It must be different from the column delimiter.
Indicates whether the CSV file contains a header.
A list of strings representing column names.
Specifies not to trim values before identifying the type of column values. The default value is true .
Enables the processing of files that contain only one column.
Enables the custom datatype to be configured.
A list of custom datatypes including "BINARY", "BOOLEAN", "DATE", "DECIMAL", "DOUBLE", "FLOAT", "INT", "LONG", "SHORT", "STRING", "TIMESTAMP".
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_classifiers(**kwargs)¶Lists all classifier objects in the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.get_classifiers(
MaxResults=123,
NextToken='string'
)
dict
Response Syntax
{
'Classifiers': [
{
'GrokClassifier': {
'Name': 'string',
'Classification': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'GrokPattern': 'string',
'CustomPatterns': 'string'
},
'XMLClassifier': {
'Name': 'string',
'Classification': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'RowTag': 'string'
},
'JsonClassifier': {
'Name': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'JsonPath': 'string'
},
'CsvClassifier': {
'Name': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'Delimiter': 'string',
'QuoteSymbol': 'string',
'ContainsHeader': 'UNKNOWN'|'PRESENT'|'ABSENT',
'Header': [
'string',
],
'DisableValueTrimming': True|False,
'AllowSingleColumn': True|False,
'CustomDatatypeConfigured': True|False,
'CustomDatatypes': [
'string',
]
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Classifiers (list) --
The requested list of classifier objects.
(dict) --
Classifiers are triggered during a crawl task. A classifier checks whether a given file is in a format it can handle. If it is, the classifier creates a schema in the form of a StructType object that matches that data format.
You can use the standard classifiers that Glue provides, or you can write your own classifiers to best categorize your data sources and specify the appropriate schemas to use for them. A classifier can be a grok classifier, an XML classifier, a JSON classifier, or a custom CSV classifier, as specified in one of the fields in the Classifier object.
GrokClassifier (dict) --
A classifier that uses grok .
Name (string) --
The name of the classifier.
Classification (string) --
An identifier of the data format that the classifier matches, such as Twitter, JSON, Omniture logs, and so on.
CreationTime (datetime) --
The time that this classifier was registered.
LastUpdated (datetime) --
The time that this classifier was last updated.
Version (integer) --
The version of this classifier.
GrokPattern (string) --
The grok pattern applied to a data store by this classifier. For more information, see built-in patterns in Writing Custom Classifiers.
CustomPatterns (string) --
Optional custom grok patterns defined by this classifier. For more information, see custom patterns in Writing Custom Classifiers.
XMLClassifier (dict) --
A classifier for XML content.
Name (string) --
The name of the classifier.
Classification (string) --
An identifier of the data format that the classifier matches.
CreationTime (datetime) --
The time that this classifier was registered.
LastUpdated (datetime) --
The time that this classifier was last updated.
Version (integer) --
The version of this classifier.
RowTag (string) --
The XML tag designating the element that contains each record in an XML document being parsed. This can't identify a self-closing element (closed by /> ). An empty row element that contains only attributes can be parsed as long as it ends with a closing tag (for example, <row item_a="A" item_b="B"></row> is okay, but <row item_a="A" item_b="B" /> is not).
JsonClassifier (dict) --
A classifier for JSON content.
Name (string) --
The name of the classifier.
CreationTime (datetime) --
The time that this classifier was registered.
LastUpdated (datetime) --
The time that this classifier was last updated.
Version (integer) --
The version of this classifier.
JsonPath (string) --
A JsonPath string defining the JSON data for the classifier to classify. Glue supports a subset of JsonPath, as described in Writing JsonPath Custom Classifiers.
CsvClassifier (dict) --
A classifier for comma-separated values (CSV).
Name (string) --
The name of the classifier.
CreationTime (datetime) --
The time that this classifier was registered.
LastUpdated (datetime) --
The time that this classifier was last updated.
Version (integer) --
The version of this classifier.
Delimiter (string) --
A custom symbol to denote what separates each column entry in the row.
QuoteSymbol (string) --
A custom symbol to denote what combines content into a single column value. It must be different from the column delimiter.
ContainsHeader (string) --
Indicates whether the CSV file contains a header.
Header (list) --
A list of strings representing column names.
DisableValueTrimming (boolean) --
Specifies not to trim values before identifying the type of column values. The default value is true .
AllowSingleColumn (boolean) --
Enables the processing of files that contain only one column.
CustomDatatypeConfigured (boolean) --
Enables the custom datatype to be configured.
CustomDatatypes (list) --
A list of custom datatypes including "BINARY", "BOOLEAN", "DATE", "DECIMAL", "DOUBLE", "FLOAT", "INT", "LONG", "SHORT", "STRING", "TIMESTAMP".
NextToken (string) --
A continuation token.
Exceptions
Glue.Client.exceptions.OperationTimeoutExceptionget_column_statistics_for_partition(**kwargs)¶Retrieves partition statistics of columns.
The Identity and Access Management (IAM) permission required for this operation is GetPartition .
See also: AWS API Documentation
Request Syntax
response = client.get_column_statistics_for_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionValues=[
'string',
],
ColumnNames=[
'string',
]
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
[REQUIRED]
A list of partition values identifying the partition.
[REQUIRED]
A list of the column names.
dict
Response Syntax
{
'ColumnStatisticsList': [
{
'ColumnName': 'string',
'ColumnType': 'string',
'AnalyzedTime': datetime(2015, 1, 1),
'StatisticsData': {
'Type': 'BOOLEAN'|'DATE'|'DECIMAL'|'DOUBLE'|'LONG'|'STRING'|'BINARY',
'BooleanColumnStatisticsData': {
'NumberOfTrues': 123,
'NumberOfFalses': 123,
'NumberOfNulls': 123
},
'DateColumnStatisticsData': {
'MinimumValue': datetime(2015, 1, 1),
'MaximumValue': datetime(2015, 1, 1),
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DecimalColumnStatisticsData': {
'MinimumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'MaximumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DoubleColumnStatisticsData': {
'MinimumValue': 123.0,
'MaximumValue': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'LongColumnStatisticsData': {
'MinimumValue': 123,
'MaximumValue': 123,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'StringColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'BinaryColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123
}
}
},
],
'Errors': [
{
'ColumnName': 'string',
'Error': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
ColumnStatisticsList (list) --
List of ColumnStatistics that failed to be retrieved.
(dict) --
Represents the generated column-level statistics for a table or partition.
ColumnName (string) --
Name of column which statistics belong to.
ColumnType (string) --
The data type of the column.
AnalyzedTime (datetime) --
The timestamp of when column statistics were generated.
StatisticsData (dict) --
A ColumnStatisticData object that contains the statistics data values.
Type (string) --
The type of column statistics data.
BooleanColumnStatisticsData (dict) --
Boolean column statistics data.
NumberOfTrues (integer) --
The number of true values in the column.
NumberOfFalses (integer) --
The number of false values in the column.
NumberOfNulls (integer) --
The number of null values in the column.
DateColumnStatisticsData (dict) --
Date column statistics data.
MinimumValue (datetime) --
The lowest value in the column.
MaximumValue (datetime) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
DecimalColumnStatisticsData (dict) --
Decimal column statistics data.
MinimumValue (dict) --
The lowest value in the column.
UnscaledValue (bytes) --
The unscaled numeric value.
Scale (integer) --
The scale that determines where the decimal point falls in the unscaled value.
MaximumValue (dict) --
The highest value in the column.
UnscaledValue (bytes) --
The unscaled numeric value.
Scale (integer) --
The scale that determines where the decimal point falls in the unscaled value.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
DoubleColumnStatisticsData (dict) --
Double column statistics data.
MinimumValue (float) --
The lowest value in the column.
MaximumValue (float) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
LongColumnStatisticsData (dict) --
Long column statistics data.
MinimumValue (integer) --
The lowest value in the column.
MaximumValue (integer) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
StringColumnStatisticsData (dict) --
String column statistics data.
MaximumLength (integer) --
The size of the longest string in the column.
AverageLength (float) --
The average string length in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
BinaryColumnStatisticsData (dict) --
Binary column statistics data.
MaximumLength (integer) --
The size of the longest bit sequence in the column.
AverageLength (float) --
The average bit sequence length in the column.
NumberOfNulls (integer) --
The number of null values in the column.
Errors (list) --
Error occurred during retrieving column statistics data.
(dict) --
Encapsulates a column name that failed and the reason for failure.
ColumnName (string) --
The name of the column that failed.
Error (dict) --
An error message with the reason for the failure of an operation.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_column_statistics_for_table(**kwargs)¶Retrieves table statistics of columns.
The Identity and Access Management (IAM) permission required for this operation is GetTable .
See also: AWS API Documentation
Request Syntax
response = client.get_column_statistics_for_table(
CatalogId='string',
DatabaseName='string',
TableName='string',
ColumnNames=[
'string',
]
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
[REQUIRED]
A list of the column names.
dict
Response Syntax
{
'ColumnStatisticsList': [
{
'ColumnName': 'string',
'ColumnType': 'string',
'AnalyzedTime': datetime(2015, 1, 1),
'StatisticsData': {
'Type': 'BOOLEAN'|'DATE'|'DECIMAL'|'DOUBLE'|'LONG'|'STRING'|'BINARY',
'BooleanColumnStatisticsData': {
'NumberOfTrues': 123,
'NumberOfFalses': 123,
'NumberOfNulls': 123
},
'DateColumnStatisticsData': {
'MinimumValue': datetime(2015, 1, 1),
'MaximumValue': datetime(2015, 1, 1),
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DecimalColumnStatisticsData': {
'MinimumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'MaximumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DoubleColumnStatisticsData': {
'MinimumValue': 123.0,
'MaximumValue': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'LongColumnStatisticsData': {
'MinimumValue': 123,
'MaximumValue': 123,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'StringColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'BinaryColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123
}
}
},
],
'Errors': [
{
'ColumnName': 'string',
'Error': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
ColumnStatisticsList (list) --
List of ColumnStatistics that failed to be retrieved.
(dict) --
Represents the generated column-level statistics for a table or partition.
ColumnName (string) --
Name of column which statistics belong to.
ColumnType (string) --
The data type of the column.
AnalyzedTime (datetime) --
The timestamp of when column statistics were generated.
StatisticsData (dict) --
A ColumnStatisticData object that contains the statistics data values.
Type (string) --
The type of column statistics data.
BooleanColumnStatisticsData (dict) --
Boolean column statistics data.
NumberOfTrues (integer) --
The number of true values in the column.
NumberOfFalses (integer) --
The number of false values in the column.
NumberOfNulls (integer) --
The number of null values in the column.
DateColumnStatisticsData (dict) --
Date column statistics data.
MinimumValue (datetime) --
The lowest value in the column.
MaximumValue (datetime) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
DecimalColumnStatisticsData (dict) --
Decimal column statistics data.
MinimumValue (dict) --
The lowest value in the column.
UnscaledValue (bytes) --
The unscaled numeric value.
Scale (integer) --
The scale that determines where the decimal point falls in the unscaled value.
MaximumValue (dict) --
The highest value in the column.
UnscaledValue (bytes) --
The unscaled numeric value.
Scale (integer) --
The scale that determines where the decimal point falls in the unscaled value.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
DoubleColumnStatisticsData (dict) --
Double column statistics data.
MinimumValue (float) --
The lowest value in the column.
MaximumValue (float) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
LongColumnStatisticsData (dict) --
Long column statistics data.
MinimumValue (integer) --
The lowest value in the column.
MaximumValue (integer) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
StringColumnStatisticsData (dict) --
String column statistics data.
MaximumLength (integer) --
The size of the longest string in the column.
AverageLength (float) --
The average string length in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
BinaryColumnStatisticsData (dict) --
Binary column statistics data.
MaximumLength (integer) --
The size of the longest bit sequence in the column.
AverageLength (float) --
The average bit sequence length in the column.
NumberOfNulls (integer) --
The number of null values in the column.
Errors (list) --
List of ColumnStatistics that failed to be retrieved.
(dict) --
Encapsulates a column name that failed and the reason for failure.
ColumnName (string) --
The name of the column that failed.
Error (dict) --
An error message with the reason for the failure of an operation.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_connection(**kwargs)¶Retrieves a connection definition from the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.get_connection(
CatalogId='string',
Name='string',
HidePassword=True|False
)
[REQUIRED]
The name of the connection definition to retrieve.
dict
Response Syntax
{
'Connection': {
'Name': 'string',
'Description': 'string',
'ConnectionType': 'JDBC'|'SFTP'|'MONGODB'|'KAFKA'|'NETWORK'|'MARKETPLACE'|'CUSTOM',
'MatchCriteria': [
'string',
],
'ConnectionProperties': {
'string': 'string'
},
'PhysicalConnectionRequirements': {
'SubnetId': 'string',
'SecurityGroupIdList': [
'string',
],
'AvailabilityZone': 'string'
},
'CreationTime': datetime(2015, 1, 1),
'LastUpdatedTime': datetime(2015, 1, 1),
'LastUpdatedBy': 'string'
}
}
Response Structure
(dict) --
Connection (dict) --
The requested connection definition.
Name (string) --
The name of the connection definition.
Description (string) --
The description of the connection.
ConnectionType (string) --
The type of the connection. Currently, SFTP is not supported.
MatchCriteria (list) --
A list of criteria that can be used in selecting this connection.
ConnectionProperties (dict) --
These key-value pairs define parameters for the connection:
HOST - The host URI: either the fully qualified domain name (FQDN) or the IPv4 address of the database host.PORT - The port number, between 1024 and 65535, of the port on which the database host is listening for database connections.USER_NAME - The name under which to log in to the database. The value string for USER_NAME is " USERNAME ".PASSWORD - A password, if one is used, for the user name.ENCRYPTED_PASSWORD - When you enable connection password protection by setting ConnectionPasswordEncryption in the Data Catalog encryption settings, this field stores the encrypted password.JDBC_DRIVER_JAR_URI - The Amazon Simple Storage Service (Amazon S3) path of the JAR file that contains the JDBC driver to use.JDBC_DRIVER_CLASS_NAME - The class name of the JDBC driver to use.JDBC_ENGINE - The name of the JDBC engine to use.JDBC_ENGINE_VERSION - The version of the JDBC engine to use.CONFIG_FILES - (Reserved for future use.)INSTANCE_ID - The instance ID to use.JDBC_CONNECTION_URL - The URL for connecting to a JDBC data source.JDBC_ENFORCE_SSL - A Boolean string (true, false) specifying whether Secure Sockets Layer (SSL) with hostname matching is enforced for the JDBC connection on the client. The default is false.CUSTOM_JDBC_CERT - An Amazon S3 location specifying the customer's root certificate. Glue uses this root certificate to validate the customer’s certificate when connecting to the customer database. Glue only handles X.509 certificates. The certificate provided must be DER-encoded and supplied in Base64 encoding PEM format.SKIP_CUSTOM_JDBC_CERT_VALIDATION - By default, this is false . Glue validates the Signature algorithm and Subject Public Key Algorithm for the customer certificate. The only permitted algorithms for the Signature algorithm are SHA256withRSA, SHA384withRSA or SHA512withRSA. For the Subject Public Key Algorithm, the key length must be at least 2048. You can set the value of this property to true to skip Glue’s validation of the customer certificate.CUSTOM_JDBC_CERT_STRING - A custom JDBC certificate string which is used for domain match or distinguished name match to prevent a man-in-the-middle attack. In Oracle database, this is used as the SSL_SERVER_CERT_DN ; in Microsoft SQL Server, this is used as the hostNameInCertificate .CONNECTION_URL - The URL for connecting to a general (non-JDBC) data source.SECRET_ID - The secret ID used for the secret manager of credentials.CONNECTOR_URL - The connector URL for a MARKETPLACE or CUSTOM connection.CONNECTOR_TYPE - The connector type for a MARKETPLACE or CUSTOM connection.CONNECTOR_CLASS_NAME - The connector class name for a MARKETPLACE or CUSTOM connection.KAFKA_BOOTSTRAP_SERVERS - A comma-separated list of host and port pairs that are the addresses of the Apache Kafka brokers in a Kafka cluster to which a Kafka client will connect to and bootstrap itself.KAFKA_SSL_ENABLED - Whether to enable or disable SSL on an Apache Kafka connection. Default value is "true".KAFKA_CUSTOM_CERT - The Amazon S3 URL for the private CA cert file (.pem format). The default is an empty string.KAFKA_SKIP_CUSTOM_CERT_VALIDATION - Whether to skip the validation of the CA cert file or not. Glue validates for three algorithms: SHA256withRSA, SHA384withRSA and SHA512withRSA. Default value is "false".KAFKA_CLIENT_KEYSTORE - The Amazon S3 location of the client keystore file for Kafka client side authentication (Optional).KAFKA_CLIENT_KEYSTORE_PASSWORD - The password to access the provided keystore (Optional).KAFKA_CLIENT_KEY_PASSWORD - A keystore can consist of multiple keys, so this is the password to access the client key to be used with the Kafka server side key (Optional).ENCRYPTED_KAFKA_CLIENT_KEYSTORE_PASSWORD - The encrypted version of the Kafka client keystore password (if the user has the Glue encrypt passwords setting selected).ENCRYPTED_KAFKA_CLIENT_KEY_PASSWORD - The encrypted version of the Kafka client key password (if the user has the Glue encrypt passwords setting selected).KAFKA_SASL_MECHANISM - "SCRAM-SHA-512" or "GSSAPI" . These are the two supported SASL Mechanisms.KAFKA_SASL_SCRAM_USERNAME - A plaintext username used to authenticate with the "SCRAM-SHA-512" mechanism.KAFKA_SASL_SCRAM_PASSWORD - A plaintext password used to authenticate with the "SCRAM-SHA-512" mechanism.ENCRYPTED_KAFKA_SASL_SCRAM_PASSWORD - The encrypted version of the Kafka SASL SCRAM password (if the user has the Glue encrypt passwords setting selected).KAFKA_SASL_GSSAPI_KEYTAB - The S3 location of a Kerberos keytab file. A keytab stores long-term keys for one or more principals. For more information, see MIT Kerberos Documentation: Keytab.KAFKA_SASL_GSSAPI_KRB5_CONF - The S3 location of a Kerberos krb5.conf file. A krb5.conf stores Kerberos configuration information, such as the location of the KDC server. For more information, see MIT Kerberos Documentation: krb5.conf.KAFKA_SASL_GSSAPI_SERVICE - The Kerberos service name, as set with sasl.kerberos.service.name in your Kafka Configuration.KAFKA_SASL_GSSAPI_PRINCIPAL - The name of the Kerberos princial used by Glue. For more information, see Kafka Documentation: Configuring Kafka Brokers.PhysicalConnectionRequirements (dict) --
A map of physical connection requirements, such as virtual private cloud (VPC) and SecurityGroup , that are needed to make this connection successfully.
SubnetId (string) --
The subnet ID used by the connection.
SecurityGroupIdList (list) --
The security group ID list used by the connection.
AvailabilityZone (string) --
The connection's Availability Zone. This field is redundant because the specified subnet implies the Availability Zone to be used. Currently the field must be populated, but it will be deprecated in the future.
CreationTime (datetime) --
The time that this connection definition was created.
LastUpdatedTime (datetime) --
The last time that this connection definition was updated.
LastUpdatedBy (string) --
The user, group, or role that last updated this connection definition.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_connections(**kwargs)¶Retrieves a list of connection definitions from the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.get_connections(
CatalogId='string',
Filter={
'MatchCriteria': [
'string',
],
'ConnectionType': 'JDBC'|'SFTP'|'MONGODB'|'KAFKA'|'NETWORK'|'MARKETPLACE'|'CUSTOM'
},
HidePassword=True|False,
NextToken='string',
MaxResults=123
)
A filter that controls which connections are returned.
A criteria string that must match the criteria recorded in the connection definition for that connection definition to be returned.
The type of connections to return. Currently, SFTP is not supported.
dict
Response Syntax
{
'ConnectionList': [
{
'Name': 'string',
'Description': 'string',
'ConnectionType': 'JDBC'|'SFTP'|'MONGODB'|'KAFKA'|'NETWORK'|'MARKETPLACE'|'CUSTOM',
'MatchCriteria': [
'string',
],
'ConnectionProperties': {
'string': 'string'
},
'PhysicalConnectionRequirements': {
'SubnetId': 'string',
'SecurityGroupIdList': [
'string',
],
'AvailabilityZone': 'string'
},
'CreationTime': datetime(2015, 1, 1),
'LastUpdatedTime': datetime(2015, 1, 1),
'LastUpdatedBy': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
ConnectionList (list) --
A list of requested connection definitions.
(dict) --
Defines a connection to a data source.
Name (string) --
The name of the connection definition.
Description (string) --
The description of the connection.
ConnectionType (string) --
The type of the connection. Currently, SFTP is not supported.
MatchCriteria (list) --
A list of criteria that can be used in selecting this connection.
ConnectionProperties (dict) --
These key-value pairs define parameters for the connection:
HOST - The host URI: either the fully qualified domain name (FQDN) or the IPv4 address of the database host.PORT - The port number, between 1024 and 65535, of the port on which the database host is listening for database connections.USER_NAME - The name under which to log in to the database. The value string for USER_NAME is " USERNAME ".PASSWORD - A password, if one is used, for the user name.ENCRYPTED_PASSWORD - When you enable connection password protection by setting ConnectionPasswordEncryption in the Data Catalog encryption settings, this field stores the encrypted password.JDBC_DRIVER_JAR_URI - The Amazon Simple Storage Service (Amazon S3) path of the JAR file that contains the JDBC driver to use.JDBC_DRIVER_CLASS_NAME - The class name of the JDBC driver to use.JDBC_ENGINE - The name of the JDBC engine to use.JDBC_ENGINE_VERSION - The version of the JDBC engine to use.CONFIG_FILES - (Reserved for future use.)INSTANCE_ID - The instance ID to use.JDBC_CONNECTION_URL - The URL for connecting to a JDBC data source.JDBC_ENFORCE_SSL - A Boolean string (true, false) specifying whether Secure Sockets Layer (SSL) with hostname matching is enforced for the JDBC connection on the client. The default is false.CUSTOM_JDBC_CERT - An Amazon S3 location specifying the customer's root certificate. Glue uses this root certificate to validate the customer’s certificate when connecting to the customer database. Glue only handles X.509 certificates. The certificate provided must be DER-encoded and supplied in Base64 encoding PEM format.SKIP_CUSTOM_JDBC_CERT_VALIDATION - By default, this is false . Glue validates the Signature algorithm and Subject Public Key Algorithm for the customer certificate. The only permitted algorithms for the Signature algorithm are SHA256withRSA, SHA384withRSA or SHA512withRSA. For the Subject Public Key Algorithm, the key length must be at least 2048. You can set the value of this property to true to skip Glue’s validation of the customer certificate.CUSTOM_JDBC_CERT_STRING - A custom JDBC certificate string which is used for domain match or distinguished name match to prevent a man-in-the-middle attack. In Oracle database, this is used as the SSL_SERVER_CERT_DN ; in Microsoft SQL Server, this is used as the hostNameInCertificate .CONNECTION_URL - The URL for connecting to a general (non-JDBC) data source.SECRET_ID - The secret ID used for the secret manager of credentials.CONNECTOR_URL - The connector URL for a MARKETPLACE or CUSTOM connection.CONNECTOR_TYPE - The connector type for a MARKETPLACE or CUSTOM connection.CONNECTOR_CLASS_NAME - The connector class name for a MARKETPLACE or CUSTOM connection.KAFKA_BOOTSTRAP_SERVERS - A comma-separated list of host and port pairs that are the addresses of the Apache Kafka brokers in a Kafka cluster to which a Kafka client will connect to and bootstrap itself.KAFKA_SSL_ENABLED - Whether to enable or disable SSL on an Apache Kafka connection. Default value is "true".KAFKA_CUSTOM_CERT - The Amazon S3 URL for the private CA cert file (.pem format). The default is an empty string.KAFKA_SKIP_CUSTOM_CERT_VALIDATION - Whether to skip the validation of the CA cert file or not. Glue validates for three algorithms: SHA256withRSA, SHA384withRSA and SHA512withRSA. Default value is "false".KAFKA_CLIENT_KEYSTORE - The Amazon S3 location of the client keystore file for Kafka client side authentication (Optional).KAFKA_CLIENT_KEYSTORE_PASSWORD - The password to access the provided keystore (Optional).KAFKA_CLIENT_KEY_PASSWORD - A keystore can consist of multiple keys, so this is the password to access the client key to be used with the Kafka server side key (Optional).ENCRYPTED_KAFKA_CLIENT_KEYSTORE_PASSWORD - The encrypted version of the Kafka client keystore password (if the user has the Glue encrypt passwords setting selected).ENCRYPTED_KAFKA_CLIENT_KEY_PASSWORD - The encrypted version of the Kafka client key password (if the user has the Glue encrypt passwords setting selected).KAFKA_SASL_MECHANISM - "SCRAM-SHA-512" or "GSSAPI" . These are the two supported SASL Mechanisms.KAFKA_SASL_SCRAM_USERNAME - A plaintext username used to authenticate with the "SCRAM-SHA-512" mechanism.KAFKA_SASL_SCRAM_PASSWORD - A plaintext password used to authenticate with the "SCRAM-SHA-512" mechanism.ENCRYPTED_KAFKA_SASL_SCRAM_PASSWORD - The encrypted version of the Kafka SASL SCRAM password (if the user has the Glue encrypt passwords setting selected).KAFKA_SASL_GSSAPI_KEYTAB - The S3 location of a Kerberos keytab file. A keytab stores long-term keys for one or more principals. For more information, see MIT Kerberos Documentation: Keytab.KAFKA_SASL_GSSAPI_KRB5_CONF - The S3 location of a Kerberos krb5.conf file. A krb5.conf stores Kerberos configuration information, such as the location of the KDC server. For more information, see MIT Kerberos Documentation: krb5.conf.KAFKA_SASL_GSSAPI_SERVICE - The Kerberos service name, as set with sasl.kerberos.service.name in your Kafka Configuration.KAFKA_SASL_GSSAPI_PRINCIPAL - The name of the Kerberos princial used by Glue. For more information, see Kafka Documentation: Configuring Kafka Brokers.PhysicalConnectionRequirements (dict) --
A map of physical connection requirements, such as virtual private cloud (VPC) and SecurityGroup , that are needed to make this connection successfully.
SubnetId (string) --
The subnet ID used by the connection.
SecurityGroupIdList (list) --
The security group ID list used by the connection.
AvailabilityZone (string) --
The connection's Availability Zone. This field is redundant because the specified subnet implies the Availability Zone to be used. Currently the field must be populated, but it will be deprecated in the future.
CreationTime (datetime) --
The time that this connection definition was created.
LastUpdatedTime (datetime) --
The last time that this connection definition was updated.
LastUpdatedBy (string) --
The user, group, or role that last updated this connection definition.
NextToken (string) --
A continuation token, if the list of connections returned does not include the last of the filtered connections.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_crawler(**kwargs)¶Retrieves metadata for a specified crawler.
See also: AWS API Documentation
Request Syntax
response = client.get_crawler(
Name='string'
)
[REQUIRED]
The name of the crawler to retrieve metadata for.
{
'Crawler': {
'Name': 'string',
'Role': 'string',
'Targets': {
'S3Targets': [
{
'Path': 'string',
'Exclusions': [
'string',
],
'ConnectionName': 'string',
'SampleSize': 123,
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'JdbcTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'Exclusions': [
'string',
],
'EnableAdditionalMetadata': [
'COMMENTS'|'RAWTYPES',
]
},
],
'MongoDBTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'ScanAll': True|False
},
],
'DynamoDBTargets': [
{
'Path': 'string',
'scanAll': True|False,
'scanRate': 123.0
},
],
'CatalogTargets': [
{
'DatabaseName': 'string',
'Tables': [
'string',
],
'ConnectionName': 'string',
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'DeltaTargets': [
{
'DeltaTables': [
'string',
],
'ConnectionName': 'string',
'WriteManifest': True|False,
'CreateNativeDeltaTable': True|False
},
]
},
'DatabaseName': 'string',
'Description': 'string',
'Classifiers': [
'string',
],
'RecrawlPolicy': {
'RecrawlBehavior': 'CRAWL_EVERYTHING'|'CRAWL_NEW_FOLDERS_ONLY'|'CRAWL_EVENT_MODE'
},
'SchemaChangePolicy': {
'UpdateBehavior': 'LOG'|'UPDATE_IN_DATABASE',
'DeleteBehavior': 'LOG'|'DELETE_FROM_DATABASE'|'DEPRECATE_IN_DATABASE'
},
'LineageConfiguration': {
'CrawlerLineageSettings': 'ENABLE'|'DISABLE'
},
'State': 'READY'|'RUNNING'|'STOPPING',
'TablePrefix': 'string',
'Schedule': {
'ScheduleExpression': 'string',
'State': 'SCHEDULED'|'NOT_SCHEDULED'|'TRANSITIONING'
},
'CrawlElapsedTime': 123,
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'LastCrawl': {
'Status': 'SUCCEEDED'|'CANCELLED'|'FAILED',
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string',
'MessagePrefix': 'string',
'StartTime': datetime(2015, 1, 1)
},
'Version': 123,
'Configuration': 'string',
'CrawlerSecurityConfiguration': 'string',
'LakeFormationConfiguration': {
'UseLakeFormationCredentials': True|False,
'AccountId': 'string'
}
}
}
Response Structure
The metadata for the specified crawler.
The name of the crawler.
The Amazon Resource Name (ARN) of an IAM role that's used to access customer resources, such as Amazon Simple Storage Service (Amazon S3) data.
A collection of targets to crawl.
Specifies Amazon Simple Storage Service (Amazon S3) targets.
Specifies a data store in Amazon Simple Storage Service (Amazon S3).
The path to the Amazon S3 target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
The name of a connection which allows a job or crawler to access data in Amazon S3 within an Amazon Virtual Private Cloud environment (Amazon VPC).
Sets the number of files in each leaf folder to be crawled when crawling sample files in a dataset. If not set, all the files are crawled. A valid value is an integer between 1 and 249.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies JDBC targets.
Specifies a JDBC data store to crawl.
The name of the connection to use to connect to the JDBC target.
The path of the JDBC target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
Specify a value of RAWTYPES or COMMENTS to enable additional metadata in table responses. RAWTYPES provides the native-level datatype. COMMENTS provides comments associated with a column or table in the database.
If you do not need additional metadata, keep the field empty.
Specifies Amazon DocumentDB or MongoDB targets.
Specifies an Amazon DocumentDB or MongoDB data store to crawl.
The name of the connection to use to connect to the Amazon DocumentDB or MongoDB target.
The path of the Amazon DocumentDB or MongoDB target (database/collection).
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
Specifies Amazon DynamoDB targets.
Specifies an Amazon DynamoDB table to crawl.
The name of the DynamoDB table to crawl.
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
The percentage of the configured read capacity units to use by the Glue crawler. Read capacity units is a term defined by DynamoDB, and is a numeric value that acts as rate limiter for the number of reads that can be performed on that table per second.
The valid values are null or a value between 0.1 to 1.5. A null value is used when user does not provide a value, and defaults to 0.5 of the configured Read Capacity Unit (for provisioned tables), or 0.25 of the max configured Read Capacity Unit (for tables using on-demand mode).
Specifies Glue Data Catalog targets.
Specifies an Glue Data Catalog target.
The name of the database to be synchronized.
A list of the tables to be synchronized.
The name of the connection for an Amazon S3-backed Data Catalog table to be a target of the crawl when using a Catalog connection type paired with a NETWORK Connection type.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies Delta data store targets.
Specifies a Delta data store to crawl one or more Delta tables.
A list of the Amazon S3 paths to the Delta tables.
The name of the connection to use to connect to the Delta table target.
Specifies whether to write the manifest files to the Delta table path.
Specifies whether the crawler will create native tables, to allow integration with query engines that support querying of the Delta transaction log directly.
The name of the database in which the crawler's output is stored.
A description of the crawler.
A list of UTF-8 strings that specify the custom classifiers that are associated with the crawler.
A policy that specifies whether to crawl the entire dataset again, or to crawl only folders that were added since the last crawler run.
Specifies whether to crawl the entire dataset again or to crawl only folders that were added since the last crawler run.
A value of CRAWL_EVERYTHING specifies crawling the entire dataset again.
A value of CRAWL_NEW_FOLDERS_ONLY specifies crawling only folders that were added since the last crawler run.
A value of CRAWL_EVENT_MODE specifies crawling only the changes identified by Amazon S3 events.
The policy that specifies update and delete behaviors for the crawler.
The update behavior when the crawler finds a changed schema.
The deletion behavior when the crawler finds a deleted object.
A configuration that specifies whether data lineage is enabled for the crawler.
Specifies whether data lineage is enabled for the crawler. Valid values are:
Indicates whether the crawler is running, or whether a run is pending.
The prefix added to the names of tables that are created.
For scheduled crawlers, the schedule when the crawler runs.
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
The state of the schedule.
If the crawler is running, contains the total time elapsed since the last crawl began.
The time that the crawler was created.
The time that the crawler was last updated.
The status of the last crawl, and potentially error information if an error occurred.
Status of the last crawl.
If an error occurred, the error information about the last crawl.
The log group for the last crawl.
The log stream for the last crawl.
The prefix for a message about this crawl.
The time at which the crawl started.
The version of the crawler.
Crawler configuration information. This versioned JSON string allows users to specify aspects of a crawler's behavior. For more information, see Setting crawler configuration options.
The name of the SecurityConfiguration structure to be used by this crawler.
Specifies whether the crawler should use Lake Formation credentials for the crawler instead of the IAM role credentials.
Specifies whether to use Lake Formation credentials for the crawler instead of the IAM role credentials.
Required for cross account crawls. For same account crawls as the target data, this can be left as null.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_crawler_metrics(**kwargs)¶Retrieves metrics about specified crawlers.
See also: AWS API Documentation
Request Syntax
response = client.get_crawler_metrics(
CrawlerNameList=[
'string',
],
MaxResults=123,
NextToken='string'
)
A list of the names of crawlers about which to retrieve metrics.
dict
Response Syntax
{
'CrawlerMetricsList': [
{
'CrawlerName': 'string',
'TimeLeftSeconds': 123.0,
'StillEstimating': True|False,
'LastRuntimeSeconds': 123.0,
'MedianRuntimeSeconds': 123.0,
'TablesCreated': 123,
'TablesUpdated': 123,
'TablesDeleted': 123
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
CrawlerMetricsList (list) --
A list of metrics for the specified crawler.
(dict) --
Metrics for a specified crawler.
CrawlerName (string) --
The name of the crawler.
TimeLeftSeconds (float) --
The estimated time left to complete a running crawl.
StillEstimating (boolean) --
True if the crawler is still estimating how long it will take to complete this run.
LastRuntimeSeconds (float) --
The duration of the crawler's most recent run, in seconds.
MedianRuntimeSeconds (float) --
The median duration of this crawler's runs, in seconds.
TablesCreated (integer) --
The number of tables created by this crawler.
TablesUpdated (integer) --
The number of tables updated by this crawler.
TablesDeleted (integer) --
The number of tables deleted by this crawler.
NextToken (string) --
A continuation token, if the returned list does not contain the last metric available.
Exceptions
Glue.Client.exceptions.OperationTimeoutExceptionget_crawlers(**kwargs)¶Retrieves metadata for all crawlers defined in the customer account.
See also: AWS API Documentation
Request Syntax
response = client.get_crawlers(
MaxResults=123,
NextToken='string'
)
dict
Response Syntax
{
'Crawlers': [
{
'Name': 'string',
'Role': 'string',
'Targets': {
'S3Targets': [
{
'Path': 'string',
'Exclusions': [
'string',
],
'ConnectionName': 'string',
'SampleSize': 123,
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'JdbcTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'Exclusions': [
'string',
],
'EnableAdditionalMetadata': [
'COMMENTS'|'RAWTYPES',
]
},
],
'MongoDBTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'ScanAll': True|False
},
],
'DynamoDBTargets': [
{
'Path': 'string',
'scanAll': True|False,
'scanRate': 123.0
},
],
'CatalogTargets': [
{
'DatabaseName': 'string',
'Tables': [
'string',
],
'ConnectionName': 'string',
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'DeltaTargets': [
{
'DeltaTables': [
'string',
],
'ConnectionName': 'string',
'WriteManifest': True|False,
'CreateNativeDeltaTable': True|False
},
]
},
'DatabaseName': 'string',
'Description': 'string',
'Classifiers': [
'string',
],
'RecrawlPolicy': {
'RecrawlBehavior': 'CRAWL_EVERYTHING'|'CRAWL_NEW_FOLDERS_ONLY'|'CRAWL_EVENT_MODE'
},
'SchemaChangePolicy': {
'UpdateBehavior': 'LOG'|'UPDATE_IN_DATABASE',
'DeleteBehavior': 'LOG'|'DELETE_FROM_DATABASE'|'DEPRECATE_IN_DATABASE'
},
'LineageConfiguration': {
'CrawlerLineageSettings': 'ENABLE'|'DISABLE'
},
'State': 'READY'|'RUNNING'|'STOPPING',
'TablePrefix': 'string',
'Schedule': {
'ScheduleExpression': 'string',
'State': 'SCHEDULED'|'NOT_SCHEDULED'|'TRANSITIONING'
},
'CrawlElapsedTime': 123,
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'LastCrawl': {
'Status': 'SUCCEEDED'|'CANCELLED'|'FAILED',
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string',
'MessagePrefix': 'string',
'StartTime': datetime(2015, 1, 1)
},
'Version': 123,
'Configuration': 'string',
'CrawlerSecurityConfiguration': 'string',
'LakeFormationConfiguration': {
'UseLakeFormationCredentials': True|False,
'AccountId': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Crawlers (list) --
A list of crawler metadata.
(dict) --
Specifies a crawler program that examines a data source and uses classifiers to try to determine its schema. If successful, the crawler records metadata concerning the data source in the Glue Data Catalog.
Name (string) --
The name of the crawler.
Role (string) --
The Amazon Resource Name (ARN) of an IAM role that's used to access customer resources, such as Amazon Simple Storage Service (Amazon S3) data.
Targets (dict) --
A collection of targets to crawl.
S3Targets (list) --
Specifies Amazon Simple Storage Service (Amazon S3) targets.
(dict) --
Specifies a data store in Amazon Simple Storage Service (Amazon S3).
Path (string) --
The path to the Amazon S3 target.
Exclusions (list) --
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
ConnectionName (string) --
The name of a connection which allows a job or crawler to access data in Amazon S3 within an Amazon Virtual Private Cloud environment (Amazon VPC).
SampleSize (integer) --
Sets the number of files in each leaf folder to be crawled when crawling sample files in a dataset. If not set, all the files are crawled. A valid value is an integer between 1 and 249.
EventQueueArn (string) --
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
DlqEventQueueArn (string) --
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
JdbcTargets (list) --
Specifies JDBC targets.
(dict) --
Specifies a JDBC data store to crawl.
ConnectionName (string) --
The name of the connection to use to connect to the JDBC target.
Path (string) --
The path of the JDBC target.
Exclusions (list) --
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
EnableAdditionalMetadata (list) --
Specify a value of RAWTYPES or COMMENTS to enable additional metadata in table responses. RAWTYPES provides the native-level datatype. COMMENTS provides comments associated with a column or table in the database.
If you do not need additional metadata, keep the field empty.
MongoDBTargets (list) --
Specifies Amazon DocumentDB or MongoDB targets.
(dict) --
Specifies an Amazon DocumentDB or MongoDB data store to crawl.
ConnectionName (string) --
The name of the connection to use to connect to the Amazon DocumentDB or MongoDB target.
Path (string) --
The path of the Amazon DocumentDB or MongoDB target (database/collection).
ScanAll (boolean) --
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
DynamoDBTargets (list) --
Specifies Amazon DynamoDB targets.
(dict) --
Specifies an Amazon DynamoDB table to crawl.
Path (string) --
The name of the DynamoDB table to crawl.
scanAll (boolean) --
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
scanRate (float) --
The percentage of the configured read capacity units to use by the Glue crawler. Read capacity units is a term defined by DynamoDB, and is a numeric value that acts as rate limiter for the number of reads that can be performed on that table per second.
The valid values are null or a value between 0.1 to 1.5. A null value is used when user does not provide a value, and defaults to 0.5 of the configured Read Capacity Unit (for provisioned tables), or 0.25 of the max configured Read Capacity Unit (for tables using on-demand mode).
CatalogTargets (list) --
Specifies Glue Data Catalog targets.
(dict) --
Specifies an Glue Data Catalog target.
DatabaseName (string) --
The name of the database to be synchronized.
Tables (list) --
A list of the tables to be synchronized.
ConnectionName (string) --
The name of the connection for an Amazon S3-backed Data Catalog table to be a target of the crawl when using a Catalog connection type paired with a NETWORK Connection type.
EventQueueArn (string) --
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
DlqEventQueueArn (string) --
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
DeltaTargets (list) --
Specifies Delta data store targets.
(dict) --
Specifies a Delta data store to crawl one or more Delta tables.
DeltaTables (list) --
A list of the Amazon S3 paths to the Delta tables.
ConnectionName (string) --
The name of the connection to use to connect to the Delta table target.
WriteManifest (boolean) --
Specifies whether to write the manifest files to the Delta table path.
CreateNativeDeltaTable (boolean) --
Specifies whether the crawler will create native tables, to allow integration with query engines that support querying of the Delta transaction log directly.
DatabaseName (string) --
The name of the database in which the crawler's output is stored.
Description (string) --
A description of the crawler.
Classifiers (list) --
A list of UTF-8 strings that specify the custom classifiers that are associated with the crawler.
RecrawlPolicy (dict) --
A policy that specifies whether to crawl the entire dataset again, or to crawl only folders that were added since the last crawler run.
RecrawlBehavior (string) --
Specifies whether to crawl the entire dataset again or to crawl only folders that were added since the last crawler run.
A value of CRAWL_EVERYTHING specifies crawling the entire dataset again.
A value of CRAWL_NEW_FOLDERS_ONLY specifies crawling only folders that were added since the last crawler run.
A value of CRAWL_EVENT_MODE specifies crawling only the changes identified by Amazon S3 events.
SchemaChangePolicy (dict) --
The policy that specifies update and delete behaviors for the crawler.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
DeleteBehavior (string) --
The deletion behavior when the crawler finds a deleted object.
LineageConfiguration (dict) --
A configuration that specifies whether data lineage is enabled for the crawler.
CrawlerLineageSettings (string) --
Specifies whether data lineage is enabled for the crawler. Valid values are:
State (string) --
Indicates whether the crawler is running, or whether a run is pending.
TablePrefix (string) --
The prefix added to the names of tables that are created.
Schedule (dict) --
For scheduled crawlers, the schedule when the crawler runs.
ScheduleExpression (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
State (string) --
The state of the schedule.
CrawlElapsedTime (integer) --
If the crawler is running, contains the total time elapsed since the last crawl began.
CreationTime (datetime) --
The time that the crawler was created.
LastUpdated (datetime) --
The time that the crawler was last updated.
LastCrawl (dict) --
The status of the last crawl, and potentially error information if an error occurred.
Status (string) --
Status of the last crawl.
ErrorMessage (string) --
If an error occurred, the error information about the last crawl.
LogGroup (string) --
The log group for the last crawl.
LogStream (string) --
The log stream for the last crawl.
MessagePrefix (string) --
The prefix for a message about this crawl.
StartTime (datetime) --
The time at which the crawl started.
Version (integer) --
The version of the crawler.
Configuration (string) --
Crawler configuration information. This versioned JSON string allows users to specify aspects of a crawler's behavior. For more information, see Setting crawler configuration options.
CrawlerSecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used by this crawler.
LakeFormationConfiguration (dict) --
Specifies whether the crawler should use Lake Formation credentials for the crawler instead of the IAM role credentials.
UseLakeFormationCredentials (boolean) --
Specifies whether to use Lake Formation credentials for the crawler instead of the IAM role credentials.
AccountId (string) --
Required for cross account crawls. For same account crawls as the target data, this can be left as null.
NextToken (string) --
A continuation token, if the returned list has not reached the end of those defined in this customer account.
Exceptions
Glue.Client.exceptions.OperationTimeoutExceptionget_custom_entity_type(**kwargs)¶Retrieves the details of a custom pattern by specifying its name.
See also: AWS API Documentation
Request Syntax
response = client.get_custom_entity_type(
Name='string'
)
[REQUIRED]
The name of the custom pattern that you want to retrieve.
{
'Name': 'string',
'RegexString': 'string',
'ContextWords': [
'string',
]
}
Response Structure
The name of the custom pattern that you retrieved.
A regular expression string that is used for detecting sensitive data in a custom pattern.
A list of context words if specified when you created the custom pattern. If none of these context words are found within the vicinity of the regular expression the data will not be detected as sensitive data.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_data_catalog_encryption_settings(**kwargs)¶Retrieves the security configuration for a specified catalog.
See also: AWS API Documentation
Request Syntax
response = client.get_data_catalog_encryption_settings(
CatalogId='string'
)
{
'DataCatalogEncryptionSettings': {
'EncryptionAtRest': {
'CatalogEncryptionMode': 'DISABLED'|'SSE-KMS',
'SseAwsKmsKeyId': 'string'
},
'ConnectionPasswordEncryption': {
'ReturnConnectionPasswordEncrypted': True|False,
'AwsKmsKeyId': 'string'
}
}
}
Response Structure
The requested security configuration.
Specifies the encryption-at-rest configuration for the Data Catalog.
The encryption-at-rest mode for encrypting Data Catalog data.
The ID of the KMS key to use for encryption at rest.
When connection password protection is enabled, the Data Catalog uses a customer-provided key to encrypt the password as part of CreateConnection or UpdateConnection and store it in the ENCRYPTED_PASSWORD field in the connection properties. You can enable catalog encryption or only password encryption.
When the ReturnConnectionPasswordEncrypted flag is set to "true", passwords remain encrypted in the responses of GetConnection and GetConnections . This encryption takes effect independently from catalog encryption.
An KMS key that is used to encrypt the connection password.
If connection password protection is enabled, the caller of CreateConnection and UpdateConnection needs at least kms:Encrypt permission on the specified KMS key, to encrypt passwords before storing them in the Data Catalog.
You can set the decrypt permission to enable or restrict access on the password key according to your security requirements.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_data_quality_result(**kwargs)¶Retrieves the result of a data quality rule evaluation.
See also: AWS API Documentation
Request Syntax
response = client.get_data_quality_result(
ResultId='string'
)
[REQUIRED]
A unique result ID for the data quality result.
{
'ResultId': 'string',
'Score': 123.0,
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'RulesetName': 'string',
'EvaluationContext': 'string',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobName': 'string',
'JobRunId': 'string',
'RulesetEvaluationRunId': 'string',
'RuleResults': [
{
'Name': 'string',
'Description': 'string',
'EvaluationMessage': 'string',
'Result': 'PASS'|'FAIL'|'ERROR'
},
]
}
Response Structure
A unique result ID for the data quality result.
An aggregate data quality score. Represents the ratio of rules that passed to the total number of rules.
The table associated with the data quality result, if any.
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.The name of the ruleset associated with the data quality result.
In the context of a job in Glue Studio, each node in the canvas is typically assigned some sort of name and data quality nodes will have names. In the case of multiple nodes, the evaluationContext can differentiate the nodes.
The date and time when the run for this data quality result started.
The date and time when the run for this data quality result was completed.
The job name associated with the data quality result, if any.
The job run ID associated with the data quality result, if any.
The unique run ID associated with the ruleset evaluation.
A list of DataQualityRuleResult objects representing the results for each rule.
Describes the result of the evaluation of a data quality rule.
The name of the data quality rule.
A description of the data quality rule.
An evaluation message.
A pass or fail status for the rule.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.EntityNotFoundExceptionget_data_quality_rule_recommendation_run(**kwargs)¶Gets the specified recommendation run that was used to generate rules.
See also: AWS API Documentation
Request Syntax
response = client.get_data_quality_rule_recommendation_run(
RunId='string'
)
[REQUIRED]
The unique run identifier associated with this run.
{
'RunId': 'string',
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'Role': 'string',
'NumberOfWorkers': 123,
'Timeout': 123,
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'ErrorString': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ExecutionTime': 123,
'RecommendedRuleset': 'string',
'CreatedRulesetName': 'string'
}
Response Structure
The unique run identifier associated with this run.
The data source (an Glue table) associated with this run.
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.An IAM role supplied to encrypt the results of the run.
The number of G.1X workers to be used in the run. The default is 5.
The timeout for a run in minutes. This is the maximum time that a run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
The status for this run.
The error strings that are associated with the run.
The date and time when this run started.
A timestamp. The last point in time when this data quality rule recommendation run was modified.
The date and time when this run was completed.
The amount of time (in seconds) that the run consumed resources.
When a start rule recommendation run completes, it creates a recommended ruleset (a set of rules). This member has those rules in Data Quality Definition Language (DQDL) format.
The name of the ruleset that was created by the run.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionget_data_quality_ruleset(**kwargs)¶Returns an existing ruleset by identifier or name.
See also: AWS API Documentation
Request Syntax
response = client.get_data_quality_ruleset(
Name='string'
)
[REQUIRED]
The name of the ruleset.
{
'Name': 'string',
'Description': 'string',
'Ruleset': 'string',
'TargetTable': {
'TableName': 'string',
'DatabaseName': 'string'
},
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'RecommendationRunId': 'string'
}
Response Structure
The name of the ruleset.
A description of the ruleset.
A Data Quality Definition Language (DQDL) ruleset. For more information, see the Glue developer guide.
The name and database name of the target table.
The name of the Glue table.
The name of the database where the Glue table exists.
A timestamp. The time and date that this data quality ruleset was created.
A timestamp. The last point in time when this data quality ruleset was modified.
When a ruleset was created from a recommendation run, this run ID is generated to link the two together.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionget_data_quality_ruleset_evaluation_run(**kwargs)¶Retrieves a specific run where a ruleset is evaluated against a data source.
See also: AWS API Documentation
Request Syntax
response = client.get_data_quality_ruleset_evaluation_run(
RunId='string'
)
[REQUIRED]
The unique run identifier associated with this run.
{
'RunId': 'string',
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'Role': 'string',
'NumberOfWorkers': 123,
'Timeout': 123,
'AdditionalRunOptions': {
'CloudWatchMetricsEnabled': True|False,
'ResultsS3Prefix': 'string'
},
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'ErrorString': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ExecutionTime': 123,
'RulesetNames': [
'string',
],
'ResultIds': [
'string',
]
}
Response Structure
The unique run identifier associated with this run.
The data source (an Glue table) associated with this evaluation run.
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.An IAM role supplied to encrypt the results of the run.
The number of G.1X workers to be used in the run. The default is 5.
The timeout for a run in minutes. This is the maximum time that a run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
Additional run options you can specify for an evaluation run.
Whether or not to enable CloudWatch metrics.
Prefix for Amazon S3 to store results.
The status for this run.
The error strings that are associated with the run.
The date and time when this run started.
A timestamp. The last point in time when this data quality rule recommendation run was modified.
The date and time when this run was completed.
The amount of time (in seconds) that the run consumed resources.
A list of ruleset names for the run.
A list of result IDs for the data quality results for the run.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionget_database(**kwargs)¶Retrieves the definition of a specified database.
See also: AWS API Documentation
Request Syntax
response = client.get_database(
CatalogId='string',
Name='string'
)
[REQUIRED]
The name of the database to retrieve. For Hive compatibility, this should be all lowercase.
dict
Response Syntax
{
'Database': {
'Name': 'string',
'Description': 'string',
'LocationUri': 'string',
'Parameters': {
'string': 'string'
},
'CreateTime': datetime(2015, 1, 1),
'CreateTableDefaultPermissions': [
{
'Principal': {
'DataLakePrincipalIdentifier': 'string'
},
'Permissions': [
'ALL'|'SELECT'|'ALTER'|'DROP'|'DELETE'|'INSERT'|'CREATE_DATABASE'|'CREATE_TABLE'|'DATA_LOCATION_ACCESS',
]
},
],
'TargetDatabase': {
'CatalogId': 'string',
'DatabaseName': 'string'
},
'CatalogId': 'string'
}
}
Response Structure
(dict) --
Database (dict) --
The definition of the specified database in the Data Catalog.
Name (string) --
The name of the database. For Hive compatibility, this is folded to lowercase when it is stored.
Description (string) --
A description of the database.
LocationUri (string) --
The location of the database (for example, an HDFS path).
Parameters (dict) --
These key-value pairs define parameters and properties of the database.
CreateTime (datetime) --
The time at which the metadata database was created in the catalog.
CreateTableDefaultPermissions (list) --
Creates a set of default permissions on the table for principals.
(dict) --
Permissions granted to a principal.
Principal (dict) --
The principal who is granted permissions.
DataLakePrincipalIdentifier (string) --
An identifier for the Lake Formation principal.
Permissions (list) --
The permissions that are granted to the principal.
TargetDatabase (dict) --
A DatabaseIdentifier structure that describes a target database for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the database resides.
DatabaseName (string) --
The name of the catalog database.
CatalogId (string) --
The ID of the Data Catalog in which the database resides.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_databases(**kwargs)¶Retrieves all databases defined in a given Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.get_databases(
CatalogId='string',
NextToken='string',
MaxResults=123,
ResourceShareType='FOREIGN'|'ALL'
)
Databases . If none is provided, the Amazon Web Services account ID is used by default.Allows you to specify that you want to list the databases shared with your account. The allowable values are FOREIGN or ALL .
FOREIGN , will list the databases shared with your account.ALL , will list the databases shared with your account, as well as the databases in yor local account.dict
Response Syntax
{
'DatabaseList': [
{
'Name': 'string',
'Description': 'string',
'LocationUri': 'string',
'Parameters': {
'string': 'string'
},
'CreateTime': datetime(2015, 1, 1),
'CreateTableDefaultPermissions': [
{
'Principal': {
'DataLakePrincipalIdentifier': 'string'
},
'Permissions': [
'ALL'|'SELECT'|'ALTER'|'DROP'|'DELETE'|'INSERT'|'CREATE_DATABASE'|'CREATE_TABLE'|'DATA_LOCATION_ACCESS',
]
},
],
'TargetDatabase': {
'CatalogId': 'string',
'DatabaseName': 'string'
},
'CatalogId': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
DatabaseList (list) --
A list of Database objects from the specified catalog.
(dict) --
The Database object represents a logical grouping of tables that might reside in a Hive metastore or an RDBMS.
Name (string) --
The name of the database. For Hive compatibility, this is folded to lowercase when it is stored.
Description (string) --
A description of the database.
LocationUri (string) --
The location of the database (for example, an HDFS path).
Parameters (dict) --
These key-value pairs define parameters and properties of the database.
CreateTime (datetime) --
The time at which the metadata database was created in the catalog.
CreateTableDefaultPermissions (list) --
Creates a set of default permissions on the table for principals.
(dict) --
Permissions granted to a principal.
Principal (dict) --
The principal who is granted permissions.
DataLakePrincipalIdentifier (string) --
An identifier for the Lake Formation principal.
Permissions (list) --
The permissions that are granted to the principal.
TargetDatabase (dict) --
A DatabaseIdentifier structure that describes a target database for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the database resides.
DatabaseName (string) --
The name of the catalog database.
CatalogId (string) --
The ID of the Data Catalog in which the database resides.
NextToken (string) --
A continuation token for paginating the returned list of tokens, returned if the current segment of the list is not the last.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_dataflow_graph(**kwargs)¶Transforms a Python script into a directed acyclic graph (DAG).
See also: AWS API Documentation
Request Syntax
response = client.get_dataflow_graph(
PythonScript='string'
)
{
'DagNodes': [
{
'Id': 'string',
'NodeType': 'string',
'Args': [
{
'Name': 'string',
'Value': 'string',
'Param': True|False
},
],
'LineNumber': 123
},
],
'DagEdges': [
{
'Source': 'string',
'Target': 'string',
'TargetParameter': 'string'
},
]
}
Response Structure
A list of the nodes in the resulting DAG.
Represents a node in a directed acyclic graph (DAG)
A node identifier that is unique within the node's graph.
The type of node that this is.
Properties of the node, in the form of name-value pairs.
An argument or property of a node.
The name of the argument or property.
The value of the argument or property.
True if the value is used as a parameter.
The line number of the node.
A list of the edges in the resulting DAG.
Represents a directional edge in a directed acyclic graph (DAG).
The ID of the node at which the edge starts.
The ID of the node at which the edge ends.
The target of the edge.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_dev_endpoint(**kwargs)¶Retrieves information about a specified development endpoint.
Note
When you create a development endpoint in a virtual private cloud (VPC), Glue returns only a private IP address, and the public IP address field is not populated. When you create a non-VPC development endpoint, Glue returns only a public IP address.
See also: AWS API Documentation
Request Syntax
response = client.get_dev_endpoint(
EndpointName='string'
)
[REQUIRED]
Name of the DevEndpoint to retrieve information for.
{
'DevEndpoint': {
'EndpointName': 'string',
'RoleArn': 'string',
'SecurityGroupIds': [
'string',
],
'SubnetId': 'string',
'YarnEndpointAddress': 'string',
'PrivateAddress': 'string',
'ZeppelinRemoteSparkInterpreterPort': 123,
'PublicAddress': 'string',
'Status': 'string',
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'GlueVersion': 'string',
'NumberOfWorkers': 123,
'NumberOfNodes': 123,
'AvailabilityZone': 'string',
'VpcId': 'string',
'ExtraPythonLibsS3Path': 'string',
'ExtraJarsS3Path': 'string',
'FailureReason': 'string',
'LastUpdateStatus': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'LastModifiedTimestamp': datetime(2015, 1, 1),
'PublicKey': 'string',
'PublicKeys': [
'string',
],
'SecurityConfiguration': 'string',
'Arguments': {
'string': 'string'
}
}
}
Response Structure
A DevEndpoint definition.
The name of the DevEndpoint .
The Amazon Resource Name (ARN) of the IAM role used in this DevEndpoint .
A list of security group identifiers used in this DevEndpoint .
The subnet ID for this DevEndpoint .
The YARN endpoint address used by this DevEndpoint .
A private IP address to access the DevEndpoint within a VPC if the DevEndpoint is created within one. The PrivateAddress field is present only when you create the DevEndpoint within your VPC.
The Apache Zeppelin port for the remote Apache Spark interpreter.
The public IP address used by this DevEndpoint . The PublicAddress field is present only when you create a non-virtual private cloud (VPC) DevEndpoint .
The current status of this DevEndpoint .
The type of predefined worker that is allocated to the development endpoint. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.Known issue: when a development endpoint is created with the G.2X WorkerType configuration, the Spark drivers for the development endpoint will run on 4 vCPU, 16 GB of memory, and a 64 GB disk.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for running your ETL scripts on development endpoints.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Development endpoints that are created without specifying a Glue version default to Glue 0.9.
You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
The number of workers of a defined workerType that are allocated to the development endpoint.
The maximum number of workers you can define are 299 for G.1X , and 149 for G.2X .
The number of Glue Data Processing Units (DPUs) allocated to this DevEndpoint .
The Amazon Web Services Availability Zone where this DevEndpoint is located.
The ID of the virtual private cloud (VPC) used by this DevEndpoint .
The paths to one or more Python libraries in an Amazon S3 bucket that should be loaded in your DevEndpoint . Multiple values must be complete paths separated by a comma.
Note
You can only use pure Python libraries with a DevEndpoint . Libraries that rely on C extensions, such as the pandas Python data analysis library, are not currently supported.
The path to one or more Java .jar files in an S3 bucket that should be loaded in your DevEndpoint .
Note
You can only use pure Java/Scala libraries with a DevEndpoint .
The reason for a current failure in this DevEndpoint .
The status of the last update.
The point in time at which this DevEndpoint was created.
The point in time at which this DevEndpoint was last modified.
The public key to be used by this DevEndpoint for authentication. This attribute is provided for backward compatibility because the recommended attribute to use is public keys.
A list of public keys to be used by the DevEndpoints for authentication. Using this attribute is preferred over a single public key because the public keys allow you to have a different private key per client.
Note
If you previously created an endpoint with a public key, you must remove that key to be able to set a list of public keys. Call the UpdateDevEndpoint API operation with the public key content in the deletePublicKeys attribute, and the list of new keys in the addPublicKeys attribute.
The name of the SecurityConfiguration structure to be used with this DevEndpoint .
A map of arguments used to configure the DevEndpoint .
Valid arguments are:
"--enable-glue-datacatalog": ""You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionget_dev_endpoints(**kwargs)¶Retrieves all the development endpoints in this Amazon Web Services account.
Note
When you create a development endpoint in a virtual private cloud (VPC), Glue returns only a private IP address and the public IP address field is not populated. When you create a non-VPC development endpoint, Glue returns only a public IP address.
See also: AWS API Documentation
Request Syntax
response = client.get_dev_endpoints(
MaxResults=123,
NextToken='string'
)
dict
Response Syntax
{
'DevEndpoints': [
{
'EndpointName': 'string',
'RoleArn': 'string',
'SecurityGroupIds': [
'string',
],
'SubnetId': 'string',
'YarnEndpointAddress': 'string',
'PrivateAddress': 'string',
'ZeppelinRemoteSparkInterpreterPort': 123,
'PublicAddress': 'string',
'Status': 'string',
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'GlueVersion': 'string',
'NumberOfWorkers': 123,
'NumberOfNodes': 123,
'AvailabilityZone': 'string',
'VpcId': 'string',
'ExtraPythonLibsS3Path': 'string',
'ExtraJarsS3Path': 'string',
'FailureReason': 'string',
'LastUpdateStatus': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'LastModifiedTimestamp': datetime(2015, 1, 1),
'PublicKey': 'string',
'PublicKeys': [
'string',
],
'SecurityConfiguration': 'string',
'Arguments': {
'string': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
DevEndpoints (list) --
A list of DevEndpoint definitions.
(dict) --
A development endpoint where a developer can remotely debug extract, transform, and load (ETL) scripts.
EndpointName (string) --
The name of the DevEndpoint .
RoleArn (string) --
The Amazon Resource Name (ARN) of the IAM role used in this DevEndpoint .
SecurityGroupIds (list) --
A list of security group identifiers used in this DevEndpoint .
SubnetId (string) --
The subnet ID for this DevEndpoint .
YarnEndpointAddress (string) --
The YARN endpoint address used by this DevEndpoint .
PrivateAddress (string) --
A private IP address to access the DevEndpoint within a VPC if the DevEndpoint is created within one. The PrivateAddress field is present only when you create the DevEndpoint within your VPC.
ZeppelinRemoteSparkInterpreterPort (integer) --
The Apache Zeppelin port for the remote Apache Spark interpreter.
PublicAddress (string) --
The public IP address used by this DevEndpoint . The PublicAddress field is present only when you create a non-virtual private cloud (VPC) DevEndpoint .
Status (string) --
The current status of this DevEndpoint .
WorkerType (string) --
The type of predefined worker that is allocated to the development endpoint. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.Known issue: when a development endpoint is created with the G.2X WorkerType configuration, the Spark drivers for the development endpoint will run on 4 vCPU, 16 GB of memory, and a 64 GB disk.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for running your ETL scripts on development endpoints.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Development endpoints that are created without specifying a Glue version default to Glue 0.9.
You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated to the development endpoint.
The maximum number of workers you can define are 299 for G.1X , and 149 for G.2X .
NumberOfNodes (integer) --
The number of Glue Data Processing Units (DPUs) allocated to this DevEndpoint .
AvailabilityZone (string) --
The Amazon Web Services Availability Zone where this DevEndpoint is located.
VpcId (string) --
The ID of the virtual private cloud (VPC) used by this DevEndpoint .
ExtraPythonLibsS3Path (string) --
The paths to one or more Python libraries in an Amazon S3 bucket that should be loaded in your DevEndpoint . Multiple values must be complete paths separated by a comma.
Note
You can only use pure Python libraries with a DevEndpoint . Libraries that rely on C extensions, such as the pandas Python data analysis library, are not currently supported.
ExtraJarsS3Path (string) --
The path to one or more Java .jar files in an S3 bucket that should be loaded in your DevEndpoint .
Note
You can only use pure Java/Scala libraries with a DevEndpoint .
FailureReason (string) --
The reason for a current failure in this DevEndpoint .
LastUpdateStatus (string) --
The status of the last update.
CreatedTimestamp (datetime) --
The point in time at which this DevEndpoint was created.
LastModifiedTimestamp (datetime) --
The point in time at which this DevEndpoint was last modified.
PublicKey (string) --
The public key to be used by this DevEndpoint for authentication. This attribute is provided for backward compatibility because the recommended attribute to use is public keys.
PublicKeys (list) --
A list of public keys to be used by the DevEndpoints for authentication. Using this attribute is preferred over a single public key because the public keys allow you to have a different private key per client.
Note
If you previously created an endpoint with a public key, you must remove that key to be able to set a list of public keys. Call the UpdateDevEndpoint API operation with the public key content in the deletePublicKeys attribute, and the list of new keys in the addPublicKeys attribute.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this DevEndpoint .
Arguments (dict) --
A map of arguments used to configure the DevEndpoint .
Valid arguments are:
"--enable-glue-datacatalog": ""You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
NextToken (string) --
A continuation token, if not all DevEndpoint definitions have yet been returned.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionget_job(**kwargs)¶Retrieves an existing job definition.
See also: AWS API Documentation
Request Syntax
response = client.get_job(
JobName='string'
)
[REQUIRED]
The name of the job definition to retrieve.
{
'Job': {
'Name': 'string',
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
}
}
Response Structure
The requested job definition.
The name you assign to this job definition.
A description of the job.
This field is reserved for future use.
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
The time and date that this job definition was created.
The last point in time when this job definition was modified.
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
The JobCommand that runs this job.
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
The default arguments for this job, specified as name-value pairs.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Non-overridable arguments for this job, specified as name-value pairs.
The connections used for this job.
A list of connections used by the job.
The maximum number of times to retry this job after a JobRun fails.
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to runs of this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.The number of workers of a defined workerType that are allocated when a job runs.
The name of the SecurityConfiguration structure to be used with this job.
Specifies configuration properties of a job notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
CodeGenConfigurationNodeenumerates all valid Node types. One and only one of its member variables can be populated.
Specifies a connector to an Amazon Athena data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
The name of the table in the data source.
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
Specifies the data schema for the custom Athena source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to a JDBC data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
Additional connection options for the connector.
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
The minimum value of partitionColumn that is used to decide partition stride.
The maximum value of partitionColumn that is used to decide partition stride.
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
The name of the job bookmark keys on which to sort.
Specifies an ascending or descending sort order.
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
The name of the table in the data source.
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
Specifies the data schema for the custom JDBC source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to an Apache Spark data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies data schema for the custom spark source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a data store in the Glue Data Catalog.
The name of the data store.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Amazon Redshift data store.
The name of the Amazon Redshift data store.
The database to read from.
The database table to read from.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
Specifies an Amazon S3 data store in the Glue Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a command-separated value (CSV) data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
A Boolean value that specifies whether to write the header to output. The default value is True .
A Boolean value that specifies whether to skip the first data line. The default value is False .
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
Specifies the data schema for the S3 CSV source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a JSON data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
A JsonPath string defining the JSON data.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
Specifies the data schema for the S3 JSON source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies an Apache Parquet data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the data schema for the S3 Parquet source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a Relational database data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a DynamoDB data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
The name of the connection that is associated with the connector.
The name of the table in the data target.
The name of a connector that will be used.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
Additional connection options for the connector.
Specifies the data schema for the JDBC target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses an Apache Spark connector.
The name of the data target.
The nodes that are inputs to the data target.
The name of a connection for an Apache Spark connector.
The name of an Apache Spark connector.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies the data schema for the custom spark target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses a Glue Data Catalog table.
The name of your data target.
The nodes that are inputs to the data target.
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
Specifies a target that uses Amazon Redshift.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
The set of options to configure an upsert operation when writing to a Redshift target.
The physical location of the Redshift table.
The name of the connection to use to write to Redshift.
The keys used to determine whether to perform an update or insert.
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a data target that writes to Amazon S3.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Specifies the data output format for the target.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
The name of the transform node.
The data inputs identified by their node names.
Specifies the mapping of data property keys in the data source to data property keys in the data target.
Specifies the mapping of data property keys.
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
The table or column to be modified.
The type of the data to be modified.
The data type that the data is to be modified to.
If true, then the column is removed.
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
Specifies a transform that chooses the data property keys that you want to keep.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses the data property keys that you want to drop.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that renames a single data property key.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the source data.
A JSON path to a variable in the data structure for the target data.
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
The name of the transform node.
The data inputs identified by their node names.
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Specifies a number of records to write starting from the beginning of the dataset.
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
The name of the transform node.
The data inputs identified by their node names.
Specifies the type of join to be performed on the datasets.
A list of the two columns to be joined.
Specifies a column to be joined.
The column to be joined.
The key of the column to be joined.
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
The name of the transform node.
The data inputs identified by their node names.
The index for the DynamicFrame to be selected.
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the dataset that is imputed.
A JSON path to a variable in the data structure for the dataset that is filled.
Specifies a transform that splits a dataset into two, based on a filter condition.
The name of the transform node.
The data inputs identified by their node names.
The operator used to filter rows by comparing the key value to a specified value.
Specifies a filter expression.
Specifies a filter expression.
The type of operation to perform in the expression.
Whether the expression is to be negated.
A list of filter values.
Represents a single entry in the list of values for a FilterExpression .
The type of filter value.
The value to be associated.
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
The name of the transform node.
The data inputs identified by their node names.
The custom code that is used to perform the data transformation.
The name defined for the custom code node class.
Specifies the data schema for the custom code transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
The name of the transform node.
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
A SQL query that must use Spark SQL syntax and return a single data set.
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
Represents a single entry in the list of values for SqlAliases .
A table, or a column in a table.
A temporary name given to a table, or a column in a table.
Specifies the data schema for the SparkSQL transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a direct Amazon Kinesis data source.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store.
The name of the data store.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a Kinesis data source in the Glue Data Catalog.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store in the Data Catalog.
The name of the data store.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
The name of the transform node.
The data inputs identified by their node names.
A structure that represents whether certain values are recognized as null values for removal.
Specifies that an empty string is considered as a null value.
Specifies that a value spelling out the word 'null' is considered as a null value.
Specifies that an integer value of -1 is considered as a null value.
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
The value of the null placeholder.
The datatype of the value.
The datatype of the value.
A label assigned to the datatype.
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
The name of the transform node.
The data inputs identified by their node names.
The source DynamicFrame that will be merged with a staging DynamicFrame .
The list of primary key fields to match records from the source and staging dynamic frames.
Specifies a transform that combines the rows from two or more datasets into a single result.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
Specifies a transform that identifies, removes or masks PII data.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of PIIDetection transform.
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
Indicates the output column name that will contain any entity type detected in that row.
Indicates the fraction of the data to sample when scanning for PII entities.
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
Indicates the value that will replace the detected entity.
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
The name of the transform node.
Specifies the fields and rows to use as inputs for the aggregate transform.
Specifies the fields to group by.
Specifies the aggregate functions to be performed on specified fields.
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Specifies the column on the data set on which the aggregation function will be applied.
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
Specifies a transform that removes rows of repeating data from a data set.
The name of the transform node.
The data inputs identified by their node names.
The name of the columns to be merged or removed if repeating.
Specifies a data target that writes to a goverened catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the governed catalog.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data source in a goverened Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a MySQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Oracle data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a PostgresSQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a target that uses Microsoft SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses MySQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Oracle SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Postgres SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a custom visual transform created by a user.
Specifies the name of the dynamic transform.
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Specifies the inputs for the dynamic transform that are required.
Specifies the parameters of the dynamic transform.
Specifies the parameters in the config file of the dynamic transform.
Specifies the name of the parameter in the config file of the dynamic transform.
Specifies the parameter type in the config file of the dynamic transform.
Specifies the validation rule in the config file of the dynamic transform.
Specifies the validation message in the config file of the dynamic transform.
Specifies the value of the parameter in the config file of the dynamic transform.
Specifies the list type of the parameter in the config file of the dynamic transform.
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
Specifies the name of the function of the dynamic transform.
Specifies the path of the dynamic transform source and config files.
This field is not used and will be deprecated in future release.
Specifies your data quality evaluation criteria.
The name of the data quality evaluation.
The inputs of your data quality evaluation.
The ruleset for your data quality evaluation.
The output of your data quality evaluation.
Options to configure how your results are published.
The context of the evaluation.
The Amazon S3 prefix prepended to the results.
Enable metrics for your data quality results.
Enable publishing for your data quality results.
Options to configure how your job will stop if your data quality evaluation fails.
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
Indicates whether the job is run with a standard or flexible execution class. The standard execution class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
The provider for the remote repository.
The name of the remote repository that contains the job artifacts.
The owner of the remote repository that contains the job artifacts.
An optional branch in the remote repository.
An optional folder in the remote repository.
The last commit ID for a commit in the remote repository.
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
The value of an authorization token.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_job_bookmark(**kwargs)¶Returns information on a job bookmark entry.
For more information about enabling and using job bookmarks, see:
See also: AWS API Documentation
Request Syntax
response = client.get_job_bookmark(
JobName='string',
RunId='string'
)
[REQUIRED]
The name of the job in question.
dict
Response Syntax
{
'JobBookmarkEntry': {
'JobName': 'string',
'Version': 123,
'Run': 123,
'Attempt': 123,
'PreviousRunId': 'string',
'RunId': 'string',
'JobBookmark': 'string'
}
}
Response Structure
(dict) --
JobBookmarkEntry (dict) --
A structure that defines a point that a job can resume processing.
JobName (string) --
The name of the job in question.
Version (integer) --
The version of the job.
Run (integer) --
The run ID number.
Attempt (integer) --
The attempt ID number.
PreviousRunId (string) --
The unique run identifier associated with the previous job run.
RunId (string) --
The run ID number.
JobBookmark (string) --
The bookmark itself.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ValidationExceptionget_job_run(**kwargs)¶Retrieves the metadata for a given job run.
See also: AWS API Documentation
Request Syntax
response = client.get_job_run(
JobName='string',
RunId='string',
PredecessorsIncluded=True|False
)
[REQUIRED]
Name of the job definition being run.
[REQUIRED]
The ID of the job run.
dict
Response Syntax
{
'JobRun': {
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
}
}
Response Structure
(dict) --
JobRun (dict) --
The requested job-run metadata.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_job_runs(**kwargs)¶Retrieves metadata for all runs of a given job definition.
See also: AWS API Documentation
Request Syntax
response = client.get_job_runs(
JobName='string',
NextToken='string',
MaxResults=123
)
[REQUIRED]
The name of the job definition for which to retrieve all job runs.
dict
Response Syntax
{
'JobRuns': [
{
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
JobRuns (list) --
A list of job-run metadata objects.
(dict) --
Contains information about a job run.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
NextToken (string) --
A continuation token, if not all requested job runs have been returned.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_jobs(**kwargs)¶Retrieves all current job definitions.
See also: AWS API Documentation
Request Syntax
response = client.get_jobs(
NextToken='string',
MaxResults=123
)
dict
Response Syntax
{
'Jobs': [
{
'Name': 'string',
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Jobs (list) --
A list of job definitions.
(dict) --
Specifies a job definition.
Name (string) --
The name you assign to this job definition.
Description (string) --
A description of the job.
LogUri (string) --
This field is reserved for future use.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
CreatedOn (datetime) --
The time and date that this job definition was created.
LastModifiedOn (datetime) --
The last point in time when this job definition was modified.
ExecutionProperty (dict) --
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
MaxConcurrentRuns (integer) --
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
Command (dict) --
The JobCommand that runs this job.
Name (string) --
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
ScriptLocation (string) --
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
PythonVersion (string) --
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
DefaultArguments (dict) --
The default arguments for this job, specified as name-value pairs.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
NonOverridableArguments (dict) --
Non-overridable arguments for this job, specified as name-value pairs.
Connections (dict) --
The connections used for this job.
Connections (list) --
A list of connections used by the job.
MaxRetries (integer) --
The maximum number of times to retry this job after a JobRun fails.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to runs of this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Timeout (integer) --
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
MaxCapacity (float) --
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job.
NotificationProperty (dict) --
Specifies configuration properties of a job notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
CodeGenConfigurationNodes (dict) --
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
(string) --
(dict) --
CodeGenConfigurationNodeenumerates all valid Node types. One and only one of its member variables can be populated.
AthenaConnectorSource (dict) --
Specifies a connector to an Amazon Athena data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
ConnectionTable (string) --
The name of the table in the data source.
SchemaName (string) --
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
OutputSchemas (list) --
Specifies the data schema for the custom Athena source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
JDBCConnectorSource (dict) --
Specifies a connector to a JDBC data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
FilterPredicate (string) --
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
PartitionColumn (string) --
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
LowerBound (integer) --
The minimum value of partitionColumn that is used to decide partition stride.
UpperBound (integer) --
The maximum value of partitionColumn that is used to decide partition stride.
NumPartitions (integer) --
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
JobBookmarkKeys (list) --
The name of the job bookmark keys on which to sort.
JobBookmarkKeysSortOrder (string) --
Specifies an ascending or descending sort order.
DataTypeMapping (dict) --
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
ConnectionTable (string) --
The name of the table in the data source.
Query (string) --
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
OutputSchemas (list) --
Specifies the data schema for the custom JDBC source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorSource (dict) --
Specifies a connector to an Apache Spark data source.
Name (string) --
The name of the data source.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectorName (string) --
The name of a connector that assists with accessing the data store in Glue Studio.
ConnectionType (string) --
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
OutputSchemas (list) --
Specifies data schema for the custom spark source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogSource (dict) --
Specifies a data store in the Glue Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
RedshiftSource (dict) --
Specifies an Amazon Redshift data store.
Name (string) --
The name of the Amazon Redshift data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
S3CatalogSource (dict) --
Specifies an Amazon S3 data store in the Glue Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
S3CsvSource (dict) --
Specifies a command-separated value (CSV) data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
Separator (string) --
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Escaper (string) --
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
QuoteChar (string) --
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
WithHeader (boolean) --
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
WriteHeader (boolean) --
A Boolean value that specifies whether to write the header to output. The default value is True .
SkipFirst (boolean) --
A Boolean value that specifies whether to skip the first data line. The default value is False .
OptimizePerformance (boolean) --
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
OutputSchemas (list) --
Specifies the data schema for the S3 CSV source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3JsonSource (dict) --
Specifies a JSON data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
JsonPath (string) --
A JsonPath string defining the JSON data.
Multiline (boolean) --
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
OutputSchemas (list) --
Specifies the data schema for the S3 JSON source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
S3ParquetSource (dict) --
Specifies an Apache Parquet data store stored in Amazon S3.
Name (string) --
The name of the data store.
Paths (list) --
A list of the Amazon S3 paths to read from.
CompressionType (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Exclusions (list) --
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
GroupSize (string) --
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
GroupFiles (string) --
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
Recurse (boolean) --
If set to true, recursively reads files in all subdirectories under the specified paths.
MaxBand (integer) --
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
MaxFilesInBand (integer) --
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
EnableSamplePath (boolean) --
Sets option to enable a sample path.
SamplePath (string) --
If enabled, specifies the sample path.
OutputSchemas (list) --
Specifies the data schema for the S3 Parquet source.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
RelationalCatalogSource (dict) --
Specifies a Relational database data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
DynamoDBCatalogSource (dict) --
Specifies a DynamoDB data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
JDBCConnectorTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
ConnectionName (string) --
The name of the connection that is associated with the connector.
ConnectionTable (string) --
The name of the table in the data target.
ConnectorName (string) --
The name of a connector that will be used.
ConnectionType (string) --
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
AdditionalOptions (dict) --
Additional connection options for the connector.
OutputSchemas (list) --
Specifies the data schema for the JDBC target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkConnectorTarget (dict) --
Specifies a target that uses an Apache Spark connector.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
ConnectionName (string) --
The name of a connection for an Apache Spark connector.
ConnectorName (string) --
The name of an Apache Spark connector.
ConnectionType (string) --
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
AdditionalOptions (dict) --
Additional connection options for the connector.
OutputSchemas (list) --
Specifies the data schema for the custom spark target.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
CatalogTarget (dict) --
Specifies a target that uses a Glue Data Catalog table.
Name (string) --
The name of your data target.
Inputs (list) --
The nodes that are inputs to the data target.
Database (string) --
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
Table (string) --
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
RedshiftTarget (dict) --
Specifies a target that uses Amazon Redshift.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
RedshiftTmpDir (string) --
The Amazon S3 path where temporary data can be staged when copying out of the database.
TmpDirIAMRole (string) --
The IAM role with permissions.
UpsertRedshiftOptions (dict) --
The set of options to configure an upsert operation when writing to a Redshift target.
TableLocation (string) --
The physical location of the Redshift table.
ConnectionName (string) --
The name of the connection to use to write to Redshift.
UpsertKeys (list) --
The keys used to determine whether to perform an update or insert.
S3CatalogTarget (dict) --
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
Table (string) --
The name of the table in the database to write to.
Database (string) --
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
S3GlueParquetTarget (dict) --
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
Path (string) --
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
S3DirectTarget (dict) --
Specifies a data target that writes to Amazon S3.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
Path (string) --
A single Amazon S3 path to write to.
Compression (string) --
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Format (string) --
Specifies the data output format for the target.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the crawler.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
Table (string) --
Specifies the table in the database that the schema change policy applies to.
Database (string) --
Specifies the database that the schema change policy applies to.
ApplyMapping (dict) --
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Mapping (list) --
Specifies the mapping of data property keys in the data source to data property keys in the data target.
(dict) --
Specifies the mapping of data property keys.
ToKey (string) --
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
FromPath (list) --
The table or column to be modified.
FromType (string) --
The type of the data to be modified.
ToType (string) --
The data type that the data is to be modified to.
Dropped (boolean) --
If true, then the column is removed.
Children (list) --
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
SelectFields (dict) --
Specifies a transform that chooses the data property keys that you want to keep.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Paths (list) --
A JSON path to a variable in the data structure.
DropFields (dict) --
Specifies a transform that chooses the data property keys that you want to drop.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Paths (list) --
A JSON path to a variable in the data structure.
RenameField (dict) --
Specifies a transform that renames a single data property key.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
SourcePath (list) --
A JSON path to a variable in the data structure for the source data.
TargetPath (list) --
A JSON path to a variable in the data structure for the target data.
Spigot (dict) --
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Path (string) --
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Topk (integer) --
Specifies a number of records to write starting from the beginning of the dataset.
Prob (float) --
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Join (dict) --
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
JoinType (string) --
Specifies the type of join to be performed on the datasets.
Columns (list) --
A list of the two columns to be joined.
(dict) --
Specifies a column to be joined.
From (string) --
The column to be joined.
Keys (list) --
The key of the column to be joined.
SplitFields (dict) --
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Paths (list) --
A JSON path to a variable in the data structure.
SelectFromCollection (dict) --
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Index (integer) --
The index for the DynamicFrame to be selected.
FillMissingValues (dict) --
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
ImputedPath (string) --
A JSON path to a variable in the data structure for the dataset that is imputed.
FilledPath (string) --
A JSON path to a variable in the data structure for the dataset that is filled.
Filter (dict) --
Specifies a transform that splits a dataset into two, based on a filter condition.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
LogicalOperator (string) --
The operator used to filter rows by comparing the key value to a specified value.
Filters (list) --
Specifies a filter expression.
(dict) --
Specifies a filter expression.
Operation (string) --
The type of operation to perform in the expression.
Negated (boolean) --
Whether the expression is to be negated.
Values (list) --
A list of filter values.
(dict) --
Represents a single entry in the list of values for a FilterExpression .
Type (string) --
The type of filter value.
Value (list) --
The value to be associated.
CustomCode (dict) --
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Code (string) --
The custom code that is used to perform the data transformation.
ClassName (string) --
The name defined for the custom code node class.
OutputSchemas (list) --
Specifies the data schema for the custom code transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
SparkSQL (dict) --
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
SqlQuery (string) --
A SQL query that must use Spark SQL syntax and return a single data set.
SqlAliases (list) --
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
(dict) --
Represents a single entry in the list of values for SqlAliases .
From (string) --
A table, or a column in a table.
Alias (string) --
A temporary name given to a table, or a column in a table.
OutputSchemas (list) --
Specifies the data schema for the SparkSQL transform.
(dict) --
Specifies a user-defined schema when a schema cannot be determined by Glue.
Columns (list) --
Specifies the column definitions that make up a Glue schema.
(dict) --
Specifies a single column in a Glue schema definition.
Name (string) --
The name of the column in the Glue Studio schema.
Type (string) --
The hive type for this column in the Glue Studio schema.
DirectKinesisSource (dict) --
Specifies a direct Amazon Kinesis data source.
Name (string) --
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DirectKafkaSource (dict) --
Specifies an Apache Kafka data store.
Name (string) --
The name of the data store.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKinesisSource (dict) --
Specifies a Kinesis data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) --
The name of the table in the database to read from.
Database (string) --
The name of the database to read from.
StreamingOptions (dict) --
Additional options for the Kinesis streaming data source.
EndpointUrl (string) --
The URL of the Kinesis endpoint.
StreamName (string) --
The name of the Kinesis data stream.
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingPosition (string) --
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
MaxFetchTimeInMs (integer) --
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
MaxFetchRecordsPerShard (integer) --
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
MaxRecordPerRead (integer) --
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
AddIdleTimeBetweenReads (boolean) --
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
IdleTimeBetweenReadsInMs (integer) --
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
DescribeShardInterval (integer) --
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
NumRetries (integer) --
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
RetryIntervalMs (integer) --
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
MaxRetryIntervalMs (integer) --
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
AvoidEmptyBatches (boolean) --
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
StreamArn (string) --
The Amazon Resource Name (ARN) of the Kinesis data stream.
RoleArn (string) --
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
RoleSessionName (string) --
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
DataPreviewOptions (dict) --
Additional options for data preview.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
CatalogKafkaSource (dict) --
Specifies an Apache Kafka data store in the Data Catalog.
Name (string) --
The name of the data store.
WindowSize (integer) --
The amount of time to spend processing each micro batch.
DetectSchema (boolean) --
Whether to automatically determine the schema from the incoming data.
Table (string) --
The name of the table in the database to read from.
Database (string) --
The name of the database to read from.
StreamingOptions (dict) --
Specifies the streaming options.
BootstrapServers (string) --
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
SecurityProtocol (string) --
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
ConnectionName (string) --
The name of the connection.
TopicName (string) --
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Assign (string) --
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
SubscribePattern (string) --
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
Classification (string) --
An optional classification.
Delimiter (string) --
Specifies the delimiter character.
StartingOffsets (string) --
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
EndingOffsets (string) --
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
PollTimeoutMs (integer) --
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
NumRetries (integer) --
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
RetryIntervalMs (integer) --
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
MaxOffsetsPerTrigger (integer) --
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
MinPartitions (integer) --
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
DataPreviewOptions (dict) --
Specifies options related to data preview for viewing a sample of your data.
PollingTime (integer) --
The polling time in milliseconds.
RecordPollingLimit (integer) --
The limit to the number of records polled.
DropNullFields (dict) --
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
NullCheckBoxList (dict) --
A structure that represents whether certain values are recognized as null values for removal.
IsEmpty (boolean) --
Specifies that an empty string is considered as a null value.
IsNullString (boolean) --
Specifies that a value spelling out the word 'null' is considered as a null value.
IsNegOne (boolean) --
Specifies that an integer value of -1 is considered as a null value.
NullTextList (list) --
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
(dict) --
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
Value (string) --
The value of the null placeholder.
Datatype (dict) --
The datatype of the value.
Id (string) --
The datatype of the value.
Label (string) --
A label assigned to the datatype.
Merge (dict) --
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Source (string) --
The source DynamicFrame that will be merged with a staging DynamicFrame .
PrimaryKeys (list) --
The list of primary key fields to match records from the source and staging dynamic frames.
Union (dict) --
Specifies a transform that combines the rows from two or more datasets into a single result.
Name (string) --
The name of the transform node.
Inputs (list) --
The node ID inputs to the transform.
UnionType (string) --
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
PIIDetection (dict) --
Specifies a transform that identifies, removes or masks PII data.
Name (string) --
The name of the transform node.
Inputs (list) --
The node ID inputs to the transform.
PiiType (string) --
Indicates the type of PIIDetection transform.
EntityTypesToDetect (list) --
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
OutputColumnName (string) --
Indicates the output column name that will contain any entity type detected in that row.
SampleFraction (float) --
Indicates the fraction of the data to sample when scanning for PII entities.
ThresholdFraction (float) --
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
MaskValue (string) --
Indicates the value that will replace the detected entity.
Aggregate (dict) --
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
Name (string) --
The name of the transform node.
Inputs (list) --
Specifies the fields and rows to use as inputs for the aggregate transform.
Groups (list) --
Specifies the fields to group by.
Aggs (list) --
Specifies the aggregate functions to be performed on specified fields.
(dict) --
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Column (list) --
Specifies the column on the data set on which the aggregation function will be applied.
AggFunc (string) --
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
DropDuplicates (dict) --
Specifies a transform that removes rows of repeating data from a data set.
Name (string) --
The name of the transform node.
Inputs (list) --
The data inputs identified by their node names.
Columns (list) --
The name of the columns to be merged or removed if repeating.
GovernedCatalogTarget (dict) --
Specifies a data target that writes to a goverened catalog.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
PartitionKeys (list) --
Specifies native partitioning using a sequence of keys.
Table (string) --
The name of the table in the database to write to.
Database (string) --
The name of the database to write to.
SchemaChangePolicy (dict) --
A policy that specifies update behavior for the governed catalog.
EnableUpdateCatalog (boolean) --
Whether to use the specified update behavior when the crawler finds a changed schema.
UpdateBehavior (string) --
The update behavior when the crawler finds a changed schema.
GovernedCatalogSource (dict) --
Specifies a data source in a goverened Data Catalog.
Name (string) --
The name of the data store.
Database (string) --
The database to read from.
Table (string) --
The database table to read from.
PartitionPredicate (string) --
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
AdditionalOptions (dict) --
Specifies additional connection options.
BoundedSize (integer) --
Sets the upper limit for the target size of the dataset in bytes that will be processed.
BoundedFiles (integer) --
Sets the upper limit for the target number of files that will be processed.
MicrosoftSQLServerCatalogSource (dict) --
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
MySQLCatalogSource (dict) --
Specifies a MySQL data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
OracleSQLCatalogSource (dict) --
Specifies an Oracle data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
PostgreSQLCatalogSource (dict) --
Specifies a PostgresSQL data source in the Glue Data Catalog.
Name (string) --
The name of the data source.
Database (string) --
The name of the database to read from.
Table (string) --
The name of the table in the database to read from.
MicrosoftSQLServerCatalogTarget (dict) --
Specifies a target that uses Microsoft SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
MySQLCatalogTarget (dict) --
Specifies a target that uses MySQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
OracleSQLCatalogTarget (dict) --
Specifies a target that uses Oracle SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
PostgreSQLCatalogTarget (dict) --
Specifies a target that uses Postgres SQL.
Name (string) --
The name of the data target.
Inputs (list) --
The nodes that are inputs to the data target.
Database (string) --
The name of the database to write to.
Table (string) --
The name of the table in the database to write to.
DynamicTransform (dict) --
Specifies a custom visual transform created by a user.
Name (string) --
Specifies the name of the dynamic transform.
TransformName (string) --
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Inputs (list) --
Specifies the inputs for the dynamic transform that are required.
Parameters (list) --
Specifies the parameters of the dynamic transform.
(dict) --
Specifies the parameters in the config file of the dynamic transform.
Name (string) --
Specifies the name of the parameter in the config file of the dynamic transform.
Type (string) --
Specifies the parameter type in the config file of the dynamic transform.
ValidationRule (string) --
Specifies the validation rule in the config file of the dynamic transform.
ValidationMessage (string) --
Specifies the validation message in the config file of the dynamic transform.
Value (list) --
Specifies the value of the parameter in the config file of the dynamic transform.
ListType (string) --
Specifies the list type of the parameter in the config file of the dynamic transform.
IsOptional (boolean) --
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
FunctionName (string) --
Specifies the name of the function of the dynamic transform.
Path (string) --
Specifies the path of the dynamic transform source and config files.
Version (string) --
This field is not used and will be deprecated in future release.
EvaluateDataQuality (dict) --
Specifies your data quality evaluation criteria.
Name (string) --
The name of the data quality evaluation.
Inputs (list) --
The inputs of your data quality evaluation.
Ruleset (string) --
The ruleset for your data quality evaluation.
Output (string) --
The output of your data quality evaluation.
PublishingOptions (dict) --
Options to configure how your results are published.
EvaluationContext (string) --
The context of the evaluation.
ResultsS3Prefix (string) --
The Amazon S3 prefix prepended to the results.
CloudWatchMetricsEnabled (boolean) --
Enable metrics for your data quality results.
ResultsPublishingEnabled (boolean) --
Enable publishing for your data quality results.
StopJobOnFailureOptions (dict) --
Options to configure how your job will stop if your data quality evaluation fails.
StopJobOnFailureTiming (string) --
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
SourceControlDetails (dict) --
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
Provider (string) --
The provider for the remote repository.
Repository (string) --
The name of the remote repository that contains the job artifacts.
Owner (string) --
The owner of the remote repository that contains the job artifacts.
Branch (string) --
An optional branch in the remote repository.
Folder (string) --
An optional folder in the remote repository.
LastCommitId (string) --
The last commit ID for a commit in the remote repository.
AuthStrategy (string) --
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
AuthToken (string) --
The value of an authorization token.
NextToken (string) --
A continuation token, if not all job definitions have yet been returned.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_mapping(**kwargs)¶Creates mappings.
See also: AWS API Documentation
Request Syntax
response = client.get_mapping(
Source={
'DatabaseName': 'string',
'TableName': 'string'
},
Sinks=[
{
'DatabaseName': 'string',
'TableName': 'string'
},
],
Location={
'Jdbc': [
{
'Name': 'string',
'Value': 'string',
'Param': True|False
},
],
'S3': [
{
'Name': 'string',
'Value': 'string',
'Param': True|False
},
],
'DynamoDB': [
{
'Name': 'string',
'Value': 'string',
'Param': True|False
},
]
}
)
[REQUIRED]
Specifies the source table.
The database in which the table metadata resides.
The name of the table in question.
A list of target tables.
Specifies a table definition in the Glue Data Catalog.
The database in which the table metadata resides.
The name of the table in question.
Parameters for the mapping.
A JDBC location.
An argument or property of a node.
The name of the argument or property.
The value of the argument or property.
True if the value is used as a parameter.
An Amazon Simple Storage Service (Amazon S3) location.
An argument or property of a node.
The name of the argument or property.
The value of the argument or property.
True if the value is used as a parameter.
An Amazon DynamoDB table location.
An argument or property of a node.
The name of the argument or property.
The value of the argument or property.
True if the value is used as a parameter.
dict
Response Syntax
{
'Mapping': [
{
'SourceTable': 'string',
'SourcePath': 'string',
'SourceType': 'string',
'TargetTable': 'string',
'TargetPath': 'string',
'TargetType': 'string'
},
]
}
Response Structure
(dict) --
Mapping (list) --
A list of mappings to the specified targets.
(dict) --
Defines a mapping.
SourceTable (string) --
The name of the source table.
SourcePath (string) --
The source path.
SourceType (string) --
The source type.
TargetTable (string) --
The target table.
TargetPath (string) --
The target path.
TargetType (string) --
The target type.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.EntityNotFoundExceptionget_ml_task_run(**kwargs)¶Gets details for a specific task run on a machine learning transform. Machine learning task runs are asynchronous tasks that Glue runs on your behalf as part of various machine learning workflows. You can check the stats of any task run by calling GetMLTaskRun with the TaskRunID and its parent transform's TransformID .
See also: AWS API Documentation
Request Syntax
response = client.get_ml_task_run(
TransformId='string',
TaskRunId='string'
)
[REQUIRED]
The unique identifier of the machine learning transform.
[REQUIRED]
The unique identifier of the task run.
dict
Response Syntax
{
'TransformId': 'string',
'TaskRunId': 'string',
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'LogGroupName': 'string',
'Properties': {
'TaskType': 'EVALUATION'|'LABELING_SET_GENERATION'|'IMPORT_LABELS'|'EXPORT_LABELS'|'FIND_MATCHES',
'ImportLabelsTaskRunProperties': {
'InputS3Path': 'string',
'Replace': True|False
},
'ExportLabelsTaskRunProperties': {
'OutputS3Path': 'string'
},
'LabelingSetGenerationTaskRunProperties': {
'OutputS3Path': 'string'
},
'FindMatchesTaskRunProperties': {
'JobId': 'string',
'JobName': 'string',
'JobRunId': 'string'
}
},
'ErrorString': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ExecutionTime': 123
}
Response Structure
(dict) --
TransformId (string) --
The unique identifier of the task run.
TaskRunId (string) --
The unique run identifier associated with this run.
Status (string) --
The status for this task run.
LogGroupName (string) --
The names of the log groups that are associated with the task run.
Properties (dict) --
The list of properties that are associated with the task run.
TaskType (string) --
The type of task run.
ImportLabelsTaskRunProperties (dict) --
The configuration properties for an importing labels task run.
InputS3Path (string) --
The Amazon Simple Storage Service (Amazon S3) path from where you will import the labels.
Replace (boolean) --
Indicates whether to overwrite your existing labels.
ExportLabelsTaskRunProperties (dict) --
The configuration properties for an exporting labels task run.
OutputS3Path (string) --
The Amazon Simple Storage Service (Amazon S3) path where you will export the labels.
LabelingSetGenerationTaskRunProperties (dict) --
The configuration properties for a labeling set generation task run.
OutputS3Path (string) --
The Amazon Simple Storage Service (Amazon S3) path where you will generate the labeling set.
FindMatchesTaskRunProperties (dict) --
The configuration properties for a find matches task run.
JobId (string) --
The job ID for the Find Matches task run.
JobName (string) --
The name assigned to the job for the Find Matches task run.
JobRunId (string) --
The job run ID for the Find Matches task run.
ErrorString (string) --
The error strings that are associated with the task run.
StartedOn (datetime) --
The date and time when this task run started.
LastModifiedOn (datetime) --
The date and time when this task run was last modified.
CompletedOn (datetime) --
The date and time when this task run was completed.
ExecutionTime (integer) --
The amount of time (in seconds) that the task run consumed resources.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionget_ml_task_runs(**kwargs)¶Gets a list of runs for a machine learning transform. Machine learning task runs are asynchronous tasks that Glue runs on your behalf as part of various machine learning workflows. You can get a sortable, filterable list of machine learning task runs by calling GetMLTaskRuns with their parent transform's TransformID and other optional parameters as documented in this section.
This operation returns a list of historic runs and must be paginated.
See also: AWS API Documentation
Request Syntax
response = client.get_ml_task_runs(
TransformId='string',
NextToken='string',
MaxResults=123,
Filter={
'TaskRunType': 'EVALUATION'|'LABELING_SET_GENERATION'|'IMPORT_LABELS'|'EXPORT_LABELS'|'FIND_MATCHES',
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'StartedBefore': datetime(2015, 1, 1),
'StartedAfter': datetime(2015, 1, 1)
},
Sort={
'Column': 'TASK_RUN_TYPE'|'STATUS'|'STARTED',
'SortDirection': 'DESCENDING'|'ASCENDING'
}
)
[REQUIRED]
The unique identifier of the machine learning transform.
The filter criteria, in the TaskRunFilterCriteria structure, for the task run.
The type of task run.
The current status of the task run.
Filter on task runs started before this date.
Filter on task runs started after this date.
The sorting criteria, in the TaskRunSortCriteria structure, for the task run.
The column to be used to sort the list of task runs for the machine learning transform.
The sort direction to be used to sort the list of task runs for the machine learning transform.
dict
Response Syntax
{
'TaskRuns': [
{
'TransformId': 'string',
'TaskRunId': 'string',
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'LogGroupName': 'string',
'Properties': {
'TaskType': 'EVALUATION'|'LABELING_SET_GENERATION'|'IMPORT_LABELS'|'EXPORT_LABELS'|'FIND_MATCHES',
'ImportLabelsTaskRunProperties': {
'InputS3Path': 'string',
'Replace': True|False
},
'ExportLabelsTaskRunProperties': {
'OutputS3Path': 'string'
},
'LabelingSetGenerationTaskRunProperties': {
'OutputS3Path': 'string'
},
'FindMatchesTaskRunProperties': {
'JobId': 'string',
'JobName': 'string',
'JobRunId': 'string'
}
},
'ErrorString': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ExecutionTime': 123
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
TaskRuns (list) --
A list of task runs that are associated with the transform.
(dict) --
The sampling parameters that are associated with the machine learning transform.
TransformId (string) --
The unique identifier for the transform.
TaskRunId (string) --
The unique identifier for this task run.
Status (string) --
The current status of the requested task run.
LogGroupName (string) --
The names of the log group for secure logging, associated with this task run.
Properties (dict) --
Specifies configuration properties associated with this task run.
TaskType (string) --
The type of task run.
ImportLabelsTaskRunProperties (dict) --
The configuration properties for an importing labels task run.
InputS3Path (string) --
The Amazon Simple Storage Service (Amazon S3) path from where you will import the labels.
Replace (boolean) --
Indicates whether to overwrite your existing labels.
ExportLabelsTaskRunProperties (dict) --
The configuration properties for an exporting labels task run.
OutputS3Path (string) --
The Amazon Simple Storage Service (Amazon S3) path where you will export the labels.
LabelingSetGenerationTaskRunProperties (dict) --
The configuration properties for a labeling set generation task run.
OutputS3Path (string) --
The Amazon Simple Storage Service (Amazon S3) path where you will generate the labeling set.
FindMatchesTaskRunProperties (dict) --
The configuration properties for a find matches task run.
JobId (string) --
The job ID for the Find Matches task run.
JobName (string) --
The name assigned to the job for the Find Matches task run.
JobRunId (string) --
The job run ID for the Find Matches task run.
ErrorString (string) --
The list of error strings associated with this task run.
StartedOn (datetime) --
The date and time that this task run started.
LastModifiedOn (datetime) --
The last point in time that the requested task run was updated.
CompletedOn (datetime) --
The last point in time that the requested task run was completed.
ExecutionTime (integer) --
The amount of time (in seconds) that the task run consumed resources.
NextToken (string) --
A pagination token, if more results are available.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionget_ml_transform(**kwargs)¶Gets an Glue machine learning transform artifact and all its corresponding metadata. Machine learning transforms are a special type of transform that use machine learning to learn the details of the transformation to be performed by learning from examples provided by humans. These transformations are then saved by Glue. You can retrieve their metadata by calling GetMLTransform .
See also: AWS API Documentation
Request Syntax
response = client.get_ml_transform(
TransformId='string'
)
[REQUIRED]
The unique identifier of the transform, generated at the time that the transform was created.
{
'TransformId': 'string',
'Name': 'string',
'Description': 'string',
'Status': 'NOT_READY'|'READY'|'DELETING',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'InputRecordTables': [
{
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
},
],
'Parameters': {
'TransformType': 'FIND_MATCHES',
'FindMatchesParameters': {
'PrimaryKeyColumnName': 'string',
'PrecisionRecallTradeoff': 123.0,
'AccuracyCostTradeoff': 123.0,
'EnforceProvidedLabels': True|False
}
},
'EvaluationMetrics': {
'TransformType': 'FIND_MATCHES',
'FindMatchesMetrics': {
'AreaUnderPRCurve': 123.0,
'Precision': 123.0,
'Recall': 123.0,
'F1': 123.0,
'ConfusionMatrix': {
'NumTruePositives': 123,
'NumFalsePositives': 123,
'NumTrueNegatives': 123,
'NumFalseNegatives': 123
},
'ColumnImportances': [
{
'ColumnName': 'string',
'Importance': 123.0
},
]
}
},
'LabelCount': 123,
'Schema': [
{
'Name': 'string',
'DataType': 'string'
},
],
'Role': 'string',
'GlueVersion': 'string',
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'Timeout': 123,
'MaxRetries': 123,
'TransformEncryption': {
'MlUserDataEncryption': {
'MlUserDataEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyId': 'string'
},
'TaskRunSecurityConfigurationName': 'string'
}
}
Response Structure
The unique identifier of the transform, generated at the time that the transform was created.
The unique name given to the transform when it was created.
A description of the transform.
The last known status of the transform (to indicate whether it can be used or not). One of "NOT_READY", "READY", or "DELETING".
The date and time when the transform was created.
The date and time when the transform was last modified.
A list of Glue table definitions used by the transform.
The database and table in the Glue Data Catalog that is used for input or output data.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.The configuration parameters that are specific to the algorithm used.
The type of machine learning transform.
For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
The parameters for the find matches algorithm.
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
The value selected when tuning your transform for a balance between precision and recall. A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.
The precision metric indicates how often your model is correct when it predicts a match.
The recall metric indicates that for an actual match, how often your model predicts the match.
The value that is selected when tuning your transform for a balance between accuracy and cost. A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate FindMatches transform, sometimes with unacceptable accuracy.
Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall.
Cost measures how many compute resources, and thus money, are consumed to run the transform.
The value to switch on or off to force the output to match the provided labels from users. If the value is True , the find matches transform forces the output to match the provided labels. The results override the normal conflation results. If the value is False , the find matches transform does not ensure all the labels provided are respected, and the results rely on the trained model.
Note that setting this value to true may increase the conflation execution time.
The latest evaluation metrics.
The type of machine learning transform.
The evaluation metrics for the find matches algorithm.
The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs. recall. Higher values indicate that you have a more attractive precision vs. recall tradeoff.
For more information, see Precision and recall in Wikipedia.
The precision metric indicates when often your transform is correct when it predicts a match. Specifically, it measures how well the transform finds true positives from the total true positives possible.
For more information, see Precision and recall in Wikipedia.
The recall metric indicates that for an actual match, how often your transform predicts the match. Specifically, it measures how well the transform finds true positives from the total records in the source data.
For more information, see Precision and recall in Wikipedia.
The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.
For more information, see F1 score in Wikipedia.
The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.
For more information, see Confusion matrix in Wikipedia.
The number of matches in the data that the transform correctly found, in the confusion matrix for your transform.
The number of nonmatches in the data that the transform incorrectly classified as a match, in the confusion matrix for your transform.
The number of nonmatches in the data that the transform correctly rejected, in the confusion matrix for your transform.
The number of matches in the data that the transform didn't find, in the confusion matrix for your transform.
A list of ColumnImportance structures containing column importance metrics, sorted in order of descending importance.
A structure containing the column name and column importance score for a column.
Column importance helps you understand how columns contribute to your model, by identifying which columns in your records are more important than others.
The name of a column.
The column importance score for the column, as a decimal.
The number of labels available for this transform.
The Map<Column, Type> object that represents the schema that this transform accepts. Has an upper bound of 100 columns.
A key-value pair representing a column and data type that this transform can run against. The Schema parameter of the MLTransform may contain up to 100 of these structures.
The name of the column.
The type of data in the column.
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions.
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
The type of predefined worker that is allocated when this task runs. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.The number of workers of a defined workerType that are allocated when this task runs.
The timeout for a task run for this transform in minutes. This is the maximum time that a task run for this transform can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
The maximum number of times to retry a task for this transform after a task run fails.
The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
An MLUserDataEncryption object containing the encryption mode and customer-provided KMS key ID.
The encryption mode applied to user data. Valid values are:
The ID for the customer-provided KMS key.
The name of the security configuration.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionget_ml_transforms(**kwargs)¶Gets a sortable, filterable list of existing Glue machine learning transforms. Machine learning transforms are a special type of transform that use machine learning to learn the details of the transformation to be performed by learning from examples provided by humans. These transformations are then saved by Glue, and you can retrieve their metadata by calling GetMLTransforms .
See also: AWS API Documentation
Request Syntax
response = client.get_ml_transforms(
NextToken='string',
MaxResults=123,
Filter={
'Name': 'string',
'TransformType': 'FIND_MATCHES',
'Status': 'NOT_READY'|'READY'|'DELETING',
'GlueVersion': 'string',
'CreatedBefore': datetime(2015, 1, 1),
'CreatedAfter': datetime(2015, 1, 1),
'LastModifiedBefore': datetime(2015, 1, 1),
'LastModifiedAfter': datetime(2015, 1, 1),
'Schema': [
{
'Name': 'string',
'DataType': 'string'
},
]
},
Sort={
'Column': 'NAME'|'TRANSFORM_TYPE'|'STATUS'|'CREATED'|'LAST_MODIFIED',
'SortDirection': 'DESCENDING'|'ASCENDING'
}
)
The filter transformation criteria.
A unique transform name that is used to filter the machine learning transforms.
The type of machine learning transform that is used to filter the machine learning transforms.
Filters the list of machine learning transforms by the last known status of the transforms (to indicate whether a transform can be used or not). One of "NOT_READY", "READY", or "DELETING".
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
The time and date before which the transforms were created.
The time and date after which the transforms were created.
Filter on transforms last modified before this date.
Filter on transforms last modified after this date.
Filters on datasets with a specific schema. The Map<Column, Type> object is an array of key-value pairs representing the schema this transform accepts, where Column is the name of a column, and Type is the type of the data such as an integer or string. Has an upper bound of 100 columns.
A key-value pair representing a column and data type that this transform can run against. The Schema parameter of the MLTransform may contain up to 100 of these structures.
The name of the column.
The type of data in the column.
The sorting criteria.
The column to be used in the sorting criteria that are associated with the machine learning transform.
The sort direction to be used in the sorting criteria that are associated with the machine learning transform.
dict
Response Syntax
{
'Transforms': [
{
'TransformId': 'string',
'Name': 'string',
'Description': 'string',
'Status': 'NOT_READY'|'READY'|'DELETING',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'InputRecordTables': [
{
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
},
],
'Parameters': {
'TransformType': 'FIND_MATCHES',
'FindMatchesParameters': {
'PrimaryKeyColumnName': 'string',
'PrecisionRecallTradeoff': 123.0,
'AccuracyCostTradeoff': 123.0,
'EnforceProvidedLabels': True|False
}
},
'EvaluationMetrics': {
'TransformType': 'FIND_MATCHES',
'FindMatchesMetrics': {
'AreaUnderPRCurve': 123.0,
'Precision': 123.0,
'Recall': 123.0,
'F1': 123.0,
'ConfusionMatrix': {
'NumTruePositives': 123,
'NumFalsePositives': 123,
'NumTrueNegatives': 123,
'NumFalseNegatives': 123
},
'ColumnImportances': [
{
'ColumnName': 'string',
'Importance': 123.0
},
]
}
},
'LabelCount': 123,
'Schema': [
{
'Name': 'string',
'DataType': 'string'
},
],
'Role': 'string',
'GlueVersion': 'string',
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'Timeout': 123,
'MaxRetries': 123,
'TransformEncryption': {
'MlUserDataEncryption': {
'MlUserDataEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyId': 'string'
},
'TaskRunSecurityConfigurationName': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Transforms (list) --
A list of machine learning transforms.
(dict) --
A structure for a machine learning transform.
TransformId (string) --
The unique transform ID that is generated for the machine learning transform. The ID is guaranteed to be unique and does not change.
Name (string) --
A user-defined name for the machine learning transform. Names are not guaranteed unique and can be changed at any time.
Description (string) --
A user-defined, long-form description text for the machine learning transform. Descriptions are not guaranteed to be unique and can be changed at any time.
Status (string) --
The current status of the machine learning transform.
CreatedOn (datetime) --
A timestamp. The time and date that this machine learning transform was created.
LastModifiedOn (datetime) --
A timestamp. The last point in time when this machine learning transform was modified.
InputRecordTables (list) --
A list of Glue table definitions used by the transform.
(dict) --
The database and table in the Glue Data Catalog that is used for input or output data.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.Parameters (dict) --
A TransformParameters object. You can use parameters to tune (customize) the behavior of the machine learning transform by specifying what data it learns from and your preference on various tradeoffs (such as precious vs. recall, or accuracy vs. cost).
TransformType (string) --
The type of machine learning transform.
For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
FindMatchesParameters (dict) --
The parameters for the find matches algorithm.
PrimaryKeyColumnName (string) --
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
PrecisionRecallTradeoff (float) --
The value selected when tuning your transform for a balance between precision and recall. A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.
The precision metric indicates how often your model is correct when it predicts a match.
The recall metric indicates that for an actual match, how often your model predicts the match.
AccuracyCostTradeoff (float) --
The value that is selected when tuning your transform for a balance between accuracy and cost. A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate FindMatches transform, sometimes with unacceptable accuracy.
Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall.
Cost measures how many compute resources, and thus money, are consumed to run the transform.
EnforceProvidedLabels (boolean) --
The value to switch on or off to force the output to match the provided labels from users. If the value is True , the find matches transform forces the output to match the provided labels. The results override the normal conflation results. If the value is False , the find matches transform does not ensure all the labels provided are respected, and the results rely on the trained model.
Note that setting this value to true may increase the conflation execution time.
EvaluationMetrics (dict) --
An EvaluationMetrics object. Evaluation metrics provide an estimate of the quality of your machine learning transform.
TransformType (string) --
The type of machine learning transform.
FindMatchesMetrics (dict) --
The evaluation metrics for the find matches algorithm.
AreaUnderPRCurve (float) --
The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs. recall. Higher values indicate that you have a more attractive precision vs. recall tradeoff.
For more information, see Precision and recall in Wikipedia.
Precision (float) --
The precision metric indicates when often your transform is correct when it predicts a match. Specifically, it measures how well the transform finds true positives from the total true positives possible.
For more information, see Precision and recall in Wikipedia.
Recall (float) --
The recall metric indicates that for an actual match, how often your transform predicts the match. Specifically, it measures how well the transform finds true positives from the total records in the source data.
For more information, see Precision and recall in Wikipedia.
F1 (float) --
The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.
For more information, see F1 score in Wikipedia.
ConfusionMatrix (dict) --
The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.
For more information, see Confusion matrix in Wikipedia.
NumTruePositives (integer) --
The number of matches in the data that the transform correctly found, in the confusion matrix for your transform.
NumFalsePositives (integer) --
The number of nonmatches in the data that the transform incorrectly classified as a match, in the confusion matrix for your transform.
NumTrueNegatives (integer) --
The number of nonmatches in the data that the transform correctly rejected, in the confusion matrix for your transform.
NumFalseNegatives (integer) --
The number of matches in the data that the transform didn't find, in the confusion matrix for your transform.
ColumnImportances (list) --
A list of ColumnImportance structures containing column importance metrics, sorted in order of descending importance.
(dict) --
A structure containing the column name and column importance score for a column.
Column importance helps you understand how columns contribute to your model, by identifying which columns in your records are more important than others.
ColumnName (string) --
The name of a column.
Importance (float) --
The column importance score for the column, as a decimal.
LabelCount (integer) --
A count identifier for the labeling files generated by Glue for this transform. As you create a better transform, you can iteratively download, label, and upload the labeling file.
Schema (list) --
A map of key-value pairs representing the columns and data types that this transform can run against. Has an upper bound of 100 columns.
(dict) --
A key-value pair representing a column and data type that this transform can run against. The Schema parameter of the MLTransform may contain up to 100 of these structures.
Name (string) --
The name of the column.
DataType (string) --
The type of data in the column.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role with the required permissions. The required permissions include both Glue service role permissions to Glue resources, and Amazon S3 permissions required by the transform.
GlueVersion (string) --
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
MaxCapacityis a mutually exclusive option withNumberOfWorkersandWorkerType.
NumberOfWorkers or WorkerType is set, then MaxCapacity cannot be set.MaxCapacity is set then neither NumberOfWorkers or WorkerType can be set.WorkerType is set, then NumberOfWorkers is required (and vice versa).MaxCapacity and NumberOfWorkers must both be at least 1.When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
WorkerType (string) --
The type of predefined worker that is allocated when a task of this transform runs. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.
MaxCapacityis a mutually exclusive option withNumberOfWorkersandWorkerType.
NumberOfWorkers or WorkerType is set, then MaxCapacity cannot be set.MaxCapacity is set then neither NumberOfWorkers or WorkerType can be set.WorkerType is set, then NumberOfWorkers is required (and vice versa).MaxCapacity and NumberOfWorkers must both be at least 1.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a task of the transform runs.
If WorkerType is set, then NumberOfWorkers is required (and vice versa).
Timeout (integer) --
The timeout in minutes of the machine learning transform.
MaxRetries (integer) --
The maximum number of times to retry after an MLTaskRun of the machine learning transform fails.
TransformEncryption (dict) --
The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
MlUserDataEncryption (dict) --
An MLUserDataEncryption object containing the encryption mode and customer-provided KMS key ID.
MlUserDataEncryptionMode (string) --
The encryption mode applied to user data. Valid values are:
KmsKeyId (string) --
The ID for the customer-provided KMS key.
TaskRunSecurityConfigurationName (string) --
The name of the security configuration.
NextToken (string) --
A pagination token, if more results are available.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionget_paginator(operation_name)¶Create a paginator for an operation.
create_foo, and you'd normally invoke the
operation as client.create_foo(**kwargs), if the
create_foo operation can be paginated, you can use the
call client.get_paginator("create_foo").client.can_paginate method to
check if an operation is pageable.get_partition(**kwargs)¶Retrieves information about a specified partition.
See also: AWS API Documentation
Request Syntax
response = client.get_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionValues=[
'string',
]
)
[REQUIRED]
The name of the catalog database where the partition resides.
[REQUIRED]
The name of the partition's table.
[REQUIRED]
The values that define the partition.
dict
Response Syntax
{
'Partition': {
'Values': [
'string',
],
'DatabaseName': 'string',
'TableName': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1),
'CatalogId': 'string'
}
}
Response Structure
(dict) --
Partition (dict) --
The requested information, in the form of a Partition object.
Values (list) --
The values of the partition.
DatabaseName (string) --
The name of the catalog database in which to create the partition.
TableName (string) --
The name of the database table in which to create the partition.
CreationTime (datetime) --
The time at which the partition was created.
LastAccessTime (datetime) --
The last time at which the partition was accessed.
StorageDescriptor (dict) --
Provides information about the physical location where the partition is stored.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
Parameters (dict) --
These key-value pairs define partition parameters.
LastAnalyzedTime (datetime) --
The last time at which column statistics were computed for this partition.
CatalogId (string) --
The ID of the Data Catalog in which the partition resides.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_partition_indexes(**kwargs)¶Retrieves the partition indexes associated with a table.
See also: AWS API Documentation
Request Syntax
response = client.get_partition_indexes(
CatalogId='string',
DatabaseName='string',
TableName='string',
NextToken='string'
)
[REQUIRED]
Specifies the name of a database from which you want to retrieve partition indexes.
[REQUIRED]
Specifies the name of a table for which you want to retrieve the partition indexes.
dict
Response Syntax
{
'PartitionIndexDescriptorList': [
{
'IndexName': 'string',
'Keys': [
{
'Name': 'string',
'Type': 'string'
},
],
'IndexStatus': 'CREATING'|'ACTIVE'|'DELETING'|'FAILED',
'BackfillErrors': [
{
'Code': 'ENCRYPTED_PARTITION_ERROR'|'INTERNAL_ERROR'|'INVALID_PARTITION_TYPE_DATA_ERROR'|'MISSING_PARTITION_VALUE_ERROR'|'UNSUPPORTED_PARTITION_CHARACTER_ERROR',
'Partitions': [
{
'Values': [
'string',
]
},
]
},
]
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
PartitionIndexDescriptorList (list) --
A list of index descriptors.
(dict) --
A descriptor for a partition index in a table.
IndexName (string) --
The name of the partition index.
Keys (list) --
A list of one or more keys, as KeySchemaElement structures, for the partition index.
(dict) --
A partition key pair consisting of a name and a type.
Name (string) --
The name of a partition key.
Type (string) --
The type of a partition key.
IndexStatus (string) --
The status of the partition index.
The possible statuses are:
BackfillErrors (list) --
A list of errors that can occur when registering partition indexes for an existing table.
(dict) --
A list of errors that can occur when registering partition indexes for an existing table.
These errors give the details about why an index registration failed and provide a limited number of partitions in the response, so that you can fix the partitions at fault and try registering the index again. The most common set of errors that can occur are categorized as follows:
Code (string) --
The error code for an error that occurred when registering partition indexes for an existing table.
Partitions (list) --
A list of a limited number of partitions in the response.
(dict) --
Contains a list of values defining partitions.
Values (list) --
The list of values.
NextToken (string) --
A continuation token, present if the current list segment is not the last.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ConflictExceptionget_partitions(**kwargs)¶Retrieves information about the partitions in a table.
See also: AWS API Documentation
Request Syntax
response = client.get_partitions(
CatalogId='string',
DatabaseName='string',
TableName='string',
Expression='string',
NextToken='string',
Segment={
'SegmentNumber': 123,
'TotalSegments': 123
},
MaxResults=123,
ExcludeColumnSchema=True|False,
TransactionId='string',
QueryAsOfTime=datetime(2015, 1, 1)
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
An expression that filters the partitions to be returned.
The expression uses SQL syntax similar to the SQL WHERE filter clause. The SQL statement parser JSQLParser parses the expression.
Operators : The following are the operators that you can use in theExpressionAPI call:=
Checks whether the values of the two operands are equal; if yes, then the condition becomes true.
Example: Assume 'variable a' holds 10 and 'variable b' holds 20.
(a = b) is not true.
< >
Checks whether the values of two operands are equal; if the values are not equal, then the condition becomes true.
Example: (a < > b) is true.
>
Checks whether the value of the left operand is greater than the value of the right operand; if yes, then the condition becomes true.
Example: (a > b) is not true.
<
Checks whether the value of the left operand is less than the value of the right operand; if yes, then the condition becomes true.
Example: (a < b) is true.
>=
Checks whether the value of the left operand is greater than or equal to the value of the right operand; if yes, then the condition becomes true.
Example: (a >= b) is not true.
<=
Checks whether the value of the left operand is less than or equal to the value of the right operand; if yes, then the condition becomes true.
Example: (a <= b) is true.
AND, OR, IN, BETWEEN, LIKE, NOT, IS NULL
Logical operators.
Supported Partition Key Types : The following are the supported partition keys.
stringdatetimestampintbigintlongtinyintsmallintdecimalIf an type is encountered that is not valid, an exception is thrown.
The following list shows the valid operators on each type. When you define a crawler, the partitionKey type is created as a STRING , to be compatible with the catalog partitions.
Sample API Call :
The segment of the table's partitions to scan in this request.
The zero-based index number of the segment. For example, if the total number of segments is 4, SegmentNumber values range from 0 through 3.
The total number of segments.
TransactionId .dict
Response Syntax
{
'Partitions': [
{
'Values': [
'string',
],
'DatabaseName': 'string',
'TableName': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1),
'CatalogId': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Partitions (list) --
A list of requested partitions.
(dict) --
Represents a slice of table data.
Values (list) --
The values of the partition.
DatabaseName (string) --
The name of the catalog database in which to create the partition.
TableName (string) --
The name of the database table in which to create the partition.
CreationTime (datetime) --
The time at which the partition was created.
LastAccessTime (datetime) --
The last time at which the partition was accessed.
StorageDescriptor (dict) --
Provides information about the physical location where the partition is stored.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
Parameters (dict) --
These key-value pairs define partition parameters.
LastAnalyzedTime (datetime) --
The last time at which column statistics were computed for this partition.
CatalogId (string) --
The ID of the Data Catalog in which the partition resides.
NextToken (string) --
A continuation token, if the returned list of partitions does not include the last one.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.InvalidStateExceptionGlue.Client.exceptions.ResourceNotReadyExceptionget_plan(**kwargs)¶Gets code to perform a specified mapping.
See also: AWS API Documentation
Request Syntax
response = client.get_plan(
Mapping=[
{
'SourceTable': 'string',
'SourcePath': 'string',
'SourceType': 'string',
'TargetTable': 'string',
'TargetPath': 'string',
'TargetType': 'string'
},
],
Source={
'DatabaseName': 'string',
'TableName': 'string'
},
Sinks=[
{
'DatabaseName': 'string',
'TableName': 'string'
},
],
Location={
'Jdbc': [
{
'Name': 'string',
'Value': 'string',
'Param': True|False
},
],
'S3': [
{
'Name': 'string',
'Value': 'string',
'Param': True|False
},
],
'DynamoDB': [
{
'Name': 'string',
'Value': 'string',
'Param': True|False
},
]
},
Language='PYTHON'|'SCALA',
AdditionalPlanOptionsMap={
'string': 'string'
}
)
[REQUIRED]
The list of mappings from a source table to target tables.
Defines a mapping.
The name of the source table.
The source path.
The source type.
The target table.
The target path.
The target type.
[REQUIRED]
The source table.
The database in which the table metadata resides.
The name of the table in question.
The target tables.
Specifies a table definition in the Glue Data Catalog.
The database in which the table metadata resides.
The name of the table in question.
The parameters for the mapping.
A JDBC location.
An argument or property of a node.
The name of the argument or property.
The value of the argument or property.
True if the value is used as a parameter.
An Amazon Simple Storage Service (Amazon S3) location.
An argument or property of a node.
The name of the argument or property.
The value of the argument or property.
True if the value is used as a parameter.
An Amazon DynamoDB table location.
An argument or property of a node.
The name of the argument or property.
The value of the argument or property.
True if the value is used as a parameter.
A map to hold additional optional key-value parameters.
Currently, these key-value pairs are supported:
inferSchema — Specifies whether to set inferSchema to true or false for the default script generated by an Glue job. For example, to set inferSchema to true, pass the following key value pair: --additional-plan-options-map '{"inferSchema":"true"}'dict
Response Syntax
{
'PythonScript': 'string',
'ScalaCode': 'string'
}
Response Structure
(dict) --
PythonScript (string) --
A Python script to perform the mapping.
ScalaCode (string) --
The Scala code to perform the mapping.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_registry(**kwargs)¶Describes the specified registry in detail.
See also: AWS API Documentation
Request Syntax
response = client.get_registry(
RegistryId={
'RegistryName': 'string',
'RegistryArn': 'string'
}
)
[REQUIRED]
This is a wrapper structure that may contain the registry name and Amazon Resource Name (ARN).
Name of the registry. Used only for lookup. One of RegistryArn or RegistryName has to be provided.
Arn of the registry to be updated. One of RegistryArn or RegistryName has to be provided.
{
'RegistryName': 'string',
'RegistryArn': 'string',
'Description': 'string',
'Status': 'AVAILABLE'|'DELETING',
'CreatedTime': 'string',
'UpdatedTime': 'string'
}
Response Structure
The name of the registry.
The Amazon Resource Name (ARN) of the registry.
A description of the registry.
The status of the registry.
The date and time the registry was created.
The date and time the registry was updated.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionget_resource_policies(**kwargs)¶Retrieves the resource policies set on individual resources by Resource Access Manager during cross-account permission grants. Also retrieves the Data Catalog resource policy.
If you enabled metadata encryption in Data Catalog settings, and you do not have permission on the KMS key, the operation can't return the Data Catalog resource policy.
See also: AWS API Documentation
Request Syntax
response = client.get_resource_policies(
NextToken='string',
MaxResults=123
)
dict
Response Syntax
{
'GetResourcePoliciesResponseList': [
{
'PolicyInJson': 'string',
'PolicyHash': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1)
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
GetResourcePoliciesResponseList (list) --
A list of the individual resource policies and the account-level resource policy.
(dict) --
A structure for returning a resource policy.
PolicyInJson (string) --
Contains the requested policy document, in JSON format.
PolicyHash (string) --
Contains the hash value associated with this policy.
CreateTime (datetime) --
The date and time at which the policy was created.
UpdateTime (datetime) --
The date and time at which the policy was last updated.
NextToken (string) --
A continuation token, if the returned list does not contain the last resource policy available.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_resource_policy(**kwargs)¶Retrieves a specified resource policy.
See also: AWS API Documentation
Request Syntax
response = client.get_resource_policy(
ResourceArn='string'
)
GetResourcePolicies to view all existing resource policies. For more information see Specifying Glue Resource ARNs.{
'PolicyInJson': 'string',
'PolicyHash': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1)
}
Response Structure
Contains the requested policy document, in JSON format.
Contains the hash value associated with this policy.
The date and time at which the policy was created.
The date and time at which the policy was last updated.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionget_schema(**kwargs)¶Describes the specified schema in detail.
See also: AWS API Documentation
Request Syntax
response = client.get_schema(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
}
)
[REQUIRED]
This is a wrapper structure to contain schema identity fields. The structure contains:
SchemaArn or SchemaName and RegistryName has to be provided.SchemaArn or SchemaName and RegistryName has to be provided.The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
{
'RegistryName': 'string',
'RegistryArn': 'string',
'SchemaName': 'string',
'SchemaArn': 'string',
'Description': 'string',
'DataFormat': 'AVRO'|'JSON'|'PROTOBUF',
'Compatibility': 'NONE'|'DISABLED'|'BACKWARD'|'BACKWARD_ALL'|'FORWARD'|'FORWARD_ALL'|'FULL'|'FULL_ALL',
'SchemaCheckpoint': 123,
'LatestSchemaVersion': 123,
'NextSchemaVersion': 123,
'SchemaStatus': 'AVAILABLE'|'PENDING'|'DELETING',
'CreatedTime': 'string',
'UpdatedTime': 'string'
}
Response Structure
The name of the registry.
The Amazon Resource Name (ARN) of the registry.
The name of the schema.
The Amazon Resource Name (ARN) of the schema.
A description of schema if specified when created
The data format of the schema definition. Currently AVRO , JSON and PROTOBUF are supported.
The compatibility mode of the schema.
The version number of the checkpoint (the last time the compatibility mode was changed).
The latest version of the schema associated with the returned schema definition.
The next version of the schema associated with the returned schema definition.
The status of the schema.
The date and time the schema was created.
The date and time the schema was updated.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionget_schema_by_definition(**kwargs)¶Retrieves a schema by the SchemaDefinition . The schema definition is sent to the Schema Registry, canonicalized, and hashed. If the hash is matched within the scope of the SchemaName or ARN (or the default registry, if none is supplied), that schema’s metadata is returned. Otherwise, a 404 or NotFound error is returned. Schema versions in Deleted statuses will not be included in the results.
See also: AWS API Documentation
Request Syntax
response = client.get_schema_by_definition(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
SchemaDefinition='string'
)
[REQUIRED]
This is a wrapper structure to contain schema identity fields. The structure contains:
SchemaArn or SchemaName has to be provided.SchemaArn or SchemaName has to be provided.The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
[REQUIRED]
The definition of the schema for which schema details are required.
dict
Response Syntax
{
'SchemaVersionId': 'string',
'SchemaArn': 'string',
'DataFormat': 'AVRO'|'JSON'|'PROTOBUF',
'Status': 'AVAILABLE'|'PENDING'|'FAILURE'|'DELETING',
'CreatedTime': 'string'
}
Response Structure
(dict) --
SchemaVersionId (string) --
The schema ID of the schema version.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema.
DataFormat (string) --
The data format of the schema definition. Currently AVRO , JSON and PROTOBUF are supported.
Status (string) --
The status of the schema version.
CreatedTime (string) --
The date and time the schema was created.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionget_schema_version(**kwargs)¶Get the specified schema by its unique ID assigned when a version of the schema is created or registered. Schema versions in Deleted status will not be included in the results.
See also: AWS API Documentation
Request Syntax
response = client.get_schema_version(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
SchemaVersionId='string',
SchemaVersionNumber={
'LatestVersion': True|False,
'VersionNumber': 123
}
)
This is a wrapper structure to contain schema identity fields. The structure contains:
SchemaArn or SchemaName and RegistryName has to be provided.SchemaArn or SchemaName and RegistryName has to be provided.The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
SchemaVersionId of the schema version. This field is required for fetching by schema ID. Either this or the SchemaId wrapper has to be provided.The version number of the schema.
The latest version available for the schema.
The version number of the schema.
dict
Response Syntax
{
'SchemaVersionId': 'string',
'SchemaDefinition': 'string',
'DataFormat': 'AVRO'|'JSON'|'PROTOBUF',
'SchemaArn': 'string',
'VersionNumber': 123,
'Status': 'AVAILABLE'|'PENDING'|'FAILURE'|'DELETING',
'CreatedTime': 'string'
}
Response Structure
(dict) --
SchemaVersionId (string) --
The SchemaVersionId of the schema version.
SchemaDefinition (string) --
The schema definition for the schema ID.
DataFormat (string) --
The data format of the schema definition. Currently AVRO , JSON and PROTOBUF are supported.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema.
VersionNumber (integer) --
The version number of the schema.
Status (string) --
The status of the schema version.
CreatedTime (string) --
The date and time the schema version was created.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionget_schema_versions_diff(**kwargs)¶Fetches the schema version difference in the specified difference type between two stored schema versions in the Schema Registry.
This API allows you to compare two schema versions between two schema definitions under the same schema.
See also: AWS API Documentation
Request Syntax
response = client.get_schema_versions_diff(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
FirstSchemaVersionNumber={
'LatestVersion': True|False,
'VersionNumber': 123
},
SecondSchemaVersionNumber={
'LatestVersion': True|False,
'VersionNumber': 123
},
SchemaDiffType='SYNTAX_DIFF'
)
[REQUIRED]
This is a wrapper structure to contain schema identity fields. The structure contains:
SchemaArn or SchemaName has to be provided.SchemaArn or SchemaName has to be provided.The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
[REQUIRED]
The first of the two schema versions to be compared.
The latest version available for the schema.
The version number of the schema.
[REQUIRED]
The second of the two schema versions to be compared.
The latest version available for the schema.
The version number of the schema.
[REQUIRED]
Refers to SYNTAX_DIFF , which is the currently supported diff type.
dict
Response Syntax
{
'Diff': 'string'
}
Response Structure
(dict) --
Diff (string) --
The difference between schemas as a string in JsonPatch format.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionget_security_configuration(**kwargs)¶Retrieves a specified security configuration.
See also: AWS API Documentation
Request Syntax
response = client.get_security_configuration(
Name='string'
)
[REQUIRED]
The name of the security configuration to retrieve.
{
'SecurityConfiguration': {
'Name': 'string',
'CreatedTimeStamp': datetime(2015, 1, 1),
'EncryptionConfiguration': {
'S3Encryption': [
{
'S3EncryptionMode': 'DISABLED'|'SSE-KMS'|'SSE-S3',
'KmsKeyArn': 'string'
},
],
'CloudWatchEncryption': {
'CloudWatchEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyArn': 'string'
},
'JobBookmarksEncryption': {
'JobBookmarksEncryptionMode': 'DISABLED'|'CSE-KMS',
'KmsKeyArn': 'string'
}
}
}
}
Response Structure
The requested security configuration.
The name of the security configuration.
The time at which this security configuration was created.
The encryption configuration associated with this security configuration.
The encryption configuration for Amazon Simple Storage Service (Amazon S3) data.
Specifies how Amazon Simple Storage Service (Amazon S3) data should be encrypted.
The encryption mode to use for Amazon S3 data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
The encryption configuration for Amazon CloudWatch.
The encryption mode to use for CloudWatch data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
The encryption configuration for job bookmarks.
The encryption mode to use for job bookmarks data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_security_configurations(**kwargs)¶Retrieves a list of all security configurations.
See also: AWS API Documentation
Request Syntax
response = client.get_security_configurations(
MaxResults=123,
NextToken='string'
)
dict
Response Syntax
{
'SecurityConfigurations': [
{
'Name': 'string',
'CreatedTimeStamp': datetime(2015, 1, 1),
'EncryptionConfiguration': {
'S3Encryption': [
{
'S3EncryptionMode': 'DISABLED'|'SSE-KMS'|'SSE-S3',
'KmsKeyArn': 'string'
},
],
'CloudWatchEncryption': {
'CloudWatchEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyArn': 'string'
},
'JobBookmarksEncryption': {
'JobBookmarksEncryptionMode': 'DISABLED'|'CSE-KMS',
'KmsKeyArn': 'string'
}
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
SecurityConfigurations (list) --
A list of security configurations.
(dict) --
Specifies a security configuration.
Name (string) --
The name of the security configuration.
CreatedTimeStamp (datetime) --
The time at which this security configuration was created.
EncryptionConfiguration (dict) --
The encryption configuration associated with this security configuration.
S3Encryption (list) --
The encryption configuration for Amazon Simple Storage Service (Amazon S3) data.
(dict) --
Specifies how Amazon Simple Storage Service (Amazon S3) data should be encrypted.
S3EncryptionMode (string) --
The encryption mode to use for Amazon S3 data.
KmsKeyArn (string) --
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
CloudWatchEncryption (dict) --
The encryption configuration for Amazon CloudWatch.
CloudWatchEncryptionMode (string) --
The encryption mode to use for CloudWatch data.
KmsKeyArn (string) --
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
JobBookmarksEncryption (dict) --
The encryption configuration for job bookmarks.
JobBookmarksEncryptionMode (string) --
The encryption mode to use for job bookmarks data.
KmsKeyArn (string) --
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
NextToken (string) --
A continuation token, if there are more security configurations to return.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_session(**kwargs)¶Retrieves the session.
See also: AWS API Documentation
Request Syntax
response = client.get_session(
Id='string',
RequestOrigin='string'
)
[REQUIRED]
The ID of the session.
dict
Response Syntax
{
'Session': {
'Id': 'string',
'CreatedOn': datetime(2015, 1, 1),
'Status': 'PROVISIONING'|'READY'|'FAILED'|'TIMEOUT'|'STOPPING'|'STOPPED',
'ErrorMessage': 'string',
'Description': 'string',
'Role': 'string',
'Command': {
'Name': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'Progress': 123.0,
'MaxCapacity': 123.0,
'SecurityConfiguration': 'string',
'GlueVersion': 'string'
}
}
Response Structure
(dict) --
Session (dict) --
The session object is returned in the response.
Id (string) --
The ID of the session.
CreatedOn (datetime) --
The time and date when the session was created.
Status (string) --
The session status.
ErrorMessage (string) --
The error message displayed during the session.
Description (string) --
The description of the session.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role associated with the Session.
Command (dict) --
The command object.See SessionCommand.
Name (string) --
Specifies the name of the SessionCommand. Can be 'glueetl' or 'gluestreaming'.
PythonVersion (string) --
Specifies the Python version. The Python version indicates the version supported for jobs of type Spark.
DefaultArguments (dict) --
A map array of key-value pairs. Max is 75 pairs.
Connections (dict) --
The number of connections used for the session.
Connections (list) --
A list of connections used by the job.
Progress (float) --
The code execution progress of the session.
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when the job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB memory.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with the session.
GlueVersion (string) --
The Glue version determines the versions of Apache Spark and Python that Glue supports. The GlueVersion must be greater than 2.0.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionget_statement(**kwargs)¶Retrieves the statement.
See also: AWS API Documentation
Request Syntax
response = client.get_statement(
SessionId='string',
Id=123,
RequestOrigin='string'
)
[REQUIRED]
The Session ID of the statement.
[REQUIRED]
The Id of the statement.
dict
Response Syntax
{
'Statement': {
'Id': 123,
'Code': 'string',
'State': 'WAITING'|'RUNNING'|'AVAILABLE'|'CANCELLING'|'CANCELLED'|'ERROR',
'Output': {
'Data': {
'TextPlain': 'string'
},
'ExecutionCount': 123,
'Status': 'WAITING'|'RUNNING'|'AVAILABLE'|'CANCELLING'|'CANCELLED'|'ERROR',
'ErrorName': 'string',
'ErrorValue': 'string',
'Traceback': [
'string',
]
},
'Progress': 123.0,
'StartedOn': 123,
'CompletedOn': 123
}
}
Response Structure
(dict) --
Statement (dict) --
Returns the statement.
Id (integer) --
The ID of the statement.
Code (string) --
The execution code of the statement.
State (string) --
The state while request is actioned.
Output (dict) --
The output in JSON.
Data (dict) --
The code execution output.
TextPlain (string) --
The code execution output in text format.
ExecutionCount (integer) --
The execution count of the output.
Status (string) --
The status of the code execution output.
ErrorName (string) --
The name of the error in the output.
ErrorValue (string) --
The error value of the output.
Traceback (list) --
The traceback of the output.
Progress (float) --
The code execution progress.
StartedOn (integer) --
The unix time and date that the job definition was started.
CompletedOn (integer) --
The unix time and date that the job definition was completed.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.IllegalSessionStateExceptionget_table(**kwargs)¶Retrieves the Table definition in a Data Catalog for a specified table.
See also: AWS API Documentation
Request Syntax
response = client.get_table(
CatalogId='string',
DatabaseName='string',
Name='string',
TransactionId='string',
QueryAsOfTime=datetime(2015, 1, 1)
)
[REQUIRED]
The name of the database in the catalog in which the table resides. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The name of the table for which to retrieve the definition. For Hive compatibility, this name is entirely lowercase.
TransactionId .dict
Response Syntax
{
'Table': {
'Name': 'string',
'DatabaseName': 'string',
'Description': 'string',
'Owner': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'CreatedBy': 'string',
'IsRegisteredWithLakeFormation': True|False,
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
},
'CatalogId': 'string',
'VersionId': 'string'
}
}
Response Structure
(dict) --
Table (dict) --
The Table object that defines the specified table.
Name (string) --
The table name. For Hive compatibility, this must be entirely lowercase.
DatabaseName (string) --
The name of the database where the table metadata resides. For Hive compatibility, this must be all lowercase.
Description (string) --
A description of the table.
Owner (string) --
The owner of the table.
CreateTime (datetime) --
The time when the table definition was created in the Data Catalog.
UpdateTime (datetime) --
The last time that the table was updated.
LastAccessTime (datetime) --
The last time that the table was accessed. This is usually taken from HDFS, and might not be reliable.
LastAnalyzedTime (datetime) --
The last time that column statistics were computed for this table.
Retention (integer) --
The retention time for this table.
StorageDescriptor (dict) --
A storage descriptor containing information about the physical storage of this table.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
PartitionKeys (list) --
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
ViewOriginalText (string) --
If the table is a view, the original text of the view; otherwise null .
ViewExpandedText (string) --
If the table is a view, the expanded text of the view; otherwise null .
TableType (string) --
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
Parameters (dict) --
These key-value pairs define properties associated with the table.
CreatedBy (string) --
The person or entity who created the table.
IsRegisteredWithLakeFormation (boolean) --
Indicates whether the table has been registered with Lake Formation.
TargetTable (dict) --
A TableIdentifier structure that describes a target table for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
DatabaseName (string) --
The name of the catalog database that contains the target table.
Name (string) --
The name of the target table.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
VersionId (string) --
The ID of the table version.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.ResourceNotReadyExceptionget_table_version(**kwargs)¶Retrieves a specified version of a table.
See also: AWS API Documentation
Request Syntax
response = client.get_table_version(
CatalogId='string',
DatabaseName='string',
TableName='string',
VersionId='string'
)
[REQUIRED]
The database in the catalog in which the table resides. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The name of the table. For Hive compatibility, this name is entirely lowercase.
VersionID is a string representation of an integer. Each version is incremented by 1.dict
Response Syntax
{
'TableVersion': {
'Table': {
'Name': 'string',
'DatabaseName': 'string',
'Description': 'string',
'Owner': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'CreatedBy': 'string',
'IsRegisteredWithLakeFormation': True|False,
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
},
'CatalogId': 'string',
'VersionId': 'string'
},
'VersionId': 'string'
}
}
Response Structure
(dict) --
TableVersion (dict) --
The requested table version.
Table (dict) --
The table in question.
Name (string) --
The table name. For Hive compatibility, this must be entirely lowercase.
DatabaseName (string) --
The name of the database where the table metadata resides. For Hive compatibility, this must be all lowercase.
Description (string) --
A description of the table.
Owner (string) --
The owner of the table.
CreateTime (datetime) --
The time when the table definition was created in the Data Catalog.
UpdateTime (datetime) --
The last time that the table was updated.
LastAccessTime (datetime) --
The last time that the table was accessed. This is usually taken from HDFS, and might not be reliable.
LastAnalyzedTime (datetime) --
The last time that column statistics were computed for this table.
Retention (integer) --
The retention time for this table.
StorageDescriptor (dict) --
A storage descriptor containing information about the physical storage of this table.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
PartitionKeys (list) --
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
ViewOriginalText (string) --
If the table is a view, the original text of the view; otherwise null .
ViewExpandedText (string) --
If the table is a view, the expanded text of the view; otherwise null .
TableType (string) --
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
Parameters (dict) --
These key-value pairs define properties associated with the table.
CreatedBy (string) --
The person or entity who created the table.
IsRegisteredWithLakeFormation (boolean) --
Indicates whether the table has been registered with Lake Formation.
TargetTable (dict) --
A TableIdentifier structure that describes a target table for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
DatabaseName (string) --
The name of the catalog database that contains the target table.
Name (string) --
The name of the target table.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
VersionId (string) --
The ID of the table version.
VersionId (string) --
The ID value that identifies this table version. A VersionId is a string representation of an integer. Each version is incremented by 1.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_table_versions(**kwargs)¶Retrieves a list of strings that identify available versions of a specified table.
See also: AWS API Documentation
Request Syntax
response = client.get_table_versions(
CatalogId='string',
DatabaseName='string',
TableName='string',
NextToken='string',
MaxResults=123
)
[REQUIRED]
The database in the catalog in which the table resides. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The name of the table. For Hive compatibility, this name is entirely lowercase.
dict
Response Syntax
{
'TableVersions': [
{
'Table': {
'Name': 'string',
'DatabaseName': 'string',
'Description': 'string',
'Owner': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'CreatedBy': 'string',
'IsRegisteredWithLakeFormation': True|False,
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
},
'CatalogId': 'string',
'VersionId': 'string'
},
'VersionId': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
TableVersions (list) --
A list of strings identifying available versions of the specified table.
(dict) --
Specifies a version of a table.
Table (dict) --
The table in question.
Name (string) --
The table name. For Hive compatibility, this must be entirely lowercase.
DatabaseName (string) --
The name of the database where the table metadata resides. For Hive compatibility, this must be all lowercase.
Description (string) --
A description of the table.
Owner (string) --
The owner of the table.
CreateTime (datetime) --
The time when the table definition was created in the Data Catalog.
UpdateTime (datetime) --
The last time that the table was updated.
LastAccessTime (datetime) --
The last time that the table was accessed. This is usually taken from HDFS, and might not be reliable.
LastAnalyzedTime (datetime) --
The last time that column statistics were computed for this table.
Retention (integer) --
The retention time for this table.
StorageDescriptor (dict) --
A storage descriptor containing information about the physical storage of this table.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
PartitionKeys (list) --
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
ViewOriginalText (string) --
If the table is a view, the original text of the view; otherwise null .
ViewExpandedText (string) --
If the table is a view, the expanded text of the view; otherwise null .
TableType (string) --
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
Parameters (dict) --
These key-value pairs define properties associated with the table.
CreatedBy (string) --
The person or entity who created the table.
IsRegisteredWithLakeFormation (boolean) --
Indicates whether the table has been registered with Lake Formation.
TargetTable (dict) --
A TableIdentifier structure that describes a target table for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
DatabaseName (string) --
The name of the catalog database that contains the target table.
Name (string) --
The name of the target table.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
VersionId (string) --
The ID of the table version.
VersionId (string) --
The ID value that identifies this table version. A VersionId is a string representation of an integer. Each version is incremented by 1.
NextToken (string) --
A continuation token, if the list of available versions does not include the last one.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_tables(**kwargs)¶Retrieves the definitions of some or all of the tables in a given Database .
See also: AWS API Documentation
Request Syntax
response = client.get_tables(
CatalogId='string',
DatabaseName='string',
Expression='string',
NextToken='string',
MaxResults=123,
TransactionId='string',
QueryAsOfTime=datetime(2015, 1, 1)
)
[REQUIRED]
The database in the catalog whose tables to list. For Hive compatibility, this name is entirely lowercase.
TransactionId .dict
Response Syntax
{
'TableList': [
{
'Name': 'string',
'DatabaseName': 'string',
'Description': 'string',
'Owner': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'CreatedBy': 'string',
'IsRegisteredWithLakeFormation': True|False,
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
},
'CatalogId': 'string',
'VersionId': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
TableList (list) --
A list of the requested Table objects.
(dict) --
Represents a collection of related data organized in columns and rows.
Name (string) --
The table name. For Hive compatibility, this must be entirely lowercase.
DatabaseName (string) --
The name of the database where the table metadata resides. For Hive compatibility, this must be all lowercase.
Description (string) --
A description of the table.
Owner (string) --
The owner of the table.
CreateTime (datetime) --
The time when the table definition was created in the Data Catalog.
UpdateTime (datetime) --
The last time that the table was updated.
LastAccessTime (datetime) --
The last time that the table was accessed. This is usually taken from HDFS, and might not be reliable.
LastAnalyzedTime (datetime) --
The last time that column statistics were computed for this table.
Retention (integer) --
The retention time for this table.
StorageDescriptor (dict) --
A storage descriptor containing information about the physical storage of this table.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
PartitionKeys (list) --
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
ViewOriginalText (string) --
If the table is a view, the original text of the view; otherwise null .
ViewExpandedText (string) --
If the table is a view, the expanded text of the view; otherwise null .
TableType (string) --
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
Parameters (dict) --
These key-value pairs define properties associated with the table.
CreatedBy (string) --
The person or entity who created the table.
IsRegisteredWithLakeFormation (boolean) --
Indicates whether the table has been registered with Lake Formation.
TargetTable (dict) --
A TableIdentifier structure that describes a target table for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
DatabaseName (string) --
The name of the catalog database that contains the target table.
Name (string) --
The name of the target table.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
VersionId (string) --
The ID of the table version.
NextToken (string) --
A continuation token, present if the current list segment is not the last.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.GlueEncryptionExceptionRetrieves a list of tags associated with a resource.
See also: AWS API Documentation
Request Syntax
response = client.get_tags(
ResourceArn='string'
)
[REQUIRED]
The Amazon Resource Name (ARN) of the resource for which to retrieve tags.
{
'Tags': {
'string': 'string'
}
}
Response Structure
The requested tags.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.EntityNotFoundExceptionget_trigger(**kwargs)¶Retrieves the definition of a trigger.
See also: AWS API Documentation
Request Syntax
response = client.get_trigger(
Name='string'
)
[REQUIRED]
The name of the trigger to retrieve.
{
'Trigger': {
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
}
Response Structure
The requested trigger definition.
The name of the trigger.
The name of the workflow associated with the trigger.
Reserved for future use.
The type of trigger that this is.
The current state of the trigger.
A description of this trigger.
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
The actions initiated by this trigger.
Defines an action to be initiated by a trigger.
The name of a job to be run.
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
The name of the SecurityConfiguration structure to be used with this action.
Specifies configuration properties of a job run notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
The name of the crawler to be used with this action.
The predicate of this trigger, which defines when it will fire.
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
A list of the conditions that determine when the trigger will fire.
Defines a condition under which a trigger fires.
A logical operator.
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
The name of the crawler to which this condition applies.
The state of the crawler to which this condition applies.
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_triggers(**kwargs)¶Gets all the triggers associated with a job.
See also: AWS API Documentation
Request Syntax
response = client.get_triggers(
NextToken='string',
DependentJobName='string',
MaxResults=123
)
dict
Response Syntax
{
'Triggers': [
{
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Triggers (list) --
A list of triggers for the specified job.
(dict) --
Information about a specific trigger.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
NextToken (string) --
A continuation token, if not all the requested triggers have yet been returned.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_unfiltered_partition_metadata(**kwargs)¶See also: AWS API Documentation
Request Syntax
response = client.get_unfiltered_partition_metadata(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionValues=[
'string',
],
AuditContext={
'AdditionalAuditContext': 'string',
'RequestedColumns': [
'string',
],
'AllColumnsRequested': True|False
},
SupportedPermissionTypes=[
'COLUMN_PERMISSION'|'CELL_FILTER_PERMISSION',
]
)
[REQUIRED]
A structure containing information for audit.
The context for the audit..
The requested columns for audit.
All columns request for audit.
[REQUIRED]
dict
Response Syntax
{
'Partition': {
'Values': [
'string',
],
'DatabaseName': 'string',
'TableName': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1),
'CatalogId': 'string'
},
'AuthorizedColumns': [
'string',
],
'IsRegisteredWithLakeFormation': True|False
}
Response Structure
(dict) --
Partition (dict) --
Represents a slice of table data.
Values (list) --
The values of the partition.
DatabaseName (string) --
The name of the catalog database in which to create the partition.
TableName (string) --
The name of the database table in which to create the partition.
CreationTime (datetime) --
The time at which the partition was created.
LastAccessTime (datetime) --
The last time at which the partition was accessed.
StorageDescriptor (dict) --
Provides information about the physical location where the partition is stored.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
Parameters (dict) --
These key-value pairs define partition parameters.
LastAnalyzedTime (datetime) --
The last time at which column statistics were computed for this partition.
CatalogId (string) --
The ID of the Data Catalog in which the partition resides.
AuthorizedColumns (list) --
IsRegisteredWithLakeFormation (boolean) --
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.PermissionTypeMismatchExceptionget_unfiltered_partitions_metadata(**kwargs)¶See also: AWS API Documentation
Request Syntax
response = client.get_unfiltered_partitions_metadata(
CatalogId='string',
DatabaseName='string',
TableName='string',
Expression='string',
AuditContext={
'AdditionalAuditContext': 'string',
'RequestedColumns': [
'string',
],
'AllColumnsRequested': True|False
},
SupportedPermissionTypes=[
'COLUMN_PERMISSION'|'CELL_FILTER_PERMISSION',
],
NextToken='string',
Segment={
'SegmentNumber': 123,
'TotalSegments': 123
},
MaxResults=123
)
A structure containing information for audit.
The context for the audit..
The requested columns for audit.
All columns request for audit.
[REQUIRED]
Defines a non-overlapping region of a table's partitions, allowing multiple requests to be run in parallel.
The zero-based index number of the segment. For example, if the total number of segments is 4, SegmentNumber values range from 0 through 3.
The total number of segments.
dict
Response Syntax
{
'UnfilteredPartitions': [
{
'Partition': {
'Values': [
'string',
],
'DatabaseName': 'string',
'TableName': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1),
'CatalogId': 'string'
},
'AuthorizedColumns': [
'string',
],
'IsRegisteredWithLakeFormation': True|False
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
UnfilteredPartitions (list) --
(dict) --
Partition (dict) --
Represents a slice of table data.
Values (list) --
The values of the partition.
DatabaseName (string) --
The name of the catalog database in which to create the partition.
TableName (string) --
The name of the database table in which to create the partition.
CreationTime (datetime) --
The time at which the partition was created.
LastAccessTime (datetime) --
The last time at which the partition was accessed.
StorageDescriptor (dict) --
Provides information about the physical location where the partition is stored.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
Parameters (dict) --
These key-value pairs define partition parameters.
LastAnalyzedTime (datetime) --
The last time at which column statistics were computed for this partition.
CatalogId (string) --
The ID of the Data Catalog in which the partition resides.
AuthorizedColumns (list) --
IsRegisteredWithLakeFormation (boolean) --
NextToken (string) --
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.PermissionTypeMismatchExceptionget_unfiltered_table_metadata(**kwargs)¶See also: AWS API Documentation
Request Syntax
response = client.get_unfiltered_table_metadata(
CatalogId='string',
DatabaseName='string',
Name='string',
AuditContext={
'AdditionalAuditContext': 'string',
'RequestedColumns': [
'string',
],
'AllColumnsRequested': True|False
},
SupportedPermissionTypes=[
'COLUMN_PERMISSION'|'CELL_FILTER_PERMISSION',
]
)
A structure containing information for audit.
The context for the audit..
The requested columns for audit.
All columns request for audit.
[REQUIRED]
dict
Response Syntax
{
'Table': {
'Name': 'string',
'DatabaseName': 'string',
'Description': 'string',
'Owner': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'CreatedBy': 'string',
'IsRegisteredWithLakeFormation': True|False,
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
},
'CatalogId': 'string',
'VersionId': 'string'
},
'AuthorizedColumns': [
'string',
],
'IsRegisteredWithLakeFormation': True|False,
'CellFilters': [
{
'ColumnName': 'string',
'RowFilterExpression': 'string'
},
]
}
Response Structure
(dict) --
Table (dict) --
Represents a collection of related data organized in columns and rows.
Name (string) --
The table name. For Hive compatibility, this must be entirely lowercase.
DatabaseName (string) --
The name of the database where the table metadata resides. For Hive compatibility, this must be all lowercase.
Description (string) --
A description of the table.
Owner (string) --
The owner of the table.
CreateTime (datetime) --
The time when the table definition was created in the Data Catalog.
UpdateTime (datetime) --
The last time that the table was updated.
LastAccessTime (datetime) --
The last time that the table was accessed. This is usually taken from HDFS, and might not be reliable.
LastAnalyzedTime (datetime) --
The last time that column statistics were computed for this table.
Retention (integer) --
The retention time for this table.
StorageDescriptor (dict) --
A storage descriptor containing information about the physical storage of this table.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
PartitionKeys (list) --
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
ViewOriginalText (string) --
If the table is a view, the original text of the view; otherwise null .
ViewExpandedText (string) --
If the table is a view, the expanded text of the view; otherwise null .
TableType (string) --
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
Parameters (dict) --
These key-value pairs define properties associated with the table.
CreatedBy (string) --
The person or entity who created the table.
IsRegisteredWithLakeFormation (boolean) --
Indicates whether the table has been registered with Lake Formation.
TargetTable (dict) --
A TableIdentifier structure that describes a target table for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
DatabaseName (string) --
The name of the catalog database that contains the target table.
Name (string) --
The name of the target table.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
VersionId (string) --
The ID of the table version.
AuthorizedColumns (list) --
IsRegisteredWithLakeFormation (boolean) --
CellFilters (list) --
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.PermissionTypeMismatchExceptionget_user_defined_function(**kwargs)¶Retrieves a specified function definition from the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.get_user_defined_function(
CatalogId='string',
DatabaseName='string',
FunctionName='string'
)
[REQUIRED]
The name of the catalog database where the function is located.
[REQUIRED]
The name of the function.
dict
Response Syntax
{
'UserDefinedFunction': {
'FunctionName': 'string',
'DatabaseName': 'string',
'ClassName': 'string',
'OwnerName': 'string',
'OwnerType': 'USER'|'ROLE'|'GROUP',
'CreateTime': datetime(2015, 1, 1),
'ResourceUris': [
{
'ResourceType': 'JAR'|'FILE'|'ARCHIVE',
'Uri': 'string'
},
],
'CatalogId': 'string'
}
}
Response Structure
(dict) --
UserDefinedFunction (dict) --
The requested function definition.
FunctionName (string) --
The name of the function.
DatabaseName (string) --
The name of the catalog database that contains the function.
ClassName (string) --
The Java class that contains the function code.
OwnerName (string) --
The owner of the function.
OwnerType (string) --
The owner type.
CreateTime (datetime) --
The time at which the function was created.
ResourceUris (list) --
The resource URIs for the function.
(dict) --
The URIs for function resources.
ResourceType (string) --
The type of the resource.
Uri (string) --
The URI for accessing the resource.
CatalogId (string) --
The ID of the Data Catalog in which the function resides.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_user_defined_functions(**kwargs)¶Retrieves multiple function definitions from the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.get_user_defined_functions(
CatalogId='string',
DatabaseName='string',
Pattern='string',
NextToken='string',
MaxResults=123
)
[REQUIRED]
An optional function-name pattern string that filters the function definitions returned.
dict
Response Syntax
{
'UserDefinedFunctions': [
{
'FunctionName': 'string',
'DatabaseName': 'string',
'ClassName': 'string',
'OwnerName': 'string',
'OwnerType': 'USER'|'ROLE'|'GROUP',
'CreateTime': datetime(2015, 1, 1),
'ResourceUris': [
{
'ResourceType': 'JAR'|'FILE'|'ARCHIVE',
'Uri': 'string'
},
],
'CatalogId': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
UserDefinedFunctions (list) --
A list of requested function definitions.
(dict) --
Represents the equivalent of a Hive user-defined function ( UDF ) definition.
FunctionName (string) --
The name of the function.
DatabaseName (string) --
The name of the catalog database that contains the function.
ClassName (string) --
The Java class that contains the function code.
OwnerName (string) --
The owner of the function.
OwnerType (string) --
The owner type.
CreateTime (datetime) --
The time at which the function was created.
ResourceUris (list) --
The resource URIs for the function.
(dict) --
The URIs for function resources.
ResourceType (string) --
The type of the resource.
Uri (string) --
The URI for accessing the resource.
CatalogId (string) --
The ID of the Data Catalog in which the function resides.
NextToken (string) --
A continuation token, if the list of functions returned does not include the last requested function.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.GlueEncryptionExceptionget_waiter(waiter_name)¶Returns an object that can wait for some condition.
get_workflow(**kwargs)¶Retrieves resource metadata for a workflow.
See also: AWS API Documentation
Request Syntax
response = client.get_workflow(
Name='string',
IncludeGraph=True|False
)
[REQUIRED]
The name of the workflow to retrieve.
dict
Response Syntax
{
'Workflow': {
'Name': 'string',
'Description': 'string',
'DefaultRunProperties': {
'string': 'string'
},
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'LastRun': {
'Name': 'string',
'WorkflowRunId': 'string',
'PreviousRunId': 'string',
'WorkflowRunProperties': {
'string': 'string'
},
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'Status': 'RUNNING'|'COMPLETED'|'STOPPING'|'STOPPED'|'ERROR',
'ErrorMessage': 'string',
'Statistics': {
'TotalActions': 123,
'TimeoutActions': 123,
'FailedActions': 123,
'StoppedActions': 123,
'SucceededActions': 123,
'RunningActions': 123,
'ErroredActions': 123,
'WaitingActions': 123
},
'Graph': {
'Nodes': [
{
'Type': 'CRAWLER'|'JOB'|'TRIGGER',
'Name': 'string',
'UniqueId': 'string',
'TriggerDetails': {
'Trigger': {
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
},
'JobDetails': {
'JobRuns': [
{
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
},
]
},
'CrawlerDetails': {
'Crawls': [
{
'State': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string'
},
]
}
},
],
'Edges': [
{
'SourceId': 'string',
'DestinationId': 'string'
},
]
},
'StartingEventBatchCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
},
'Graph': {
'Nodes': [
{
'Type': 'CRAWLER'|'JOB'|'TRIGGER',
'Name': 'string',
'UniqueId': 'string',
'TriggerDetails': {
'Trigger': {
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
},
'JobDetails': {
'JobRuns': [
{
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
},
]
},
'CrawlerDetails': {
'Crawls': [
{
'State': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string'
},
]
}
},
],
'Edges': [
{
'SourceId': 'string',
'DestinationId': 'string'
},
]
},
'MaxConcurrentRuns': 123,
'BlueprintDetails': {
'BlueprintName': 'string',
'RunId': 'string'
}
}
}
Response Structure
(dict) --
Workflow (dict) --
The resource metadata for the workflow.
Name (string) --
The name of the workflow.
Description (string) --
A description of the workflow.
DefaultRunProperties (dict) --
A collection of properties to be used as part of each execution of the workflow. The run properties are made available to each job in the workflow. A job can modify the properties for the next jobs in the flow.
CreatedOn (datetime) --
The date and time when the workflow was created.
LastModifiedOn (datetime) --
The date and time when the workflow was last modified.
LastRun (dict) --
The information about the last execution of the workflow.
Name (string) --
Name of the workflow that was run.
WorkflowRunId (string) --
The ID of this workflow run.
PreviousRunId (string) --
The ID of the previous workflow run.
WorkflowRunProperties (dict) --
The workflow run properties which were set during the run.
StartedOn (datetime) --
The date and time when the workflow run was started.
CompletedOn (datetime) --
The date and time when the workflow run completed.
Status (string) --
The status of the workflow run.
ErrorMessage (string) --
This error message describes any error that may have occurred in starting the workflow run. Currently the only error message is "Concurrent runs exceeded for workflow: foo ."
Statistics (dict) --
The statistics of the run.
TotalActions (integer) --
Total number of Actions in the workflow run.
TimeoutActions (integer) --
Total number of Actions that timed out.
FailedActions (integer) --
Total number of Actions that have failed.
StoppedActions (integer) --
Total number of Actions that have stopped.
SucceededActions (integer) --
Total number of Actions that have succeeded.
RunningActions (integer) --
Total number Actions in running state.
ErroredActions (integer) --
Indicates the count of job runs in the ERROR state in the workflow run.
WaitingActions (integer) --
Indicates the count of job runs in WAITING state in the workflow run.
Graph (dict) --
The graph representing all the Glue components that belong to the workflow as nodes and directed connections between them as edges.
Nodes (list) --
A list of the the Glue components belong to the workflow represented as nodes.
(dict) --
A node represents an Glue component (trigger, crawler, or job) on a workflow graph.
Type (string) --
The type of Glue component represented by the node.
Name (string) --
The name of the Glue component represented by the node.
UniqueId (string) --
The unique Id assigned to the node within the workflow.
TriggerDetails (dict) --
Details of the Trigger when the node represents a Trigger.
Trigger (dict) --
The information of the trigger represented by the trigger node.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
JobDetails (dict) --
Details of the Job when the node represents a Job.
JobRuns (list) --
The information for the job runs represented by the job node.
(dict) --
Contains information about a job run.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
CrawlerDetails (dict) --
Details of the crawler when the node represents a crawler.
Crawls (list) --
A list of crawls represented by the crawl node.
(dict) --
The details of a crawl in the workflow.
State (string) --
The state of the crawler.
StartedOn (datetime) --
The date and time on which the crawl started.
CompletedOn (datetime) --
The date and time on which the crawl completed.
ErrorMessage (string) --
The error message associated with the crawl.
LogGroup (string) --
The log group associated with the crawl.
LogStream (string) --
The log stream associated with the crawl.
Edges (list) --
A list of all the directed connections between the nodes belonging to the workflow.
(dict) --
An edge represents a directed connection between two Glue components that are part of the workflow the edge belongs to.
SourceId (string) --
The unique of the node within the workflow where the edge starts.
DestinationId (string) --
The unique of the node within the workflow where the edge ends.
StartingEventBatchCondition (dict) --
The batch condition that started the workflow run.
BatchSize (integer) --
Number of events in the batch.
BatchWindow (integer) --
Duration of the batch window in seconds.
Graph (dict) --
The graph representing all the Glue components that belong to the workflow as nodes and directed connections between them as edges.
Nodes (list) --
A list of the the Glue components belong to the workflow represented as nodes.
(dict) --
A node represents an Glue component (trigger, crawler, or job) on a workflow graph.
Type (string) --
The type of Glue component represented by the node.
Name (string) --
The name of the Glue component represented by the node.
UniqueId (string) --
The unique Id assigned to the node within the workflow.
TriggerDetails (dict) --
Details of the Trigger when the node represents a Trigger.
Trigger (dict) --
The information of the trigger represented by the trigger node.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
JobDetails (dict) --
Details of the Job when the node represents a Job.
JobRuns (list) --
The information for the job runs represented by the job node.
(dict) --
Contains information about a job run.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
CrawlerDetails (dict) --
Details of the crawler when the node represents a crawler.
Crawls (list) --
A list of crawls represented by the crawl node.
(dict) --
The details of a crawl in the workflow.
State (string) --
The state of the crawler.
StartedOn (datetime) --
The date and time on which the crawl started.
CompletedOn (datetime) --
The date and time on which the crawl completed.
ErrorMessage (string) --
The error message associated with the crawl.
LogGroup (string) --
The log group associated with the crawl.
LogStream (string) --
The log stream associated with the crawl.
Edges (list) --
A list of all the directed connections between the nodes belonging to the workflow.
(dict) --
An edge represents a directed connection between two Glue components that are part of the workflow the edge belongs to.
SourceId (string) --
The unique of the node within the workflow where the edge starts.
DestinationId (string) --
The unique of the node within the workflow where the edge ends.
MaxConcurrentRuns (integer) --
You can use this parameter to prevent unwanted multiple updates to data, to control costs, or in some cases, to prevent exceeding the maximum number of concurrent runs of any of the component jobs. If you leave this parameter blank, there is no limit to the number of concurrent workflow runs.
BlueprintDetails (dict) --
This structure indicates the details of the blueprint that this particular workflow is created from.
BlueprintName (string) --
The name of the blueprint.
RunId (string) --
The run ID for this blueprint.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_workflow_run(**kwargs)¶Retrieves the metadata for a given workflow run.
See also: AWS API Documentation
Request Syntax
response = client.get_workflow_run(
Name='string',
RunId='string',
IncludeGraph=True|False
)
[REQUIRED]
Name of the workflow being run.
[REQUIRED]
The ID of the workflow run.
dict
Response Syntax
{
'Run': {
'Name': 'string',
'WorkflowRunId': 'string',
'PreviousRunId': 'string',
'WorkflowRunProperties': {
'string': 'string'
},
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'Status': 'RUNNING'|'COMPLETED'|'STOPPING'|'STOPPED'|'ERROR',
'ErrorMessage': 'string',
'Statistics': {
'TotalActions': 123,
'TimeoutActions': 123,
'FailedActions': 123,
'StoppedActions': 123,
'SucceededActions': 123,
'RunningActions': 123,
'ErroredActions': 123,
'WaitingActions': 123
},
'Graph': {
'Nodes': [
{
'Type': 'CRAWLER'|'JOB'|'TRIGGER',
'Name': 'string',
'UniqueId': 'string',
'TriggerDetails': {
'Trigger': {
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
},
'JobDetails': {
'JobRuns': [
{
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
},
]
},
'CrawlerDetails': {
'Crawls': [
{
'State': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string'
},
]
}
},
],
'Edges': [
{
'SourceId': 'string',
'DestinationId': 'string'
},
]
},
'StartingEventBatchCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
}
Response Structure
(dict) --
Run (dict) --
The requested workflow run metadata.
Name (string) --
Name of the workflow that was run.
WorkflowRunId (string) --
The ID of this workflow run.
PreviousRunId (string) --
The ID of the previous workflow run.
WorkflowRunProperties (dict) --
The workflow run properties which were set during the run.
StartedOn (datetime) --
The date and time when the workflow run was started.
CompletedOn (datetime) --
The date and time when the workflow run completed.
Status (string) --
The status of the workflow run.
ErrorMessage (string) --
This error message describes any error that may have occurred in starting the workflow run. Currently the only error message is "Concurrent runs exceeded for workflow: foo ."
Statistics (dict) --
The statistics of the run.
TotalActions (integer) --
Total number of Actions in the workflow run.
TimeoutActions (integer) --
Total number of Actions that timed out.
FailedActions (integer) --
Total number of Actions that have failed.
StoppedActions (integer) --
Total number of Actions that have stopped.
SucceededActions (integer) --
Total number of Actions that have succeeded.
RunningActions (integer) --
Total number Actions in running state.
ErroredActions (integer) --
Indicates the count of job runs in the ERROR state in the workflow run.
WaitingActions (integer) --
Indicates the count of job runs in WAITING state in the workflow run.
Graph (dict) --
The graph representing all the Glue components that belong to the workflow as nodes and directed connections between them as edges.
Nodes (list) --
A list of the the Glue components belong to the workflow represented as nodes.
(dict) --
A node represents an Glue component (trigger, crawler, or job) on a workflow graph.
Type (string) --
The type of Glue component represented by the node.
Name (string) --
The name of the Glue component represented by the node.
UniqueId (string) --
The unique Id assigned to the node within the workflow.
TriggerDetails (dict) --
Details of the Trigger when the node represents a Trigger.
Trigger (dict) --
The information of the trigger represented by the trigger node.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
JobDetails (dict) --
Details of the Job when the node represents a Job.
JobRuns (list) --
The information for the job runs represented by the job node.
(dict) --
Contains information about a job run.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
CrawlerDetails (dict) --
Details of the crawler when the node represents a crawler.
Crawls (list) --
A list of crawls represented by the crawl node.
(dict) --
The details of a crawl in the workflow.
State (string) --
The state of the crawler.
StartedOn (datetime) --
The date and time on which the crawl started.
CompletedOn (datetime) --
The date and time on which the crawl completed.
ErrorMessage (string) --
The error message associated with the crawl.
LogGroup (string) --
The log group associated with the crawl.
LogStream (string) --
The log stream associated with the crawl.
Edges (list) --
A list of all the directed connections between the nodes belonging to the workflow.
(dict) --
An edge represents a directed connection between two Glue components that are part of the workflow the edge belongs to.
SourceId (string) --
The unique of the node within the workflow where the edge starts.
DestinationId (string) --
The unique of the node within the workflow where the edge ends.
StartingEventBatchCondition (dict) --
The batch condition that started the workflow run.
BatchSize (integer) --
Number of events in the batch.
BatchWindow (integer) --
Duration of the batch window in seconds.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_workflow_run_properties(**kwargs)¶Retrieves the workflow run properties which were set during the run.
See also: AWS API Documentation
Request Syntax
response = client.get_workflow_run_properties(
Name='string',
RunId='string'
)
[REQUIRED]
Name of the workflow which was run.
[REQUIRED]
The ID of the workflow run whose run properties should be returned.
dict
Response Syntax
{
'RunProperties': {
'string': 'string'
}
}
Response Structure
(dict) --
RunProperties (dict) --
The workflow run properties which were set during the specified run.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionget_workflow_runs(**kwargs)¶Retrieves metadata for all runs of a given workflow.
See also: AWS API Documentation
Request Syntax
response = client.get_workflow_runs(
Name='string',
IncludeGraph=True|False,
NextToken='string',
MaxResults=123
)
[REQUIRED]
Name of the workflow whose metadata of runs should be returned.
dict
Response Syntax
{
'Runs': [
{
'Name': 'string',
'WorkflowRunId': 'string',
'PreviousRunId': 'string',
'WorkflowRunProperties': {
'string': 'string'
},
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'Status': 'RUNNING'|'COMPLETED'|'STOPPING'|'STOPPED'|'ERROR',
'ErrorMessage': 'string',
'Statistics': {
'TotalActions': 123,
'TimeoutActions': 123,
'FailedActions': 123,
'StoppedActions': 123,
'SucceededActions': 123,
'RunningActions': 123,
'ErroredActions': 123,
'WaitingActions': 123
},
'Graph': {
'Nodes': [
{
'Type': 'CRAWLER'|'JOB'|'TRIGGER',
'Name': 'string',
'UniqueId': 'string',
'TriggerDetails': {
'Trigger': {
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
},
'JobDetails': {
'JobRuns': [
{
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
},
]
},
'CrawlerDetails': {
'Crawls': [
{
'State': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR',
'StartedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string'
},
]
}
},
],
'Edges': [
{
'SourceId': 'string',
'DestinationId': 'string'
},
]
},
'StartingEventBatchCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Runs (list) --
A list of workflow run metadata objects.
(dict) --
A workflow run is an execution of a workflow providing all the runtime information.
Name (string) --
Name of the workflow that was run.
WorkflowRunId (string) --
The ID of this workflow run.
PreviousRunId (string) --
The ID of the previous workflow run.
WorkflowRunProperties (dict) --
The workflow run properties which were set during the run.
StartedOn (datetime) --
The date and time when the workflow run was started.
CompletedOn (datetime) --
The date and time when the workflow run completed.
Status (string) --
The status of the workflow run.
ErrorMessage (string) --
This error message describes any error that may have occurred in starting the workflow run. Currently the only error message is "Concurrent runs exceeded for workflow: foo ."
Statistics (dict) --
The statistics of the run.
TotalActions (integer) --
Total number of Actions in the workflow run.
TimeoutActions (integer) --
Total number of Actions that timed out.
FailedActions (integer) --
Total number of Actions that have failed.
StoppedActions (integer) --
Total number of Actions that have stopped.
SucceededActions (integer) --
Total number of Actions that have succeeded.
RunningActions (integer) --
Total number Actions in running state.
ErroredActions (integer) --
Indicates the count of job runs in the ERROR state in the workflow run.
WaitingActions (integer) --
Indicates the count of job runs in WAITING state in the workflow run.
Graph (dict) --
The graph representing all the Glue components that belong to the workflow as nodes and directed connections between them as edges.
Nodes (list) --
A list of the the Glue components belong to the workflow represented as nodes.
(dict) --
A node represents an Glue component (trigger, crawler, or job) on a workflow graph.
Type (string) --
The type of Glue component represented by the node.
Name (string) --
The name of the Glue component represented by the node.
UniqueId (string) --
The unique Id assigned to the node within the workflow.
TriggerDetails (dict) --
Details of the Trigger when the node represents a Trigger.
Trigger (dict) --
The information of the trigger represented by the trigger node.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
JobDetails (dict) --
Details of the Job when the node represents a Job.
JobRuns (list) --
The information for the job runs represented by the job node.
(dict) --
Contains information about a job run.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
CrawlerDetails (dict) --
Details of the crawler when the node represents a crawler.
Crawls (list) --
A list of crawls represented by the crawl node.
(dict) --
The details of a crawl in the workflow.
State (string) --
The state of the crawler.
StartedOn (datetime) --
The date and time on which the crawl started.
CompletedOn (datetime) --
The date and time on which the crawl completed.
ErrorMessage (string) --
The error message associated with the crawl.
LogGroup (string) --
The log group associated with the crawl.
LogStream (string) --
The log stream associated with the crawl.
Edges (list) --
A list of all the directed connections between the nodes belonging to the workflow.
(dict) --
An edge represents a directed connection between two Glue components that are part of the workflow the edge belongs to.
SourceId (string) --
The unique of the node within the workflow where the edge starts.
DestinationId (string) --
The unique of the node within the workflow where the edge ends.
StartingEventBatchCondition (dict) --
The batch condition that started the workflow run.
BatchSize (integer) --
Number of events in the batch.
BatchWindow (integer) --
Duration of the batch window in seconds.
NextToken (string) --
A continuation token, if not all requested workflow runs have been returned.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionimport_catalog_to_glue(**kwargs)¶Imports an existing Amazon Athena Data Catalog to Glue.
See also: AWS API Documentation
Request Syntax
response = client.import_catalog_to_glue(
CatalogId='string'
)
{}
Response Structure
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionlist_blueprints(**kwargs)¶Lists all the blueprint names in an account.
See also: AWS API Documentation
Request Syntax
response = client.list_blueprints(
NextToken='string',
MaxResults=123,
Tags={
'string': 'string'
}
)
Filters the list by an Amazon Web Services resource tag.
dict
Response Syntax
{
'Blueprints': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) --
Blueprints (list) --
List of names of blueprints in the account.
NextToken (string) --
A continuation token, if not all blueprint names have been returned.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionlist_crawlers(**kwargs)¶Retrieves the names of all crawler resources in this Amazon Web Services account, or the resources with the specified tag. This operation allows you to see which resources are available in your account, and their names.
This operation takes the optional Tags field, which you can use as a filter on the response so that tagged resources can be retrieved as a group. If you choose to use tags filtering, only resources with the tag are retrieved.
See also: AWS API Documentation
Request Syntax
response = client.list_crawlers(
MaxResults=123,
NextToken='string',
Tags={
'string': 'string'
}
)
Specifies to return only these tagged resources.
dict
Response Syntax
{
'CrawlerNames': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) --
CrawlerNames (list) --
The names of all crawlers in the account, or the crawlers with the specified tags.
NextToken (string) --
A continuation token, if the returned list does not contain the last metric available.
Exceptions
Glue.Client.exceptions.OperationTimeoutExceptionlist_crawls(**kwargs)¶Returns all the crawls of a specified crawler. Returns only the crawls that have occurred since the launch date of the crawler history feature, and only retains up to 12 months of crawls. Older crawls will not be returned.
You may use this API to:
See also: AWS API Documentation
Request Syntax
response = client.list_crawls(
CrawlerName='string',
MaxResults=123,
Filters=[
{
'FieldName': 'CRAWL_ID'|'STATE'|'START_TIME'|'END_TIME'|'DPU_HOUR',
'FilterOperator': 'GT'|'GE'|'LT'|'LE'|'EQ'|'NE',
'FieldValue': 'string'
},
],
NextToken='string'
)
[REQUIRED]
The name of the crawler whose runs you want to retrieve.
Filters the crawls by the criteria you specify in a list of CrawlsFilter objects.
A list of fields, comparators and value that you can use to filter the crawler runs for a specified crawler.
A key used to filter the crawler runs for a specified crawler. Valid values for each of the field names are:
CRAWL_ID : A string representing the UUID identifier for a crawl.STATE : A string representing the state of the crawl.START_TIME and END_TIME : The epoch timestamp in milliseconds.DPU_HOUR : The number of data processing unit (DPU) hours used for the crawl.A defined comparator that operates on the value. The available operators are:
GT : Greater than.GE : Greater than or equal to.LT : Less than.LE : Less than or equal to.EQ : Equal to.NE : Not equal to.The value provided for comparison on the crawl field.
dict
Response Syntax
{
'Crawls': [
{
'CrawlId': 'string',
'State': 'RUNNING'|'COMPLETED'|'FAILED'|'STOPPED',
'StartTime': datetime(2015, 1, 1),
'EndTime': datetime(2015, 1, 1),
'Summary': 'string',
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string',
'MessagePrefix': 'string',
'DPUHour': 123.0
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Crawls (list) --
A list of CrawlerHistory objects representing the crawl runs that meet your criteria.
(dict) --
Contains the information for a run of a crawler.
CrawlId (string) --
A UUID identifier for each crawl.
State (string) --
The state of the crawl.
StartTime (datetime) --
The date and time on which the crawl started.
EndTime (datetime) --
The date and time on which the crawl ended.
Summary (string) --
A run summary for the specific crawl in JSON. Contains the catalog tables and partitions that were added, updated, or deleted.
ErrorMessage (string) --
If an error occurred, the error message associated with the crawl.
LogGroup (string) --
The log group associated with the crawl.
LogStream (string) --
The log stream associated with the crawl.
MessagePrefix (string) --
The prefix for a CloudWatch message about this crawl.
DPUHour (float) --
The number of data processing units (DPU) used in hours for the crawl.
NextToken (string) --
A continuation token for paginating the returned list of tokens, returned if the current segment of the list is not the last.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionlist_custom_entity_types(**kwargs)¶Lists all the custom patterns that have been created.
See also: AWS API Documentation
Request Syntax
response = client.list_custom_entity_types(
NextToken='string',
MaxResults=123
)
dict
Response Syntax
{
'CustomEntityTypes': [
{
'Name': 'string',
'RegexString': 'string',
'ContextWords': [
'string',
]
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
CustomEntityTypes (list) --
A list of CustomEntityType objects representing custom patterns.
(dict) --
An object representing a custom pattern for detecting sensitive data across the columns and rows of your structured data.
Name (string) --
A name for the custom pattern that allows it to be retrieved or deleted later. This name must be unique per Amazon Web Services account.
RegexString (string) --
A regular expression string that is used for detecting sensitive data in a custom pattern.
ContextWords (list) --
A list of context words. If none of these context words are found within the vicinity of the regular expression the data will not be detected as sensitive data.
If no context words are passed only a regular expression is checked.
NextToken (string) --
A pagination token, if more results are available.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionlist_data_quality_results(**kwargs)¶Returns all data quality execution results for your account.
See also: AWS API Documentation
Request Syntax
response = client.list_data_quality_results(
Filter={
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'JobName': 'string',
'JobRunId': 'string',
'StartedAfter': datetime(2015, 1, 1),
'StartedBefore': datetime(2015, 1, 1)
},
NextToken='string',
MaxResults=123
)
The filter criteria.
Filter results by the specified data source. For example, retrieving all results for an Glue table.
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.Filter results by the specified job name.
Filter results by the specified job run ID.
Filter results by runs that started after this time.
Filter results by runs that started before this time.
dict
Response Syntax
{
'Results': [
{
'ResultId': 'string',
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'JobName': 'string',
'JobRunId': 'string',
'StartedOn': datetime(2015, 1, 1)
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Results (list) --
A list of DataQualityResultDescription objects.
(dict) --
Describes a data quality result.
ResultId (string) --
The unique result ID for this data quality result.
DataSource (dict) --
The table name associated with the data quality result.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.JobName (string) --
The job name associated with the data quality result.
JobRunId (string) --
The job run ID associated with the data quality result.
StartedOn (datetime) --
The time that the run started for this data quality result.
NextToken (string) --
A pagination token, if more results are available.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionlist_data_quality_rule_recommendation_runs(**kwargs)¶Lists the recommendation runs meeting the filter criteria.
See also: AWS API Documentation
Request Syntax
response = client.list_data_quality_rule_recommendation_runs(
Filter={
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'StartedBefore': datetime(2015, 1, 1),
'StartedAfter': datetime(2015, 1, 1)
},
NextToken='string',
MaxResults=123
)
The filter criteria.
Filter based on a specified data source (Glue table).
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.Filter based on time for results started before provided time.
Filter based on time for results started after provided time.
dict
Response Syntax
{
'Runs': [
{
'RunId': 'string',
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'StartedOn': datetime(2015, 1, 1),
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Runs (list) --
A list of DataQualityRuleRecommendationRunDescription objects.
(dict) --
Describes the result of a data quality rule recommendation run.
RunId (string) --
The unique run identifier associated with this run.
Status (string) --
The status for this run.
StartedOn (datetime) --
The date and time when this run started.
DataSource (dict) --
The data source (Glue table) associated with the recommendation run.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.NextToken (string) --
A pagination token, if more results are available.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionlist_data_quality_ruleset_evaluation_runs(**kwargs)¶Lists all the runs meeting the filter criteria, where a ruleset is evaluated against a data source.
See also: AWS API Documentation
Request Syntax
response = client.list_data_quality_ruleset_evaluation_runs(
Filter={
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
'StartedBefore': datetime(2015, 1, 1),
'StartedAfter': datetime(2015, 1, 1)
},
NextToken='string',
MaxResults=123
)
The filter criteria.
Filter based on a data source (an Glue table) associated with the run.
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.Filter results by runs that started before this time.
Filter results by runs that started after this time.
dict
Response Syntax
{
'Runs': [
{
'RunId': 'string',
'Status': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT',
'StartedOn': datetime(2015, 1, 1),
'DataSource': {
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Runs (list) --
A list of DataQualityRulesetEvaluationRunDescription objects representing data quality ruleset runs.
(dict) --
Describes the result of a data quality ruleset evaluation run.
RunId (string) --
The unique run identifier associated with this run.
Status (string) --
The status for this run.
StartedOn (datetime) --
The date and time when the run started.
DataSource (dict) --
The data source (an Glue table) associated with the run.
GlueTable (dict) --
An Glue table.
DatabaseName (string) --
A database name in the Glue Data Catalog.
TableName (string) --
A table name in the Glue Data Catalog.
CatalogId (string) --
A unique identifier for the Glue Data Catalog.
ConnectionName (string) --
The name of the connection to the Glue Data Catalog.
AdditionalOptions (dict) --
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.NextToken (string) --
A pagination token, if more results are available.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionlist_data_quality_rulesets(**kwargs)¶Returns a paginated list of rulesets for the specified list of Glue tables.
See also: AWS API Documentation
Request Syntax
response = client.list_data_quality_rulesets(
NextToken='string',
MaxResults=123,
Filter={
'Name': 'string',
'Description': 'string',
'CreatedBefore': datetime(2015, 1, 1),
'CreatedAfter': datetime(2015, 1, 1),
'LastModifiedBefore': datetime(2015, 1, 1),
'LastModifiedAfter': datetime(2015, 1, 1),
'TargetTable': {
'TableName': 'string',
'DatabaseName': 'string'
}
},
Tags={
'string': 'string'
}
)
The filter criteria.
The name of the ruleset filter criteria.
The description of the ruleset filter criteria.
Filter on rulesets created before this date.
Filter on rulesets created after this date.
Filter on rulesets last modified before this date.
Filter on rulesets last modified after this date.
The name and database name of the target table.
The name of the Glue table.
The name of the database where the Glue table exists.
A list of key-value pair tags.
dict
Response Syntax
{
'Rulesets': [
{
'Name': 'string',
'Description': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'TargetTable': {
'TableName': 'string',
'DatabaseName': 'string'
},
'RecommendationRunId': 'string',
'RuleCount': 123
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Rulesets (list) --
A paginated list of rulesets for the specified list of Glue tables.
(dict) --
Describes a data quality ruleset returned by GetDataQualityRuleset .
Name (string) --
The name of the data quality ruleset.
Description (string) --
A description of the data quality ruleset.
CreatedOn (datetime) --
The date and time the data quality ruleset was created.
LastModifiedOn (datetime) --
The date and time the data quality ruleset was last modified.
TargetTable (dict) --
An object representing an Glue table.
TableName (string) --
The name of the Glue table.
DatabaseName (string) --
The name of the database where the Glue table exists.
RecommendationRunId (string) --
When a ruleset was created from a recommendation run, this run ID is generated to link the two together.
RuleCount (integer) --
The number of rules in the ruleset.
NextToken (string) --
A pagination token, if more results are available.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionlist_dev_endpoints(**kwargs)¶Retrieves the names of all DevEndpoint resources in this Amazon Web Services account, or the resources with the specified tag. This operation allows you to see which resources are available in your account, and their names.
This operation takes the optional Tags field, which you can use as a filter on the response so that tagged resources can be retrieved as a group. If you choose to use tags filtering, only resources with the tag are retrieved.
See also: AWS API Documentation
Request Syntax
response = client.list_dev_endpoints(
NextToken='string',
MaxResults=123,
Tags={
'string': 'string'
}
)
Specifies to return only these tagged resources.
dict
Response Syntax
{
'DevEndpointNames': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) --
DevEndpointNames (list) --
The names of all the DevEndpoint s in the account, or the DevEndpoint s with the specified tags.
NextToken (string) --
A continuation token, if the returned list does not contain the last metric available.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionlist_jobs(**kwargs)¶Retrieves the names of all job resources in this Amazon Web Services account, or the resources with the specified tag. This operation allows you to see which resources are available in your account, and their names.
This operation takes the optional Tags field, which you can use as a filter on the response so that tagged resources can be retrieved as a group. If you choose to use tags filtering, only resources with the tag are retrieved.
See also: AWS API Documentation
Request Syntax
response = client.list_jobs(
NextToken='string',
MaxResults=123,
Tags={
'string': 'string'
}
)
Specifies to return only these tagged resources.
dict
Response Syntax
{
'JobNames': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) --
JobNames (list) --
The names of all jobs in the account, or the jobs with the specified tags.
NextToken (string) --
A continuation token, if the returned list does not contain the last metric available.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionlist_ml_transforms(**kwargs)¶Retrieves a sortable, filterable list of existing Glue machine learning transforms in this Amazon Web Services account, or the resources with the specified tag. This operation takes the optional Tags field, which you can use as a filter of the responses so that tagged resources can be retrieved as a group. If you choose to use tag filtering, only resources with the tags are retrieved.
See also: AWS API Documentation
Request Syntax
response = client.list_ml_transforms(
NextToken='string',
MaxResults=123,
Filter={
'Name': 'string',
'TransformType': 'FIND_MATCHES',
'Status': 'NOT_READY'|'READY'|'DELETING',
'GlueVersion': 'string',
'CreatedBefore': datetime(2015, 1, 1),
'CreatedAfter': datetime(2015, 1, 1),
'LastModifiedBefore': datetime(2015, 1, 1),
'LastModifiedAfter': datetime(2015, 1, 1),
'Schema': [
{
'Name': 'string',
'DataType': 'string'
},
]
},
Sort={
'Column': 'NAME'|'TRANSFORM_TYPE'|'STATUS'|'CREATED'|'LAST_MODIFIED',
'SortDirection': 'DESCENDING'|'ASCENDING'
},
Tags={
'string': 'string'
}
)
A TransformFilterCriteria used to filter the machine learning transforms.
A unique transform name that is used to filter the machine learning transforms.
The type of machine learning transform that is used to filter the machine learning transforms.
Filters the list of machine learning transforms by the last known status of the transforms (to indicate whether a transform can be used or not). One of "NOT_READY", "READY", or "DELETING".
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
The time and date before which the transforms were created.
The time and date after which the transforms were created.
Filter on transforms last modified before this date.
Filter on transforms last modified after this date.
Filters on datasets with a specific schema. The Map<Column, Type> object is an array of key-value pairs representing the schema this transform accepts, where Column is the name of a column, and Type is the type of the data such as an integer or string. Has an upper bound of 100 columns.
A key-value pair representing a column and data type that this transform can run against. The Schema parameter of the MLTransform may contain up to 100 of these structures.
The name of the column.
The type of data in the column.
A TransformSortCriteria used to sort the machine learning transforms.
The column to be used in the sorting criteria that are associated with the machine learning transform.
The sort direction to be used in the sorting criteria that are associated with the machine learning transform.
Specifies to return only these tagged resources.
dict
Response Syntax
{
'TransformIds': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) --
TransformIds (list) --
The identifiers of all the machine learning transforms in the account, or the machine learning transforms with the specified tags.
NextToken (string) --
A continuation token, if the returned list does not contain the last metric available.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionlist_registries(**kwargs)¶Returns a list of registries that you have created, with minimal registry information. Registries in the Deleting status will not be included in the results. Empty results will be returned if there are no registries available.
See also: AWS API Documentation
Request Syntax
response = client.list_registries(
MaxResults=123,
NextToken='string'
)
dict
Response Syntax
{
'Registries': [
{
'RegistryName': 'string',
'RegistryArn': 'string',
'Description': 'string',
'Status': 'AVAILABLE'|'DELETING',
'CreatedTime': 'string',
'UpdatedTime': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Registries (list) --
An array of RegistryDetailedListItem objects containing minimal details of each registry.
(dict) --
A structure containing the details for a registry.
RegistryName (string) --
The name of the registry.
RegistryArn (string) --
The Amazon Resource Name (ARN) of the registry.
Description (string) --
A description of the registry.
Status (string) --
The status of the registry.
CreatedTime (string) --
The data the registry was created.
UpdatedTime (string) --
The date the registry was updated.
NextToken (string) --
A continuation token for paginating the returned list of tokens, returned if the current segment of the list is not the last.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionlist_schema_versions(**kwargs)¶Returns a list of schema versions that you have created, with minimal information. Schema versions in Deleted status will not be included in the results. Empty results will be returned if there are no schema versions available.
See also: AWS API Documentation
Request Syntax
response = client.list_schema_versions(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
MaxResults=123,
NextToken='string'
)
[REQUIRED]
This is a wrapper structure to contain schema identity fields. The structure contains:
SchemaArn or SchemaName and RegistryName has to be provided.SchemaArn or SchemaName and RegistryName has to be provided.The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
dict
Response Syntax
{
'Schemas': [
{
'SchemaArn': 'string',
'SchemaVersionId': 'string',
'VersionNumber': 123,
'Status': 'AVAILABLE'|'PENDING'|'FAILURE'|'DELETING',
'CreatedTime': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Schemas (list) --
An array of SchemaVersionList objects containing details of each schema version.
(dict) --
An object containing the details about a schema version.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema.
SchemaVersionId (string) --
The unique identifier of the schema version.
VersionNumber (integer) --
The version number of the schema.
Status (string) --
The status of the schema version.
CreatedTime (string) --
The date and time the schema version was created.
NextToken (string) --
A continuation token for paginating the returned list of tokens, returned if the current segment of the list is not the last.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionlist_schemas(**kwargs)¶Returns a list of schemas with minimal details. Schemas in Deleting status will not be included in the results. Empty results will be returned if there are no schemas available.
When the RegistryId is not provided, all the schemas across registries will be part of the API response.
See also: AWS API Documentation
Request Syntax
response = client.list_schemas(
RegistryId={
'RegistryName': 'string',
'RegistryArn': 'string'
},
MaxResults=123,
NextToken='string'
)
A wrapper structure that may contain the registry name and Amazon Resource Name (ARN).
Name of the registry. Used only for lookup. One of RegistryArn or RegistryName has to be provided.
Arn of the registry to be updated. One of RegistryArn or RegistryName has to be provided.
dict
Response Syntax
{
'Schemas': [
{
'RegistryName': 'string',
'SchemaName': 'string',
'SchemaArn': 'string',
'Description': 'string',
'SchemaStatus': 'AVAILABLE'|'PENDING'|'DELETING',
'CreatedTime': 'string',
'UpdatedTime': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Schemas (list) --
An array of SchemaListItem objects containing details of each schema.
(dict) --
An object that contains minimal details for a schema.
RegistryName (string) --
the name of the registry where the schema resides.
SchemaName (string) --
The name of the schema.
SchemaArn (string) --
The Amazon Resource Name (ARN) for the schema.
Description (string) --
A description for the schema.
SchemaStatus (string) --
The status of the schema.
CreatedTime (string) --
The date and time that a schema was created.
UpdatedTime (string) --
The date and time that a schema was updated.
NextToken (string) --
A continuation token for paginating the returned list of tokens, returned if the current segment of the list is not the last.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionlist_sessions(**kwargs)¶Retrieve a list of sessions.
See also: AWS API Documentation
Request Syntax
response = client.list_sessions(
NextToken='string',
MaxResults=123,
Tags={
'string': 'string'
},
RequestOrigin='string'
)
Tags belonging to the session.
dict
Response Syntax
{
'Ids': [
'string',
],
'Sessions': [
{
'Id': 'string',
'CreatedOn': datetime(2015, 1, 1),
'Status': 'PROVISIONING'|'READY'|'FAILED'|'TIMEOUT'|'STOPPING'|'STOPPED',
'ErrorMessage': 'string',
'Description': 'string',
'Role': 'string',
'Command': {
'Name': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'Progress': 123.0,
'MaxCapacity': 123.0,
'SecurityConfiguration': 'string',
'GlueVersion': 'string'
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Ids (list) --
Returns the ID of the session.
Sessions (list) --
Returns the session object.
(dict) --
The period in which a remote Spark runtime environment is running.
Id (string) --
The ID of the session.
CreatedOn (datetime) --
The time and date when the session was created.
Status (string) --
The session status.
ErrorMessage (string) --
The error message displayed during the session.
Description (string) --
The description of the session.
Role (string) --
The name or Amazon Resource Name (ARN) of the IAM role associated with the Session.
Command (dict) --
The command object.See SessionCommand.
Name (string) --
Specifies the name of the SessionCommand. Can be 'glueetl' or 'gluestreaming'.
PythonVersion (string) --
Specifies the Python version. The Python version indicates the version supported for jobs of type Spark.
DefaultArguments (dict) --
A map array of key-value pairs. Max is 75 pairs.
Connections (dict) --
The number of connections used for the session.
Connections (list) --
A list of connections used by the job.
Progress (float) --
The code execution progress of the session.
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when the job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB memory.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with the session.
GlueVersion (string) --
The Glue version determines the versions of Apache Spark and Python that Glue supports. The GlueVersion must be greater than 2.0.
NextToken (string) --
The token for the next set of results, or null if there are no more result.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionlist_statements(**kwargs)¶Lists statements for the session.
See also: AWS API Documentation
Request Syntax
response = client.list_statements(
SessionId='string',
RequestOrigin='string',
NextToken='string'
)
[REQUIRED]
The Session ID of the statements.
dict
Response Syntax
{
'Statements': [
{
'Id': 123,
'Code': 'string',
'State': 'WAITING'|'RUNNING'|'AVAILABLE'|'CANCELLING'|'CANCELLED'|'ERROR',
'Output': {
'Data': {
'TextPlain': 'string'
},
'ExecutionCount': 123,
'Status': 'WAITING'|'RUNNING'|'AVAILABLE'|'CANCELLING'|'CANCELLED'|'ERROR',
'ErrorName': 'string',
'ErrorValue': 'string',
'Traceback': [
'string',
]
},
'Progress': 123.0,
'StartedOn': 123,
'CompletedOn': 123
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Statements (list) --
Returns the list of statements.
(dict) --
The statement or request for a particular action to occur in a session.
Id (integer) --
The ID of the statement.
Code (string) --
The execution code of the statement.
State (string) --
The state while request is actioned.
Output (dict) --
The output in JSON.
Data (dict) --
The code execution output.
TextPlain (string) --
The code execution output in text format.
ExecutionCount (integer) --
The execution count of the output.
Status (string) --
The status of the code execution output.
ErrorName (string) --
The name of the error in the output.
ErrorValue (string) --
The error value of the output.
Traceback (list) --
The traceback of the output.
Progress (float) --
The code execution progress.
StartedOn (integer) --
The unix time and date that the job definition was started.
CompletedOn (integer) --
The unix time and date that the job definition was completed.
NextToken (string) --
A continuation token, if not all statements have yet been returned.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.IllegalSessionStateExceptionlist_triggers(**kwargs)¶Retrieves the names of all trigger resources in this Amazon Web Services account, or the resources with the specified tag. This operation allows you to see which resources are available in your account, and their names.
This operation takes the optional Tags field, which you can use as a filter on the response so that tagged resources can be retrieved as a group. If you choose to use tags filtering, only resources with the tag are retrieved.
See also: AWS API Documentation
Request Syntax
response = client.list_triggers(
NextToken='string',
DependentJobName='string',
MaxResults=123,
Tags={
'string': 'string'
}
)
Specifies to return only these tagged resources.
dict
Response Syntax
{
'TriggerNames': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) --
TriggerNames (list) --
The names of all triggers in the account, or the triggers with the specified tags.
NextToken (string) --
A continuation token, if the returned list does not contain the last metric available.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionlist_workflows(**kwargs)¶Lists names of workflows created in the account.
See also: AWS API Documentation
Request Syntax
response = client.list_workflows(
NextToken='string',
MaxResults=123
)
dict
Response Syntax
{
'Workflows': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) --
Workflows (list) --
List of names of workflows in the account.
NextToken (string) --
A continuation token, if not all workflow names have been returned.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionput_data_catalog_encryption_settings(**kwargs)¶Sets the security configuration for a specified catalog. After the configuration has been set, the specified encryption is applied to every catalog write thereafter.
See also: AWS API Documentation
Request Syntax
response = client.put_data_catalog_encryption_settings(
CatalogId='string',
DataCatalogEncryptionSettings={
'EncryptionAtRest': {
'CatalogEncryptionMode': 'DISABLED'|'SSE-KMS',
'SseAwsKmsKeyId': 'string'
},
'ConnectionPasswordEncryption': {
'ReturnConnectionPasswordEncrypted': True|False,
'AwsKmsKeyId': 'string'
}
}
)
[REQUIRED]
The security configuration to set.
Specifies the encryption-at-rest configuration for the Data Catalog.
The encryption-at-rest mode for encrypting Data Catalog data.
The ID of the KMS key to use for encryption at rest.
When connection password protection is enabled, the Data Catalog uses a customer-provided key to encrypt the password as part of CreateConnection or UpdateConnection and store it in the ENCRYPTED_PASSWORD field in the connection properties. You can enable catalog encryption or only password encryption.
When the ReturnConnectionPasswordEncrypted flag is set to "true", passwords remain encrypted in the responses of GetConnection and GetConnections . This encryption takes effect independently from catalog encryption.
An KMS key that is used to encrypt the connection password.
If connection password protection is enabled, the caller of CreateConnection and UpdateConnection needs at least kms:Encrypt permission on the specified KMS key, to encrypt passwords before storing them in the Data Catalog.
You can set the decrypt permission to enable or restrict access on the password key according to your security requirements.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionput_resource_policy(**kwargs)¶Sets the Data Catalog resource policy for access control.
See also: AWS API Documentation
Request Syntax
response = client.put_resource_policy(
PolicyInJson='string',
ResourceArn='string',
PolicyHashCondition='string',
PolicyExistsCondition='MUST_EXIST'|'NOT_EXIST'|'NONE',
EnableHybrid='TRUE'|'FALSE'
)
[REQUIRED]
Contains the policy document to set, in JSON format.
PutResourcePolicy . Its purpose is to prevent concurrent modifications of a policy. Do not use this parameter if no previous policy has been set.MUST_EXIST is used to update a policy. A value of NOT_EXIST is used to create a new policy. If a value of NONE or a null value is used, the call does not depend on the existence of a policy.If 'TRUE' , indicates that you are using both methods to grant cross-account access to Data Catalog resources:
PutResourePolicyMust be set to 'TRUE' if you have already used the Management Console to grant cross-account access, otherwise the call fails. Default is 'FALSE'.
dict
Response Syntax
{
'PolicyHash': 'string'
}
Response Structure
(dict) --
PolicyHash (string) --
A hash of the policy that has just been set. This must be included in a subsequent call that overwrites or updates this policy.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.ConditionCheckFailureExceptionput_schema_version_metadata(**kwargs)¶Puts the metadata key value pair for a specified schema version ID. A maximum of 10 key value pairs will be allowed per schema version. They can be added over one or more calls.
See also: AWS API Documentation
Request Syntax
response = client.put_schema_version_metadata(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
SchemaVersionNumber={
'LatestVersion': True|False,
'VersionNumber': 123
},
SchemaVersionId='string',
MetadataKeyValue={
'MetadataKey': 'string',
'MetadataValue': 'string'
}
)
The unique ID for the schema.
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The version number of the schema.
The latest version available for the schema.
The version number of the schema.
[REQUIRED]
The metadata key's corresponding value.
A metadata key.
A metadata key’s corresponding value.
dict
Response Syntax
{
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string',
'LatestVersion': True|False,
'VersionNumber': 123,
'SchemaVersionId': 'string',
'MetadataKey': 'string',
'MetadataValue': 'string'
}
Response Structure
(dict) --
SchemaArn (string) --
The Amazon Resource Name (ARN) for the schema.
SchemaName (string) --
The name for the schema.
RegistryName (string) --
The name for the registry.
LatestVersion (boolean) --
The latest version of the schema.
VersionNumber (integer) --
The version number of the schema.
SchemaVersionId (string) --
The unique version ID of the schema version.
MetadataKey (string) --
The metadata key.
MetadataValue (string) --
The value of the metadata key.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionput_workflow_run_properties(**kwargs)¶Puts the specified workflow run properties for the given workflow run. If a property already exists for the specified run, then it overrides the value otherwise adds the property to existing properties.
See also: AWS API Documentation
Request Syntax
response = client.put_workflow_run_properties(
Name='string',
RunId='string',
RunProperties={
'string': 'string'
}
)
[REQUIRED]
Name of the workflow which was run.
[REQUIRED]
The ID of the workflow run for which the run properties should be updated.
[REQUIRED]
The properties to put for the specified run.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentModificationExceptionquery_schema_version_metadata(**kwargs)¶Queries for the schema version metadata information.
See also: AWS API Documentation
Request Syntax
response = client.query_schema_version_metadata(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
SchemaVersionNumber={
'LatestVersion': True|False,
'VersionNumber': 123
},
SchemaVersionId='string',
MetadataList=[
{
'MetadataKey': 'string',
'MetadataValue': 'string'
},
],
MaxResults=123,
NextToken='string'
)
A wrapper structure that may contain the schema name and Amazon Resource Name (ARN).
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The version number of the schema.
The latest version available for the schema.
The version number of the schema.
Search key-value pairs for metadata, if they are not provided all the metadata information will be fetched.
A structure containing a key value pair for metadata.
A metadata key.
A metadata key’s corresponding value.
dict
Response Syntax
{
'MetadataInfoMap': {
'string': {
'MetadataValue': 'string',
'CreatedTime': 'string',
'OtherMetadataValueList': [
{
'MetadataValue': 'string',
'CreatedTime': 'string'
},
]
}
},
'SchemaVersionId': 'string',
'NextToken': 'string'
}
Response Structure
(dict) --
MetadataInfoMap (dict) --
A map of a metadata key and associated values.
(string) --
(dict) --
A structure containing metadata information for a schema version.
MetadataValue (string) --
The metadata key’s corresponding value.
CreatedTime (string) --
The time at which the entry was created.
OtherMetadataValueList (list) --
Other metadata belonging to the same metadata key.
(dict) --
A structure containing other metadata for a schema version belonging to the same metadata key.
MetadataValue (string) --
The metadata key’s corresponding value for the other metadata belonging to the same metadata key.
CreatedTime (string) --
The time at which the entry was created.
SchemaVersionId (string) --
The unique version ID of the schema version.
NextToken (string) --
A continuation token for paginating the returned list of tokens, returned if the current segment of the list is not the last.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionregister_schema_version(**kwargs)¶Adds a new version to the existing schema. Returns an error if new version of schema does not meet the compatibility requirements of the schema set. This API will not create a new schema set and will return a 404 error if the schema set is not already present in the Schema Registry.
If this is the first schema definition to be registered in the Schema Registry, this API will store the schema version and return immediately. Otherwise, this call has the potential to run longer than other operations due to compatibility modes. You can call the GetSchemaVersion API with the SchemaVersionId to check compatibility modes.
If the same schema definition is already stored in Schema Registry as a version, the schema ID of the existing schema is returned to the caller.
See also: AWS API Documentation
Request Syntax
response = client.register_schema_version(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
SchemaDefinition='string'
)
[REQUIRED]
This is a wrapper structure to contain schema identity fields. The structure contains:
SchemaArn or SchemaName and RegistryName has to be provided.SchemaArn or SchemaName and RegistryName has to be provided.The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
[REQUIRED]
The schema definition using the DataFormat setting for the SchemaName .
dict
Response Syntax
{
'SchemaVersionId': 'string',
'VersionNumber': 123,
'Status': 'AVAILABLE'|'PENDING'|'FAILURE'|'DELETING'
}
Response Structure
(dict) --
SchemaVersionId (string) --
The unique ID that represents the version of this schema.
VersionNumber (integer) --
The version of this schema (for sync flow only, in case this is the first version).
Status (string) --
The status of the schema version.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.InternalServiceExceptionremove_schema_version_metadata(**kwargs)¶Removes a key value pair from the schema version metadata for the specified schema version ID.
See also: AWS API Documentation
Request Syntax
response = client.remove_schema_version_metadata(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
SchemaVersionNumber={
'LatestVersion': True|False,
'VersionNumber': 123
},
SchemaVersionId='string',
MetadataKeyValue={
'MetadataKey': 'string',
'MetadataValue': 'string'
}
)
A wrapper structure that may contain the schema name and Amazon Resource Name (ARN).
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The version number of the schema.
The latest version available for the schema.
The version number of the schema.
[REQUIRED]
The value of the metadata key.
A metadata key.
A metadata key’s corresponding value.
dict
Response Syntax
{
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string',
'LatestVersion': True|False,
'VersionNumber': 123,
'SchemaVersionId': 'string',
'MetadataKey': 'string',
'MetadataValue': 'string'
}
Response Structure
(dict) --
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema.
SchemaName (string) --
The name of the schema.
RegistryName (string) --
The name of the registry.
LatestVersion (boolean) --
The latest version of the schema.
VersionNumber (integer) --
The version number of the schema.
SchemaVersionId (string) --
The version ID for the schema version.
MetadataKey (string) --
The metadata key.
MetadataValue (string) --
The value of the metadata key.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionreset_job_bookmark(**kwargs)¶Resets a bookmark entry.
For more information about enabling and using job bookmarks, see:
See also: AWS API Documentation
Request Syntax
response = client.reset_job_bookmark(
JobName='string',
RunId='string'
)
[REQUIRED]
The name of the job in question.
dict
Response Syntax
{
'JobBookmarkEntry': {
'JobName': 'string',
'Version': 123,
'Run': 123,
'Attempt': 123,
'PreviousRunId': 'string',
'RunId': 'string',
'JobBookmark': 'string'
}
}
Response Structure
(dict) --
JobBookmarkEntry (dict) --
The reset bookmark entry.
JobName (string) --
The name of the job in question.
Version (integer) --
The version of the job.
Run (integer) --
The run ID number.
Attempt (integer) --
The attempt ID number.
PreviousRunId (string) --
The unique run identifier associated with the previous job run.
RunId (string) --
The run ID number.
JobBookmark (string) --
The bookmark itself.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionresume_workflow_run(**kwargs)¶Restarts selected nodes of a previous partially completed workflow run and resumes the workflow run. The selected nodes and all nodes that are downstream from the selected nodes are run.
See also: AWS API Documentation
Request Syntax
response = client.resume_workflow_run(
Name='string',
RunId='string',
NodeIds=[
'string',
]
)
[REQUIRED]
The name of the workflow to resume.
[REQUIRED]
The ID of the workflow run to resume.
[REQUIRED]
A list of the node IDs for the nodes you want to restart. The nodes that are to be restarted must have a run attempt in the original run.
dict
Response Syntax
{
'RunId': 'string',
'NodeIds': [
'string',
]
}
Response Structure
(dict) --
RunId (string) --
The new ID assigned to the resumed workflow run. Each resume of a workflow run will have a new run ID.
NodeIds (list) --
A list of the node IDs for the nodes that were actually restarted.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentRunsExceededExceptionGlue.Client.exceptions.IllegalWorkflowStateExceptionrun_statement(**kwargs)¶Executes the statement.
See also: AWS API Documentation
Request Syntax
response = client.run_statement(
SessionId='string',
Code='string',
RequestOrigin='string'
)
[REQUIRED]
The Session Id of the statement to be run.
[REQUIRED]
The statement code to be run.
dict
Response Syntax
{
'Id': 123
}
Response Structure
(dict) --
Id (integer) --
Returns the Id of the statement that was run.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.ValidationExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.IllegalSessionStateExceptionsearch_tables(**kwargs)¶Searches a set of tables based on properties in the table metadata as well as on the parent database. You can search against text or filter conditions.
You can only get tables that you have access to based on the security policies defined in Lake Formation. You need at least a read-only access to the table for it to be returned. If you do not have access to all the columns in the table, these columns will not be searched against when returning the list of tables back to you. If you have access to the columns but not the data in the columns, those columns and the associated metadata for those columns will be included in the search.
See also: AWS API Documentation
Request Syntax
response = client.search_tables(
CatalogId='string',
NextToken='string',
Filters=[
{
'Key': 'string',
'Value': 'string',
'Comparator': 'EQUALS'|'GREATER_THAN'|'LESS_THAN'|'GREATER_THAN_EQUALS'|'LESS_THAN_EQUALS'
},
],
SearchText='string',
SortCriteria=[
{
'FieldName': 'string',
'Sort': 'ASC'|'DESC'
},
],
MaxResults=123,
ResourceShareType='FOREIGN'|'ALL'
)
account_id .A list of key-value pairs, and a comparator used to filter the search results. Returns all entities matching the predicate.
The Comparator member of the PropertyPredicate struct is used only for time fields, and can be omitted for other field types. Also, when comparing string values, such as when Key=Name , a fuzzy match algorithm is used. The Key field (for example, the value of the Name field) is split on certain punctuation characters, for example, -, :, #, etc. into tokens. Then each token is exact-match compared with the Value member of PropertyPredicate . For example, if Key=Name and Value=link , tables named customer-link and xx-link-yy are returned, but xxlinkyy is not returned.
Defines a property predicate.
The key of the property.
The value of the property.
The comparator used to compare this property to others.
A string used for a text search.
Specifying a value in quotes filters based on an exact match to the value.
A list of criteria for sorting the results by a field name, in an ascending or descending order.
Specifies a field to sort by and a sort order.
The name of the field on which to sort.
An ascending or descending sort.
Allows you to specify that you want to search the tables shared with your account. The allowable values are FOREIGN or ALL .
FOREIGN , will search the tables shared with your account.ALL , will search the tables shared with your account, as well as the tables in yor local account.dict
Response Syntax
{
'NextToken': 'string',
'TableList': [
{
'Name': 'string',
'DatabaseName': 'string',
'Description': 'string',
'Owner': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'CreatedBy': 'string',
'IsRegisteredWithLakeFormation': True|False,
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
},
'CatalogId': 'string',
'VersionId': 'string'
},
]
}
Response Structure
(dict) --
NextToken (string) --
A continuation token, present if the current list segment is not the last.
TableList (list) --
A list of the requested Table objects. The SearchTables response returns only the tables that you have access to.
(dict) --
Represents a collection of related data organized in columns and rows.
Name (string) --
The table name. For Hive compatibility, this must be entirely lowercase.
DatabaseName (string) --
The name of the database where the table metadata resides. For Hive compatibility, this must be all lowercase.
Description (string) --
A description of the table.
Owner (string) --
The owner of the table.
CreateTime (datetime) --
The time when the table definition was created in the Data Catalog.
UpdateTime (datetime) --
The last time that the table was updated.
LastAccessTime (datetime) --
The last time that the table was accessed. This is usually taken from HDFS, and might not be reliable.
LastAnalyzedTime (datetime) --
The last time that column statistics were computed for this table.
Retention (integer) --
The retention time for this table.
StorageDescriptor (dict) --
A storage descriptor containing information about the physical storage of this table.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
PartitionKeys (list) --
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
ViewOriginalText (string) --
If the table is a view, the original text of the view; otherwise null .
ViewExpandedText (string) --
If the table is a view, the expanded text of the view; otherwise null .
TableType (string) --
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
Parameters (dict) --
These key-value pairs define properties associated with the table.
CreatedBy (string) --
The person or entity who created the table.
IsRegisteredWithLakeFormation (boolean) --
Indicates whether the table has been registered with Lake Formation.
TargetTable (dict) --
A TableIdentifier structure that describes a target table for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
DatabaseName (string) --
The name of the catalog database that contains the target table.
Name (string) --
The name of the target table.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
VersionId (string) --
The ID of the table version.
Exceptions
Glue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionstart_blueprint_run(**kwargs)¶Starts a new run of the specified blueprint.
See also: AWS API Documentation
Request Syntax
response = client.start_blueprint_run(
BlueprintName='string',
Parameters='string',
RoleArn='string'
)
[REQUIRED]
The name of the blueprint.
BlueprintParameters object.[REQUIRED]
Specifies the IAM role used to create the workflow.
dict
Response Syntax
{
'RunId': 'string'
}
Response Structure
(dict) --
RunId (string) --
The run ID for this blueprint run.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.IllegalBlueprintStateExceptionstart_crawler(**kwargs)¶Starts a crawl using the specified crawler, regardless of what is scheduled. If the crawler is already running, returns a CrawlerRunningException.
See also: AWS API Documentation
Request Syntax
response = client.start_crawler(
Name='string'
)
[REQUIRED]
Name of the crawler to start.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.CrawlerRunningExceptionGlue.Client.exceptions.OperationTimeoutExceptionstart_crawler_schedule(**kwargs)¶Changes the schedule state of the specified crawler to SCHEDULED , unless the crawler is already running or the schedule state is already SCHEDULED .
See also: AWS API Documentation
Request Syntax
response = client.start_crawler_schedule(
CrawlerName='string'
)
[REQUIRED]
Name of the crawler to schedule.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.SchedulerRunningExceptionGlue.Client.exceptions.SchedulerTransitioningExceptionGlue.Client.exceptions.NoScheduleExceptionGlue.Client.exceptions.OperationTimeoutExceptionstart_data_quality_rule_recommendation_run(**kwargs)¶Starts a recommendation run that is used to generate rules when you don't know what rules to write. Glue Data Quality analyzes the data and comes up with recommendations for a potential ruleset. You can then triage the ruleset and modify the generated ruleset to your liking.
See also: AWS API Documentation
Request Syntax
response = client.start_data_quality_rule_recommendation_run(
DataSource={
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
Role='string',
NumberOfWorkers=123,
Timeout=123,
CreatedRulesetName='string',
ClientToken='string'
)
[REQUIRED]
The data source (Glue table) associated with this run.
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.[REQUIRED]
An IAM role supplied to encrypt the results of the run.
G.1X workers to be used in the run. The default is 5.TIMEOUT status. The default is 2,880 minutes (48 hours).dict
Response Syntax
{
'RunId': 'string'
}
Response Structure
(dict) --
RunId (string) --
The unique run identifier associated with this run.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.ConflictExceptionstart_data_quality_ruleset_evaluation_run(**kwargs)¶Once you have a ruleset definition (either recommended or your own), you call this operation to evaluate the ruleset against a data source (Glue table). The evaluation computes results which you can retrieve with the GetDataQualityResult API.
See also: AWS API Documentation
Request Syntax
response = client.start_data_quality_ruleset_evaluation_run(
DataSource={
'GlueTable': {
'DatabaseName': 'string',
'TableName': 'string',
'CatalogId': 'string',
'ConnectionName': 'string',
'AdditionalOptions': {
'string': 'string'
}
}
},
Role='string',
NumberOfWorkers=123,
Timeout=123,
ClientToken='string',
AdditionalRunOptions={
'CloudWatchMetricsEnabled': True|False,
'ResultsS3Prefix': 'string'
},
RulesetNames=[
'string',
]
)
[REQUIRED]
The data source (Glue table) associated with this run.
An Glue table.
A database name in the Glue Data Catalog.
A table name in the Glue Data Catalog.
A unique identifier for the Glue Data Catalog.
The name of the connection to the Glue Data Catalog.
Additional options for the table. Currently there are two keys supported:
pushDownPredicate : to filter on partitions without having to list and read all the files in your dataset.catalogPartitionPredicate : to use server-side partition pruning using partition indexes in the Glue Data Catalog.[REQUIRED]
An IAM role supplied to encrypt the results of the run.
G.1X workers to be used in the run. The default is 5.TIMEOUT status. The default is 2,880 minutes (48 hours).Additional run options you can specify for an evaluation run.
Whether or not to enable CloudWatch metrics.
Prefix for Amazon S3 to store results.
[REQUIRED]
A list of ruleset names.
dict
Response Syntax
{
'RunId': 'string'
}
Response Structure
(dict) --
RunId (string) --
The unique run identifier associated with this run.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.ConflictExceptionstart_export_labels_task_run(**kwargs)¶Begins an asynchronous task to export all labeled data for a particular transform. This task is the only label-related API call that is not part of the typical active learning workflow. You typically use StartExportLabelsTaskRun when you want to work with all of your existing labels at the same time, such as when you want to remove or change labels that were previously submitted as truth. This API operation accepts the TransformId whose labels you want to export and an Amazon Simple Storage Service (Amazon S3) path to export the labels to. The operation returns a TaskRunId . You can check on the status of your task run by calling the GetMLTaskRun API.
See also: AWS API Documentation
Request Syntax
response = client.start_export_labels_task_run(
TransformId='string',
OutputS3Path='string'
)
[REQUIRED]
The unique identifier of the machine learning transform.
[REQUIRED]
The Amazon S3 path where you export the labels.
dict
Response Syntax
{
'TaskRunId': 'string'
}
Response Structure
(dict) --
TaskRunId (string) --
The unique identifier for the task run.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionstart_import_labels_task_run(**kwargs)¶Enables you to provide additional labels (examples of truth) to be used to teach the machine learning transform and improve its quality. This API operation is generally used as part of the active learning workflow that starts with the StartMLLabelingSetGenerationTaskRun call and that ultimately results in improving the quality of your machine learning transform.
After the StartMLLabelingSetGenerationTaskRun finishes, Glue machine learning will have generated a series of questions for humans to answer. (Answering these questions is often called 'labeling' in the machine learning workflows). In the case of the FindMatches transform, these questions are of the form, “What is the correct way to group these rows together into groups composed entirely of matching records?” After the labeling process is finished, users upload their answers/labels with a call to StartImportLabelsTaskRun . After StartImportLabelsTaskRun finishes, all future runs of the machine learning transform use the new and improved labels and perform a higher-quality transformation.
By default, StartMLLabelingSetGenerationTaskRun continually learns from and combines all labels that you upload unless you set Replace to true. If you set Replace to true, StartImportLabelsTaskRun deletes and forgets all previously uploaded labels and learns only from the exact set that you upload. Replacing labels can be helpful if you realize that you previously uploaded incorrect labels, and you believe that they are having a negative effect on your transform quality.
You can check on the status of your task run by calling the GetMLTaskRun operation.
See also: AWS API Documentation
Request Syntax
response = client.start_import_labels_task_run(
TransformId='string',
InputS3Path='string',
ReplaceAllLabels=True|False
)
[REQUIRED]
The unique identifier of the machine learning transform.
[REQUIRED]
The Amazon Simple Storage Service (Amazon S3) path from where you import the labels.
dict
Response Syntax
{
'TaskRunId': 'string'
}
Response Structure
(dict) --
TaskRunId (string) --
The unique identifier for the task run.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.InternalServiceExceptionstart_job_run(**kwargs)¶Starts a job run using a job definition.
See also: AWS API Documentation
Request Syntax
response = client.start_job_run(
JobName='string',
JobRunId='string',
Arguments={
'string': 'string'
},
AllocatedCapacity=123,
Timeout=123,
MaxCapacity=123.0,
SecurityConfiguration='string',
NotificationProperty={
'NotifyDelayAfter': 123
},
WorkerType='Standard'|'G.1X'|'G.2X'|'G.025X',
NumberOfWorkers=123,
ExecutionClass='FLEX'|'STANDARD'
)
[REQUIRED]
The name of the job definition to use.
JobRun to retry.The job arguments specifically for this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) to allocate to this JobRun. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.SecurityConfiguration structure to be used with this job run.Specifies configuration properties of a job run notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.workerType that are allocated when a job runs.Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
dict
Response Syntax
{
'JobRunId': 'string'
}
Response Structure
(dict) --
JobRunId (string) --
The ID assigned to this job run.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentRunsExceededExceptionstart_ml_evaluation_task_run(**kwargs)¶Starts a task to estimate the quality of the transform.
When you provide label sets as examples of truth, Glue machine learning uses some of those examples to learn from them. The rest of the labels are used as a test to estimate quality.
Returns a unique identifier for the run. You can call GetMLTaskRun to get more information about the stats of the EvaluationTaskRun .
See also: AWS API Documentation
Request Syntax
response = client.start_ml_evaluation_task_run(
TransformId='string'
)
[REQUIRED]
The unique identifier of the machine learning transform.
{
'TaskRunId': 'string'
}
Response Structure
The unique identifier associated with this run.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.ConcurrentRunsExceededExceptionGlue.Client.exceptions.MLTransformNotReadyExceptionstart_ml_labeling_set_generation_task_run(**kwargs)¶Starts the active learning workflow for your machine learning transform to improve the transform's quality by generating label sets and adding labels.
When the StartMLLabelingSetGenerationTaskRun finishes, Glue will have generated a "labeling set" or a set of questions for humans to answer.
In the case of the FindMatches transform, these questions are of the form, “What is the correct way to group these rows together into groups composed entirely of matching records?”
After the labeling process is finished, you can upload your labels with a call to StartImportLabelsTaskRun . After StartImportLabelsTaskRun finishes, all future runs of the machine learning transform will use the new and improved labels and perform a higher-quality transformation.
See also: AWS API Documentation
Request Syntax
response = client.start_ml_labeling_set_generation_task_run(
TransformId='string',
OutputS3Path='string'
)
[REQUIRED]
The unique identifier of the machine learning transform.
[REQUIRED]
The Amazon Simple Storage Service (Amazon S3) path where you generate the labeling set.
dict
Response Syntax
{
'TaskRunId': 'string'
}
Response Structure
(dict) --
TaskRunId (string) --
The unique run identifier that is associated with this task run.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.ConcurrentRunsExceededExceptionstart_trigger(**kwargs)¶Starts an existing trigger. See Triggering Jobs for information about how different types of trigger are started.
See also: AWS API Documentation
Request Syntax
response = client.start_trigger(
Name='string'
)
[REQUIRED]
The name of the trigger to start.
{
'Name': 'string'
}
Response Structure
The name of the trigger that was started.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentRunsExceededExceptionstart_workflow_run(**kwargs)¶Starts a new run of the specified workflow.
See also: AWS API Documentation
Request Syntax
response = client.start_workflow_run(
Name='string',
RunProperties={
'string': 'string'
}
)
[REQUIRED]
The name of the workflow to start.
The workflow run properties for the new workflow run.
dict
Response Syntax
{
'RunId': 'string'
}
Response Structure
(dict) --
RunId (string) --
An Id for the new run.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.ConcurrentRunsExceededExceptionstop_crawler(**kwargs)¶If the specified crawler is running, stops the crawl.
See also: AWS API Documentation
Request Syntax
response = client.stop_crawler(
Name='string'
)
[REQUIRED]
Name of the crawler to stop.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.CrawlerNotRunningExceptionGlue.Client.exceptions.CrawlerStoppingExceptionGlue.Client.exceptions.OperationTimeoutExceptionstop_crawler_schedule(**kwargs)¶Sets the schedule state of the specified crawler to NOT_SCHEDULED , but does not stop the crawler if it is already running.
See also: AWS API Documentation
Request Syntax
response = client.stop_crawler_schedule(
CrawlerName='string'
)
[REQUIRED]
Name of the crawler whose schedule state to set.
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.SchedulerNotRunningExceptionGlue.Client.exceptions.SchedulerTransitioningExceptionGlue.Client.exceptions.OperationTimeoutExceptionstop_session(**kwargs)¶Stops the session.
See also: AWS API Documentation
Request Syntax
response = client.stop_session(
Id='string',
RequestOrigin='string'
)
[REQUIRED]
The ID of the session to be stopped.
dict
Response Syntax
{
'Id': 'string'
}
Response Structure
(dict) --
Id (string) --
Returns the Id of the stopped session.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.IllegalSessionStateExceptionGlue.Client.exceptions.ConcurrentModificationExceptionstop_trigger(**kwargs)¶Stops a specified trigger.
See also: AWS API Documentation
Request Syntax
response = client.stop_trigger(
Name='string'
)
[REQUIRED]
The name of the trigger to stop.
{
'Name': 'string'
}
Response Structure
The name of the trigger that was stopped.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptionstop_workflow_run(**kwargs)¶Stops the execution of the specified workflow run.
See also: AWS API Documentation
Request Syntax
response = client.stop_workflow_run(
Name='string',
RunId='string'
)
[REQUIRED]
The name of the workflow to stop.
[REQUIRED]
The ID of the workflow run to stop.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.IllegalWorkflowStateExceptiontag_resource(**kwargs)¶Adds tags to a resource. A tag is a label you can assign to an Amazon Web Services resource. In Glue, you can tag only certain resources. For information about what resources you can tag, see Amazon Web Services Tags in Glue.
See also: AWS API Documentation
Request Syntax
response = client.tag_resource(
ResourceArn='string',
TagsToAdd={
'string': 'string'
}
)
[REQUIRED]
The ARN of the Glue resource to which to add the tags. For more information about Glue resource ARNs, see the Glue ARN string pattern.
[REQUIRED]
Tags to add to this resource.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.EntityNotFoundExceptionuntag_resource(**kwargs)¶Removes tags from a resource.
See also: AWS API Documentation
Request Syntax
response = client.untag_resource(
ResourceArn='string',
TagsToRemove=[
'string',
]
)
[REQUIRED]
The Amazon Resource Name (ARN) of the resource from which to remove the tags.
[REQUIRED]
Tags to remove from this resource.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.EntityNotFoundExceptionupdate_blueprint(**kwargs)¶Updates a registered blueprint.
See also: AWS API Documentation
Request Syntax
response = client.update_blueprint(
Name='string',
Description='string',
BlueprintLocation='string'
)
[REQUIRED]
The name of the blueprint.
[REQUIRED]
Specifies a path in Amazon S3 where the blueprint is published.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
Returns the name of the blueprint that was updated.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.IllegalBlueprintStateExceptionupdate_classifier(**kwargs)¶Modifies an existing classifier (a GrokClassifier , an XMLClassifier , a JsonClassifier , or a CsvClassifier , depending on which field is present).
See also: AWS API Documentation
Request Syntax
response = client.update_classifier(
GrokClassifier={
'Name': 'string',
'Classification': 'string',
'GrokPattern': 'string',
'CustomPatterns': 'string'
},
XMLClassifier={
'Name': 'string',
'Classification': 'string',
'RowTag': 'string'
},
JsonClassifier={
'Name': 'string',
'JsonPath': 'string'
},
CsvClassifier={
'Name': 'string',
'Delimiter': 'string',
'QuoteSymbol': 'string',
'ContainsHeader': 'UNKNOWN'|'PRESENT'|'ABSENT',
'Header': [
'string',
],
'DisableValueTrimming': True|False,
'AllowSingleColumn': True|False,
'CustomDatatypeConfigured': True|False,
'CustomDatatypes': [
'string',
]
}
)
A GrokClassifier object with updated fields.
The name of the GrokClassifier .
An identifier of the data format that the classifier matches, such as Twitter, JSON, Omniture logs, Amazon CloudWatch Logs, and so on.
The grok pattern used by this classifier.
Optional custom grok patterns used by this classifier.
An XMLClassifier object with updated fields.
The name of the classifier.
An identifier of the data format that the classifier matches.
The XML tag designating the element that contains each record in an XML document being parsed. This cannot identify a self-closing element (closed by /> ). An empty row element that contains only attributes can be parsed as long as it ends with a closing tag (for example, <row item_a="A" item_b="B"></row> is okay, but <row item_a="A" item_b="B" /> is not).
A JsonClassifier object with updated fields.
The name of the classifier.
A JsonPath string defining the JSON data for the classifier to classify. Glue supports a subset of JsonPath, as described in Writing JsonPath Custom Classifiers.
A CsvClassifier object with updated fields.
The name of the classifier.
A custom symbol to denote what separates each column entry in the row.
A custom symbol to denote what combines content into a single column value. It must be different from the column delimiter.
Indicates whether the CSV file contains a header.
A list of strings representing column names.
Specifies not to trim values before identifying the type of column values. The default value is true.
Enables the processing of files that contain only one column.
Specifies the configuration of custom datatypes.
Specifies a list of supported custom datatypes.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.VersionMismatchExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionupdate_column_statistics_for_partition(**kwargs)¶Creates or updates partition statistics of columns.
The Identity and Access Management (IAM) permission required for this operation is UpdatePartition .
See also: AWS API Documentation
Request Syntax
response = client.update_column_statistics_for_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionValues=[
'string',
],
ColumnStatisticsList=[
{
'ColumnName': 'string',
'ColumnType': 'string',
'AnalyzedTime': datetime(2015, 1, 1),
'StatisticsData': {
'Type': 'BOOLEAN'|'DATE'|'DECIMAL'|'DOUBLE'|'LONG'|'STRING'|'BINARY',
'BooleanColumnStatisticsData': {
'NumberOfTrues': 123,
'NumberOfFalses': 123,
'NumberOfNulls': 123
},
'DateColumnStatisticsData': {
'MinimumValue': datetime(2015, 1, 1),
'MaximumValue': datetime(2015, 1, 1),
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DecimalColumnStatisticsData': {
'MinimumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'MaximumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DoubleColumnStatisticsData': {
'MinimumValue': 123.0,
'MaximumValue': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'LongColumnStatisticsData': {
'MinimumValue': 123,
'MaximumValue': 123,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'StringColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'BinaryColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123
}
}
},
]
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
[REQUIRED]
A list of partition values identifying the partition.
[REQUIRED]
A list of the column statistics.
Represents the generated column-level statistics for a table or partition.
Name of column which statistics belong to.
The data type of the column.
The timestamp of when column statistics were generated.
A ColumnStatisticData object that contains the statistics data values.
The type of column statistics data.
Boolean column statistics data.
The number of true values in the column.
The number of false values in the column.
The number of null values in the column.
Date column statistics data.
The lowest value in the column.
The highest value in the column.
The number of null values in the column.
The number of distinct values in a column.
Decimal column statistics data.
The lowest value in the column.
The unscaled numeric value.
The scale that determines where the decimal point falls in the unscaled value.
The highest value in the column.
The unscaled numeric value.
The scale that determines where the decimal point falls in the unscaled value.
The number of null values in the column.
The number of distinct values in a column.
Double column statistics data.
The lowest value in the column.
The highest value in the column.
The number of null values in the column.
The number of distinct values in a column.
Long column statistics data.
The lowest value in the column.
The highest value in the column.
The number of null values in the column.
The number of distinct values in a column.
String column statistics data.
The size of the longest string in the column.
The average string length in the column.
The number of null values in the column.
The number of distinct values in a column.
Binary column statistics data.
The size of the longest bit sequence in the column.
The average bit sequence length in the column.
The number of null values in the column.
dict
Response Syntax
{
'Errors': [
{
'ColumnStatistics': {
'ColumnName': 'string',
'ColumnType': 'string',
'AnalyzedTime': datetime(2015, 1, 1),
'StatisticsData': {
'Type': 'BOOLEAN'|'DATE'|'DECIMAL'|'DOUBLE'|'LONG'|'STRING'|'BINARY',
'BooleanColumnStatisticsData': {
'NumberOfTrues': 123,
'NumberOfFalses': 123,
'NumberOfNulls': 123
},
'DateColumnStatisticsData': {
'MinimumValue': datetime(2015, 1, 1),
'MaximumValue': datetime(2015, 1, 1),
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DecimalColumnStatisticsData': {
'MinimumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'MaximumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DoubleColumnStatisticsData': {
'MinimumValue': 123.0,
'MaximumValue': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'LongColumnStatisticsData': {
'MinimumValue': 123,
'MaximumValue': 123,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'StringColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'BinaryColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123
}
}
},
'Error': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
Errors (list) --
Error occurred during updating column statistics data.
(dict) --
Encapsulates a ColumnStatistics object that failed and the reason for failure.
ColumnStatistics (dict) --
The ColumnStatistics of the column.
ColumnName (string) --
Name of column which statistics belong to.
ColumnType (string) --
The data type of the column.
AnalyzedTime (datetime) --
The timestamp of when column statistics were generated.
StatisticsData (dict) --
A ColumnStatisticData object that contains the statistics data values.
Type (string) --
The type of column statistics data.
BooleanColumnStatisticsData (dict) --
Boolean column statistics data.
NumberOfTrues (integer) --
The number of true values in the column.
NumberOfFalses (integer) --
The number of false values in the column.
NumberOfNulls (integer) --
The number of null values in the column.
DateColumnStatisticsData (dict) --
Date column statistics data.
MinimumValue (datetime) --
The lowest value in the column.
MaximumValue (datetime) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
DecimalColumnStatisticsData (dict) --
Decimal column statistics data.
MinimumValue (dict) --
The lowest value in the column.
UnscaledValue (bytes) --
The unscaled numeric value.
Scale (integer) --
The scale that determines where the decimal point falls in the unscaled value.
MaximumValue (dict) --
The highest value in the column.
UnscaledValue (bytes) --
The unscaled numeric value.
Scale (integer) --
The scale that determines where the decimal point falls in the unscaled value.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
DoubleColumnStatisticsData (dict) --
Double column statistics data.
MinimumValue (float) --
The lowest value in the column.
MaximumValue (float) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
LongColumnStatisticsData (dict) --
Long column statistics data.
MinimumValue (integer) --
The lowest value in the column.
MaximumValue (integer) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
StringColumnStatisticsData (dict) --
String column statistics data.
MaximumLength (integer) --
The size of the longest string in the column.
AverageLength (float) --
The average string length in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
BinaryColumnStatisticsData (dict) --
Binary column statistics data.
MaximumLength (integer) --
The size of the longest bit sequence in the column.
AverageLength (float) --
The average bit sequence length in the column.
NumberOfNulls (integer) --
The number of null values in the column.
Error (dict) --
An error message with the reason for the failure of an operation.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionupdate_column_statistics_for_table(**kwargs)¶Creates or updates table statistics of columns.
The Identity and Access Management (IAM) permission required for this operation is UpdateTable .
See also: AWS API Documentation
Request Syntax
response = client.update_column_statistics_for_table(
CatalogId='string',
DatabaseName='string',
TableName='string',
ColumnStatisticsList=[
{
'ColumnName': 'string',
'ColumnType': 'string',
'AnalyzedTime': datetime(2015, 1, 1),
'StatisticsData': {
'Type': 'BOOLEAN'|'DATE'|'DECIMAL'|'DOUBLE'|'LONG'|'STRING'|'BINARY',
'BooleanColumnStatisticsData': {
'NumberOfTrues': 123,
'NumberOfFalses': 123,
'NumberOfNulls': 123
},
'DateColumnStatisticsData': {
'MinimumValue': datetime(2015, 1, 1),
'MaximumValue': datetime(2015, 1, 1),
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DecimalColumnStatisticsData': {
'MinimumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'MaximumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DoubleColumnStatisticsData': {
'MinimumValue': 123.0,
'MaximumValue': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'LongColumnStatisticsData': {
'MinimumValue': 123,
'MaximumValue': 123,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'StringColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'BinaryColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123
}
}
},
]
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
[REQUIRED]
A list of the column statistics.
Represents the generated column-level statistics for a table or partition.
Name of column which statistics belong to.
The data type of the column.
The timestamp of when column statistics were generated.
A ColumnStatisticData object that contains the statistics data values.
The type of column statistics data.
Boolean column statistics data.
The number of true values in the column.
The number of false values in the column.
The number of null values in the column.
Date column statistics data.
The lowest value in the column.
The highest value in the column.
The number of null values in the column.
The number of distinct values in a column.
Decimal column statistics data.
The lowest value in the column.
The unscaled numeric value.
The scale that determines where the decimal point falls in the unscaled value.
The highest value in the column.
The unscaled numeric value.
The scale that determines where the decimal point falls in the unscaled value.
The number of null values in the column.
The number of distinct values in a column.
Double column statistics data.
The lowest value in the column.
The highest value in the column.
The number of null values in the column.
The number of distinct values in a column.
Long column statistics data.
The lowest value in the column.
The highest value in the column.
The number of null values in the column.
The number of distinct values in a column.
String column statistics data.
The size of the longest string in the column.
The average string length in the column.
The number of null values in the column.
The number of distinct values in a column.
Binary column statistics data.
The size of the longest bit sequence in the column.
The average bit sequence length in the column.
The number of null values in the column.
dict
Response Syntax
{
'Errors': [
{
'ColumnStatistics': {
'ColumnName': 'string',
'ColumnType': 'string',
'AnalyzedTime': datetime(2015, 1, 1),
'StatisticsData': {
'Type': 'BOOLEAN'|'DATE'|'DECIMAL'|'DOUBLE'|'LONG'|'STRING'|'BINARY',
'BooleanColumnStatisticsData': {
'NumberOfTrues': 123,
'NumberOfFalses': 123,
'NumberOfNulls': 123
},
'DateColumnStatisticsData': {
'MinimumValue': datetime(2015, 1, 1),
'MaximumValue': datetime(2015, 1, 1),
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DecimalColumnStatisticsData': {
'MinimumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'MaximumValue': {
'UnscaledValue': b'bytes',
'Scale': 123
},
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'DoubleColumnStatisticsData': {
'MinimumValue': 123.0,
'MaximumValue': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'LongColumnStatisticsData': {
'MinimumValue': 123,
'MaximumValue': 123,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'StringColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123,
'NumberOfDistinctValues': 123
},
'BinaryColumnStatisticsData': {
'MaximumLength': 123,
'AverageLength': 123.0,
'NumberOfNulls': 123
}
}
},
'Error': {
'ErrorCode': 'string',
'ErrorMessage': 'string'
}
},
]
}
Response Structure
(dict) --
Errors (list) --
List of ColumnStatisticsErrors.
(dict) --
Encapsulates a ColumnStatistics object that failed and the reason for failure.
ColumnStatistics (dict) --
The ColumnStatistics of the column.
ColumnName (string) --
Name of column which statistics belong to.
ColumnType (string) --
The data type of the column.
AnalyzedTime (datetime) --
The timestamp of when column statistics were generated.
StatisticsData (dict) --
A ColumnStatisticData object that contains the statistics data values.
Type (string) --
The type of column statistics data.
BooleanColumnStatisticsData (dict) --
Boolean column statistics data.
NumberOfTrues (integer) --
The number of true values in the column.
NumberOfFalses (integer) --
The number of false values in the column.
NumberOfNulls (integer) --
The number of null values in the column.
DateColumnStatisticsData (dict) --
Date column statistics data.
MinimumValue (datetime) --
The lowest value in the column.
MaximumValue (datetime) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
DecimalColumnStatisticsData (dict) --
Decimal column statistics data.
MinimumValue (dict) --
The lowest value in the column.
UnscaledValue (bytes) --
The unscaled numeric value.
Scale (integer) --
The scale that determines where the decimal point falls in the unscaled value.
MaximumValue (dict) --
The highest value in the column.
UnscaledValue (bytes) --
The unscaled numeric value.
Scale (integer) --
The scale that determines where the decimal point falls in the unscaled value.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
DoubleColumnStatisticsData (dict) --
Double column statistics data.
MinimumValue (float) --
The lowest value in the column.
MaximumValue (float) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
LongColumnStatisticsData (dict) --
Long column statistics data.
MinimumValue (integer) --
The lowest value in the column.
MaximumValue (integer) --
The highest value in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
StringColumnStatisticsData (dict) --
String column statistics data.
MaximumLength (integer) --
The size of the longest string in the column.
AverageLength (float) --
The average string length in the column.
NumberOfNulls (integer) --
The number of null values in the column.
NumberOfDistinctValues (integer) --
The number of distinct values in a column.
BinaryColumnStatisticsData (dict) --
Binary column statistics data.
MaximumLength (integer) --
The size of the longest bit sequence in the column.
AverageLength (float) --
The average bit sequence length in the column.
NumberOfNulls (integer) --
The number of null values in the column.
Error (dict) --
An error message with the reason for the failure of an operation.
ErrorCode (string) --
The code associated with this error.
ErrorMessage (string) --
A message describing the error.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionupdate_connection(**kwargs)¶Updates a connection definition in the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.update_connection(
CatalogId='string',
Name='string',
ConnectionInput={
'Name': 'string',
'Description': 'string',
'ConnectionType': 'JDBC'|'SFTP'|'MONGODB'|'KAFKA'|'NETWORK'|'MARKETPLACE'|'CUSTOM',
'MatchCriteria': [
'string',
],
'ConnectionProperties': {
'string': 'string'
},
'PhysicalConnectionRequirements': {
'SubnetId': 'string',
'SecurityGroupIdList': [
'string',
],
'AvailabilityZone': 'string'
}
}
)
[REQUIRED]
The name of the connection definition to update.
[REQUIRED]
A ConnectionInput object that redefines the connection in question.
The name of the connection.
The description of the connection.
The type of the connection. Currently, these types are supported:
JDBC - Designates a connection to a database through Java Database Connectivity (JDBC).KAFKA - Designates a connection to an Apache Kafka streaming platform.MONGODB - Designates a connection to a MongoDB document database.NETWORK - Designates a network connection to a data source within an Amazon Virtual Private Cloud environment (Amazon VPC).MARKETPLACE - Uses configuration settings contained in a connector purchased from Amazon Web Services Marketplace to read from and write to data stores that are not natively supported by Glue.CUSTOM - Uses configuration settings contained in a custom connector to read from and write to data stores that are not natively supported by Glue.SFTP is not supported.
A list of criteria that can be used in selecting this connection.
These key-value pairs define parameters for the connection.
A map of physical connection requirements, such as virtual private cloud (VPC) and SecurityGroup , that are needed to successfully make this connection.
The subnet ID used by the connection.
The security group ID list used by the connection.
The connection's Availability Zone. This field is redundant because the specified subnet implies the Availability Zone to be used. Currently the field must be populated, but it will be deprecated in the future.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.GlueEncryptionExceptionupdate_crawler(**kwargs)¶Updates a crawler. If a crawler is running, you must stop it using StopCrawler before updating it.
See also: AWS API Documentation
Request Syntax
response = client.update_crawler(
Name='string',
Role='string',
DatabaseName='string',
Description='string',
Targets={
'S3Targets': [
{
'Path': 'string',
'Exclusions': [
'string',
],
'ConnectionName': 'string',
'SampleSize': 123,
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'JdbcTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'Exclusions': [
'string',
],
'EnableAdditionalMetadata': [
'COMMENTS'|'RAWTYPES',
]
},
],
'MongoDBTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'ScanAll': True|False
},
],
'DynamoDBTargets': [
{
'Path': 'string',
'scanAll': True|False,
'scanRate': 123.0
},
],
'CatalogTargets': [
{
'DatabaseName': 'string',
'Tables': [
'string',
],
'ConnectionName': 'string',
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'DeltaTargets': [
{
'DeltaTables': [
'string',
],
'ConnectionName': 'string',
'WriteManifest': True|False,
'CreateNativeDeltaTable': True|False
},
]
},
Schedule='string',
Classifiers=[
'string',
],
TablePrefix='string',
SchemaChangePolicy={
'UpdateBehavior': 'LOG'|'UPDATE_IN_DATABASE',
'DeleteBehavior': 'LOG'|'DELETE_FROM_DATABASE'|'DEPRECATE_IN_DATABASE'
},
RecrawlPolicy={
'RecrawlBehavior': 'CRAWL_EVERYTHING'|'CRAWL_NEW_FOLDERS_ONLY'|'CRAWL_EVENT_MODE'
},
LineageConfiguration={
'CrawlerLineageSettings': 'ENABLE'|'DISABLE'
},
LakeFormationConfiguration={
'UseLakeFormationCredentials': True|False,
'AccountId': 'string'
},
Configuration='string',
CrawlerSecurityConfiguration='string'
)
[REQUIRED]
Name of the new crawler.
arn:aws:daylight:us-east-1::database/sometable/* .A list of targets to crawl.
Specifies Amazon Simple Storage Service (Amazon S3) targets.
Specifies a data store in Amazon Simple Storage Service (Amazon S3).
The path to the Amazon S3 target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
The name of a connection which allows a job or crawler to access data in Amazon S3 within an Amazon Virtual Private Cloud environment (Amazon VPC).
Sets the number of files in each leaf folder to be crawled when crawling sample files in a dataset. If not set, all the files are crawled. A valid value is an integer between 1 and 249.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies JDBC targets.
Specifies a JDBC data store to crawl.
The name of the connection to use to connect to the JDBC target.
The path of the JDBC target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
Specify a value of RAWTYPES or COMMENTS to enable additional metadata in table responses. RAWTYPES provides the native-level datatype. COMMENTS provides comments associated with a column or table in the database.
If you do not need additional metadata, keep the field empty.
Specifies Amazon DocumentDB or MongoDB targets.
Specifies an Amazon DocumentDB or MongoDB data store to crawl.
The name of the connection to use to connect to the Amazon DocumentDB or MongoDB target.
The path of the Amazon DocumentDB or MongoDB target (database/collection).
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
Specifies Amazon DynamoDB targets.
Specifies an Amazon DynamoDB table to crawl.
The name of the DynamoDB table to crawl.
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
The percentage of the configured read capacity units to use by the Glue crawler. Read capacity units is a term defined by DynamoDB, and is a numeric value that acts as rate limiter for the number of reads that can be performed on that table per second.
The valid values are null or a value between 0.1 to 1.5. A null value is used when user does not provide a value, and defaults to 0.5 of the configured Read Capacity Unit (for provisioned tables), or 0.25 of the max configured Read Capacity Unit (for tables using on-demand mode).
Specifies Glue Data Catalog targets.
Specifies an Glue Data Catalog target.
The name of the database to be synchronized.
A list of the tables to be synchronized.
The name of the connection for an Amazon S3-backed Data Catalog table to be a target of the crawl when using a Catalog connection type paired with a NETWORK Connection type.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies Delta data store targets.
Specifies a Delta data store to crawl one or more Delta tables.
A list of the Amazon S3 paths to the Delta tables.
The name of the connection to use to connect to the Delta table target.
Specifies whether to write the manifest files to the Delta table path.
Specifies whether the crawler will create native tables, to allow integration with query engines that support querying of the Delta transaction log directly.
cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .A list of custom classifiers that the user has registered. By default, all built-in classifiers are included in a crawl, but these custom classifiers always override the default classifiers for a given classification.
The policy for the crawler's update and deletion behavior.
The update behavior when the crawler finds a changed schema.
The deletion behavior when the crawler finds a deleted object.
A policy that specifies whether to crawl the entire dataset again, or to crawl only folders that were added since the last crawler run.
Specifies whether to crawl the entire dataset again or to crawl only folders that were added since the last crawler run.
A value of CRAWL_EVERYTHING specifies crawling the entire dataset again.
A value of CRAWL_NEW_FOLDERS_ONLY specifies crawling only folders that were added since the last crawler run.
A value of CRAWL_EVENT_MODE specifies crawling only the changes identified by Amazon S3 events.
Specifies data lineage configuration settings for the crawler.
Specifies whether data lineage is enabled for the crawler. Valid values are:
Specifies Lake Formation configuration settings for the crawler.
Specifies whether to use Lake Formation credentials for the crawler instead of the IAM role credentials.
Required for cross account crawls. For same account crawls as the target data, this can be left as null.
SecurityConfiguration structure to be used by this crawler.dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.VersionMismatchExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.CrawlerRunningExceptionGlue.Client.exceptions.OperationTimeoutExceptionupdate_crawler_schedule(**kwargs)¶Updates the schedule of a crawler using a cron expression.
See also: AWS API Documentation
Request Syntax
response = client.update_crawler_schedule(
CrawlerName='string',
Schedule='string'
)
[REQUIRED]
The name of the crawler whose schedule to update.
cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.VersionMismatchExceptionGlue.Client.exceptions.SchedulerTransitioningExceptionGlue.Client.exceptions.OperationTimeoutExceptionupdate_data_quality_ruleset(**kwargs)¶Updates the specified data quality ruleset.
See also: AWS API Documentation
Request Syntax
response = client.update_data_quality_ruleset(
Name='string',
UpdatedName='string',
Description='string',
Ruleset='string'
)
[REQUIRED]
The name of the data quality ruleset.
dict
Response Syntax
{
'Name': 'string',
'Description': 'string',
'Ruleset': 'string'
}
Response Structure
(dict) --
Name (string) --
The name of the data quality ruleset.
Description (string) --
A description of the ruleset.
Ruleset (string) --
A Data Quality Definition Language (DQDL) ruleset. For more information, see the Glue developer guide.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.IdempotentParameterMismatchExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionupdate_database(**kwargs)¶Updates an existing database definition in a Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.update_database(
CatalogId='string',
Name='string',
DatabaseInput={
'Name': 'string',
'Description': 'string',
'LocationUri': 'string',
'Parameters': {
'string': 'string'
},
'CreateTableDefaultPermissions': [
{
'Principal': {
'DataLakePrincipalIdentifier': 'string'
},
'Permissions': [
'ALL'|'SELECT'|'ALTER'|'DROP'|'DELETE'|'INSERT'|'CREATE_DATABASE'|'CREATE_TABLE'|'DATA_LOCATION_ACCESS',
]
},
],
'TargetDatabase': {
'CatalogId': 'string',
'DatabaseName': 'string'
}
}
)
[REQUIRED]
The name of the database to update in the catalog. For Hive compatibility, this is folded to lowercase.
[REQUIRED]
A DatabaseInput object specifying the new definition of the metadata database in the catalog.
The name of the database. For Hive compatibility, this is folded to lowercase when it is stored.
A description of the database.
The location of the database (for example, an HDFS path).
These key-value pairs define parameters and properties of the database.
These key-value pairs define parameters and properties of the database.
Creates a set of default permissions on the table for principals.
Permissions granted to a principal.
The principal who is granted permissions.
An identifier for the Lake Formation principal.
The permissions that are granted to the principal.
A DatabaseIdentifier structure that describes a target database for resource linking.
The ID of the Data Catalog in which the database resides.
The name of the catalog database.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.ConcurrentModificationExceptionupdate_dev_endpoint(**kwargs)¶Updates a specified development endpoint.
See also: AWS API Documentation
Request Syntax
response = client.update_dev_endpoint(
EndpointName='string',
PublicKey='string',
AddPublicKeys=[
'string',
],
DeletePublicKeys=[
'string',
],
CustomLibraries={
'ExtraPythonLibsS3Path': 'string',
'ExtraJarsS3Path': 'string'
},
UpdateEtlLibraries=True|False,
DeleteArguments=[
'string',
],
AddArguments={
'string': 'string'
}
)
[REQUIRED]
The name of the DevEndpoint to be updated.
DevEndpoint to use.The list of public keys for the DevEndpoint to use.
The list of public keys to be deleted from the DevEndpoint .
Custom Python or Java libraries to be loaded in the DevEndpoint .
The paths to one or more Python libraries in an Amazon Simple Storage Service (Amazon S3) bucket that should be loaded in your DevEndpoint . Multiple values must be complete paths separated by a comma.
Note
You can only use pure Python libraries with a DevEndpoint . Libraries that rely on C extensions, such as the pandas Python data analysis library, are not currently supported.
The path to one or more Java .jar files in an S3 bucket that should be loaded in your DevEndpoint .
Note
You can only use pure Java/Scala libraries with a DevEndpoint .
True if the list of custom libraries to be loaded in the development endpoint needs to be updated, or False if otherwise.The list of argument keys to be deleted from the map of arguments used to configure the DevEndpoint .
The map of arguments to add the map of arguments used to configure the DevEndpoint .
Valid arguments are:
"--enable-glue-datacatalog": ""You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.ValidationExceptionupdate_job(**kwargs)¶Updates an existing job definition. The previous job definition is completely overwritten by this information.
See also: AWS API Documentation
Request Syntax
response = client.update_job(
JobName='string',
JobUpdate={
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
}
)
[REQUIRED]
The name of the job definition to update.
[REQUIRED]
Specifies the values with which to update the job definition. Unspecified configuration is removed or reset to default values.
Description of the job being defined.
This field is reserved for future use.
The name or Amazon Resource Name (ARN) of the IAM role associated with this job (required).
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
The JobCommand that runs this job (required).
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
The default arguments for this job.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Non-overridable arguments for this job, specified as name-value pairs.
The connections used for this job.
A list of connections used by the job.
The maximum number of times to retry this job if it fails.
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) to allocate to this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.The number of workers of a defined workerType that are allocated when a job runs.
The name of the SecurityConfiguration structure to be used with this job.
Specifies the configuration properties of a job notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
CodeGenConfigurationNodeenumerates all valid Node types. One and only one of its member variables can be populated.
Specifies a connector to an Amazon Athena data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
The name of the table in the data source.
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
Specifies the data schema for the custom Athena source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to a JDBC data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
Additional connection options for the connector.
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
The minimum value of partitionColumn that is used to decide partition stride.
The maximum value of partitionColumn that is used to decide partition stride.
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
The name of the job bookmark keys on which to sort.
Specifies an ascending or descending sort order.
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
The name of the table in the data source.
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
Specifies the data schema for the custom JDBC source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to an Apache Spark data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies data schema for the custom spark source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a data store in the Glue Data Catalog.
The name of the data store.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Amazon Redshift data store.
The name of the Amazon Redshift data store.
The database to read from.
The database table to read from.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
Specifies an Amazon S3 data store in the Glue Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a command-separated value (CSV) data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
A Boolean value that specifies whether to write the header to output. The default value is True .
A Boolean value that specifies whether to skip the first data line. The default value is False .
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
Specifies the data schema for the S3 CSV source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a JSON data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
A JsonPath string defining the JSON data.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
Specifies the data schema for the S3 JSON source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies an Apache Parquet data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the data schema for the S3 Parquet source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a Relational database data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a DynamoDB data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
The name of the connection that is associated with the connector.
The name of the table in the data target.
The name of a connector that will be used.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
Additional connection options for the connector.
Specifies the data schema for the JDBC target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses an Apache Spark connector.
The name of the data target.
The nodes that are inputs to the data target.
The name of a connection for an Apache Spark connector.
The name of an Apache Spark connector.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies the data schema for the custom spark target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses a Glue Data Catalog table.
The name of your data target.
The nodes that are inputs to the data target.
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
Specifies a target that uses Amazon Redshift.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
The set of options to configure an upsert operation when writing to a Redshift target.
The physical location of the Redshift table.
The name of the connection to use to write to Redshift.
The keys used to determine whether to perform an update or insert.
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a data target that writes to Amazon S3.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Specifies the data output format for the target.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
The name of the transform node.
The data inputs identified by their node names.
Specifies the mapping of data property keys in the data source to data property keys in the data target.
Specifies the mapping of data property keys.
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
The table or column to be modified.
The type of the data to be modified.
The data type that the data is to be modified to.
If true, then the column is removed.
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
Specifies a transform that chooses the data property keys that you want to keep.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses the data property keys that you want to drop.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that renames a single data property key.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the source data.
A JSON path to a variable in the data structure for the target data.
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
The name of the transform node.
The data inputs identified by their node names.
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Specifies a number of records to write starting from the beginning of the dataset.
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
The name of the transform node.
The data inputs identified by their node names.
Specifies the type of join to be performed on the datasets.
A list of the two columns to be joined.
Specifies a column to be joined.
The column to be joined.
The key of the column to be joined.
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
The name of the transform node.
The data inputs identified by their node names.
The index for the DynamicFrame to be selected.
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the dataset that is imputed.
A JSON path to a variable in the data structure for the dataset that is filled.
Specifies a transform that splits a dataset into two, based on a filter condition.
The name of the transform node.
The data inputs identified by their node names.
The operator used to filter rows by comparing the key value to a specified value.
Specifies a filter expression.
Specifies a filter expression.
The type of operation to perform in the expression.
Whether the expression is to be negated.
A list of filter values.
Represents a single entry in the list of values for a FilterExpression .
The type of filter value.
The value to be associated.
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
The name of the transform node.
The data inputs identified by their node names.
The custom code that is used to perform the data transformation.
The name defined for the custom code node class.
Specifies the data schema for the custom code transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
The name of the transform node.
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
A SQL query that must use Spark SQL syntax and return a single data set.
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
Represents a single entry in the list of values for SqlAliases .
A table, or a column in a table.
A temporary name given to a table, or a column in a table.
Specifies the data schema for the SparkSQL transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a direct Amazon Kinesis data source.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store.
The name of the data store.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a Kinesis data source in the Glue Data Catalog.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store in the Data Catalog.
The name of the data store.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
The name of the transform node.
The data inputs identified by their node names.
A structure that represents whether certain values are recognized as null values for removal.
Specifies that an empty string is considered as a null value.
Specifies that a value spelling out the word 'null' is considered as a null value.
Specifies that an integer value of -1 is considered as a null value.
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
The value of the null placeholder.
The datatype of the value.
The datatype of the value.
A label assigned to the datatype.
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
The name of the transform node.
The data inputs identified by their node names.
The source DynamicFrame that will be merged with a staging DynamicFrame .
The list of primary key fields to match records from the source and staging dynamic frames.
Specifies a transform that combines the rows from two or more datasets into a single result.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
Specifies a transform that identifies, removes or masks PII data.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of PIIDetection transform.
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
Indicates the output column name that will contain any entity type detected in that row.
Indicates the fraction of the data to sample when scanning for PII entities.
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
Indicates the value that will replace the detected entity.
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
The name of the transform node.
Specifies the fields and rows to use as inputs for the aggregate transform.
Specifies the fields to group by.
Specifies the aggregate functions to be performed on specified fields.
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Specifies the column on the data set on which the aggregation function will be applied.
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
Specifies a transform that removes rows of repeating data from a data set.
The name of the transform node.
The data inputs identified by their node names.
The name of the columns to be merged or removed if repeating.
Specifies a data target that writes to a goverened catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the governed catalog.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data source in a goverened Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a MySQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Oracle data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a PostgresSQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a target that uses Microsoft SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses MySQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Oracle SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Postgres SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a custom visual transform created by a user.
Specifies the name of the dynamic transform.
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Specifies the inputs for the dynamic transform that are required.
Specifies the parameters of the dynamic transform.
Specifies the parameters in the config file of the dynamic transform.
Specifies the name of the parameter in the config file of the dynamic transform.
Specifies the parameter type in the config file of the dynamic transform.
Specifies the validation rule in the config file of the dynamic transform.
Specifies the validation message in the config file of the dynamic transform.
Specifies the value of the parameter in the config file of the dynamic transform.
Specifies the list type of the parameter in the config file of the dynamic transform.
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
Specifies the name of the function of the dynamic transform.
Specifies the path of the dynamic transform source and config files.
This field is not used and will be deprecated in future release.
Specifies your data quality evaluation criteria.
The name of the data quality evaluation.
The inputs of your data quality evaluation.
The ruleset for your data quality evaluation.
The output of your data quality evaluation.
Options to configure how your results are published.
The context of the evaluation.
The Amazon S3 prefix prepended to the results.
Enable metrics for your data quality results.
Enable publishing for your data quality results.
Options to configure how your job will stop if your data quality evaluation fails.
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
The provider for the remote repository.
The name of the remote repository that contains the job artifacts.
The owner of the remote repository that contains the job artifacts.
An optional branch in the remote repository.
An optional folder in the remote repository.
The last commit ID for a commit in the remote repository.
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
The value of an authorization token.
dict
Response Syntax
{
'JobName': 'string'
}
Response Structure
(dict) --
JobName (string) --
Returns the name of the updated job definition.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptionupdate_job_from_source_control(**kwargs)¶Synchronizes a job from the source control repository. This operation takes the job artifacts that are located in the remote repository and updates the Glue internal stores with these artifacts.
This API supports optional parameters which take in the repository information.
See also: AWS API Documentation
Request Syntax
response = client.update_job_from_source_control(
JobName='string',
Provider='GITHUB'|'AWS_CODE_COMMIT',
RepositoryName='string',
RepositoryOwner='string',
BranchName='string',
Folder='string',
CommitId='string',
AuthStrategy='PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
AuthToken='string'
)
dict
Response Syntax
{
'JobName': 'string'
}
Response Structure
(dict) --
JobName (string) --
The name of the Glue job.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.ValidationExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionupdate_ml_transform(**kwargs)¶Updates an existing machine learning transform. Call this operation to tune the algorithm parameters to achieve better results.
After calling this operation, you can call the StartMLEvaluationTaskRun operation to assess how well your new parameters achieved your goals (such as improving the quality of your machine learning transform, or making it more cost-effective).
See also: AWS API Documentation
Request Syntax
response = client.update_ml_transform(
TransformId='string',
Name='string',
Description='string',
Parameters={
'TransformType': 'FIND_MATCHES',
'FindMatchesParameters': {
'PrimaryKeyColumnName': 'string',
'PrecisionRecallTradeoff': 123.0,
'AccuracyCostTradeoff': 123.0,
'EnforceProvidedLabels': True|False
}
},
Role='string',
GlueVersion='string',
MaxCapacity=123.0,
WorkerType='Standard'|'G.1X'|'G.2X'|'G.025X',
NumberOfWorkers=123,
Timeout=123,
MaxRetries=123
)
[REQUIRED]
A unique identifier that was generated when the transform was created.
The configuration parameters that are specific to the transform type (algorithm) used. Conditionally dependent on the transform type.
The type of machine learning transform.
For information about the types of machine learning transforms, see Creating Machine Learning Transforms.
The parameters for the find matches algorithm.
The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
The value selected when tuning your transform for a balance between precision and recall. A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.
The precision metric indicates how often your model is correct when it predicts a match.
The recall metric indicates that for an actual match, how often your model predicts the match.
The value that is selected when tuning your transform for a balance between accuracy and cost. A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate FindMatches transform, sometimes with unacceptable accuracy.
Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall.
Cost measures how many compute resources, and thus money, are consumed to run the transform.
The value to switch on or off to force the output to match the provided labels from users. If the value is True , the find matches transform forces the output to match the provided labels. The results override the normal conflation results. If the value is False , the find matches transform does not ensure all the labels provided are respected, and the results rely on the trained model.
Note that setting this value to true may increase the conflation execution time.
The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
When the WorkerType field is set to a value other than Standard , the MaxCapacity field is set automatically and becomes read-only.
The type of predefined worker that is allocated when this task runs. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.workerType that are allocated when this task runs.TIMEOUT status. The default is 2,880 minutes (48 hours).dict
Response Syntax
{
'TransformId': 'string'
}
Response Structure
(dict) --
TransformId (string) --
The unique identifier for the transform that was updated.
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.AccessDeniedExceptionupdate_partition(**kwargs)¶Updates a partition.
See also: AWS API Documentation
Request Syntax
response = client.update_partition(
CatalogId='string',
DatabaseName='string',
TableName='string',
PartitionValueList=[
'string',
],
PartitionInput={
'Values': [
'string',
],
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1)
}
)
[REQUIRED]
The name of the catalog database in which the table in question resides.
[REQUIRED]
The name of the table in which the partition to be updated is located.
[REQUIRED]
List of partition key values that define the partition to update.
[REQUIRED]
The new partition object to update the partition to.
The Values property can't be changed. If you want to change the partition key values for a partition, delete and recreate the partition.
The values of the partition. Although this parameter is not required by the SDK, you must specify this parameter for a valid input.
The values for the keys for the new partition must be passed as an array of String objects that must be ordered in the same order as the partition keys appearing in the Amazon S3 prefix. Otherwise Glue will add the values to the wrong keys.
The last time at which the partition was accessed.
Provides information about the physical location where the partition is stored.
A list of the Columns in the table.
A column in a Table .
The name of the Column .
The data type of the Column .
A free-form text comment.
These key-value pairs define properties associated with the column.
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
A list of locations that point to the path where a Delta table is located.
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Trueif the data in the table is compressed, orFalseif not.
Must be specified if the table contains any dimension columns.
The serialization/deserialization (SerDe) information.
Name of the SerDe.
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
These key-value pairs define initialization parameters for the SerDe.
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
A list specifying the sort order of each bucket in the table.
Specifies the sort order of a sorted column.
The name of the column.
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
The user-supplied properties in key-value form.
The information about values that appear frequently in a column (skewed values).
A list of names of columns that contain skewed values.
A list of values that appear so frequently as to be considered skewed.
A mapping of skewed values to the columns that contain them.
Trueif the table data is stored in subdirectories, orFalseif not.
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
The version number of the schema.
These key-value pairs define partition parameters.
The last time at which column statistics were computed for this partition.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionupdate_registry(**kwargs)¶Updates an existing registry which is used to hold a collection of schemas. The updated properties relate to the registry, and do not modify any of the schemas within the registry.
See also: AWS API Documentation
Request Syntax
response = client.update_registry(
RegistryId={
'RegistryName': 'string',
'RegistryArn': 'string'
},
Description='string'
)
[REQUIRED]
This is a wrapper structure that may contain the registry name and Amazon Resource Name (ARN).
Name of the registry. Used only for lookup. One of RegistryArn or RegistryName has to be provided.
Arn of the registry to be updated. One of RegistryArn or RegistryName has to be provided.
[REQUIRED]
A description of the registry. If description is not provided, this field will not be updated.
dict
Response Syntax
{
'RegistryName': 'string',
'RegistryArn': 'string'
}
Response Structure
(dict) --
RegistryName (string) --
The name of the updated registry.
RegistryArn (string) --
The Amazon Resource name (ARN) of the updated registry.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.InternalServiceExceptionupdate_schema(**kwargs)¶Updates the description, compatibility setting, or version checkpoint for a schema set.
For updating the compatibility setting, the call will not validate compatibility for the entire set of schema versions with the new compatibility setting. If the value for Compatibility is provided, the VersionNumber (a checkpoint) is also required. The API will validate the checkpoint version number for consistency.
If the value for the VersionNumber (checkpoint) is provided, Compatibility is optional and this can be used to set/reset a checkpoint for the schema.
This update will happen only if the schema is in the AVAILABLE state.
See also: AWS API Documentation
Request Syntax
response = client.update_schema(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
SchemaVersionNumber={
'LatestVersion': True|False,
'VersionNumber': 123
},
Compatibility='NONE'|'DISABLED'|'BACKWARD'|'BACKWARD_ALL'|'FORWARD'|'FORWARD_ALL'|'FULL'|'FULL_ALL',
Description='string'
)
[REQUIRED]
This is a wrapper structure to contain schema identity fields. The structure contains:
SchemaArn or SchemaName has to be provided.SchemaArn or SchemaName has to be provided.The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
Version number required for check pointing. One of VersionNumber or Compatibility has to be provided.
The latest version available for the schema.
The version number of the schema.
dict
Response Syntax
{
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
}
Response Structure
(dict) --
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema.
SchemaName (string) --
The name of the schema.
RegistryName (string) --
The name of the registry that contains the schema.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.InternalServiceExceptionupdate_source_control_from_job(**kwargs)¶Synchronizes a job to the source control repository. This operation takes the job artifacts from the Glue internal stores and makes a commit to the remote repository that is configured on the job.
This API supports optional parameters which take in the repository information.
See also: AWS API Documentation
Request Syntax
response = client.update_source_control_from_job(
JobName='string',
Provider='GITHUB'|'AWS_CODE_COMMIT',
RepositoryName='string',
RepositoryOwner='string',
BranchName='string',
Folder='string',
CommitId='string',
AuthStrategy='PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
AuthToken='string'
)
dict
Response Syntax
{
'JobName': 'string'
}
Response Structure
(dict) --
JobName (string) --
The name of the Glue job.
Exceptions
Glue.Client.exceptions.AccessDeniedExceptionGlue.Client.exceptions.AlreadyExistsExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.ValidationExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionupdate_table(**kwargs)¶Updates a metadata table in the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.update_table(
CatalogId='string',
DatabaseName='string',
TableInput={
'Name': 'string',
'Description': 'string',
'Owner': 'string',
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
}
},
SkipArchive=True|False,
TransactionId='string',
VersionId='string'
)
[REQUIRED]
The name of the catalog database in which the table resides. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
An updated TableInput object to define the metadata table in the catalog.
The table name. For Hive compatibility, this is folded to lowercase when it is stored.
A description of the table.
The table owner.
The last time that the table was accessed.
The last time that column statistics were computed for this table.
The retention time for this table.
A storage descriptor containing information about the physical storage of this table.
A list of the Columns in the table.
A column in a Table .
The name of the Column .
The data type of the Column .
A free-form text comment.
These key-value pairs define properties associated with the column.
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
A list of locations that point to the path where a Delta table is located.
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Trueif the data in the table is compressed, orFalseif not.
Must be specified if the table contains any dimension columns.
The serialization/deserialization (SerDe) information.
Name of the SerDe.
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
These key-value pairs define initialization parameters for the SerDe.
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
A list specifying the sort order of each bucket in the table.
Specifies the sort order of a sorted column.
The name of the column.
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
The user-supplied properties in key-value form.
The information about values that appear frequently in a column (skewed values).
A list of names of columns that contain skewed values.
A list of values that appear so frequently as to be considered skewed.
A mapping of skewed values to the columns that contain them.
Trueif the table data is stored in subdirectories, orFalseif not.
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
The version number of the schema.
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
A column in a Table .
The name of the Column .
The data type of the Column .
A free-form text comment.
These key-value pairs define properties associated with the column.
If the table is a view, the original text of the view; otherwise null .
If the table is a view, the expanded text of the view; otherwise null .
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
These key-value pairs define properties associated with the table.
A TableIdentifier structure that describes a target table for resource linking.
The ID of the Data Catalog in which the table resides.
The name of the catalog database that contains the target table.
The name of the target table.
UpdateTable always creates an archived version of the table before updating it. However, if skipArchive is set to true, UpdateTable does not create the archived version.dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptionGlue.Client.exceptions.ResourceNumberLimitExceededExceptionGlue.Client.exceptions.GlueEncryptionExceptionGlue.Client.exceptions.ResourceNotReadyExceptionupdate_trigger(**kwargs)¶Updates a trigger definition.
See also: AWS API Documentation
Request Syntax
response = client.update_trigger(
Name='string',
TriggerUpdate={
'Name': 'string',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
)
[REQUIRED]
The name of the trigger to update.
[REQUIRED]
The new values with which to update the trigger.
Reserved for future use.
A description of this trigger.
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
The actions initiated by this trigger.
Defines an action to be initiated by a trigger.
The name of a job to be run.
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
The name of the SecurityConfiguration structure to be used with this action.
Specifies configuration properties of a job run notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
The name of the crawler to be used with this action.
The predicate of this trigger, which defines when it will fire.
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
A list of the conditions that determine when the trigger will fire.
Defines a condition under which a trigger fires.
A logical operator.
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
The name of the crawler to which this condition applies.
The state of the crawler to which this condition applies.
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
dict
Response Syntax
{
'Trigger': {
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
}
}
Response Structure
(dict) --
Trigger (dict) --
The resulting trigger definition.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptionupdate_user_defined_function(**kwargs)¶Updates an existing function definition in the Data Catalog.
See also: AWS API Documentation
Request Syntax
response = client.update_user_defined_function(
CatalogId='string',
DatabaseName='string',
FunctionName='string',
FunctionInput={
'FunctionName': 'string',
'ClassName': 'string',
'OwnerName': 'string',
'OwnerType': 'USER'|'ROLE'|'GROUP',
'ResourceUris': [
{
'ResourceType': 'JAR'|'FILE'|'ARCHIVE',
'Uri': 'string'
},
]
}
)
[REQUIRED]
The name of the catalog database where the function to be updated is located.
[REQUIRED]
The name of the function.
[REQUIRED]
A FunctionInput object that redefines the function in the Data Catalog.
The name of the function.
The Java class that contains the function code.
The owner of the function.
The owner type.
The resource URIs for the function.
The URIs for function resources.
The type of the resource.
The URI for accessing the resource.
dict
Response Syntax
{}
Response Structure
Exceptions
Glue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.GlueEncryptionExceptionupdate_workflow(**kwargs)¶Updates an existing workflow.
See also: AWS API Documentation
Request Syntax
response = client.update_workflow(
Name='string',
Description='string',
DefaultRunProperties={
'string': 'string'
},
MaxConcurrentRuns=123
)
[REQUIRED]
Name of the workflow to be updated.
A collection of properties to be used as part of each execution of the workflow.
dict
Response Syntax
{
'Name': 'string'
}
Response Structure
(dict) --
Name (string) --
The name of the workflow which was specified in input.
Exceptions
Glue.Client.exceptions.InvalidInputExceptionGlue.Client.exceptions.EntityNotFoundExceptionGlue.Client.exceptions.InternalServiceExceptionGlue.Client.exceptions.OperationTimeoutExceptionGlue.Client.exceptions.ConcurrentModificationExceptionThe available paginators are:
Glue.Paginator.GetClassifiersGlue.Paginator.GetConnectionsGlue.Paginator.GetCrawlerMetricsGlue.Paginator.GetCrawlersGlue.Paginator.GetDatabasesGlue.Paginator.GetDevEndpointsGlue.Paginator.GetJobRunsGlue.Paginator.GetJobsGlue.Paginator.GetPartitionIndexesGlue.Paginator.GetPartitionsGlue.Paginator.GetResourcePoliciesGlue.Paginator.GetSecurityConfigurationsGlue.Paginator.GetTableVersionsGlue.Paginator.GetTablesGlue.Paginator.GetTriggersGlue.Paginator.GetUserDefinedFunctionsGlue.Paginator.ListRegistriesGlue.Paginator.ListSchemaVersionsGlue.Paginator.ListSchemasGlue.Paginator.GetClassifiers¶paginator = client.get_paginator('get_classifiers')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_classifiers().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'Classifiers': [
{
'GrokClassifier': {
'Name': 'string',
'Classification': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'GrokPattern': 'string',
'CustomPatterns': 'string'
},
'XMLClassifier': {
'Name': 'string',
'Classification': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'RowTag': 'string'
},
'JsonClassifier': {
'Name': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'JsonPath': 'string'
},
'CsvClassifier': {
'Name': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'Version': 123,
'Delimiter': 'string',
'QuoteSymbol': 'string',
'ContainsHeader': 'UNKNOWN'|'PRESENT'|'ABSENT',
'Header': [
'string',
],
'DisableValueTrimming': True|False,
'AllowSingleColumn': True|False,
'CustomDatatypeConfigured': True|False,
'CustomDatatypes': [
'string',
]
}
},
],
}
Response Structure
The requested list of classifier objects.
Classifiers are triggered during a crawl task. A classifier checks whether a given file is in a format it can handle. If it is, the classifier creates a schema in the form of a StructType object that matches that data format.
You can use the standard classifiers that Glue provides, or you can write your own classifiers to best categorize your data sources and specify the appropriate schemas to use for them. A classifier can be a grok classifier, an XML classifier, a JSON classifier, or a custom CSV classifier, as specified in one of the fields in the Classifier object.
A classifier that uses grok .
The name of the classifier.
An identifier of the data format that the classifier matches, such as Twitter, JSON, Omniture logs, and so on.
The time that this classifier was registered.
The time that this classifier was last updated.
The version of this classifier.
The grok pattern applied to a data store by this classifier. For more information, see built-in patterns in Writing Custom Classifiers.
Optional custom grok patterns defined by this classifier. For more information, see custom patterns in Writing Custom Classifiers.
A classifier for XML content.
The name of the classifier.
An identifier of the data format that the classifier matches.
The time that this classifier was registered.
The time that this classifier was last updated.
The version of this classifier.
The XML tag designating the element that contains each record in an XML document being parsed. This can't identify a self-closing element (closed by /> ). An empty row element that contains only attributes can be parsed as long as it ends with a closing tag (for example, <row item_a="A" item_b="B"></row> is okay, but <row item_a="A" item_b="B" /> is not).
A classifier for JSON content.
The name of the classifier.
The time that this classifier was registered.
The time that this classifier was last updated.
The version of this classifier.
A JsonPath string defining the JSON data for the classifier to classify. Glue supports a subset of JsonPath, as described in Writing JsonPath Custom Classifiers.
A classifier for comma-separated values (CSV).
The name of the classifier.
The time that this classifier was registered.
The time that this classifier was last updated.
The version of this classifier.
A custom symbol to denote what separates each column entry in the row.
A custom symbol to denote what combines content into a single column value. It must be different from the column delimiter.
Indicates whether the CSV file contains a header.
A list of strings representing column names.
Specifies not to trim values before identifying the type of column values. The default value is true .
Enables the processing of files that contain only one column.
Enables the custom datatype to be configured.
A list of custom datatypes including "BINARY", "BOOLEAN", "DATE", "DECIMAL", "DOUBLE", "FLOAT", "INT", "LONG", "SHORT", "STRING", "TIMESTAMP".
Glue.Paginator.GetConnections¶paginator = client.get_paginator('get_connections')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_connections().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
CatalogId='string',
Filter={
'MatchCriteria': [
'string',
],
'ConnectionType': 'JDBC'|'SFTP'|'MONGODB'|'KAFKA'|'NETWORK'|'MARKETPLACE'|'CUSTOM'
},
HidePassword=True|False,
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A filter that controls which connections are returned.
A criteria string that must match the criteria recorded in the connection definition for that connection definition to be returned.
The type of connections to return. Currently, SFTP is not supported.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'ConnectionList': [
{
'Name': 'string',
'Description': 'string',
'ConnectionType': 'JDBC'|'SFTP'|'MONGODB'|'KAFKA'|'NETWORK'|'MARKETPLACE'|'CUSTOM',
'MatchCriteria': [
'string',
],
'ConnectionProperties': {
'string': 'string'
},
'PhysicalConnectionRequirements': {
'SubnetId': 'string',
'SecurityGroupIdList': [
'string',
],
'AvailabilityZone': 'string'
},
'CreationTime': datetime(2015, 1, 1),
'LastUpdatedTime': datetime(2015, 1, 1),
'LastUpdatedBy': 'string'
},
],
}
Response Structure
(dict) --
ConnectionList (list) --
A list of requested connection definitions.
(dict) --
Defines a connection to a data source.
Name (string) --
The name of the connection definition.
Description (string) --
The description of the connection.
ConnectionType (string) --
The type of the connection. Currently, SFTP is not supported.
MatchCriteria (list) --
A list of criteria that can be used in selecting this connection.
ConnectionProperties (dict) --
These key-value pairs define parameters for the connection:
HOST - The host URI: either the fully qualified domain name (FQDN) or the IPv4 address of the database host.PORT - The port number, between 1024 and 65535, of the port on which the database host is listening for database connections.USER_NAME - The name under which to log in to the database. The value string for USER_NAME is " USERNAME ".PASSWORD - A password, if one is used, for the user name.ENCRYPTED_PASSWORD - When you enable connection password protection by setting ConnectionPasswordEncryption in the Data Catalog encryption settings, this field stores the encrypted password.JDBC_DRIVER_JAR_URI - The Amazon Simple Storage Service (Amazon S3) path of the JAR file that contains the JDBC driver to use.JDBC_DRIVER_CLASS_NAME - The class name of the JDBC driver to use.JDBC_ENGINE - The name of the JDBC engine to use.JDBC_ENGINE_VERSION - The version of the JDBC engine to use.CONFIG_FILES - (Reserved for future use.)INSTANCE_ID - The instance ID to use.JDBC_CONNECTION_URL - The URL for connecting to a JDBC data source.JDBC_ENFORCE_SSL - A Boolean string (true, false) specifying whether Secure Sockets Layer (SSL) with hostname matching is enforced for the JDBC connection on the client. The default is false.CUSTOM_JDBC_CERT - An Amazon S3 location specifying the customer's root certificate. Glue uses this root certificate to validate the customer’s certificate when connecting to the customer database. Glue only handles X.509 certificates. The certificate provided must be DER-encoded and supplied in Base64 encoding PEM format.SKIP_CUSTOM_JDBC_CERT_VALIDATION - By default, this is false . Glue validates the Signature algorithm and Subject Public Key Algorithm for the customer certificate. The only permitted algorithms for the Signature algorithm are SHA256withRSA, SHA384withRSA or SHA512withRSA. For the Subject Public Key Algorithm, the key length must be at least 2048. You can set the value of this property to true to skip Glue’s validation of the customer certificate.CUSTOM_JDBC_CERT_STRING - A custom JDBC certificate string which is used for domain match or distinguished name match to prevent a man-in-the-middle attack. In Oracle database, this is used as the SSL_SERVER_CERT_DN ; in Microsoft SQL Server, this is used as the hostNameInCertificate .CONNECTION_URL - The URL for connecting to a general (non-JDBC) data source.SECRET_ID - The secret ID used for the secret manager of credentials.CONNECTOR_URL - The connector URL for a MARKETPLACE or CUSTOM connection.CONNECTOR_TYPE - The connector type for a MARKETPLACE or CUSTOM connection.CONNECTOR_CLASS_NAME - The connector class name for a MARKETPLACE or CUSTOM connection.KAFKA_BOOTSTRAP_SERVERS - A comma-separated list of host and port pairs that are the addresses of the Apache Kafka brokers in a Kafka cluster to which a Kafka client will connect to and bootstrap itself.KAFKA_SSL_ENABLED - Whether to enable or disable SSL on an Apache Kafka connection. Default value is "true".KAFKA_CUSTOM_CERT - The Amazon S3 URL for the private CA cert file (.pem format). The default is an empty string.KAFKA_SKIP_CUSTOM_CERT_VALIDATION - Whether to skip the validation of the CA cert file or not. Glue validates for three algorithms: SHA256withRSA, SHA384withRSA and SHA512withRSA. Default value is "false".KAFKA_CLIENT_KEYSTORE - The Amazon S3 location of the client keystore file for Kafka client side authentication (Optional).KAFKA_CLIENT_KEYSTORE_PASSWORD - The password to access the provided keystore (Optional).KAFKA_CLIENT_KEY_PASSWORD - A keystore can consist of multiple keys, so this is the password to access the client key to be used with the Kafka server side key (Optional).ENCRYPTED_KAFKA_CLIENT_KEYSTORE_PASSWORD - The encrypted version of the Kafka client keystore password (if the user has the Glue encrypt passwords setting selected).ENCRYPTED_KAFKA_CLIENT_KEY_PASSWORD - The encrypted version of the Kafka client key password (if the user has the Glue encrypt passwords setting selected).KAFKA_SASL_MECHANISM - "SCRAM-SHA-512" or "GSSAPI" . These are the two supported SASL Mechanisms.KAFKA_SASL_SCRAM_USERNAME - A plaintext username used to authenticate with the "SCRAM-SHA-512" mechanism.KAFKA_SASL_SCRAM_PASSWORD - A plaintext password used to authenticate with the "SCRAM-SHA-512" mechanism.ENCRYPTED_KAFKA_SASL_SCRAM_PASSWORD - The encrypted version of the Kafka SASL SCRAM password (if the user has the Glue encrypt passwords setting selected).KAFKA_SASL_GSSAPI_KEYTAB - The S3 location of a Kerberos keytab file. A keytab stores long-term keys for one or more principals. For more information, see MIT Kerberos Documentation: Keytab.KAFKA_SASL_GSSAPI_KRB5_CONF - The S3 location of a Kerberos krb5.conf file. A krb5.conf stores Kerberos configuration information, such as the location of the KDC server. For more information, see MIT Kerberos Documentation: krb5.conf.KAFKA_SASL_GSSAPI_SERVICE - The Kerberos service name, as set with sasl.kerberos.service.name in your Kafka Configuration.KAFKA_SASL_GSSAPI_PRINCIPAL - The name of the Kerberos princial used by Glue. For more information, see Kafka Documentation: Configuring Kafka Brokers.PhysicalConnectionRequirements (dict) --
A map of physical connection requirements, such as virtual private cloud (VPC) and SecurityGroup , that are needed to make this connection successfully.
SubnetId (string) --
The subnet ID used by the connection.
SecurityGroupIdList (list) --
The security group ID list used by the connection.
AvailabilityZone (string) --
The connection's Availability Zone. This field is redundant because the specified subnet implies the Availability Zone to be used. Currently the field must be populated, but it will be deprecated in the future.
CreationTime (datetime) --
The time that this connection definition was created.
LastUpdatedTime (datetime) --
The last time that this connection definition was updated.
LastUpdatedBy (string) --
The user, group, or role that last updated this connection definition.
Glue.Paginator.GetCrawlerMetrics¶paginator = client.get_paginator('get_crawler_metrics')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_crawler_metrics().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
CrawlerNameList=[
'string',
],
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A list of the names of crawlers about which to retrieve metrics.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'CrawlerMetricsList': [
{
'CrawlerName': 'string',
'TimeLeftSeconds': 123.0,
'StillEstimating': True|False,
'LastRuntimeSeconds': 123.0,
'MedianRuntimeSeconds': 123.0,
'TablesCreated': 123,
'TablesUpdated': 123,
'TablesDeleted': 123
},
],
}
Response Structure
(dict) --
CrawlerMetricsList (list) --
A list of metrics for the specified crawler.
(dict) --
Metrics for a specified crawler.
CrawlerName (string) --
The name of the crawler.
TimeLeftSeconds (float) --
The estimated time left to complete a running crawl.
StillEstimating (boolean) --
True if the crawler is still estimating how long it will take to complete this run.
LastRuntimeSeconds (float) --
The duration of the crawler's most recent run, in seconds.
MedianRuntimeSeconds (float) --
The median duration of this crawler's runs, in seconds.
TablesCreated (integer) --
The number of tables created by this crawler.
TablesUpdated (integer) --
The number of tables updated by this crawler.
TablesDeleted (integer) --
The number of tables deleted by this crawler.
Glue.Paginator.GetCrawlers¶paginator = client.get_paginator('get_crawlers')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_crawlers().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'Crawlers': [
{
'Name': 'string',
'Role': 'string',
'Targets': {
'S3Targets': [
{
'Path': 'string',
'Exclusions': [
'string',
],
'ConnectionName': 'string',
'SampleSize': 123,
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'JdbcTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'Exclusions': [
'string',
],
'EnableAdditionalMetadata': [
'COMMENTS'|'RAWTYPES',
]
},
],
'MongoDBTargets': [
{
'ConnectionName': 'string',
'Path': 'string',
'ScanAll': True|False
},
],
'DynamoDBTargets': [
{
'Path': 'string',
'scanAll': True|False,
'scanRate': 123.0
},
],
'CatalogTargets': [
{
'DatabaseName': 'string',
'Tables': [
'string',
],
'ConnectionName': 'string',
'EventQueueArn': 'string',
'DlqEventQueueArn': 'string'
},
],
'DeltaTargets': [
{
'DeltaTables': [
'string',
],
'ConnectionName': 'string',
'WriteManifest': True|False,
'CreateNativeDeltaTable': True|False
},
]
},
'DatabaseName': 'string',
'Description': 'string',
'Classifiers': [
'string',
],
'RecrawlPolicy': {
'RecrawlBehavior': 'CRAWL_EVERYTHING'|'CRAWL_NEW_FOLDERS_ONLY'|'CRAWL_EVENT_MODE'
},
'SchemaChangePolicy': {
'UpdateBehavior': 'LOG'|'UPDATE_IN_DATABASE',
'DeleteBehavior': 'LOG'|'DELETE_FROM_DATABASE'|'DEPRECATE_IN_DATABASE'
},
'LineageConfiguration': {
'CrawlerLineageSettings': 'ENABLE'|'DISABLE'
},
'State': 'READY'|'RUNNING'|'STOPPING',
'TablePrefix': 'string',
'Schedule': {
'ScheduleExpression': 'string',
'State': 'SCHEDULED'|'NOT_SCHEDULED'|'TRANSITIONING'
},
'CrawlElapsedTime': 123,
'CreationTime': datetime(2015, 1, 1),
'LastUpdated': datetime(2015, 1, 1),
'LastCrawl': {
'Status': 'SUCCEEDED'|'CANCELLED'|'FAILED',
'ErrorMessage': 'string',
'LogGroup': 'string',
'LogStream': 'string',
'MessagePrefix': 'string',
'StartTime': datetime(2015, 1, 1)
},
'Version': 123,
'Configuration': 'string',
'CrawlerSecurityConfiguration': 'string',
'LakeFormationConfiguration': {
'UseLakeFormationCredentials': True|False,
'AccountId': 'string'
}
},
],
}
Response Structure
A list of crawler metadata.
Specifies a crawler program that examines a data source and uses classifiers to try to determine its schema. If successful, the crawler records metadata concerning the data source in the Glue Data Catalog.
The name of the crawler.
The Amazon Resource Name (ARN) of an IAM role that's used to access customer resources, such as Amazon Simple Storage Service (Amazon S3) data.
A collection of targets to crawl.
Specifies Amazon Simple Storage Service (Amazon S3) targets.
Specifies a data store in Amazon Simple Storage Service (Amazon S3).
The path to the Amazon S3 target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
The name of a connection which allows a job or crawler to access data in Amazon S3 within an Amazon Virtual Private Cloud environment (Amazon VPC).
Sets the number of files in each leaf folder to be crawled when crawling sample files in a dataset. If not set, all the files are crawled. A valid value is an integer between 1 and 249.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies JDBC targets.
Specifies a JDBC data store to crawl.
The name of the connection to use to connect to the JDBC target.
The path of the JDBC target.
A list of glob patterns used to exclude from the crawl. For more information, see Catalog Tables with a Crawler.
Specify a value of RAWTYPES or COMMENTS to enable additional metadata in table responses. RAWTYPES provides the native-level datatype. COMMENTS provides comments associated with a column or table in the database.
If you do not need additional metadata, keep the field empty.
Specifies Amazon DocumentDB or MongoDB targets.
Specifies an Amazon DocumentDB or MongoDB data store to crawl.
The name of the connection to use to connect to the Amazon DocumentDB or MongoDB target.
The path of the Amazon DocumentDB or MongoDB target (database/collection).
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
Specifies Amazon DynamoDB targets.
Specifies an Amazon DynamoDB table to crawl.
The name of the DynamoDB table to crawl.
Indicates whether to scan all the records, or to sample rows from the table. Scanning all the records can take a long time when the table is not a high throughput table.
A value of true means to scan all records, while a value of false means to sample the records. If no value is specified, the value defaults to true .
The percentage of the configured read capacity units to use by the Glue crawler. Read capacity units is a term defined by DynamoDB, and is a numeric value that acts as rate limiter for the number of reads that can be performed on that table per second.
The valid values are null or a value between 0.1 to 1.5. A null value is used when user does not provide a value, and defaults to 0.5 of the configured Read Capacity Unit (for provisioned tables), or 0.25 of the max configured Read Capacity Unit (for tables using on-demand mode).
Specifies Glue Data Catalog targets.
Specifies an Glue Data Catalog target.
The name of the database to be synchronized.
A list of the tables to be synchronized.
The name of the connection for an Amazon S3-backed Data Catalog table to be a target of the crawl when using a Catalog connection type paired with a NETWORK Connection type.
A valid Amazon SQS ARN. For example, arn:aws:sqs:region:account:sqs .
A valid Amazon dead-letter SQS ARN. For example, arn:aws:sqs:region:account:deadLetterQueue .
Specifies Delta data store targets.
Specifies a Delta data store to crawl one or more Delta tables.
A list of the Amazon S3 paths to the Delta tables.
The name of the connection to use to connect to the Delta table target.
Specifies whether to write the manifest files to the Delta table path.
Specifies whether the crawler will create native tables, to allow integration with query engines that support querying of the Delta transaction log directly.
The name of the database in which the crawler's output is stored.
A description of the crawler.
A list of UTF-8 strings that specify the custom classifiers that are associated with the crawler.
A policy that specifies whether to crawl the entire dataset again, or to crawl only folders that were added since the last crawler run.
Specifies whether to crawl the entire dataset again or to crawl only folders that were added since the last crawler run.
A value of CRAWL_EVERYTHING specifies crawling the entire dataset again.
A value of CRAWL_NEW_FOLDERS_ONLY specifies crawling only folders that were added since the last crawler run.
A value of CRAWL_EVENT_MODE specifies crawling only the changes identified by Amazon S3 events.
The policy that specifies update and delete behaviors for the crawler.
The update behavior when the crawler finds a changed schema.
The deletion behavior when the crawler finds a deleted object.
A configuration that specifies whether data lineage is enabled for the crawler.
Specifies whether data lineage is enabled for the crawler. Valid values are:
Indicates whether the crawler is running, or whether a run is pending.
The prefix added to the names of tables that are created.
For scheduled crawlers, the schedule when the crawler runs.
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
The state of the schedule.
If the crawler is running, contains the total time elapsed since the last crawl began.
The time that the crawler was created.
The time that the crawler was last updated.
The status of the last crawl, and potentially error information if an error occurred.
Status of the last crawl.
If an error occurred, the error information about the last crawl.
The log group for the last crawl.
The log stream for the last crawl.
The prefix for a message about this crawl.
The time at which the crawl started.
The version of the crawler.
Crawler configuration information. This versioned JSON string allows users to specify aspects of a crawler's behavior. For more information, see Setting crawler configuration options.
The name of the SecurityConfiguration structure to be used by this crawler.
Specifies whether the crawler should use Lake Formation credentials for the crawler instead of the IAM role credentials.
Specifies whether to use Lake Formation credentials for the crawler instead of the IAM role credentials.
Required for cross account crawls. For same account crawls as the target data, this can be left as null.
Glue.Paginator.GetDatabases¶paginator = client.get_paginator('get_databases')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_databases().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
CatalogId='string',
ResourceShareType='FOREIGN'|'ALL',
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
Databases . If none is provided, the Amazon Web Services account ID is used by default.Allows you to specify that you want to list the databases shared with your account. The allowable values are FOREIGN or ALL .
FOREIGN , will list the databases shared with your account.ALL , will list the databases shared with your account, as well as the databases in yor local account.A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'DatabaseList': [
{
'Name': 'string',
'Description': 'string',
'LocationUri': 'string',
'Parameters': {
'string': 'string'
},
'CreateTime': datetime(2015, 1, 1),
'CreateTableDefaultPermissions': [
{
'Principal': {
'DataLakePrincipalIdentifier': 'string'
},
'Permissions': [
'ALL'|'SELECT'|'ALTER'|'DROP'|'DELETE'|'INSERT'|'CREATE_DATABASE'|'CREATE_TABLE'|'DATA_LOCATION_ACCESS',
]
},
],
'TargetDatabase': {
'CatalogId': 'string',
'DatabaseName': 'string'
},
'CatalogId': 'string'
},
],
}
Response Structure
(dict) --
DatabaseList (list) --
A list of Database objects from the specified catalog.
(dict) --
The Database object represents a logical grouping of tables that might reside in a Hive metastore or an RDBMS.
Name (string) --
The name of the database. For Hive compatibility, this is folded to lowercase when it is stored.
Description (string) --
A description of the database.
LocationUri (string) --
The location of the database (for example, an HDFS path).
Parameters (dict) --
These key-value pairs define parameters and properties of the database.
CreateTime (datetime) --
The time at which the metadata database was created in the catalog.
CreateTableDefaultPermissions (list) --
Creates a set of default permissions on the table for principals.
(dict) --
Permissions granted to a principal.
Principal (dict) --
The principal who is granted permissions.
DataLakePrincipalIdentifier (string) --
An identifier for the Lake Formation principal.
Permissions (list) --
The permissions that are granted to the principal.
TargetDatabase (dict) --
A DatabaseIdentifier structure that describes a target database for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the database resides.
DatabaseName (string) --
The name of the catalog database.
CatalogId (string) --
The ID of the Data Catalog in which the database resides.
Glue.Paginator.GetDevEndpoints¶paginator = client.get_paginator('get_dev_endpoints')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_dev_endpoints().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'DevEndpoints': [
{
'EndpointName': 'string',
'RoleArn': 'string',
'SecurityGroupIds': [
'string',
],
'SubnetId': 'string',
'YarnEndpointAddress': 'string',
'PrivateAddress': 'string',
'ZeppelinRemoteSparkInterpreterPort': 123,
'PublicAddress': 'string',
'Status': 'string',
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'GlueVersion': 'string',
'NumberOfWorkers': 123,
'NumberOfNodes': 123,
'AvailabilityZone': 'string',
'VpcId': 'string',
'ExtraPythonLibsS3Path': 'string',
'ExtraJarsS3Path': 'string',
'FailureReason': 'string',
'LastUpdateStatus': 'string',
'CreatedTimestamp': datetime(2015, 1, 1),
'LastModifiedTimestamp': datetime(2015, 1, 1),
'PublicKey': 'string',
'PublicKeys': [
'string',
],
'SecurityConfiguration': 'string',
'Arguments': {
'string': 'string'
}
},
],
}
Response Structure
A list of DevEndpoint definitions.
A development endpoint where a developer can remotely debug extract, transform, and load (ETL) scripts.
The name of the DevEndpoint .
The Amazon Resource Name (ARN) of the IAM role used in this DevEndpoint .
A list of security group identifiers used in this DevEndpoint .
The subnet ID for this DevEndpoint .
The YARN endpoint address used by this DevEndpoint .
A private IP address to access the DevEndpoint within a VPC if the DevEndpoint is created within one. The PrivateAddress field is present only when you create the DevEndpoint within your VPC.
The Apache Zeppelin port for the remote Apache Spark interpreter.
The public IP address used by this DevEndpoint . The PublicAddress field is present only when you create a non-virtual private cloud (VPC) DevEndpoint .
The current status of this DevEndpoint .
The type of predefined worker that is allocated to the development endpoint. Accepts a value of Standard, G.1X, or G.2X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.Known issue: when a development endpoint is created with the G.2X WorkerType configuration, the Spark drivers for the development endpoint will run on 4 vCPU, 16 GB of memory, and a 64 GB disk.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for running your ETL scripts on development endpoints.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Development endpoints that are created without specifying a Glue version default to Glue 0.9.
You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
The number of workers of a defined workerType that are allocated to the development endpoint.
The maximum number of workers you can define are 299 for G.1X , and 149 for G.2X .
The number of Glue Data Processing Units (DPUs) allocated to this DevEndpoint .
The Amazon Web Services Availability Zone where this DevEndpoint is located.
The ID of the virtual private cloud (VPC) used by this DevEndpoint .
The paths to one or more Python libraries in an Amazon S3 bucket that should be loaded in your DevEndpoint . Multiple values must be complete paths separated by a comma.
Note
You can only use pure Python libraries with a DevEndpoint . Libraries that rely on C extensions, such as the pandas Python data analysis library, are not currently supported.
The path to one or more Java .jar files in an S3 bucket that should be loaded in your DevEndpoint .
Note
You can only use pure Java/Scala libraries with a DevEndpoint .
The reason for a current failure in this DevEndpoint .
The status of the last update.
The point in time at which this DevEndpoint was created.
The point in time at which this DevEndpoint was last modified.
The public key to be used by this DevEndpoint for authentication. This attribute is provided for backward compatibility because the recommended attribute to use is public keys.
A list of public keys to be used by the DevEndpoints for authentication. Using this attribute is preferred over a single public key because the public keys allow you to have a different private key per client.
Note
If you previously created an endpoint with a public key, you must remove that key to be able to set a list of public keys. Call the UpdateDevEndpoint API operation with the public key content in the deletePublicKeys attribute, and the list of new keys in the addPublicKeys attribute.
The name of the SecurityConfiguration structure to be used with this DevEndpoint .
A map of arguments used to configure the DevEndpoint .
Valid arguments are:
"--enable-glue-datacatalog": ""You can specify a version of Python support for development endpoints by using the Arguments parameter in the CreateDevEndpoint or UpdateDevEndpoint APIs. If no arguments are provided, the version defaults to Python 2.
Glue.Paginator.GetJobRuns¶paginator = client.get_paginator('get_job_runs')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_job_runs().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
JobName='string',
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
The name of the job definition for which to retrieve all job runs.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'JobRuns': [
{
'Id': 'string',
'Attempt': 123,
'PreviousRunId': 'string',
'TriggerName': 'string',
'JobName': 'string',
'StartedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'CompletedOn': datetime(2015, 1, 1),
'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'Arguments': {
'string': 'string'
},
'ErrorMessage': 'string',
'PredecessorRuns': [
{
'JobName': 'string',
'RunId': 'string'
},
],
'AllocatedCapacity': 123,
'ExecutionTime': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'LogGroupName': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'DPUSeconds': 123.0,
'ExecutionClass': 'FLEX'|'STANDARD'
},
],
}
Response Structure
(dict) --
JobRuns (list) --
A list of job-run metadata objects.
(dict) --
Contains information about a job run.
Id (string) --
The ID of this job run.
Attempt (integer) --
The number of the attempt to run this job.
PreviousRunId (string) --
The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
TriggerName (string) --
The name of the trigger that started this job run.
JobName (string) --
The name of the job definition being used in this run.
StartedOn (datetime) --
The date and time at which this job run was started.
LastModifiedOn (datetime) --
The last time that this job run was modified.
CompletedOn (datetime) --
The date and time that this job run completed.
JobRunState (string) --
The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
Arguments (dict) --
The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
ErrorMessage (string) --
An error message associated with this job run.
PredecessorRuns (list) --
A list of predecessors to this job run.
(dict) --
A job run that was used in the predicate of a conditional trigger that triggered this job run.
JobName (string) --
The name of the job definition used by the predecessor job run.
RunId (string) --
The job-run ID of the predecessor job run.
AllocatedCapacity (integer) --
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
ExecutionTime (integer) --
The amount of time (in seconds) that the job run consumed resources.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
Streaming jobs do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
MaxCapacity (float) --
The number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job or an Apache Spark ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.WorkerType (string) --
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker.G.2X worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.NumberOfWorkers (integer) --
The number of workers of a defined workerType that are allocated when a job runs.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this job run.
LogGroupName (string) --
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/ , in which case the default encryption is NONE . If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/ ), then that security configuration is used to encrypt the log group.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
GlueVersion (string) --
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
DPUSeconds (float) --
This field populates only for Auto Scaling job runs, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X , 2 for G.2X , or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity . Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity .
ExecutionClass (string) --
Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
Glue.Paginator.GetJobs¶paginator = client.get_paginator('get_jobs')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_jobs().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'Jobs': [
{
'Name': 'string',
'Description': 'string',
'LogUri': 'string',
'Role': 'string',
'CreatedOn': datetime(2015, 1, 1),
'LastModifiedOn': datetime(2015, 1, 1),
'ExecutionProperty': {
'MaxConcurrentRuns': 123
},
'Command': {
'Name': 'string',
'ScriptLocation': 'string',
'PythonVersion': 'string'
},
'DefaultArguments': {
'string': 'string'
},
'NonOverridableArguments': {
'string': 'string'
},
'Connections': {
'Connections': [
'string',
]
},
'MaxRetries': 123,
'AllocatedCapacity': 123,
'Timeout': 123,
'MaxCapacity': 123.0,
'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X',
'NumberOfWorkers': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'GlueVersion': 'string',
'CodeGenConfigurationNodes': {
'string': {
'AthenaConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'ConnectionTable': 'string',
'SchemaName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'JDBCConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'FilterPredicate': 'string',
'PartitionColumn': 'string',
'LowerBound': 123,
'UpperBound': 123,
'NumPartitions': 123,
'JobBookmarkKeys': [
'string',
],
'JobBookmarkKeysSortOrder': 'string',
'DataTypeMapping': {
'string': 'DATE'|'STRING'|'TIMESTAMP'|'INT'|'FLOAT'|'LONG'|'BIGDECIMAL'|'BYTE'|'SHORT'|'DOUBLE'
}
},
'ConnectionTable': 'string',
'Query': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorSource': {
'Name': 'string',
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'RedshiftSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string'
},
'S3CatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'S3CsvSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'Separator': 'comma'|'ctrla'|'pipe'|'semicolon'|'tab',
'Escaper': 'string',
'QuoteChar': 'quote'|'quillemet'|'single_quote'|'disabled',
'Multiline': True|False,
'WithHeader': True|False,
'WriteHeader': True|False,
'SkipFirst': True|False,
'OptimizePerformance': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3JsonSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'gzip'|'bzip2',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'JsonPath': 'string',
'Multiline': True|False,
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'S3ParquetSource': {
'Name': 'string',
'Paths': [
'string',
],
'CompressionType': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'Exclusions': [
'string',
],
'GroupSize': 'string',
'GroupFiles': 'string',
'Recurse': True|False,
'MaxBand': 123,
'MaxFilesInBand': 123,
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123,
'EnableSamplePath': True|False,
'SamplePath': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'RelationalCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'DynamoDBCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'JDBCConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectionTable': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkConnectorTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'ConnectionName': 'string',
'ConnectorName': 'string',
'ConnectionType': 'string',
'AdditionalOptions': {
'string': 'string'
},
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'RedshiftTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string',
'RedshiftTmpDir': 'string',
'TmpDirIAMRole': 'string',
'UpsertRedshiftOptions': {
'TableLocation': 'string',
'ConnectionName': 'string',
'UpsertKeys': [
'string',
]
}
},
'S3CatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'S3GlueParquetTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'snappy'|'lzo'|'gzip'|'uncompressed'|'none',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'S3DirectTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Path': 'string',
'Compression': 'string',
'Format': 'json'|'csv'|'avro'|'orc'|'parquet',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG',
'Table': 'string',
'Database': 'string'
}
},
'ApplyMapping': {
'Name': 'string',
'Inputs': [
'string',
],
'Mapping': [
{
'ToKey': 'string',
'FromPath': [
'string',
],
'FromType': 'string',
'ToType': 'string',
'Dropped': True|False,
'Children': {'... recursive ...'}
},
]
},
'SelectFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'DropFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'RenameField': {
'Name': 'string',
'Inputs': [
'string',
],
'SourcePath': [
'string',
],
'TargetPath': [
'string',
]
},
'Spigot': {
'Name': 'string',
'Inputs': [
'string',
],
'Path': 'string',
'Topk': 123,
'Prob': 123.0
},
'Join': {
'Name': 'string',
'Inputs': [
'string',
],
'JoinType': 'equijoin'|'left'|'right'|'outer'|'leftsemi'|'leftanti',
'Columns': [
{
'From': 'string',
'Keys': [
[
'string',
],
]
},
]
},
'SplitFields': {
'Name': 'string',
'Inputs': [
'string',
],
'Paths': [
[
'string',
],
]
},
'SelectFromCollection': {
'Name': 'string',
'Inputs': [
'string',
],
'Index': 123
},
'FillMissingValues': {
'Name': 'string',
'Inputs': [
'string',
],
'ImputedPath': 'string',
'FilledPath': 'string'
},
'Filter': {
'Name': 'string',
'Inputs': [
'string',
],
'LogicalOperator': 'AND'|'OR',
'Filters': [
{
'Operation': 'EQ'|'LT'|'GT'|'LTE'|'GTE'|'REGEX'|'ISNULL',
'Negated': True|False,
'Values': [
{
'Type': 'COLUMNEXTRACTED'|'CONSTANT',
'Value': [
'string',
]
},
]
},
]
},
'CustomCode': {
'Name': 'string',
'Inputs': [
'string',
],
'Code': 'string',
'ClassName': 'string',
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'SparkSQL': {
'Name': 'string',
'Inputs': [
'string',
],
'SqlQuery': 'string',
'SqlAliases': [
{
'From': 'string',
'Alias': 'string'
},
],
'OutputSchemas': [
{
'Columns': [
{
'Name': 'string',
'Type': 'string'
},
]
},
]
},
'DirectKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DirectKafkaSource': {
'Name': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'WindowSize': 123,
'DetectSchema': True|False,
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKinesisSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'EndpointUrl': 'string',
'StreamName': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingPosition': 'latest'|'trim_horizon'|'earliest',
'MaxFetchTimeInMs': 123,
'MaxFetchRecordsPerShard': 123,
'MaxRecordPerRead': 123,
'AddIdleTimeBetweenReads': True|False,
'IdleTimeBetweenReadsInMs': 123,
'DescribeShardInterval': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxRetryIntervalMs': 123,
'AvoidEmptyBatches': True|False,
'StreamArn': 'string',
'RoleArn': 'string',
'RoleSessionName': 'string'
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'CatalogKafkaSource': {
'Name': 'string',
'WindowSize': 123,
'DetectSchema': True|False,
'Table': 'string',
'Database': 'string',
'StreamingOptions': {
'BootstrapServers': 'string',
'SecurityProtocol': 'string',
'ConnectionName': 'string',
'TopicName': 'string',
'Assign': 'string',
'SubscribePattern': 'string',
'Classification': 'string',
'Delimiter': 'string',
'StartingOffsets': 'string',
'EndingOffsets': 'string',
'PollTimeoutMs': 123,
'NumRetries': 123,
'RetryIntervalMs': 123,
'MaxOffsetsPerTrigger': 123,
'MinPartitions': 123
},
'DataPreviewOptions': {
'PollingTime': 123,
'RecordPollingLimit': 123
}
},
'DropNullFields': {
'Name': 'string',
'Inputs': [
'string',
],
'NullCheckBoxList': {
'IsEmpty': True|False,
'IsNullString': True|False,
'IsNegOne': True|False
},
'NullTextList': [
{
'Value': 'string',
'Datatype': {
'Id': 'string',
'Label': 'string'
}
},
]
},
'Merge': {
'Name': 'string',
'Inputs': [
'string',
],
'Source': 'string',
'PrimaryKeys': [
[
'string',
],
]
},
'Union': {
'Name': 'string',
'Inputs': [
'string',
],
'UnionType': 'ALL'|'DISTINCT'
},
'PIIDetection': {
'Name': 'string',
'Inputs': [
'string',
],
'PiiType': 'RowAudit'|'RowMasking'|'ColumnAudit'|'ColumnMasking',
'EntityTypesToDetect': [
'string',
],
'OutputColumnName': 'string',
'SampleFraction': 123.0,
'ThresholdFraction': 123.0,
'MaskValue': 'string'
},
'Aggregate': {
'Name': 'string',
'Inputs': [
'string',
],
'Groups': [
[
'string',
],
],
'Aggs': [
{
'Column': [
'string',
],
'AggFunc': 'avg'|'countDistinct'|'count'|'first'|'last'|'kurtosis'|'max'|'min'|'skewness'|'stddev_samp'|'stddev_pop'|'sum'|'sumDistinct'|'var_samp'|'var_pop'
},
]
},
'DropDuplicates': {
'Name': 'string',
'Inputs': [
'string',
],
'Columns': [
[
'string',
],
]
},
'GovernedCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'PartitionKeys': [
[
'string',
],
],
'Table': 'string',
'Database': 'string',
'SchemaChangePolicy': {
'EnableUpdateCatalog': True|False,
'UpdateBehavior': 'UPDATE_IN_DATABASE'|'LOG'
}
},
'GovernedCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string',
'PartitionPredicate': 'string',
'AdditionalOptions': {
'BoundedSize': 123,
'BoundedFiles': 123
}
},
'MicrosoftSQLServerCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogSource': {
'Name': 'string',
'Database': 'string',
'Table': 'string'
},
'MicrosoftSQLServerCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'MySQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'OracleSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'PostgreSQLCatalogTarget': {
'Name': 'string',
'Inputs': [
'string',
],
'Database': 'string',
'Table': 'string'
},
'DynamicTransform': {
'Name': 'string',
'TransformName': 'string',
'Inputs': [
'string',
],
'Parameters': [
{
'Name': 'string',
'Type': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'ValidationRule': 'string',
'ValidationMessage': 'string',
'Value': [
'string',
],
'ListType': 'str'|'int'|'float'|'complex'|'bool'|'list'|'null',
'IsOptional': True|False
},
],
'FunctionName': 'string',
'Path': 'string',
'Version': 'string'
},
'EvaluateDataQuality': {
'Name': 'string',
'Inputs': [
'string',
],
'Ruleset': 'string',
'Output': 'PrimaryInput'|'EvaluationResults',
'PublishingOptions': {
'EvaluationContext': 'string',
'ResultsS3Prefix': 'string',
'CloudWatchMetricsEnabled': True|False,
'ResultsPublishingEnabled': True|False
},
'StopJobOnFailureOptions': {
'StopJobOnFailureTiming': 'Immediate'|'AfterDataLoad'
}
}
}
},
'ExecutionClass': 'FLEX'|'STANDARD',
'SourceControlDetails': {
'Provider': 'GITHUB'|'AWS_CODE_COMMIT',
'Repository': 'string',
'Owner': 'string',
'Branch': 'string',
'Folder': 'string',
'LastCommitId': 'string',
'AuthStrategy': 'PERSONAL_ACCESS_TOKEN'|'AWS_SECRETS_MANAGER',
'AuthToken': 'string'
}
},
],
}
Response Structure
A list of job definitions.
Specifies a job definition.
The name you assign to this job definition.
A description of the job.
This field is reserved for future use.
The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
The time and date that this job definition was created.
The last point in time when this job definition was modified.
An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
The maximum number of concurrent runs allowed for the job. The default is 1. An error is returned when this threshold is reached. The maximum value you can specify is controlled by a service limit.
The JobCommand that runs this job.
The name of the job command. For an Apache Spark ETL job, this must be glueetl . For a Python shell job, it must be pythonshell . For an Apache Spark streaming ETL job, this must be gluestreaming .
Specifies the Amazon Simple Storage Service (Amazon S3) path to a script that runs a job.
The Python version being used to run a Python shell job. Allowed values are 2 or 3.
The default arguments for this job, specified as name-value pairs.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Non-overridable arguments for this job, specified as name-value pairs.
The connections used for this job.
A list of connections used by the job.
The maximum number of times to retry this job after a JobRun fails.
This field is deprecated. Use MaxCapacity instead.
The number of Glue data processing units (DPUs) allocated to runs of this job. You can allocate a minimum of 2 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
Do not set Max Capacity if using WorkerType and NumberOfWorkers .
The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
JobCommand.Name ="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.JobCommand.Name ="glueetl") or Apache Spark streaming ETL job ( JobCommand.Name ="gluestreaming"), you can allocate a minimum of 2 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.For Glue version 2.0 jobs, you cannot instead specify a Maximum capacity . Instead, you should specify a Worker type and the Number of workers .
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X.
Standard worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2 executors per worker.G.1X worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.2X worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.G.025X worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.The number of workers of a defined workerType that are allocated when a job runs.
The name of the SecurityConfiguration structure to be used with this job.
Specifies configuration properties of a job notification.
After a job run starts, the number of minutes to wait before sending a job run delay notification.
Glue version determines the versions of Apache Spark and Python that Glue supports. The Python version indicates the version supported for jobs of type Spark.
For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
Jobs that are created without specifying a Glue version default to Glue 0.9.
The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
CodeGenConfigurationNodeenumerates all valid Node types. One and only one of its member variables can be populated.
Specifies a connector to an Amazon Athena data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.athena or custom.athena, designating a connection to an Amazon Athena data store.
The name of the table in the data source.
The name of the Cloudwatch log group to read from. For example, /aws-glue/jobs/output .
Specifies the data schema for the custom Athena source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to a JDBC data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data store.
Additional connection options for the connector.
Extra condition clause to filter data from source. For example:
BillingCity='Mountain View'
When using a query instead of a table name, you should validate that the query works with the specified filterPredicate .
The name of an integer column that is used for partitioning. This option works only when it's included with lowerBound , upperBound , and numPartitions . This option works the same way as in the Spark SQL JDBC reader.
The minimum value of partitionColumn that is used to decide partition stride.
The maximum value of partitionColumn that is used to decide partition stride.
The number of partitions. This value, along with lowerBound (inclusive) and upperBound (exclusive), form partition strides for generated WHERE clause expressions that are used to split the partitionColumn .
The name of the job bookmark keys on which to sort.
Specifies an ascending or descending sort order.
Custom data type mapping that builds a mapping from a JDBC data type to an Glue data type. For example, the option "dataTypeMapping":{"FLOAT":"STRING"} maps data fields of JDBC type FLOAT into the Java String type by calling the ResultSet.getString() method of the driver, and uses it to build the Glue record. The ResultSet object is implemented by each driver, so the behavior is specific to the driver you use. Refer to the documentation for your JDBC driver to understand how the driver performs the conversions.
The name of the table in the data source.
The table or SQL query to get the data from. You can specify either ConnectionTable or query , but not both.
Specifies the data schema for the custom JDBC source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a connector to an Apache Spark data source.
The name of the data source.
The name of the connection that is associated with the connector.
The name of a connector that assists with accessing the data store in Glue Studio.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies data schema for the custom spark source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a data store in the Glue Data Catalog.
The name of the data store.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Amazon Redshift data store.
The name of the Amazon Redshift data store.
The database to read from.
The database table to read from.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
Specifies an Amazon S3 data store in the Glue Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a command-separated value (CSV) data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the delimiter character. The default is a comma: ",", but any other character can be specified.
Specifies a character to use for escaping. This option is used only when reading CSV files. The default value is none . If enabled, the character which immediately follows is used as-is, except for a small set of well-known escapes ( \n , \r , \t , and \0 ).
Specifies the character to use for quoting. The default is a double quote: '"' . Set this to -1 to turn off quoting entirely.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
A Boolean value that specifies whether to treat the first line as a header. The default value is False .
A Boolean value that specifies whether to write the header to output. The default value is True .
A Boolean value that specifies whether to skip the first data line. The default value is False .
A Boolean value that specifies whether to use the advanced SIMD CSV reader along with Apache Arrow based columnar memory formats. Only available in Glue version 3.0.
Specifies the data schema for the S3 CSV source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a JSON data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
A JsonPath string defining the JSON data.
A Boolean value that specifies whether a single record can span multiple lines. This can occur when a field contains a quoted new-line character. You must set this option to True if any record spans multiple lines. The default value is False , which allows for more aggressive file-splitting during parsing.
Specifies the data schema for the S3 JSON source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies an Apache Parquet data store stored in Amazon S3.
The name of the data store.
A list of the Amazon S3 paths to read from.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A string containing a JSON list of Unix-style glob patterns to exclude. For example, "["**.pdf"]" excludes all PDF files.
The target group size in bytes. The default is computed based on the input data size and the size of your cluster. When there are fewer than 50,000 input files, "groupFiles" must be set to "inPartition" for this to take effect.
Grouping files is turned on by default when the input contains more than 50,000 files. To turn on grouping with fewer than 50,000 files, set this parameter to "inPartition". To disable grouping when there are more than 50,000 files, set this parameter to "none" .
If set to true, recursively reads files in all subdirectories under the specified paths.
This option controls the duration in milliseconds after which the s3 listing is likely to be consistent. Files with modification timestamps falling within the last maxBand milliseconds are tracked specially when using JobBookmarks to account for Amazon S3 eventual consistency. Most users don't need to set this option. The default is 900000 milliseconds, or 15 minutes.
This option specifies the maximum number of files to save from the last maxBand seconds. If this number is exceeded, extra files are skipped and only processed in the next job run.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Sets option to enable a sample path.
If enabled, specifies the sample path.
Specifies the data schema for the S3 Parquet source.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a Relational database data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a DynamoDB data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
The name of the connection that is associated with the connector.
The name of the table in the data target.
The name of a connector that will be used.
The type of connection, such as marketplace.jdbc or custom.jdbc, designating a connection to a JDBC data target.
Additional connection options for the connector.
Specifies the data schema for the JDBC target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses an Apache Spark connector.
The name of the data target.
The nodes that are inputs to the data target.
The name of a connection for an Apache Spark connector.
The name of an Apache Spark connector.
The type of connection, such as marketplace.spark or custom.spark, designating a connection to an Apache Spark data store.
Additional connection options for the connector.
Specifies the data schema for the custom spark target.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a target that uses a Glue Data Catalog table.
The name of your data target.
The nodes that are inputs to the data target.
The database that contains the table you want to use as the target. This database must already exist in the Data Catalog.
The table that defines the schema of your output data. This table must already exist in the Data Catalog.
Specifies a target that uses Amazon Redshift.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
The Amazon S3 path where temporary data can be staged when copying out of the database.
The IAM role with permissions.
The set of options to configure an upsert operation when writing to a Redshift target.
The physical location of the Redshift table.
The name of the connection to use to write to Redshift.
The keys used to determine whether to perform an update or insert.
Specifies a data target that writes to Amazon S3 using the Glue Data Catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data target that writes to Amazon S3 in Apache Parquet columnar storage.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a data target that writes to Amazon S3.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
A single Amazon S3 path to write to.
Specifies how the data is compressed. This is generally not necessary if the data has a standard file extension. Possible values are "gzip" and "bzip" ).
Specifies the data output format for the target.
A policy that specifies update behavior for the crawler.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies the table in the database that the schema change policy applies to.
Specifies the database that the schema change policy applies to.
Specifies a transform that maps data property keys in the data source to data property keys in the data target. You can rename keys, modify the data types for keys, and choose which keys to drop from the dataset.
The name of the transform node.
The data inputs identified by their node names.
Specifies the mapping of data property keys in the data source to data property keys in the data target.
Specifies the mapping of data property keys.
After the apply mapping, what the name of the column should be. Can be the same as FromPath .
The table or column to be modified.
The type of the data to be modified.
The data type that the data is to be modified to.
If true, then the column is removed.
Only applicable to nested data structures. If you want to change the parent structure, but also one of its children, you can fill out this data strucutre. It is also Mapping , but its FromPath will be the parent's FromPath plus the FromPath from this structure.
For the children part, suppose you have the structure:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
You can specify a Mapping that looks like:
{ "FromPath": "OuterStructure", "ToKey": "OuterStructure", "ToType": "Struct", "Dropped": false, "Chidlren": [{ "FromPath": "inner", "ToKey": "inner", "ToType": "Double", "Dropped": false, }] }
Specifies a transform that chooses the data property keys that you want to keep.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses the data property keys that you want to drop.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that renames a single data property key.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the source data.
A JSON path to a variable in the data structure for the target data.
Specifies a transform that writes samples of the data to an Amazon S3 bucket.
The name of the transform node.
The data inputs identified by their node names.
A path in Amazon S3 where the transform will write a subset of records from the dataset to a JSON file in an Amazon S3 bucket.
Specifies a number of records to write starting from the beginning of the dataset.
The probability (a decimal value with a maximum value of 1) of picking any given record. A value of 1 indicates that each row read from the dataset should be included in the sample output.
Specifies a transform that joins two datasets into one dataset using a comparison phrase on the specified data property keys. You can use inner, outer, left, right, left semi, and left anti joins.
The name of the transform node.
The data inputs identified by their node names.
Specifies the type of join to be performed on the datasets.
A list of the two columns to be joined.
Specifies a column to be joined.
The column to be joined.
The key of the column to be joined.
Specifies a transform that splits data property keys into two DynamicFrames . The output is a collection of DynamicFrames : one with selected data property keys, and one with the remaining data property keys.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure.
Specifies a transform that chooses one DynamicFrame from a collection of DynamicFrames . The output is the selected DynamicFrame
The name of the transform node.
The data inputs identified by their node names.
The index for the DynamicFrame to be selected.
Specifies a transform that locates records in the dataset that have missing values and adds a new field with a value determined by imputation. The input data set is used to train the machine learning model that determines what the missing value should be.
The name of the transform node.
The data inputs identified by their node names.
A JSON path to a variable in the data structure for the dataset that is imputed.
A JSON path to a variable in the data structure for the dataset that is filled.
Specifies a transform that splits a dataset into two, based on a filter condition.
The name of the transform node.
The data inputs identified by their node names.
The operator used to filter rows by comparing the key value to a specified value.
Specifies a filter expression.
Specifies a filter expression.
The type of operation to perform in the expression.
Whether the expression is to be negated.
A list of filter values.
Represents a single entry in the list of values for a FilterExpression .
The type of filter value.
The value to be associated.
Specifies a transform that uses custom code you provide to perform the data transformation. The output is a collection of DynamicFrames.
The name of the transform node.
The data inputs identified by their node names.
The custom code that is used to perform the data transformation.
The name defined for the custom code node class.
Specifies the data schema for the custom code transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a transform where you enter a SQL query using Spark SQL syntax to transform the data. The output is a single DynamicFrame .
The name of the transform node.
The data inputs identified by their node names. You can associate a table name with each input node to use in the SQL query. The name you choose must meet the Spark SQL naming restrictions.
A SQL query that must use Spark SQL syntax and return a single data set.
A list of aliases. An alias allows you to specify what name to use in the SQL for a given input. For example, you have a datasource named "MyDataSource". If you specify From as MyDataSource, and Alias as SqlName, then in your SQL you can do:
select * from SqlName
and that gets data from MyDataSource.
Represents a single entry in the list of values for SqlAliases .
A table, or a column in a table.
A temporary name given to a table, or a column in a table.
Specifies the data schema for the SparkSQL transform.
Specifies a user-defined schema when a schema cannot be determined by Glue.
Specifies the column definitions that make up a Glue schema.
Specifies a single column in a Glue schema definition.
The name of the column in the Glue Studio schema.
The hive type for this column in the Glue Studio schema.
Specifies a direct Amazon Kinesis data source.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store.
The name of the data store.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a Kinesis data source in the Glue Data Catalog.
The name of the data source.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Additional options for the Kinesis streaming data source.
The URL of the Kinesis endpoint.
The name of the Kinesis data stream.
An optional classification.
Specifies the delimiter character.
The starting position in the Kinesis data stream to read data from. The possible values are "latest" , "trim_horizon" , or "earliest" . The default value is "latest" .
The maximum time spent in the job executor to fetch a record from the Kinesis data stream per shard, specified in milliseconds (ms). The default value is 1000 .
The maximum number of records to fetch per shard in the Kinesis data stream. The default value is 100000 .
The maximum number of records to fetch from the Kinesis data stream in each getRecords operation. The default value is 10000 .
Adds a time delay between two consecutive getRecords operations. The default value is "False" . This option is only configurable for Glue version 2.0 and above.
The minimum time delay between two consecutive getRecords operations, specified in ms. The default value is 1000 . This option is only configurable for Glue version 2.0 and above.
The minimum time interval between two ListShards API calls for your script to consider resharding. The default value is 1s .
The maximum number of retries for Kinesis Data Streams API requests. The default value is 3 .
The cool-off time period (specified in ms) before retrying the Kinesis Data Streams API call. The default value is 1000 .
The maximum cool-off time period (specified in ms) between two retries of a Kinesis Data Streams API call. The default value is 10000 .
Avoids creating an empty microbatch job by checking for unread data in the Kinesis data stream before the batch is started. The default value is "False" .
The Amazon Resource Name (ARN) of the Kinesis data stream.
The Amazon Resource Name (ARN) of the role to assume using AWS Security Token Service (AWS STS). This role must have permissions for describe or read record operations for the Kinesis data stream. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSSessionName" .
An identifier for the session assuming the role using AWS STS. You must use this parameter when accessing a data stream in a different account. Used in conjunction with "awsSTSRoleARN" .
Additional options for data preview.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies an Apache Kafka data store in the Data Catalog.
The name of the data store.
The amount of time to spend processing each micro batch.
Whether to automatically determine the schema from the incoming data.
The name of the table in the database to read from.
The name of the database to read from.
Specifies the streaming options.
A list of bootstrap server URLs, for example, as b-1.vpc-test-2.o4q88o.c6.kafka.us-east-1.amazonaws.com:9094 . This option must be specified in the API call or defined in the table metadata in the Data Catalog.
The protocol used to communicate with brokers. The possible values are "SSL" or "PLAINTEXT" .
The name of the connection.
The topic name as specified in Apache Kafka. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
The specific TopicPartitions to consume. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
A Java regex string that identifies the topic list to subscribe to. You must specify at least one of "topicName" , "assign" or "subscribePattern" .
An optional classification.
Specifies the delimiter character.
The starting position in the Kafka topic to read data from. The possible values are "earliest" or "latest" . The default value is "latest" .
The end point when a batch query is ended. Possible values are either "latest" or a JSON string that specifies an ending offset for each TopicPartition .
The timeout in milliseconds to poll data from Kafka in Spark job executors. The default value is 512 .
The number of times to retry before failing to fetch Kafka offsets. The default value is 3 .
The time in milliseconds to wait before retrying to fetch Kafka offsets. The default value is 10 .
The rate limit on the maximum number of offsets that are processed per trigger interval. The specified total number of offsets is proportionally split across topicPartitions of different volumes. The default value is null, which means that the consumer reads all offsets until the known latest offset.
The desired minimum number of partitions to read from Kafka. The default value is null, which means that the number of spark partitions is equal to the number of Kafka partitions.
Specifies options related to data preview for viewing a sample of your data.
The polling time in milliseconds.
The limit to the number of records polled.
Specifies a transform that removes columns from the dataset if all values in the column are 'null'. By default, Glue Studio will recognize null objects, but some values such as empty strings, strings that are "null", -1 integers or other placeholders such as zeros, are not automatically recognized as nulls.
The name of the transform node.
The data inputs identified by their node names.
A structure that represents whether certain values are recognized as null values for removal.
Specifies that an empty string is considered as a null value.
Specifies that a value spelling out the word 'null' is considered as a null value.
Specifies that an integer value of -1 is considered as a null value.
A structure that specifies a list of NullValueField structures that represent a custom null value such as zero or other value being used as a null placeholder unique to the dataset.
The DropNullFields transform removes custom null values only if both the value of the null placeholder and the datatype match the data.
Represents a custom null value such as a zeros or other value being used as a null placeholder unique to the dataset.
The value of the null placeholder.
The datatype of the value.
The datatype of the value.
A label assigned to the datatype.
Specifies a transform that merges a DynamicFrame with a staging DynamicFrame based on the specified primary keys to identify records. Duplicate records (records with the same primary keys) are not de-duplicated.
The name of the transform node.
The data inputs identified by their node names.
The source DynamicFrame that will be merged with a staging DynamicFrame .
The list of primary key fields to match records from the source and staging dynamic frames.
Specifies a transform that combines the rows from two or more datasets into a single result.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of Union transform.
Specify ALL to join all rows from data sources to the resulting DynamicFrame. The resulting union does not remove duplicate rows.
Specify DISTINCT to remove duplicate rows in the resulting DynamicFrame.
Specifies a transform that identifies, removes or masks PII data.
The name of the transform node.
The node ID inputs to the transform.
Indicates the type of PIIDetection transform.
Indicates the types of entities the PIIDetection transform will identify as PII data.
PII type entities include: PERSON_NAME, DATE, USA_SNN, EMAIL, USA_ITIN, USA_PASSPORT_NUMBER, PHONE_NUMBER, BANK_ACCOUNT, IP_ADDRESS, MAC_ADDRESS, USA_CPT_CODE, USA_HCPCS_CODE, USA_NATIONAL_DRUG_CODE, USA_MEDICARE_BENEFICIARY_IDENTIFIER, USA_HEALTH_INSURANCE_CLAIM_NUMBER,CREDIT_CARD,USA_NATIONAL_PROVIDER_IDENTIFIER,USA_DEA_NUMBER,USA_DRIVING_LICENSE
Indicates the output column name that will contain any entity type detected in that row.
Indicates the fraction of the data to sample when scanning for PII entities.
Indicates the fraction of the data that must be met in order for a column to be identified as PII data.
Indicates the value that will replace the detected entity.
Specifies a transform that groups rows by chosen fields and computes the aggregated value by specified function.
The name of the transform node.
Specifies the fields and rows to use as inputs for the aggregate transform.
Specifies the fields to group by.
Specifies the aggregate functions to be performed on specified fields.
Specifies the set of parameters needed to perform aggregation in the aggregate transform.
Specifies the column on the data set on which the aggregation function will be applied.
Specifies the aggregation function to apply.
Possible aggregation functions include: avg countDistinct, count, first, last, kurtosis, max, min, skewness, stddev_samp, stddev_pop, sum, sumDistinct, var_samp, var_pop
Specifies a transform that removes rows of repeating data from a data set.
The name of the transform node.
The data inputs identified by their node names.
The name of the columns to be merged or removed if repeating.
Specifies a data target that writes to a goverened catalog.
The name of the data target.
The nodes that are inputs to the data target.
Specifies native partitioning using a sequence of keys.
The name of the table in the database to write to.
The name of the database to write to.
A policy that specifies update behavior for the governed catalog.
Whether to use the specified update behavior when the crawler finds a changed schema.
The update behavior when the crawler finds a changed schema.
Specifies a data source in a goverened Data Catalog.
The name of the data store.
The database to read from.
The database table to read from.
Partitions satisfying this predicate are deleted. Files within the retention period in these partitions are not deleted. Set to "" – empty by default.
Specifies additional connection options.
Sets the upper limit for the target size of the dataset in bytes that will be processed.
Sets the upper limit for the target number of files that will be processed.
Specifies a Microsoft SQL server data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a MySQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies an Oracle data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a PostgresSQL data source in the Glue Data Catalog.
The name of the data source.
The name of the database to read from.
The name of the table in the database to read from.
Specifies a target that uses Microsoft SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses MySQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Oracle SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a target that uses Postgres SQL.
The name of the data target.
The nodes that are inputs to the data target.
The name of the database to write to.
The name of the table in the database to write to.
Specifies a custom visual transform created by a user.
Specifies the name of the dynamic transform.
Specifies the name of the dynamic transform as it appears in the Glue Studio visual editor.
Specifies the inputs for the dynamic transform that are required.
Specifies the parameters of the dynamic transform.
Specifies the parameters in the config file of the dynamic transform.
Specifies the name of the parameter in the config file of the dynamic transform.
Specifies the parameter type in the config file of the dynamic transform.
Specifies the validation rule in the config file of the dynamic transform.
Specifies the validation message in the config file of the dynamic transform.
Specifies the value of the parameter in the config file of the dynamic transform.
Specifies the list type of the parameter in the config file of the dynamic transform.
Specifies whether the parameter is optional or not in the config file of the dynamic transform.
Specifies the name of the function of the dynamic transform.
Specifies the path of the dynamic transform source and config files.
This field is not used and will be deprecated in future release.
Specifies your data quality evaluation criteria.
The name of the data quality evaluation.
The inputs of your data quality evaluation.
The ruleset for your data quality evaluation.
The output of your data quality evaluation.
Options to configure how your results are published.
The context of the evaluation.
The Amazon S3 prefix prepended to the results.
Enable metrics for your data quality results.
Enable publishing for your data quality results.
Options to configure how your job will stop if your data quality evaluation fails.
When to stop job if your data quality evaluation fails. Options are Immediate or AfterDataLoad.
Indicates whether the job is run with a standard or flexible execution class. The standard execution class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX . The flexible execution class is available for Spark jobs.
The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
The provider for the remote repository.
The name of the remote repository that contains the job artifacts.
The owner of the remote repository that contains the job artifacts.
An optional branch in the remote repository.
An optional folder in the remote repository.
The last commit ID for a commit in the remote repository.
The type of authentication, which can be an authentication token stored in Amazon Web Services Secrets Manager, or a personal access token.
The value of an authorization token.
Glue.Paginator.GetPartitionIndexes¶paginator = client.get_paginator('get_partition_indexes')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_partition_indexes().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
CatalogId='string',
DatabaseName='string',
TableName='string',
PaginationConfig={
'MaxItems': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
Specifies the name of a database from which you want to retrieve partition indexes.
[REQUIRED]
Specifies the name of a table for which you want to retrieve the partition indexes.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'PartitionIndexDescriptorList': [
{
'IndexName': 'string',
'Keys': [
{
'Name': 'string',
'Type': 'string'
},
],
'IndexStatus': 'CREATING'|'ACTIVE'|'DELETING'|'FAILED',
'BackfillErrors': [
{
'Code': 'ENCRYPTED_PARTITION_ERROR'|'INTERNAL_ERROR'|'INVALID_PARTITION_TYPE_DATA_ERROR'|'MISSING_PARTITION_VALUE_ERROR'|'UNSUPPORTED_PARTITION_CHARACTER_ERROR',
'Partitions': [
{
'Values': [
'string',
]
},
]
},
]
},
],
}
Response Structure
(dict) --
PartitionIndexDescriptorList (list) --
A list of index descriptors.
(dict) --
A descriptor for a partition index in a table.
IndexName (string) --
The name of the partition index.
Keys (list) --
A list of one or more keys, as KeySchemaElement structures, for the partition index.
(dict) --
A partition key pair consisting of a name and a type.
Name (string) --
The name of a partition key.
Type (string) --
The type of a partition key.
IndexStatus (string) --
The status of the partition index.
The possible statuses are:
BackfillErrors (list) --
A list of errors that can occur when registering partition indexes for an existing table.
(dict) --
A list of errors that can occur when registering partition indexes for an existing table.
These errors give the details about why an index registration failed and provide a limited number of partitions in the response, so that you can fix the partitions at fault and try registering the index again. The most common set of errors that can occur are categorized as follows:
Code (string) --
The error code for an error that occurred when registering partition indexes for an existing table.
Partitions (list) --
A list of a limited number of partitions in the response.
(dict) --
Contains a list of values defining partitions.
Values (list) --
The list of values.
Glue.Paginator.GetPartitions¶paginator = client.get_paginator('get_partitions')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_partitions().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
CatalogId='string',
DatabaseName='string',
TableName='string',
Expression='string',
Segment={
'SegmentNumber': 123,
'TotalSegments': 123
},
ExcludeColumnSchema=True|False,
TransactionId='string',
QueryAsOfTime=datetime(2015, 1, 1),
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
The name of the catalog database where the partitions reside.
[REQUIRED]
The name of the partitions' table.
An expression that filters the partitions to be returned.
The expression uses SQL syntax similar to the SQL WHERE filter clause. The SQL statement parser JSQLParser parses the expression.
Operators : The following are the operators that you can use in theExpressionAPI call:=
Checks whether the values of the two operands are equal; if yes, then the condition becomes true.
Example: Assume 'variable a' holds 10 and 'variable b' holds 20.
(a = b) is not true.
< >
Checks whether the values of two operands are equal; if the values are not equal, then the condition becomes true.
Example: (a < > b) is true.
>
Checks whether the value of the left operand is greater than the value of the right operand; if yes, then the condition becomes true.
Example: (a > b) is not true.
<
Checks whether the value of the left operand is less than the value of the right operand; if yes, then the condition becomes true.
Example: (a < b) is true.
>=
Checks whether the value of the left operand is greater than or equal to the value of the right operand; if yes, then the condition becomes true.
Example: (a >= b) is not true.
<=
Checks whether the value of the left operand is less than or equal to the value of the right operand; if yes, then the condition becomes true.
Example: (a <= b) is true.
AND, OR, IN, BETWEEN, LIKE, NOT, IS NULL
Logical operators.
Supported Partition Key Types : The following are the supported partition keys.
stringdatetimestampintbigintlongtinyintsmallintdecimalIf an type is encountered that is not valid, an exception is thrown.
The following list shows the valid operators on each type. When you define a crawler, the partitionKey type is created as a STRING , to be compatible with the catalog partitions.
Sample API Call :
The segment of the table's partitions to scan in this request.
The zero-based index number of the segment. For example, if the total number of segments is 4, SegmentNumber values range from 0 through 3.
The total number of segments.
TransactionId .A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'Partitions': [
{
'Values': [
'string',
],
'DatabaseName': 'string',
'TableName': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'Parameters': {
'string': 'string'
},
'LastAnalyzedTime': datetime(2015, 1, 1),
'CatalogId': 'string'
},
],
}
Response Structure
(dict) --
Partitions (list) --
A list of requested partitions.
(dict) --
Represents a slice of table data.
Values (list) --
The values of the partition.
DatabaseName (string) --
The name of the catalog database in which to create the partition.
TableName (string) --
The name of the database table in which to create the partition.
CreationTime (datetime) --
The time at which the partition was created.
LastAccessTime (datetime) --
The last time at which the partition was accessed.
StorageDescriptor (dict) --
Provides information about the physical location where the partition is stored.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
Parameters (dict) --
These key-value pairs define partition parameters.
LastAnalyzedTime (datetime) --
The last time at which column statistics were computed for this partition.
CatalogId (string) --
The ID of the Data Catalog in which the partition resides.
Glue.Paginator.GetResourcePolicies¶paginator = client.get_paginator('get_resource_policies')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_resource_policies().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'GetResourcePoliciesResponseList': [
{
'PolicyInJson': 'string',
'PolicyHash': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1)
},
],
}
Response Structure
A list of the individual resource policies and the account-level resource policy.
A structure for returning a resource policy.
Contains the requested policy document, in JSON format.
Contains the hash value associated with this policy.
The date and time at which the policy was created.
The date and time at which the policy was last updated.
Glue.Paginator.GetSecurityConfigurations¶paginator = client.get_paginator('get_security_configurations')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_security_configurations().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'SecurityConfigurations': [
{
'Name': 'string',
'CreatedTimeStamp': datetime(2015, 1, 1),
'EncryptionConfiguration': {
'S3Encryption': [
{
'S3EncryptionMode': 'DISABLED'|'SSE-KMS'|'SSE-S3',
'KmsKeyArn': 'string'
},
],
'CloudWatchEncryption': {
'CloudWatchEncryptionMode': 'DISABLED'|'SSE-KMS',
'KmsKeyArn': 'string'
},
'JobBookmarksEncryption': {
'JobBookmarksEncryptionMode': 'DISABLED'|'CSE-KMS',
'KmsKeyArn': 'string'
}
}
},
],
}
Response Structure
A list of security configurations.
Specifies a security configuration.
The name of the security configuration.
The time at which this security configuration was created.
The encryption configuration associated with this security configuration.
The encryption configuration for Amazon Simple Storage Service (Amazon S3) data.
Specifies how Amazon Simple Storage Service (Amazon S3) data should be encrypted.
The encryption mode to use for Amazon S3 data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
The encryption configuration for Amazon CloudWatch.
The encryption mode to use for CloudWatch data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
The encryption configuration for job bookmarks.
The encryption mode to use for job bookmarks data.
The Amazon Resource Name (ARN) of the KMS key to be used to encrypt the data.
Glue.Paginator.GetTableVersions¶paginator = client.get_paginator('get_table_versions')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_table_versions().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
CatalogId='string',
DatabaseName='string',
TableName='string',
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
The database in the catalog in which the table resides. For Hive compatibility, this name is entirely lowercase.
[REQUIRED]
The name of the table. For Hive compatibility, this name is entirely lowercase.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'TableVersions': [
{
'Table': {
'Name': 'string',
'DatabaseName': 'string',
'Description': 'string',
'Owner': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'CreatedBy': 'string',
'IsRegisteredWithLakeFormation': True|False,
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
},
'CatalogId': 'string',
'VersionId': 'string'
},
'VersionId': 'string'
},
],
}
Response Structure
(dict) --
TableVersions (list) --
A list of strings identifying available versions of the specified table.
(dict) --
Specifies a version of a table.
Table (dict) --
The table in question.
Name (string) --
The table name. For Hive compatibility, this must be entirely lowercase.
DatabaseName (string) --
The name of the database where the table metadata resides. For Hive compatibility, this must be all lowercase.
Description (string) --
A description of the table.
Owner (string) --
The owner of the table.
CreateTime (datetime) --
The time when the table definition was created in the Data Catalog.
UpdateTime (datetime) --
The last time that the table was updated.
LastAccessTime (datetime) --
The last time that the table was accessed. This is usually taken from HDFS, and might not be reliable.
LastAnalyzedTime (datetime) --
The last time that column statistics were computed for this table.
Retention (integer) --
The retention time for this table.
StorageDescriptor (dict) --
A storage descriptor containing information about the physical storage of this table.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
PartitionKeys (list) --
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
ViewOriginalText (string) --
If the table is a view, the original text of the view; otherwise null .
ViewExpandedText (string) --
If the table is a view, the expanded text of the view; otherwise null .
TableType (string) --
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
Parameters (dict) --
These key-value pairs define properties associated with the table.
CreatedBy (string) --
The person or entity who created the table.
IsRegisteredWithLakeFormation (boolean) --
Indicates whether the table has been registered with Lake Formation.
TargetTable (dict) --
A TableIdentifier structure that describes a target table for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
DatabaseName (string) --
The name of the catalog database that contains the target table.
Name (string) --
The name of the target table.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
VersionId (string) --
The ID of the table version.
VersionId (string) --
The ID value that identifies this table version. A VersionId is a string representation of an integer. Each version is incremented by 1.
Glue.Paginator.GetTables¶paginator = client.get_paginator('get_tables')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_tables().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
CatalogId='string',
DatabaseName='string',
Expression='string',
TransactionId='string',
QueryAsOfTime=datetime(2015, 1, 1),
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
The database in the catalog whose tables to list. For Hive compatibility, this name is entirely lowercase.
TransactionId .A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'TableList': [
{
'Name': 'string',
'DatabaseName': 'string',
'Description': 'string',
'Owner': 'string',
'CreateTime': datetime(2015, 1, 1),
'UpdateTime': datetime(2015, 1, 1),
'LastAccessTime': datetime(2015, 1, 1),
'LastAnalyzedTime': datetime(2015, 1, 1),
'Retention': 123,
'StorageDescriptor': {
'Columns': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'Location': 'string',
'AdditionalLocations': [
'string',
],
'InputFormat': 'string',
'OutputFormat': 'string',
'Compressed': True|False,
'NumberOfBuckets': 123,
'SerdeInfo': {
'Name': 'string',
'SerializationLibrary': 'string',
'Parameters': {
'string': 'string'
}
},
'BucketColumns': [
'string',
],
'SortColumns': [
{
'Column': 'string',
'SortOrder': 123
},
],
'Parameters': {
'string': 'string'
},
'SkewedInfo': {
'SkewedColumnNames': [
'string',
],
'SkewedColumnValues': [
'string',
],
'SkewedColumnValueLocationMaps': {
'string': 'string'
}
},
'StoredAsSubDirectories': True|False,
'SchemaReference': {
'SchemaId': {
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
'SchemaVersionId': 'string',
'SchemaVersionNumber': 123
}
},
'PartitionKeys': [
{
'Name': 'string',
'Type': 'string',
'Comment': 'string',
'Parameters': {
'string': 'string'
}
},
],
'ViewOriginalText': 'string',
'ViewExpandedText': 'string',
'TableType': 'string',
'Parameters': {
'string': 'string'
},
'CreatedBy': 'string',
'IsRegisteredWithLakeFormation': True|False,
'TargetTable': {
'CatalogId': 'string',
'DatabaseName': 'string',
'Name': 'string'
},
'CatalogId': 'string',
'VersionId': 'string'
},
],
}
Response Structure
(dict) --
TableList (list) --
A list of the requested Table objects.
(dict) --
Represents a collection of related data organized in columns and rows.
Name (string) --
The table name. For Hive compatibility, this must be entirely lowercase.
DatabaseName (string) --
The name of the database where the table metadata resides. For Hive compatibility, this must be all lowercase.
Description (string) --
A description of the table.
Owner (string) --
The owner of the table.
CreateTime (datetime) --
The time when the table definition was created in the Data Catalog.
UpdateTime (datetime) --
The last time that the table was updated.
LastAccessTime (datetime) --
The last time that the table was accessed. This is usually taken from HDFS, and might not be reliable.
LastAnalyzedTime (datetime) --
The last time that column statistics were computed for this table.
Retention (integer) --
The retention time for this table.
StorageDescriptor (dict) --
A storage descriptor containing information about the physical storage of this table.
Columns (list) --
A list of the Columns in the table.
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
Location (string) --
The physical location of the table. By default, this takes the form of the warehouse location, followed by the database location in the warehouse, followed by the table name.
AdditionalLocations (list) --
A list of locations that point to the path where a Delta table is located.
InputFormat (string) --
The input format: SequenceFileInputFormat (binary), or TextInputFormat , or a custom format.
OutputFormat (string) --
The output format: SequenceFileOutputFormat (binary), or IgnoreKeyTextOutputFormat , or a custom format.
Compressed (boolean) --
Trueif the data in the table is compressed, orFalseif not.
NumberOfBuckets (integer) --
Must be specified if the table contains any dimension columns.
SerdeInfo (dict) --
The serialization/deserialization (SerDe) information.
Name (string) --
Name of the SerDe.
SerializationLibrary (string) --
Usually the class that implements the SerDe. An example is org.apache.hadoop.hive.serde2.columnar.ColumnarSerDe .
Parameters (dict) --
These key-value pairs define initialization parameters for the SerDe.
BucketColumns (list) --
A list of reducer grouping columns, clustering columns, and bucketing columns in the table.
SortColumns (list) --
A list specifying the sort order of each bucket in the table.
(dict) --
Specifies the sort order of a sorted column.
Column (string) --
The name of the column.
SortOrder (integer) --
Indicates that the column is sorted in ascending order ( == 1 ), or in descending order ( ==0 ).
Parameters (dict) --
The user-supplied properties in key-value form.
SkewedInfo (dict) --
The information about values that appear frequently in a column (skewed values).
SkewedColumnNames (list) --
A list of names of columns that contain skewed values.
SkewedColumnValues (list) --
A list of values that appear so frequently as to be considered skewed.
SkewedColumnValueLocationMaps (dict) --
A mapping of skewed values to the columns that contain them.
StoredAsSubDirectories (boolean) --
Trueif the table data is stored in subdirectories, orFalseif not.
SchemaReference (dict) --
An object that references a schema stored in the Glue Schema Registry.
When creating a table, you can pass an empty list of columns for the schema, and instead use a schema reference.
SchemaId (dict) --
A structure that contains schema identity fields. Either this or the SchemaVersionId has to be provided.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
SchemaName (string) --
The name of the schema. One of SchemaArn or SchemaName has to be provided.
RegistryName (string) --
The name of the schema registry that contains the schema.
SchemaVersionId (string) --
The unique ID assigned to a version of the schema. Either this or the SchemaId has to be provided.
SchemaVersionNumber (integer) --
The version number of the schema.
PartitionKeys (list) --
A list of columns by which the table is partitioned. Only primitive types are supported as partition keys.
When you create a table used by Amazon Athena, and you do not specify any partitionKeys , you must at least set the value of partitionKeys to an empty list. For example:
"PartitionKeys": []
(dict) --
A column in a Table .
Name (string) --
The name of the Column .
Type (string) --
The data type of the Column .
Comment (string) --
A free-form text comment.
Parameters (dict) --
These key-value pairs define properties associated with the column.
ViewOriginalText (string) --
If the table is a view, the original text of the view; otherwise null .
ViewExpandedText (string) --
If the table is a view, the expanded text of the view; otherwise null .
TableType (string) --
The type of this table ( EXTERNAL_TABLE , VIRTUAL_VIEW , etc.).
Parameters (dict) --
These key-value pairs define properties associated with the table.
CreatedBy (string) --
The person or entity who created the table.
IsRegisteredWithLakeFormation (boolean) --
Indicates whether the table has been registered with Lake Formation.
TargetTable (dict) --
A TableIdentifier structure that describes a target table for resource linking.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
DatabaseName (string) --
The name of the catalog database that contains the target table.
Name (string) --
The name of the target table.
CatalogId (string) --
The ID of the Data Catalog in which the table resides.
VersionId (string) --
The ID of the table version.
Glue.Paginator.GetTriggers¶paginator = client.get_paginator('get_triggers')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_triggers().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
DependentJobName='string',
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'Triggers': [
{
'Name': 'string',
'WorkflowName': 'string',
'Id': 'string',
'Type': 'SCHEDULED'|'CONDITIONAL'|'ON_DEMAND'|'EVENT',
'State': 'CREATING'|'CREATED'|'ACTIVATING'|'ACTIVATED'|'DEACTIVATING'|'DEACTIVATED'|'DELETING'|'UPDATING',
'Description': 'string',
'Schedule': 'string',
'Actions': [
{
'JobName': 'string',
'Arguments': {
'string': 'string'
},
'Timeout': 123,
'SecurityConfiguration': 'string',
'NotificationProperty': {
'NotifyDelayAfter': 123
},
'CrawlerName': 'string'
},
],
'Predicate': {
'Logical': 'AND'|'ANY',
'Conditions': [
{
'LogicalOperator': 'EQUALS',
'JobName': 'string',
'State': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
'CrawlerName': 'string',
'CrawlState': 'RUNNING'|'CANCELLING'|'CANCELLED'|'SUCCEEDED'|'FAILED'|'ERROR'
},
]
},
'EventBatchingCondition': {
'BatchSize': 123,
'BatchWindow': 123
}
},
],
}
Response Structure
(dict) --
Triggers (list) --
A list of triggers for the specified job.
(dict) --
Information about a specific trigger.
Name (string) --
The name of the trigger.
WorkflowName (string) --
The name of the workflow associated with the trigger.
Id (string) --
Reserved for future use.
Type (string) --
The type of trigger that this is.
State (string) --
The current state of the trigger.
Description (string) --
A description of this trigger.
Schedule (string) --
A cron expression used to specify the schedule (see Time-Based Schedules for Jobs and Crawlers. For example, to run something every day at 12:15 UTC, you would specify: cron(15 12 * * ? *) .
Actions (list) --
The actions initiated by this trigger.
(dict) --
Defines an action to be initiated by a trigger.
JobName (string) --
The name of a job to be run.
Arguments (dict) --
The job arguments used when this trigger fires. For this job run, they replace the default arguments set in the job definition itself.
You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that Glue consumes to set up your job, see the Special Parameters Used by Glue topic in the developer guide.
Timeout (integer) --
The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
SecurityConfiguration (string) --
The name of the SecurityConfiguration structure to be used with this action.
NotificationProperty (dict) --
Specifies configuration properties of a job run notification.
NotifyDelayAfter (integer) --
After a job run starts, the number of minutes to wait before sending a job run delay notification.
CrawlerName (string) --
The name of the crawler to be used with this action.
Predicate (dict) --
The predicate of this trigger, which defines when it will fire.
Logical (string) --
An optional field if only one condition is listed. If multiple conditions are listed, then this field is required.
Conditions (list) --
A list of the conditions that determine when the trigger will fire.
(dict) --
Defines a condition under which a trigger fires.
LogicalOperator (string) --
A logical operator.
JobName (string) --
The name of the job whose JobRuns this condition applies to, and on which this trigger waits.
State (string) --
The condition state. Currently, the only job states that a trigger can listen for are SUCCEEDED , STOPPED , FAILED , and TIMEOUT . The only crawler states that a trigger can listen for are SUCCEEDED , FAILED , and CANCELLED .
CrawlerName (string) --
The name of the crawler to which this condition applies.
CrawlState (string) --
The state of the crawler to which this condition applies.
EventBatchingCondition (dict) --
Batch condition that must be met (specified number of events received or batch time window expired) before EventBridge event trigger fires.
BatchSize (integer) --
Number of events that must be received from Amazon EventBridge before EventBridge event trigger fires.
BatchWindow (integer) --
Window of time in seconds after which EventBridge event trigger fires. Window starts when first event is received.
Glue.Paginator.GetUserDefinedFunctions¶paginator = client.get_paginator('get_user_defined_functions')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.get_user_defined_functions().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
CatalogId='string',
DatabaseName='string',
Pattern='string',
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
An optional function-name pattern string that filters the function definitions returned.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'UserDefinedFunctions': [
{
'FunctionName': 'string',
'DatabaseName': 'string',
'ClassName': 'string',
'OwnerName': 'string',
'OwnerType': 'USER'|'ROLE'|'GROUP',
'CreateTime': datetime(2015, 1, 1),
'ResourceUris': [
{
'ResourceType': 'JAR'|'FILE'|'ARCHIVE',
'Uri': 'string'
},
],
'CatalogId': 'string'
},
],
}
Response Structure
(dict) --
UserDefinedFunctions (list) --
A list of requested function definitions.
(dict) --
Represents the equivalent of a Hive user-defined function ( UDF ) definition.
FunctionName (string) --
The name of the function.
DatabaseName (string) --
The name of the catalog database that contains the function.
ClassName (string) --
The Java class that contains the function code.
OwnerName (string) --
The owner of the function.
OwnerType (string) --
The owner type.
CreateTime (datetime) --
The time at which the function was created.
ResourceUris (list) --
The resource URIs for the function.
(dict) --
The URIs for function resources.
ResourceType (string) --
The type of the resource.
Uri (string) --
The URI for accessing the resource.
CatalogId (string) --
The ID of the Data Catalog in which the function resides.
Glue.Paginator.ListRegistries¶paginator = client.get_paginator('list_registries')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.list_registries().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
{
'Registries': [
{
'RegistryName': 'string',
'RegistryArn': 'string',
'Description': 'string',
'Status': 'AVAILABLE'|'DELETING',
'CreatedTime': 'string',
'UpdatedTime': 'string'
},
],
}
Response Structure
An array of RegistryDetailedListItem objects containing minimal details of each registry.
A structure containing the details for a registry.
The name of the registry.
The Amazon Resource Name (ARN) of the registry.
A description of the registry.
The status of the registry.
The data the registry was created.
The date the registry was updated.
Glue.Paginator.ListSchemaVersions¶paginator = client.get_paginator('list_schema_versions')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.list_schema_versions().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
SchemaId={
'SchemaArn': 'string',
'SchemaName': 'string',
'RegistryName': 'string'
},
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
This is a wrapper structure to contain schema identity fields. The structure contains:
SchemaArn or SchemaName and RegistryName has to be provided.SchemaArn or SchemaName and RegistryName has to be provided.The Amazon Resource Name (ARN) of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema. One of SchemaArn or SchemaName has to be provided.
The name of the schema registry that contains the schema.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'Schemas': [
{
'SchemaArn': 'string',
'SchemaVersionId': 'string',
'VersionNumber': 123,
'Status': 'AVAILABLE'|'PENDING'|'FAILURE'|'DELETING',
'CreatedTime': 'string'
},
],
}
Response Structure
(dict) --
Schemas (list) --
An array of SchemaVersionList objects containing details of each schema version.
(dict) --
An object containing the details about a schema version.
SchemaArn (string) --
The Amazon Resource Name (ARN) of the schema.
SchemaVersionId (string) --
The unique identifier of the schema version.
VersionNumber (integer) --
The version number of the schema.
Status (string) --
The status of the schema version.
CreatedTime (string) --
The date and time the schema version was created.
Glue.Paginator.ListSchemas¶paginator = client.get_paginator('list_schemas')
paginate(**kwargs)¶Creates an iterator that will paginate through responses from Glue.Client.list_schemas().
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
RegistryId={
'RegistryName': 'string',
'RegistryArn': 'string'
},
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
A wrapper structure that may contain the registry name and Amazon Resource Name (ARN).
Name of the registry. Used only for lookup. One of RegistryArn or RegistryName has to be provided.
Arn of the registry to be updated. One of RegistryArn or RegistryName has to be provided.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken from a previous response.
dict
Response Syntax
{
'Schemas': [
{
'RegistryName': 'string',
'SchemaName': 'string',
'SchemaArn': 'string',
'Description': 'string',
'SchemaStatus': 'AVAILABLE'|'PENDING'|'DELETING',
'CreatedTime': 'string',
'UpdatedTime': 'string'
},
],
}
Response Structure
(dict) --
Schemas (list) --
An array of SchemaListItem objects containing details of each schema.
(dict) --
An object that contains minimal details for a schema.
RegistryName (string) --
the name of the registry where the schema resides.
SchemaName (string) --
The name of the schema.
SchemaArn (string) --
The Amazon Resource Name (ARN) for the schema.
Description (string) --
A description for the schema.
SchemaStatus (string) --
The status of the schema.
CreatedTime (string) --
The date and time that a schema was created.
UpdatedTime (string) --
The date and time that a schema was updated.