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.
True
if the data in the table is compressed, orFalse
if 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.
True
if the table data is stored in subdirectories, orFalse
if 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.InvalidInputException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.GlueEncryptionException
batch_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.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
batch_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.InvalidInputException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
batch_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.InvalidInputException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.GlueEncryptionException
Glue.Client.exceptions.ResourceNotReadyException
batch_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.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
batch_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.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InvalidInputException
batch_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.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
batch_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.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
batch_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.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
batch_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.AccessDeniedException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InvalidInputException
batch_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.
CodeGenConfigurationNode
enumerates 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.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InvalidInputException
batch_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) --
True
if the data in the table is compressed, orFalse
if 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) --
True
if the table data is stored in subdirectories, orFalse
if 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.InvalidInputException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.GlueEncryptionException
Glue.Client.exceptions.InvalidStateException
batch_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.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InvalidInputException
batch_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.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InvalidInputException
batch_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.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
batch_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.
True
if the data in the table is compressed, orFalse
if 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.
True
if the table data is stored in subdirectories, orFalse
if 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.InvalidInputException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.GlueEncryptionException
can_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.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
cancel_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.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
cancel_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.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
cancel_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.AccessDeniedException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.IllegalSessionStateException
check_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.InvalidInputException
Glue.Client.exceptions.AccessDeniedException
Glue.Client.exceptions.InternalServiceException
close
()¶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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.ResourceNumberLimitExceededException
create_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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
create_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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.GlueEncryptionException
create_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.InvalidInputException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.ResourceNumberLimitExceededException
create_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.AccessDeniedException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.IdempotentParameterMismatchException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.ResourceNumberLimitExceededException
create_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.InvalidInputException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.ResourceNumberLimitExceededException
create_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.InvalidInputException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.GlueEncryptionException
Glue.Client.exceptions.ConcurrentModificationException
create_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.AccessDeniedException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.IdempotentParameterMismatchException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.ValidationException
Glue.Client.exceptions.ResourceNumberLimitExceededException
create_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.
CodeGenConfigurationNode
enumerates 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.InvalidInputException
Glue.Client.exceptions.IdempotentParameterMismatchException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.ConcurrentModificationException
create_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.
MaxCapacity
is a mutually exclusive option withNumberOfWorkers
andWorkerType
.
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.MaxCapacity
is a mutually exclusive option withNumberOfWorkers
andWorkerType
.
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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.AccessDeniedException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.IdempotentParameterMismatchException
create_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.
True
if the data in the table is compressed, orFalse
if 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.
True
if the table data is stored in subdirectories, orFalse
if 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.InvalidInputException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.GlueEncryptionException
create_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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.GlueEncryptionException
create_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.InvalidInputException
Glue.Client.exceptions.AccessDeniedException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.ConcurrentModificationException
Glue.Client.exceptions.InternalServiceException
create_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.InvalidInputException
Glue.Client.exceptions.AccessDeniedException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.ConcurrentModificationException
Glue.Client.exceptions.InternalServiceException
create_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.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
create_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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.ResourceNumberLimitExceededException
create_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.AccessDeniedException
Glue.Client.exceptions.IdempotentParameterMismatchException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.ValidationException
Glue.Client.exceptions.AlreadyExistsException
Glue.Client.exceptions.ResourceNumberLimitExceededException
create_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.
True
if the data in the table is compressed, orFalse
if 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.
True
if the table data is stored in subdirectories, orFalse
if 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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.GlueEncryptionException
Glue.Client.exceptions.ConcurrentModificationException
Glue.Client.exceptions.ResourceNotReadyException
create_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.AlreadyExistsException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.IdempotentParameterMismatchException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.ConcurrentModificationException
create_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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.GlueEncryptionException
create_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.AlreadyExistsException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.ResourceNumberLimitExceededException
Glue.Client.exceptions.ConcurrentModificationException
delete_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.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
delete_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.EntityNotFoundException
Glue.Client.exceptions.OperationTimeoutException
delete_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.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.GlueEncryptionException
delete_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.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.GlueEncryptionException
delete_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.EntityNotFoundException
Glue.Client.exceptions.OperationTimeoutException
delete_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.EntityNotFoundException
Glue.Client.exceptions.CrawlerRunningException
Glue.Client.exceptions.SchedulerTransitioningException
Glue.Client.exceptions.OperationTimeoutException
delete_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.EntityNotFoundException
Glue.Client.exceptions.AccessDeniedException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
delete_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.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
delete_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'
)