Table of Contents
EMRContainers.
Client
¶A low-level client representing Amazon EMR Containers
Amazon EMR on EKS provides a deployment option for Amazon EMR that allows you to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With this deployment option, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. For more information about Amazon EMR on EKS concepts and tasks, see What is Amazon EMR on EKS .
Amazon EMR containers is the API name for Amazon EMR on EKS. Theemr-containers
prefix is used in the following scenarios:
aws emr-containers start-job-run
."Action": [ "emr-containers:StartJobRun"]
. For more information, see Policy actions for Amazon EMR on EKS .emr-containers.us-east-2.amazonaws.com
. For more information, see Amazon EMR on EKS Service Endpoints .import boto3
client = boto3.client('emr-containers')
These are the available methods:
can_paginate()
cancel_job_run()
close()
create_managed_endpoint()
create_virtual_cluster()
delete_managed_endpoint()
delete_virtual_cluster()
describe_job_run()
describe_managed_endpoint()
describe_virtual_cluster()
get_paginator()
get_waiter()
list_job_runs()
list_managed_endpoints()
list_tags_for_resource()
list_virtual_clusters()
start_job_run()
tag_resource()
untag_resource()
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_job_run
(**kwargs)¶Cancels a job run. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
See also: AWS API Documentation
Request Syntax
response = client.cancel_job_run(
id='string',
virtualClusterId='string'
)
[REQUIRED]
The ID of the job run to cancel.
[REQUIRED]
The ID of the virtual cluster for which the job run will be canceled.
dict
Response Syntax
{
'id': 'string',
'virtualClusterId': 'string'
}
Response Structure
(dict) --
id (string) --
The output contains the ID of the cancelled job run.
virtualClusterId (string) --
The output contains the virtual cluster ID for which the job run is cancelled.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.InternalServerException
close
()¶Closes underlying endpoint connections.
create_managed_endpoint
(**kwargs)¶Creates a managed endpoint. A managed endpoint is a gateway that connects EMR Studio to Amazon EMR on EKS so that EMR Studio can communicate with your virtual cluster.
See also: AWS API Documentation
Request Syntax
response = client.create_managed_endpoint(
name='string',
virtualClusterId='string',
type='string',
releaseLabel='string',
executionRoleArn='string',
certificateArn='string',
configurationOverrides={
'applicationConfiguration': [
{
'classification': 'string',
'properties': {
'string': 'string'
},
'configurations': {'... recursive ...'}
},
],
'monitoringConfiguration': {
'persistentAppUI': 'ENABLED'|'DISABLED',
'cloudWatchMonitoringConfiguration': {
'logGroupName': 'string',
'logStreamNamePrefix': 'string'
},
's3MonitoringConfiguration': {
'logUri': 'string'
}
}
},
clientToken='string',
tags={
'string': 'string'
}
)
[REQUIRED]
The name of the managed endpoint.
[REQUIRED]
The ID of the virtual cluster for which a managed endpoint is created.
[REQUIRED]
The type of the managed endpoint.
[REQUIRED]
The Amazon EMR release version.
[REQUIRED]
The ARN of the execution role.
The configuration settings that will be used to override existing configurations.
The configurations for the application running by the job run.
A configuration specification to be used when provisioning virtual clusters, which can include configurations for applications and software bundled with Amazon EMR on EKS. A configuration consists of a classification, properties, and optional nested configurations. A classification refers to an application-specific configuration file. Properties are the settings you want to change in that file.
The classification within a configuration.
A set of properties specified within a configuration classification.
A list of additional configurations to apply within a configuration object.
The configurations for monitoring.
Monitoring configurations for the persistent application UI.
Monitoring configurations for CloudWatch.
The name of the log group for log publishing.
The specified name prefix for log streams.
Amazon S3 configuration for monitoring log publishing.
Amazon S3 destination URI for log publishing.
[REQUIRED]
The client idempotency token for this create call.
This field is autopopulated if not provided.
The tags of the managed endpoint.
dict
Response Syntax
{
'id': 'string',
'name': 'string',
'arn': 'string',
'virtualClusterId': 'string'
}
Response Structure
(dict) --
id (string) --
The output contains the ID of the managed endpoint.
name (string) --
The output contains the name of the managed endpoint.
arn (string) --
The output contains the ARN of the managed endpoint.
virtualClusterId (string) --
The output contains the ID of the virtual cluster.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
EMRContainers.Client.exceptions.InternalServerException
create_virtual_cluster
(**kwargs)¶Creates a virtual cluster. Virtual cluster is a managed entity on Amazon EMR on EKS. You can create, describe, list and delete virtual clusters. They do not consume any additional resource in your system. A single virtual cluster maps to a single Kubernetes namespace. Given this relationship, you can model virtual clusters the same way you model Kubernetes namespaces to meet your requirements.
See also: AWS API Documentation
Request Syntax
response = client.create_virtual_cluster(
name='string',
containerProvider={
'type': 'EKS',
'id': 'string',
'info': {
'eksInfo': {
'namespace': 'string'
}
}
},
clientToken='string',
tags={
'string': 'string'
}
)
[REQUIRED]
The specified name of the virtual cluster.
[REQUIRED]
The container provider of the virtual cluster.
The type of the container provider. EKS is the only supported type as of now.
The ID of the container cluster.
The information about the container cluster.
Note
This is a Tagged Union structure. Only one of the following top level keys can be set: eksInfo
.
The information about the EKS cluster.
The namespaces of the EKS cluster.
[REQUIRED]
The client token of the virtual cluster.
This field is autopopulated if not provided.
The tags assigned to the virtual cluster.
dict
Response Syntax
{
'id': 'string',
'name': 'string',
'arn': 'string'
}
Response Structure
(dict) --
id (string) --
This output contains the virtual cluster ID.
name (string) --
This output contains the name of the virtual cluster.
arn (string) --
This output contains the ARN of virtual cluster.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
EMRContainers.Client.exceptions.InternalServerException
delete_managed_endpoint
(**kwargs)¶Deletes a managed endpoint. A managed endpoint is a gateway that connects EMR Studio to Amazon EMR on EKS so that EMR Studio can communicate with your virtual cluster.
See also: AWS API Documentation
Request Syntax
response = client.delete_managed_endpoint(
id='string',
virtualClusterId='string'
)
[REQUIRED]
The ID of the managed endpoint.
[REQUIRED]
The ID of the endpoint's virtual cluster.
dict
Response Syntax
{
'id': 'string',
'virtualClusterId': 'string'
}
Response Structure
(dict) --
id (string) --
The output displays the ID of the managed endpoint.
virtualClusterId (string) --
The output displays the ID of the endpoint's virtual cluster.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.InternalServerException
delete_virtual_cluster
(**kwargs)¶Deletes a virtual cluster. Virtual cluster is a managed entity on Amazon EMR on EKS. You can create, describe, list and delete virtual clusters. They do not consume any additional resource in your system. A single virtual cluster maps to a single Kubernetes namespace. Given this relationship, you can model virtual clusters the same way you model Kubernetes namespaces to meet your requirements.
See also: AWS API Documentation
Request Syntax
response = client.delete_virtual_cluster(
id='string'
)
[REQUIRED]
The ID of the virtual cluster that will be deleted.
{
'id': 'string'
}
Response Structure
This output contains the ID of the virtual cluster that will be deleted.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.InternalServerException
describe_job_run
(**kwargs)¶Displays detailed information about a job run. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
See also: AWS API Documentation
Request Syntax
response = client.describe_job_run(
id='string',
virtualClusterId='string'
)
[REQUIRED]
The ID of the job run request.
[REQUIRED]
The ID of the virtual cluster for which the job run is submitted.
dict
Response Syntax
{
'jobRun': {
'id': 'string',
'name': 'string',
'virtualClusterId': 'string',
'arn': 'string',
'state': 'PENDING'|'SUBMITTED'|'RUNNING'|'FAILED'|'CANCELLED'|'CANCEL_PENDING'|'COMPLETED',
'clientToken': 'string',
'executionRoleArn': 'string',
'releaseLabel': 'string',
'configurationOverrides': {
'applicationConfiguration': [
{
'classification': 'string',
'properties': {
'string': 'string'
},
'configurations': {'... recursive ...'}
},
],
'monitoringConfiguration': {
'persistentAppUI': 'ENABLED'|'DISABLED',
'cloudWatchMonitoringConfiguration': {
'logGroupName': 'string',
'logStreamNamePrefix': 'string'
},
's3MonitoringConfiguration': {
'logUri': 'string'
}
}
},
'jobDriver': {
'sparkSubmitJobDriver': {
'entryPoint': 'string',
'entryPointArguments': [
'string',
],
'sparkSubmitParameters': 'string'
},
'sparkSqlJobDriver': {
'entryPoint': 'string',
'sparkSqlParameters': 'string'
}
},
'createdAt': datetime(2015, 1, 1),
'createdBy': 'string',
'finishedAt': datetime(2015, 1, 1),
'stateDetails': 'string',
'failureReason': 'INTERNAL_ERROR'|'USER_ERROR'|'VALIDATION_ERROR'|'CLUSTER_UNAVAILABLE',
'tags': {
'string': 'string'
}
}
}
Response Structure
(dict) --
jobRun (dict) --
The output displays information about a job run.
id (string) --
The ID of the job run.
name (string) --
The name of the job run.
virtualClusterId (string) --
The ID of the job run's virtual cluster.
arn (string) --
The ARN of job run.
state (string) --
The state of the job run.
clientToken (string) --
The client token used to start a job run.
executionRoleArn (string) --
The execution role ARN of the job run.
releaseLabel (string) --
The release version of Amazon EMR.
configurationOverrides (dict) --
The configuration settings that are used to override default configuration.
applicationConfiguration (list) --
The configurations for the application running by the job run.
(dict) --
A configuration specification to be used when provisioning virtual clusters, which can include configurations for applications and software bundled with Amazon EMR on EKS. A configuration consists of a classification, properties, and optional nested configurations. A classification refers to an application-specific configuration file. Properties are the settings you want to change in that file.
classification (string) --
The classification within a configuration.
properties (dict) --
A set of properties specified within a configuration classification.
configurations (list) --
A list of additional configurations to apply within a configuration object.
monitoringConfiguration (dict) --
The configurations for monitoring.
persistentAppUI (string) --
Monitoring configurations for the persistent application UI.
cloudWatchMonitoringConfiguration (dict) --
Monitoring configurations for CloudWatch.
logGroupName (string) --
The name of the log group for log publishing.
logStreamNamePrefix (string) --
The specified name prefix for log streams.
s3MonitoringConfiguration (dict) --
Amazon S3 configuration for monitoring log publishing.
logUri (string) --
Amazon S3 destination URI for log publishing.
jobDriver (dict) --
Parameters of job driver for the job run.
sparkSubmitJobDriver (dict) --
The job driver parameters specified for spark submit.
entryPoint (string) --
The entry point of job application.
entryPointArguments (list) --
The arguments for job application.
sparkSubmitParameters (string) --
The Spark submit parameters that are used for job runs.
sparkSqlJobDriver (dict) --
The job driver for job type.
entryPoint (string) --
The SQL file to be executed.
sparkSqlParameters (string) --
The Spark parameters to be included in the Spark SQL command.
createdAt (datetime) --
The date and time when the job run was created.
createdBy (string) --
The user who created the job run.
finishedAt (datetime) --
The date and time when the job run has finished.
stateDetails (string) --
Additional details of the job run state.
failureReason (string) --
The reasons why the job run has failed.
tags (dict) --
The assigned tags of the job run.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
EMRContainers.Client.exceptions.InternalServerException
describe_managed_endpoint
(**kwargs)¶Displays detailed information about a managed endpoint. A managed endpoint is a gateway that connects EMR Studio to Amazon EMR on EKS so that EMR Studio can communicate with your virtual cluster.
See also: AWS API Documentation
Request Syntax
response = client.describe_managed_endpoint(
id='string',
virtualClusterId='string'
)
[REQUIRED]
This output displays ID of the managed endpoint.
[REQUIRED]
The ID of the endpoint's virtual cluster.
dict
Response Syntax
{
'endpoint': {
'id': 'string',
'name': 'string',
'arn': 'string',
'virtualClusterId': 'string',
'type': 'string',
'state': 'CREATING'|'ACTIVE'|'TERMINATING'|'TERMINATED'|'TERMINATED_WITH_ERRORS',
'releaseLabel': 'string',
'executionRoleArn': 'string',
'certificateArn': 'string',
'certificateAuthority': {
'certificateArn': 'string',
'certificateData': 'string'
},
'configurationOverrides': {
'applicationConfiguration': [
{
'classification': 'string',
'properties': {
'string': 'string'
},
'configurations': {'... recursive ...'}
},
],
'monitoringConfiguration': {
'persistentAppUI': 'ENABLED'|'DISABLED',
'cloudWatchMonitoringConfiguration': {
'logGroupName': 'string',
'logStreamNamePrefix': 'string'
},
's3MonitoringConfiguration': {
'logUri': 'string'
}
}
},
'serverUrl': 'string',
'createdAt': datetime(2015, 1, 1),
'securityGroup': 'string',
'subnetIds': [
'string',
],
'stateDetails': 'string',
'failureReason': 'INTERNAL_ERROR'|'USER_ERROR'|'VALIDATION_ERROR'|'CLUSTER_UNAVAILABLE',
'tags': {
'string': 'string'
}
}
}
Response Structure
(dict) --
endpoint (dict) --
This output displays information about a managed endpoint.
id (string) --
The ID of the endpoint.
name (string) --
The name of the endpoint.
arn (string) --
The ARN of the endpoint.
virtualClusterId (string) --
The ID of the endpoint's virtual cluster.
type (string) --
The type of the endpoint.
state (string) --
The state of the endpoint.
releaseLabel (string) --
The EMR release version to be used for the endpoint.
executionRoleArn (string) --
The execution role ARN of the endpoint.
certificateArn (string) --
The certificate ARN of the endpoint. This field is under deprecation and will be removed in future.
certificateAuthority (dict) --
The certificate generated by emr control plane on customer behalf to secure the managed endpoint.
certificateArn (string) --
The ARN of the certificate generated for managed endpoint.
certificateData (string) --
The base64 encoded PEM certificate data generated for managed endpoint.
configurationOverrides (dict) --
The configuration settings that are used to override existing configurations for endpoints.
applicationConfiguration (list) --
The configurations for the application running by the job run.
(dict) --
A configuration specification to be used when provisioning virtual clusters, which can include configurations for applications and software bundled with Amazon EMR on EKS. A configuration consists of a classification, properties, and optional nested configurations. A classification refers to an application-specific configuration file. Properties are the settings you want to change in that file.
classification (string) --
The classification within a configuration.
properties (dict) --
A set of properties specified within a configuration classification.
configurations (list) --
A list of additional configurations to apply within a configuration object.
monitoringConfiguration (dict) --
The configurations for monitoring.
persistentAppUI (string) --
Monitoring configurations for the persistent application UI.
cloudWatchMonitoringConfiguration (dict) --
Monitoring configurations for CloudWatch.
logGroupName (string) --
The name of the log group for log publishing.
logStreamNamePrefix (string) --
The specified name prefix for log streams.
s3MonitoringConfiguration (dict) --
Amazon S3 configuration for monitoring log publishing.
logUri (string) --
Amazon S3 destination URI for log publishing.
serverUrl (string) --
The server URL of the endpoint.
createdAt (datetime) --
The date and time when the endpoint was created.
securityGroup (string) --
The security group configuration of the endpoint.
subnetIds (list) --
The subnet IDs of the endpoint.
stateDetails (string) --
Additional details of the endpoint state.
failureReason (string) --
The reasons why the endpoint has failed.
tags (dict) --
The tags of the endpoint.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
EMRContainers.Client.exceptions.InternalServerException
describe_virtual_cluster
(**kwargs)¶Displays detailed information about a specified virtual cluster. Virtual cluster is a managed entity on Amazon EMR on EKS. You can create, describe, list and delete virtual clusters. They do not consume any additional resource in your system. A single virtual cluster maps to a single Kubernetes namespace. Given this relationship, you can model virtual clusters the same way you model Kubernetes namespaces to meet your requirements.
See also: AWS API Documentation
Request Syntax
response = client.describe_virtual_cluster(
id='string'
)
[REQUIRED]
The ID of the virtual cluster that will be described.
{
'virtualCluster': {
'id': 'string',
'name': 'string',
'arn': 'string',
'state': 'RUNNING'|'TERMINATING'|'TERMINATED'|'ARRESTED',
'containerProvider': {
'type': 'EKS',
'id': 'string',
'info': {
'eksInfo': {
'namespace': 'string'
}
}
},
'createdAt': datetime(2015, 1, 1),
'tags': {
'string': 'string'
}
}
}
Response Structure
This output displays information about the specified virtual cluster.
The ID of the virtual cluster.
The name of the virtual cluster.
The ARN of the virtual cluster.
The state of the virtual cluster.
The container provider of the virtual cluster.
The type of the container provider. EKS is the only supported type as of now.
The ID of the container cluster.
The information about the container cluster.
Note
This is a Tagged Union structure. Only one of the following top level keys will be set: eksInfo
. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER
as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER
is as follows:
'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
The information about the EKS cluster.
The namespaces of the EKS cluster.
The date and time when the virtual cluster is created.
The assigned tags of the virtual cluster.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
EMRContainers.Client.exceptions.InternalServerException
get_paginator
(operation_name)¶Create a paginator for an operation.
create_foo
, and you'd normally invoke the
operation as client.create_foo(**kwargs)
, if the
create_foo
operation can be paginated, you can use the
call client.get_paginator("create_foo")
.client.can_paginate
method to
check if an operation is pageable.get_waiter
(waiter_name)¶Returns an object that can wait for some condition.
list_job_runs
(**kwargs)¶Lists job runs based on a set of parameters. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
See also: AWS API Documentation
Request Syntax
response = client.list_job_runs(
virtualClusterId='string',
createdBefore=datetime(2015, 1, 1),
createdAfter=datetime(2015, 1, 1),
name='string',
states=[
'PENDING'|'SUBMITTED'|'RUNNING'|'FAILED'|'CANCELLED'|'CANCEL_PENDING'|'COMPLETED',
],
maxResults=123,
nextToken='string'
)
[REQUIRED]
The ID of the virtual cluster for which to list the job run.
The states of the job run.
dict
Response Syntax
{
'jobRuns': [
{
'id': 'string',
'name': 'string',
'virtualClusterId': 'string',
'arn': 'string',
'state': 'PENDING'|'SUBMITTED'|'RUNNING'|'FAILED'|'CANCELLED'|'CANCEL_PENDING'|'COMPLETED',
'clientToken': 'string',
'executionRoleArn': 'string',
'releaseLabel': 'string',
'configurationOverrides': {
'applicationConfiguration': [
{
'classification': 'string',
'properties': {
'string': 'string'
},
'configurations': {'... recursive ...'}
},
],
'monitoringConfiguration': {
'persistentAppUI': 'ENABLED'|'DISABLED',
'cloudWatchMonitoringConfiguration': {
'logGroupName': 'string',
'logStreamNamePrefix': 'string'
},
's3MonitoringConfiguration': {
'logUri': 'string'
}
}
},
'jobDriver': {
'sparkSubmitJobDriver': {
'entryPoint': 'string',
'entryPointArguments': [
'string',
],
'sparkSubmitParameters': 'string'
},
'sparkSqlJobDriver': {
'entryPoint': 'string',
'sparkSqlParameters': 'string'
}
},
'createdAt': datetime(2015, 1, 1),
'createdBy': 'string',
'finishedAt': datetime(2015, 1, 1),
'stateDetails': 'string',
'failureReason': 'INTERNAL_ERROR'|'USER_ERROR'|'VALIDATION_ERROR'|'CLUSTER_UNAVAILABLE',
'tags': {
'string': 'string'
}
},
],
'nextToken': 'string'
}
Response Structure
(dict) --
jobRuns (list) --
This output lists information about the specified job runs.
(dict) --
This entity describes a job run. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
id (string) --
The ID of the job run.
name (string) --
The name of the job run.
virtualClusterId (string) --
The ID of the job run's virtual cluster.
arn (string) --
The ARN of job run.
state (string) --
The state of the job run.
clientToken (string) --
The client token used to start a job run.
executionRoleArn (string) --
The execution role ARN of the job run.
releaseLabel (string) --
The release version of Amazon EMR.
configurationOverrides (dict) --
The configuration settings that are used to override default configuration.
applicationConfiguration (list) --
The configurations for the application running by the job run.
(dict) --
A configuration specification to be used when provisioning virtual clusters, which can include configurations for applications and software bundled with Amazon EMR on EKS. A configuration consists of a classification, properties, and optional nested configurations. A classification refers to an application-specific configuration file. Properties are the settings you want to change in that file.
classification (string) --
The classification within a configuration.
properties (dict) --
A set of properties specified within a configuration classification.
configurations (list) --
A list of additional configurations to apply within a configuration object.
monitoringConfiguration (dict) --
The configurations for monitoring.
persistentAppUI (string) --
Monitoring configurations for the persistent application UI.
cloudWatchMonitoringConfiguration (dict) --
Monitoring configurations for CloudWatch.
logGroupName (string) --
The name of the log group for log publishing.
logStreamNamePrefix (string) --
The specified name prefix for log streams.
s3MonitoringConfiguration (dict) --
Amazon S3 configuration for monitoring log publishing.
logUri (string) --
Amazon S3 destination URI for log publishing.
jobDriver (dict) --
Parameters of job driver for the job run.
sparkSubmitJobDriver (dict) --
The job driver parameters specified for spark submit.
entryPoint (string) --
The entry point of job application.
entryPointArguments (list) --
The arguments for job application.
sparkSubmitParameters (string) --
The Spark submit parameters that are used for job runs.
sparkSqlJobDriver (dict) --
The job driver for job type.
entryPoint (string) --
The SQL file to be executed.
sparkSqlParameters (string) --
The Spark parameters to be included in the Spark SQL command.
createdAt (datetime) --
The date and time when the job run was created.
createdBy (string) --
The user who created the job run.
finishedAt (datetime) --
The date and time when the job run has finished.
stateDetails (string) --
Additional details of the job run state.
failureReason (string) --
The reasons why the job run has failed.
tags (dict) --
The assigned tags of the job run.
nextToken (string) --
This output displays the token for the next set of job runs.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.InternalServerException
list_managed_endpoints
(**kwargs)¶Lists managed endpoints based on a set of parameters. A managed endpoint is a gateway that connects EMR Studio to Amazon EMR on EKS so that EMR Studio can communicate with your virtual cluster.
See also: AWS API Documentation
Request Syntax
response = client.list_managed_endpoints(
virtualClusterId='string',
createdBefore=datetime(2015, 1, 1),
createdAfter=datetime(2015, 1, 1),
types=[
'string',
],
states=[
'CREATING'|'ACTIVE'|'TERMINATING'|'TERMINATED'|'TERMINATED_WITH_ERRORS',
],
maxResults=123,
nextToken='string'
)
[REQUIRED]
The ID of the virtual cluster.
The types of the managed endpoints.
The states of the managed endpoints.
dict
Response Syntax
{
'endpoints': [
{
'id': 'string',
'name': 'string',
'arn': 'string',
'virtualClusterId': 'string',
'type': 'string',
'state': 'CREATING'|'ACTIVE'|'TERMINATING'|'TERMINATED'|'TERMINATED_WITH_ERRORS',
'releaseLabel': 'string',
'executionRoleArn': 'string',
'certificateArn': 'string',
'certificateAuthority': {
'certificateArn': 'string',
'certificateData': 'string'
},
'configurationOverrides': {
'applicationConfiguration': [
{
'classification': 'string',
'properties': {
'string': 'string'
},
'configurations': {'... recursive ...'}
},
],
'monitoringConfiguration': {
'persistentAppUI': 'ENABLED'|'DISABLED',
'cloudWatchMonitoringConfiguration': {
'logGroupName': 'string',
'logStreamNamePrefix': 'string'
},
's3MonitoringConfiguration': {
'logUri': 'string'
}
}
},
'serverUrl': 'string',
'createdAt': datetime(2015, 1, 1),
'securityGroup': 'string',
'subnetIds': [
'string',
],
'stateDetails': 'string',
'failureReason': 'INTERNAL_ERROR'|'USER_ERROR'|'VALIDATION_ERROR'|'CLUSTER_UNAVAILABLE',
'tags': {
'string': 'string'
}
},
],
'nextToken': 'string'
}
Response Structure
(dict) --
endpoints (list) --
The managed endpoints to be listed.
(dict) --
This entity represents the endpoint that is managed by Amazon EMR on EKS.
id (string) --
The ID of the endpoint.
name (string) --
The name of the endpoint.
arn (string) --
The ARN of the endpoint.
virtualClusterId (string) --
The ID of the endpoint's virtual cluster.
type (string) --
The type of the endpoint.
state (string) --
The state of the endpoint.
releaseLabel (string) --
The EMR release version to be used for the endpoint.
executionRoleArn (string) --
The execution role ARN of the endpoint.
certificateArn (string) --
The certificate ARN of the endpoint. This field is under deprecation and will be removed in future.
certificateAuthority (dict) --
The certificate generated by emr control plane on customer behalf to secure the managed endpoint.
certificateArn (string) --
The ARN of the certificate generated for managed endpoint.
certificateData (string) --
The base64 encoded PEM certificate data generated for managed endpoint.
configurationOverrides (dict) --
The configuration settings that are used to override existing configurations for endpoints.
applicationConfiguration (list) --
The configurations for the application running by the job run.
(dict) --
A configuration specification to be used when provisioning virtual clusters, which can include configurations for applications and software bundled with Amazon EMR on EKS. A configuration consists of a classification, properties, and optional nested configurations. A classification refers to an application-specific configuration file. Properties are the settings you want to change in that file.
classification (string) --
The classification within a configuration.
properties (dict) --
A set of properties specified within a configuration classification.
configurations (list) --
A list of additional configurations to apply within a configuration object.
monitoringConfiguration (dict) --
The configurations for monitoring.
persistentAppUI (string) --
Monitoring configurations for the persistent application UI.
cloudWatchMonitoringConfiguration (dict) --
Monitoring configurations for CloudWatch.
logGroupName (string) --
The name of the log group for log publishing.
logStreamNamePrefix (string) --
The specified name prefix for log streams.
s3MonitoringConfiguration (dict) --
Amazon S3 configuration for monitoring log publishing.
logUri (string) --
Amazon S3 destination URI for log publishing.
serverUrl (string) --
The server URL of the endpoint.
createdAt (datetime) --
The date and time when the endpoint was created.
securityGroup (string) --
The security group configuration of the endpoint.
subnetIds (list) --
The subnet IDs of the endpoint.
stateDetails (string) --
Additional details of the endpoint state.
failureReason (string) --
The reasons why the endpoint has failed.
tags (dict) --
The tags of the endpoint.
nextToken (string) --
The token for the next set of endpoints to return.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.InternalServerException
Lists the tags assigned to the resources.
See also: AWS API Documentation
Request Syntax
response = client.list_tags_for_resource(
resourceArn='string'
)
[REQUIRED]
The ARN of tagged resources.
{
'tags': {
'string': 'string'
}
}
Response Structure
The tags assigned to resources.
Exceptions
EMRContainers.Client.exceptions.InternalServerException
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
list_virtual_clusters
(**kwargs)¶Lists information about the specified virtual cluster. Virtual cluster is a managed entity on Amazon EMR on EKS. You can create, describe, list and delete virtual clusters. They do not consume any additional resource in your system. A single virtual cluster maps to a single Kubernetes namespace. Given this relationship, you can model virtual clusters the same way you model Kubernetes namespaces to meet your requirements.
See also: AWS API Documentation
Request Syntax
response = client.list_virtual_clusters(
containerProviderId='string',
containerProviderType='EKS',
createdAfter=datetime(2015, 1, 1),
createdBefore=datetime(2015, 1, 1),
states=[
'RUNNING'|'TERMINATING'|'TERMINATED'|'ARRESTED',
],
maxResults=123,
nextToken='string'
)
The states of the requested virtual clusters.
dict
Response Syntax
{
'virtualClusters': [
{
'id': 'string',
'name': 'string',
'arn': 'string',
'state': 'RUNNING'|'TERMINATING'|'TERMINATED'|'ARRESTED',
'containerProvider': {
'type': 'EKS',
'id': 'string',
'info': {
'eksInfo': {
'namespace': 'string'
}
}
},
'createdAt': datetime(2015, 1, 1),
'tags': {
'string': 'string'
}
},
],
'nextToken': 'string'
}
Response Structure
(dict) --
virtualClusters (list) --
This output lists the specified virtual clusters.
(dict) --
This entity describes a virtual cluster. A virtual cluster is a Kubernetes namespace that Amazon EMR is registered with. Amazon EMR uses virtual clusters to run jobs and host endpoints. Multiple virtual clusters can be backed by the same physical cluster. However, each virtual cluster maps to one namespace on an EKS cluster. Virtual clusters do not create any active resources that contribute to your bill or that require lifecycle management outside the service.
id (string) --
The ID of the virtual cluster.
name (string) --
The name of the virtual cluster.
arn (string) --
The ARN of the virtual cluster.
state (string) --
The state of the virtual cluster.
containerProvider (dict) --
The container provider of the virtual cluster.
type (string) --
The type of the container provider. EKS is the only supported type as of now.
id (string) --
The ID of the container cluster.
info (dict) --
The information about the container cluster.
Note
This is a Tagged Union structure. Only one of the following top level keys will be set: eksInfo
. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER
as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER
is as follows:
'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
eksInfo (dict) --
The information about the EKS cluster.
namespace (string) --
The namespaces of the EKS cluster.
createdAt (datetime) --
The date and time when the virtual cluster is created.
tags (dict) --
The assigned tags of the virtual cluster.
nextToken (string) --
This output displays the token for the next set of virtual clusters.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.InternalServerException
start_job_run
(**kwargs)¶Starts a job run. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
See also: AWS API Documentation
Request Syntax
response = client.start_job_run(
name='string',
virtualClusterId='string',
clientToken='string',
executionRoleArn='string',
releaseLabel='string',
jobDriver={
'sparkSubmitJobDriver': {
'entryPoint': 'string',
'entryPointArguments': [
'string',
],
'sparkSubmitParameters': 'string'
},
'sparkSqlJobDriver': {
'entryPoint': 'string',
'sparkSqlParameters': 'string'
}
},
configurationOverrides={
'applicationConfiguration': [
{
'classification': 'string',
'properties': {
'string': 'string'
},
'configurations': {'... recursive ...'}
},
],
'monitoringConfiguration': {
'persistentAppUI': 'ENABLED'|'DISABLED',
'cloudWatchMonitoringConfiguration': {
'logGroupName': 'string',
'logStreamNamePrefix': 'string'
},
's3MonitoringConfiguration': {
'logUri': 'string'
}
}
},
tags={
'string': 'string'
}
)
[REQUIRED]
The virtual cluster ID for which the job run request is submitted.
[REQUIRED]
The client idempotency token of the job run request.
This field is autopopulated if not provided.
[REQUIRED]
The execution role ARN for the job run.
[REQUIRED]
The Amazon EMR release version to use for the job run.
[REQUIRED]
The job driver for the job run.
The job driver parameters specified for spark submit.
The entry point of job application.
The arguments for job application.
The Spark submit parameters that are used for job runs.
The job driver for job type.
The SQL file to be executed.
The Spark parameters to be included in the Spark SQL command.
The configuration overrides for the job run.
The configurations for the application running by the job run.
A configuration specification to be used when provisioning virtual clusters, which can include configurations for applications and software bundled with Amazon EMR on EKS. A configuration consists of a classification, properties, and optional nested configurations. A classification refers to an application-specific configuration file. Properties are the settings you want to change in that file.
The classification within a configuration.
A set of properties specified within a configuration classification.
A list of additional configurations to apply within a configuration object.
The configurations for monitoring.
Monitoring configurations for the persistent application UI.
Monitoring configurations for CloudWatch.
The name of the log group for log publishing.
The specified name prefix for log streams.
Amazon S3 configuration for monitoring log publishing.
Amazon S3 destination URI for log publishing.
The tags assigned to job runs.
dict
Response Syntax
{
'id': 'string',
'name': 'string',
'arn': 'string',
'virtualClusterId': 'string'
}
Response Structure
(dict) --
id (string) --
This output displays the started job run ID.
name (string) --
This output displays the name of the started job run.
arn (string) --
This output lists the ARN of job run.
virtualClusterId (string) --
This output displays the virtual cluster ID for which the job run was submitted.
Exceptions
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
EMRContainers.Client.exceptions.InternalServerException
tag_resource
(**kwargs)¶Assigns tags to resources. A tag is a label that you assign to an AWS resource. Each tag consists of a key and an optional value, both of which you define. Tags enable you to categorize your AWS resources by attributes such as purpose, owner, or environment. When you have many resources of the same type, you can quickly identify a specific resource based on the tags you've assigned to it. For example, you can define a set of tags for your Amazon EMR on EKS clusters to help you track each cluster's owner and stack level. We recommend that you devise a consistent set of tag keys for each resource type. You can then search and filter the resources based on the tags that you add.
See also: AWS API Documentation
Request Syntax
response = client.tag_resource(
resourceArn='string',
tags={
'string': 'string'
}
)
[REQUIRED]
The ARN of resources.
[REQUIRED]
The tags assigned to resources.
dict
Response Syntax
{}
Response Structure
Exceptions
EMRContainers.Client.exceptions.InternalServerException
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
untag_resource
(**kwargs)¶Removes tags from resources.
See also: AWS API Documentation
Request Syntax
response = client.untag_resource(
resourceArn='string',
tagKeys=[
'string',
]
)
[REQUIRED]
The ARN of resources.
[REQUIRED]
The tag keys of the resources.
dict
Response Syntax
{}
Response Structure
Exceptions
EMRContainers.Client.exceptions.InternalServerException
EMRContainers.Client.exceptions.ValidationException
EMRContainers.Client.exceptions.ResourceNotFoundException
The available paginators are:
EMRContainers.Paginator.ListJobRuns
EMRContainers.Paginator.ListManagedEndpoints
EMRContainers.Paginator.ListVirtualClusters
EMRContainers.Paginator.
ListJobRuns
¶paginator = client.get_paginator('list_job_runs')
paginate
(**kwargs)¶Creates an iterator that will paginate through responses from EMRContainers.Client.list_job_runs()
.
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
virtualClusterId='string',
createdBefore=datetime(2015, 1, 1),
createdAfter=datetime(2015, 1, 1),
name='string',
states=[
'PENDING'|'SUBMITTED'|'RUNNING'|'FAILED'|'CANCELLED'|'CANCEL_PENDING'|'COMPLETED',
],
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
The ID of the virtual cluster for which to list the job run.
The states of the job run.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken
will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken
from a previous response.
dict
Response Syntax
{
'jobRuns': [
{
'id': 'string',
'name': 'string',
'virtualClusterId': 'string',
'arn': 'string',
'state': 'PENDING'|'SUBMITTED'|'RUNNING'|'FAILED'|'CANCELLED'|'CANCEL_PENDING'|'COMPLETED',
'clientToken': 'string',
'executionRoleArn': 'string',
'releaseLabel': 'string',
'configurationOverrides': {
'applicationConfiguration': [
{
'classification': 'string',
'properties': {
'string': 'string'
},
'configurations': {'... recursive ...'}
},
],
'monitoringConfiguration': {
'persistentAppUI': 'ENABLED'|'DISABLED',
'cloudWatchMonitoringConfiguration': {
'logGroupName': 'string',
'logStreamNamePrefix': 'string'
},
's3MonitoringConfiguration': {
'logUri': 'string'
}
}
},
'jobDriver': {
'sparkSubmitJobDriver': {
'entryPoint': 'string',
'entryPointArguments': [
'string',
],
'sparkSubmitParameters': 'string'
},
'sparkSqlJobDriver': {
'entryPoint': 'string',
'sparkSqlParameters': 'string'
}
},
'createdAt': datetime(2015, 1, 1),
'createdBy': 'string',
'finishedAt': datetime(2015, 1, 1),
'stateDetails': 'string',
'failureReason': 'INTERNAL_ERROR'|'USER_ERROR'|'VALIDATION_ERROR'|'CLUSTER_UNAVAILABLE',
'tags': {
'string': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
jobRuns (list) --
This output lists information about the specified job runs.
(dict) --
This entity describes a job run. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
id (string) --
The ID of the job run.
name (string) --
The name of the job run.
virtualClusterId (string) --
The ID of the job run's virtual cluster.
arn (string) --
The ARN of job run.
state (string) --
The state of the job run.
clientToken (string) --
The client token used to start a job run.
executionRoleArn (string) --
The execution role ARN of the job run.
releaseLabel (string) --
The release version of Amazon EMR.
configurationOverrides (dict) --
The configuration settings that are used to override default configuration.
applicationConfiguration (list) --
The configurations for the application running by the job run.
(dict) --
A configuration specification to be used when provisioning virtual clusters, which can include configurations for applications and software bundled with Amazon EMR on EKS. A configuration consists of a classification, properties, and optional nested configurations. A classification refers to an application-specific configuration file. Properties are the settings you want to change in that file.
classification (string) --
The classification within a configuration.
properties (dict) --
A set of properties specified within a configuration classification.
configurations (list) --
A list of additional configurations to apply within a configuration object.
monitoringConfiguration (dict) --
The configurations for monitoring.
persistentAppUI (string) --
Monitoring configurations for the persistent application UI.
cloudWatchMonitoringConfiguration (dict) --
Monitoring configurations for CloudWatch.
logGroupName (string) --
The name of the log group for log publishing.
logStreamNamePrefix (string) --
The specified name prefix for log streams.
s3MonitoringConfiguration (dict) --
Amazon S3 configuration for monitoring log publishing.
logUri (string) --
Amazon S3 destination URI for log publishing.
jobDriver (dict) --
Parameters of job driver for the job run.
sparkSubmitJobDriver (dict) --
The job driver parameters specified for spark submit.
entryPoint (string) --
The entry point of job application.
entryPointArguments (list) --
The arguments for job application.
sparkSubmitParameters (string) --
The Spark submit parameters that are used for job runs.
sparkSqlJobDriver (dict) --
The job driver for job type.
entryPoint (string) --
The SQL file to be executed.
sparkSqlParameters (string) --
The Spark parameters to be included in the Spark SQL command.
createdAt (datetime) --
The date and time when the job run was created.
createdBy (string) --
The user who created the job run.
finishedAt (datetime) --
The date and time when the job run has finished.
stateDetails (string) --
Additional details of the job run state.
failureReason (string) --
The reasons why the job run has failed.
tags (dict) --
The assigned tags of the job run.
NextToken (string) --
A token to resume pagination.
EMRContainers.Paginator.
ListManagedEndpoints
¶paginator = client.get_paginator('list_managed_endpoints')
paginate
(**kwargs)¶Creates an iterator that will paginate through responses from EMRContainers.Client.list_managed_endpoints()
.
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
virtualClusterId='string',
createdBefore=datetime(2015, 1, 1),
createdAfter=datetime(2015, 1, 1),
types=[
'string',
],
states=[
'CREATING'|'ACTIVE'|'TERMINATING'|'TERMINATED'|'TERMINATED_WITH_ERRORS',
],
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
[REQUIRED]
The ID of the virtual cluster.
The types of the managed endpoints.
The states of the managed endpoints.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken
will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken
from a previous response.
dict
Response Syntax
{
'endpoints': [
{
'id': 'string',
'name': 'string',
'arn': 'string',
'virtualClusterId': 'string',
'type': 'string',
'state': 'CREATING'|'ACTIVE'|'TERMINATING'|'TERMINATED'|'TERMINATED_WITH_ERRORS',
'releaseLabel': 'string',
'executionRoleArn': 'string',
'certificateArn': 'string',
'certificateAuthority': {
'certificateArn': 'string',
'certificateData': 'string'
},
'configurationOverrides': {
'applicationConfiguration': [
{
'classification': 'string',
'properties': {
'string': 'string'
},
'configurations': {'... recursive ...'}
},
],
'monitoringConfiguration': {
'persistentAppUI': 'ENABLED'|'DISABLED',
'cloudWatchMonitoringConfiguration': {
'logGroupName': 'string',
'logStreamNamePrefix': 'string'
},
's3MonitoringConfiguration': {
'logUri': 'string'
}
}
},
'serverUrl': 'string',
'createdAt': datetime(2015, 1, 1),
'securityGroup': 'string',
'subnetIds': [
'string',
],
'stateDetails': 'string',
'failureReason': 'INTERNAL_ERROR'|'USER_ERROR'|'VALIDATION_ERROR'|'CLUSTER_UNAVAILABLE',
'tags': {
'string': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
endpoints (list) --
The managed endpoints to be listed.
(dict) --
This entity represents the endpoint that is managed by Amazon EMR on EKS.
id (string) --
The ID of the endpoint.
name (string) --
The name of the endpoint.
arn (string) --
The ARN of the endpoint.
virtualClusterId (string) --
The ID of the endpoint's virtual cluster.
type (string) --
The type of the endpoint.
state (string) --
The state of the endpoint.
releaseLabel (string) --
The EMR release version to be used for the endpoint.
executionRoleArn (string) --
The execution role ARN of the endpoint.
certificateArn (string) --
The certificate ARN of the endpoint. This field is under deprecation and will be removed in future.
certificateAuthority (dict) --
The certificate generated by emr control plane on customer behalf to secure the managed endpoint.
certificateArn (string) --
The ARN of the certificate generated for managed endpoint.
certificateData (string) --
The base64 encoded PEM certificate data generated for managed endpoint.
configurationOverrides (dict) --
The configuration settings that are used to override existing configurations for endpoints.
applicationConfiguration (list) --
The configurations for the application running by the job run.
(dict) --
A configuration specification to be used when provisioning virtual clusters, which can include configurations for applications and software bundled with Amazon EMR on EKS. A configuration consists of a classification, properties, and optional nested configurations. A classification refers to an application-specific configuration file. Properties are the settings you want to change in that file.
classification (string) --
The classification within a configuration.
properties (dict) --
A set of properties specified within a configuration classification.
configurations (list) --
A list of additional configurations to apply within a configuration object.
monitoringConfiguration (dict) --
The configurations for monitoring.
persistentAppUI (string) --
Monitoring configurations for the persistent application UI.
cloudWatchMonitoringConfiguration (dict) --
Monitoring configurations for CloudWatch.
logGroupName (string) --
The name of the log group for log publishing.
logStreamNamePrefix (string) --
The specified name prefix for log streams.
s3MonitoringConfiguration (dict) --
Amazon S3 configuration for monitoring log publishing.
logUri (string) --
Amazon S3 destination URI for log publishing.
serverUrl (string) --
The server URL of the endpoint.
createdAt (datetime) --
The date and time when the endpoint was created.
securityGroup (string) --
The security group configuration of the endpoint.
subnetIds (list) --
The subnet IDs of the endpoint.
stateDetails (string) --
Additional details of the endpoint state.
failureReason (string) --
The reasons why the endpoint has failed.
tags (dict) --
The tags of the endpoint.
NextToken (string) --
A token to resume pagination.
EMRContainers.Paginator.
ListVirtualClusters
¶paginator = client.get_paginator('list_virtual_clusters')
paginate
(**kwargs)¶Creates an iterator that will paginate through responses from EMRContainers.Client.list_virtual_clusters()
.
See also: AWS API Documentation
Request Syntax
response_iterator = paginator.paginate(
containerProviderId='string',
containerProviderType='EKS',
createdAfter=datetime(2015, 1, 1),
createdBefore=datetime(2015, 1, 1),
states=[
'RUNNING'|'TERMINATING'|'TERMINATED'|'ARRESTED',
],
PaginationConfig={
'MaxItems': 123,
'PageSize': 123,
'StartingToken': 'string'
}
)
The states of the requested virtual clusters.
A dictionary that provides parameters to control pagination.
The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken
will be provided in the output that you can use to resume pagination.
The size of each page.
A token to specify where to start paginating. This is the NextToken
from a previous response.
dict
Response Syntax
{
'virtualClusters': [
{
'id': 'string',
'name': 'string',
'arn': 'string',
'state': 'RUNNING'|'TERMINATING'|'TERMINATED'|'ARRESTED',
'containerProvider': {
'type': 'EKS',
'id': 'string',
'info': {
'eksInfo': {
'namespace': 'string'
}
}
},
'createdAt': datetime(2015, 1, 1),
'tags': {
'string': 'string'
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
virtualClusters (list) --
This output lists the specified virtual clusters.
(dict) --
This entity describes a virtual cluster. A virtual cluster is a Kubernetes namespace that Amazon EMR is registered with. Amazon EMR uses virtual clusters to run jobs and host endpoints. Multiple virtual clusters can be backed by the same physical cluster. However, each virtual cluster maps to one namespace on an EKS cluster. Virtual clusters do not create any active resources that contribute to your bill or that require lifecycle management outside the service.
id (string) --
The ID of the virtual cluster.
name (string) --
The name of the virtual cluster.
arn (string) --
The ARN of the virtual cluster.
state (string) --
The state of the virtual cluster.
containerProvider (dict) --
The container provider of the virtual cluster.
type (string) --
The type of the container provider. EKS is the only supported type as of now.
id (string) --
The ID of the container cluster.
info (dict) --
The information about the container cluster.
Note
This is a Tagged Union structure. Only one of the following top level keys will be set: eksInfo
. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER
as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER
is as follows:
'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
eksInfo (dict) --
The information about the EKS cluster.
namespace (string) --
The namespaces of the EKS cluster.
createdAt (datetime) --
The date and time when the virtual cluster is created.
tags (dict) --
The assigned tags of the virtual cluster.
NextToken (string) --
A token to resume pagination.