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Amazon EMR Serverless Operators

Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers. You get all the features and benefits of Amazon EMR without the need for experts to plan and manage clusters.

Prerequisite Tasks

To use these operators, you must do a few things:

Generic Parameters

aws_conn_id

Reference to Amazon Web Services Connection ID. If this parameter is set to None then the default boto3 behaviour is used without a connection lookup. Otherwise use the credentials stored in the Connection. Default: aws_default

region_name

AWS Region Name. If this parameter is set to None or omitted then region_name from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

verify

Whether or not to verify SSL certificates.

  • False - Do not validate SSL certificates.

  • path/to/cert/bundle.pem - A filename of the CA cert bundle to use. You can specify this argument if you want to use a different CA cert bundle than the one used by botocore.

If this parameter is set to None or is omitted then verify from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

botocore_config

The provided dictionary is used to construct a botocore.config.Config. This configuration can be used to configure Avoid Throttling exceptions, timeouts, etc.

Example, for more detail about parameters please have a look botocore.config.Config
{
    "signature_version": "unsigned",
    "s3": {
        "us_east_1_regional_endpoint": True,
    },
    "retries": {
      "mode": "standard",
      "max_attempts": 10,
    },
    "connect_timeout": 300,
    "read_timeout": 300,
    "tcp_keepalive": True,
}

If this parameter is set to None or omitted then config_kwargs from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

Note

Specifying an empty dictionary, {}, will overwrite the connection configuration for botocore.config.Config

Operators

Create an EMR Serverless Application

You can use EmrServerlessCreateApplicationOperator to create a new EMR Serverless Application. This operator can be run in deferrable mode by passing deferrable=True as a parameter. This requires the aiobotocore module to be installed.

tests/system/amazon/aws/example_emr_serverless.py[source]

emr_serverless_app = EmrServerlessCreateApplicationOperator(
    task_id="create_emr_serverless_task",
    release_label="emr-6.6.0",
    job_type="SPARK",
    config={"name": "new_application"},
)

Start an EMR Serverless Job

You can use EmrServerlessStartJobOperator to start an EMR Serverless Job. This operator can be run in deferrable mode by passing deferrable=True as a parameter. This requires the aiobotocore module to be installed.

tests/system/amazon/aws/example_emr_serverless.py[source]

start_job = EmrServerlessStartJobOperator(
    task_id="start_emr_serverless_job",
    application_id=emr_serverless_app_id,
    execution_role_arn=role_arn,
    job_driver=SPARK_JOB_DRIVER,
    configuration_overrides=SPARK_CONFIGURATION_OVERRIDES,
)

Open Application UIs

The operator can also be configured to generate one-time links to the application UIs and Spark stdout logs by passing the enable_application_ui_links=True as a parameter. Once the job starts running, these links are available in the Details section of the relevant Task. If enable_application_ui_links=False then the links will be present but grayed out.

You need to ensure you have the following IAM permissions to generate the dashboard link.

"emr-serverless:GetDashboardForJobRun"

If Amazon S3 or Amazon CloudWatch logs are enabled for EMR Serverless, links to the respective console will also be available in the task logs and task Details.

Stop an EMR Serverless Application

You can use EmrServerlessStopApplicationOperator to stop an EMR Serverless Application. This operator can be run in deferrable mode by passing deferrable=True as a parameter. This requires the aiobotocore module to be installed.

tests/system/amazon/aws/example_emr_serverless.py[source]

stop_app = EmrServerlessStopApplicationOperator(
    task_id="stop_application",
    application_id=emr_serverless_app_id,
    force_stop=True,
)

Delete an EMR Serverless Application

You can use EmrServerlessDeleteApplicationOperator to delete an EMR Serverless Application. This operator can be run in deferrable mode by passing deferrable=True as a parameter. This requires the aiobotocore module to be installed.

tests/system/amazon/aws/example_emr_serverless.py[source]

delete_app = EmrServerlessDeleteApplicationOperator(
    task_id="delete_application",
    application_id=emr_serverless_app_id,
)

Sensors

Wait on an EMR Serverless Job state

To monitor the state of an EMR Serverless Job you can use EmrServerlessJobSensor.

tests/system/amazon/aws/example_emr_serverless.py[source]

wait_for_job = EmrServerlessJobSensor(
    task_id="wait_for_job",
    application_id=emr_serverless_app_id,
    job_run_id=start_job.output,
    # the default is to wait for job completion, here we just wait for the job to be running.
    target_states={*EmrServerlessHook.JOB_SUCCESS_STATES, "RUNNING"},
)

Wait on an EMR Serverless Application state

To monitor the state of an EMR Serverless Application you can use EmrServerlessApplicationSensor.

tests/system/amazon/aws/example_emr_serverless.py[source]

wait_for_app_creation = EmrServerlessApplicationSensor(
    task_id="wait_for_app_creation",
    application_id=emr_serverless_app_id,
)

Reference

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