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:

Create necessary resources using AWS Console or AWS CLI.
Install API libraries via pip.
pip install 'apache-airflow[amazon]'
Detailed information is available Installation of Airflow™
Setup Connection.

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/providers/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/providers/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,
)

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/providers/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/providers/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/providers/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={"RUNNING"},
)

Wait on an EMR Serverless Application state¶

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

tests/system/providers/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¶

Was this entry helpful?