:py:mod:`astronomer.providers.amazon.aws.operators.emr`
=======================================================

.. py:module:: astronomer.providers.amazon.aws.operators.emr


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   astronomer.providers.amazon.aws.operators.emr.EmrContainerOperatorAsync




.. py:class:: EmrContainerOperatorAsync(*, name, virtual_cluster_id, execution_role_arn, release_label, job_driver, configuration_overrides = None, client_request_token = None, aws_conn_id = 'aws_default', wait_for_completion = True, poll_interval = 30, max_tries = None, tags = None, max_polling_attempts = None, **kwargs)

   Bases: :py:obj:`airflow.providers.amazon.aws.operators.emr.EmrContainerOperator`

   An async operator that submits jobs to EMR on EKS virtual clusters.

   :param name: The name of the job run.
   :param virtual_cluster_id: The EMR on EKS virtual cluster ID
   :param execution_role_arn: The IAM role ARN associated with the job run.
   :param release_label: The Amazon EMR release version to use for the job run.
   :param job_driver: Job configuration details, e.g. the Spark job parameters.
   :param configuration_overrides: The configuration overrides for the job run,
       specifically either application configuration or monitoring configuration.
   :param client_request_token: The client idempotency token of the job run request.
       Use this if you want to specify a unique ID to prevent two jobs from getting started.
       If no token is provided, a UUIDv4 token will be generated for you.
   :param aws_conn_id: The Airflow connection used for AWS credentials.
   :param poll_interval: Time (in seconds) to wait between two consecutive calls to check query status on EMR
   :param max_tries: Deprecated - use max_polling_attempts instead.
   :param max_polling_attempts: Maximum number of times to wait for the job run to finish.
       Defaults to None, which will poll until the job is *not* in a pending, submitted, or running state.
   :param tags: The tags assigned to job runs. Defaults to None

   .. py:method:: execute(context)

      Deferred and give control to trigger


   .. py:method:: execute_complete(context, event)

      Callback for when the trigger fires - returns immediately.
      Relies on trigger to throw an exception, otherwise it assumes execution was
      successful.