airflow.providers.amazon.aws.operators.batch

An Airflow operator for AWS Batch services

See also

Module Contents

Classes

BatchOperator

Execute a job on AWS Batch

AwsBatchOperator

This operator is deprecated.
class airflow.providers.amazon.aws.operators.batch.BatchOperator(*, job_name, job_definition, job_queue, overrides, array_properties=None, parameters=None, job_id=None, waiters=None, max_retries=None, status_retries=None, aws_conn_id=None, region_name=None, tags=None, **kwargs)[source]

Bases: airflow.models.BaseOperator

Execute a job on AWS Batch

See also

For more information on how to use this operator, take a look at the guide: Submit a new AWS Batch job

Parameters

  • job_name (str) – the name for the job that will run on AWS Batch (templated)

  • job_definition (str) – the job definition name on AWS Batch

  • job_queue (str) – the queue name on AWS Batch

  • overrides (dict) – the containerOverrides parameter for boto3 (templated)

  • array_properties (Optional[dict]) – the arrayProperties parameter for boto3

  • parameters (Optional[dict]) – the parameters for boto3 (templated)

  • job_id (Optional[str]) – the job ID, usually unknown (None) until the submit_job operation gets the jobId defined by AWS Batch

  • waiters (Optional[Any]) – an BatchWaiters object (see note below); if None, polling is used with max_retries and status_retries.

  • max_retries (Optional[int]) – exponential back-off retries, 4200 = 48 hours; polling is only used when waiters is None

  • status_retries (Optional[int]) – number of HTTP retries to get job status, 10; polling is only used when waiters is None

  • aws_conn_id (Optional[str]) – connection id of AWS credentials / region name. If None, credential boto3 strategy will be used.

  • region_name (Optional[str]) – region name to use in AWS Hook. Override the region_name in connection (if provided)

  • tags (Optional[dict]) – collection of tags to apply to the AWS Batch job submission if None, no tags are submitted

Note

Any custom waiters must return a waiter for these calls: .. code-block:: python

waiter = waiters.get_waiter(“JobExists”) waiter = waiters.get_waiter(“JobRunning”) waiter = waiters.get_waiter(“JobComplete”)

ui_color = #c3dae0[source]
arn :Optional[str][source]
template_fields :Sequence[str] = ['job_name', 'overrides', 'parameters'][source]
template_fields_renderers[source]
execute(self, context)[source]

Submit and monitor an AWS Batch job

Raises

AirflowException

on_kill(self)[source]

Override this method to cleanup subprocesses when a task instance gets killed. Any use of the threading, subprocess or multiprocessing module within an operator needs to be cleaned up or it will leave ghost processes behind.

submit_job(self, context)[source]

Submit an AWS Batch job

Raises

AirflowException

monitor_job(self, context)[source]

Monitor an AWS Batch job monitor_job can raise an exception or an AirflowTaskTimeout can be raised if execution_timeout is given while creating the task. These exceptions should be handled in taskinstance.py instead of here like it was previously done

Raises

AirflowException

class airflow.providers.amazon.aws.operators.batch.AwsBatchOperator(*args, **kwargs)[source]

Bases: BatchOperator

This operator is deprecated. Please use airflow.providers.amazon.aws.operators.batch.BatchOperator.

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