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An Airflow operator for AWS Batch services

.. seealso::

import warnings
from typing import TYPE_CHECKING, Any, Optional, Sequence

from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from import BatchClientHook

    from airflow.utils.context import Context

[docs]class BatchOperator(BaseOperator): """ Execute a job on AWS Batch .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BatchOperator` :param job_name: the name for the job that will run on AWS Batch (templated) :param job_definition: the job definition name on AWS Batch :param job_queue: the queue name on AWS Batch :param overrides: the `containerOverrides` parameter for boto3 (templated) :param array_properties: the `arrayProperties` parameter for boto3 :param parameters: the `parameters` for boto3 (templated) :param job_id: the job ID, usually unknown (None) until the submit_job operation gets the jobId defined by AWS Batch :param waiters: an :py:class:`.BatchWaiters` object (see note below); if None, polling is used with max_retries and status_retries. :param max_retries: exponential back-off retries, 4200 = 48 hours; polling is only used when waiters is None :param status_retries: number of HTTP retries to get job status, 10; polling is only used when waiters is None :param aws_conn_id: connection id of AWS credentials / region name. If None, credential boto3 strategy will be used. :param region_name: region name to use in AWS Hook. Override the region_name in connection (if provided) :param tags: 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") """
[docs] ui_color = "#c3dae0"
[docs] arn = None # type: Optional[str]
[docs] template_fields: Sequence[str] = ( "job_name", "overrides", "parameters",
[docs] template_fields_renderers = {"overrides": "json", "parameters": "json"}
def __init__( self, *, job_name: str, job_definition: str, job_queue: str, overrides: dict, array_properties: Optional[dict] = None, parameters: Optional[dict] = None, job_id: Optional[str] = None, waiters: Optional[Any] = None, max_retries: Optional[int] = None, status_retries: Optional[int] = None, aws_conn_id: Optional[str] = None, region_name: Optional[str] = None, tags: Optional[dict] = None, **kwargs, ): BaseOperator.__init__(self, **kwargs) self.job_id = job_id self.job_name = job_name self.job_definition = job_definition self.job_queue = job_queue self.overrides = overrides or {} self.array_properties = array_properties or {} self.parameters = parameters or {} self.waiters = waiters self.tags = tags or {} self.hook = BatchClientHook( max_retries=max_retries, status_retries=status_retries, aws_conn_id=aws_conn_id, region_name=region_name, )
[docs] def execute(self, context: 'Context'): """ Submit and monitor an AWS Batch job :raises: AirflowException """ self.submit_job(context) self.monitor_job(context)
[docs] def on_kill(self): response = self.hook.client.terminate_job(jobId=self.job_id, reason="Task killed by the user")"AWS Batch job (%s) terminated: %s", self.job_id, response)
[docs] def submit_job(self, context: 'Context'): """ Submit an AWS Batch job :raises: AirflowException """ "Running AWS Batch job - job definition: %s - on queue %s", self.job_definition, self.job_queue, )"AWS Batch job - container overrides: %s", self.overrides) try: response = self.hook.client.submit_job( jobName=self.job_name, jobQueue=self.job_queue, jobDefinition=self.job_definition, arrayProperties=self.array_properties, parameters=self.parameters, containerOverrides=self.overrides, tags=self.tags, ) self.job_id = response["jobId"]"AWS Batch job (%s) started: %s", self.job_id, response) except Exception as e: self.log.error("AWS Batch job (%s) failed submission", self.job_id) raise AirflowException(e)
[docs] def monitor_job(self, context: 'Context'): """ 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 instead of here like it was previously done :raises: AirflowException """ if not self.job_id: raise AirflowException('AWS Batch job - job_id was not found') if self.waiters: self.waiters.wait_for_job(self.job_id) else: self.hook.wait_for_job(self.job_id) self.hook.check_job_success(self.job_id)"AWS Batch job (%s) succeeded", self.job_id)
[docs]class AwsBatchOperator(BatchOperator): """ This operator is deprecated. Please use :class:``. """ def __init__(self, *args, **kwargs): warnings.warn( "This operator is deprecated. " "Please use :class:``.", DeprecationWarning, stacklevel=2, ) super().__init__(*args, **kwargs)

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