Source code for airflow.providers.amazon.aws.operators.sagemaker_processing
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[docs]classSageMakerProcessingOperator(SageMakerBaseOperator):""" Initiate a SageMaker processing job. This operator returns The ARN of the processing job created in Amazon SageMaker. :param config: The configuration necessary to start a processing job (templated). For details of the configuration parameter see :py:meth:`SageMaker.Client.create_processing_job` :type config: dict :param aws_conn_id: The AWS connection ID to use. :type aws_conn_id: str :param wait_for_completion: If wait is set to True, the time interval, in seconds, that the operation waits to check the status of the processing job. :type wait_for_completion: bool :param print_log: if the operator should print the cloudwatch log during processing :type print_log: bool :param check_interval: if wait is set to be true, this is the time interval in seconds which the operator will check the status of the processing job :type check_interval: int :param max_ingestion_time: If wait is set to True, the operation fails if the processing job doesn't finish within max_ingestion_time seconds. If you set this parameter to None, the operation does not timeout. :type max_ingestion_time: int :param action_if_job_exists: Behaviour if the job name already exists. Possible options are "increment" (default) and "fail". :type action_if_job_exists: str """def__init__(self,*,config:dict,aws_conn_id:str,wait_for_completion:bool=True,print_log:bool=True,check_interval:int=30,max_ingestion_time:Optional[int]=None,action_if_job_exists:str="increment",# TODO use typing.Literal for this in Python 3.8**kwargs,):super().__init__(config=config,aws_conn_id=aws_conn_id,**kwargs)ifaction_if_job_existsnotin("increment","fail"):raiseAirflowException("Argument action_if_job_exists accepts only 'increment' and 'fail'. "f"Provided value: '{action_if_job_exists}'.")self.action_if_job_exists=action_if_job_existsself.wait_for_completion=wait_for_completionself.print_log=print_logself.check_interval=check_intervalself.max_ingestion_time=max_ingestion_timeself._create_integer_fields()def_create_integer_fields(self)->None:"""Set fields which should be casted to integers."""self.integer_fields=[['ProcessingResources','ClusterConfig','InstanceCount'],['ProcessingResources','ClusterConfig','VolumeSizeInGB'],]if'StoppingCondition'inself.config:self.integer_fields+=[['StoppingCondition','MaxRuntimeInSeconds']]