Source code for airflow.providers.amazon.aws.operators.sagemaker_processing

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from typing import Optional

from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook
from airflow.providers.amazon.aws.operators.sagemaker_base import SageMakerBaseOperator
from airflow.utils.decorators import apply_defaults


[docs]class SageMakerProcessingOperator(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 """ @apply_defaults 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) if action_if_job_exists not in ("increment", "fail"): raise AirflowException( "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_exists self.wait_for_completion = wait_for_completion self.print_log = print_log self.check_interval = check_interval self.max_ingestion_time = max_ingestion_time self._create_integer_fields()
[docs] 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' in self.config: self.integer_fields += [['StoppingCondition', 'MaxRuntimeInSeconds']]
[docs] def expand_role(self) -> None: if 'RoleArn' in self.config: hook = AwsBaseHook(self.aws_conn_id, client_type='iam') self.config['RoleArn'] = hook.expand_role(self.config['RoleArn'])
[docs] def execute(self, context) -> dict: self.preprocess_config() processing_job_name = self.config["ProcessingJobName"] processing_jobs = self.hook.list_processing_jobs(NameContains=processing_job_name) # Check if given ProcessingJobName already exists if processing_job_name in [pj["ProcessingJobName"] for pj in processing_jobs]: if self.action_if_job_exists == "fail": raise AirflowException( f"A SageMaker processing job with name {processing_job_name} already exists." ) if self.action_if_job_exists == "increment": self.log.info("Found existing processing job with name '%s'.", processing_job_name) new_processing_job_name = f"{processing_job_name}-{len(processing_jobs) + 1}" self.config["ProcessingJobName"] = new_processing_job_name self.log.info("Incremented processing job name to '%s'.", new_processing_job_name) self.log.info("Creating SageMaker processing job %s.", self.config["ProcessingJobName"]) response = self.hook.create_processing_job( self.config, wait_for_completion=self.wait_for_completion, check_interval=self.check_interval, max_ingestion_time=self.max_ingestion_time, ) if response['ResponseMetadata']['HTTPStatusCode'] != 200: raise AirflowException('Sagemaker Processing Job creation failed: %s' % response) return {'Processing': self.hook.describe_processing_job(self.config['ProcessingJobName'])}

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