Source code for airflow.contrib.operators.awsbatch_operator

# -*- coding: utf-8 -*-
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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# http://www.apache.org/licenses/LICENSE-2.0
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import sys

from math import pow
from time import sleep

from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.utils import apply_defaults

from airflow.contrib.hooks.aws_hook import AwsHook


[docs]class AWSBatchOperator(BaseOperator): """ Execute a job on AWS Batch Service :param job_name: the name for the job that will run on AWS Batch :type job_name: str :param job_definition: the job definition name on AWS Batch :type job_definition: str :param queue: the queue name on AWS Batch :type queue: str :param: overrides: the same parameter that boto3 will receive on containerOverrides: http://boto3.readthedocs.io/en/latest/reference/services/batch.html#submit_job :type: overrides: dict :param max_retries: exponential backoff retries while waiter is not merged :type max_retries: int :param aws_conn_id: connection id of AWS credentials / region name. If None, credential boto3 strategy will be used (http://boto3.readthedocs.io/en/latest/guide/configuration.html). :type aws_conn_id: str :param region_name: region name to use in AWS Hook. Override the region_name in connection (if provided) """ ui_color = '#c3dae0' client = None arn = None template_fields = ('overrides',) @apply_defaults def __init__(self, job_name, job_definition, queue, overrides, max_retries=288, aws_conn_id=None, region_name=None, **kwargs): super(AWSBatchOperator, self).__init__(**kwargs) self.job_name = job_name self.aws_conn_id = aws_conn_id self.region_name = region_name self.job_definition = job_definition self.queue = queue self.overrides = overrides self.max_retries = max_retries self.jobId = None self.jobName = None self.hook = self.get_hook() def execute(self, context): self.log.info( 'Running AWS Batch Job - Job definition: %s - on queue %s', self.job_definition, self.queue ) self.log.info('AWSBatchOperator overrides: %s', self.overrides) self.client = self.hook.get_client_type( 'batch', region_name=self.region_name ) try: response = self.client.submit_job( jobName=self.job_name, jobQueue=self.queue, jobDefinition=self.job_definition, containerOverrides=self.overrides) self.log.info('AWS Batch Job started: %s', response) self.jobId = response['jobId'] self.jobName = response['jobName'] self._wait_for_task_ended() self._check_success_task() self.log.info('AWS Batch Job has been successfully executed: %s', response) except Exception as e: self.log.info('AWS Batch Job has failed executed') raise AirflowException(e) def _wait_for_task_ended(self): """ Try to use a waiter from the below pull request * https://github.com/boto/botocore/pull/1307 If the waiter is not available apply a exponential backoff * docs.aws.amazon.com/general/latest/gr/api-retries.html """ try: waiter = self.client.get_waiter('job_execution_complete') waiter.config.max_attempts = sys.maxsize # timeout is managed by airflow waiter.wait(jobs=[self.jobId]) except ValueError: # If waiter not available use expo retry = True retries = 0 while retries < self.max_retries or retry: response = self.client.describe_jobs( jobs=[self.jobId] ) if response['jobs'][-1]['status'] in ['SUCCEEDED', 'FAILED']: retry = False sleep(pow(2, retries) * 100) retries += 1 def _check_success_task(self): response = self.client.describe_jobs( jobs=[self.jobId], ) self.log.info('AWS Batch stopped, check status: %s', response) if len(response.get('jobs')) < 1: raise AirflowException('No job found for {}'.format(response)) for job in response['jobs']: if 'attempts' in job: containers = job['attempts'] for container in containers: if (job['status'] == 'FAILED' or container['container']['exitCode'] != 0): print("@@@@") raise AirflowException('This containers encounter an error during execution {}'.format(job)) elif job['status'] is not 'SUCCEEDED': raise AirflowException('This task is still pending {}'.format(job['status'])) def get_hook(self): return AwsHook( aws_conn_id=self.aws_conn_id ) def on_kill(self): response = self.client.terminate_job( jobId=self.jobId, reason='Task killed by the user') self.log.info(response)