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chore: routine sample maintenance (GoogleCloudPlatform#5678)
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composer/workflows/hadoop_tutorial.py

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cluster_name='composer-hadoop-tutorial-cluster-{{ ds_nodash }}',
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num_workers=2,
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zone=models.Variable.get('gce_zone'),
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master_machine_type='n1-standard-1',
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worker_machine_type='n1-standard-1')
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master_machine_type='n1-standard-2',
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worker_machine_type='n1-standard-2')
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# Run the Hadoop wordcount example installed on the Cloud Dataproc cluster
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# master node.

composer/workflows/kubernetes_pod_operator.py

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# Key of a secret stored in this Secret object
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key='sql_alchemy_conn')
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secret_volume = secret.Secret(
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'volume',
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deploy_type='volume',
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# Path where we mount the secret as volume
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'/var/secrets/google',
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deploy_target='/var/secrets/google',
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# Name of Kubernetes Secret
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'service-account',
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secret='service-account',
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# Key in the form of service account file name
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'service-account.json')
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key='service-account.json')
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# [END composer_kubernetespodoperator_secretobject]
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YESTERDAY = datetime.datetime.now() - datetime.timedelta(days=1)
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# resources = pod.Resources() instead passing a dict
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# For more info see:
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# https://github.com/apache/airflow/pull/4551
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resources={'limit_memory': 1, 'limit_cpu': 1},
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resources={'limit_memory': "250M", 'limit_cpu': "100m"},
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# Specifies path to kubernetes config. If no config is specified will
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# default to '~/.kube/config'. The config_file is templated.
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config_file='/home/airflow/composer_kube_config',

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