Source code for airflow.providers.amazon.aws.example_dags.example_emr_eks

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import os
from datetime import datetime

from airflow import DAG
from airflow.models.baseoperator import chain
from airflow.providers.amazon.aws.operators.emr import EmrContainerOperator
from airflow.providers.amazon.aws.sensors.emr import EmrContainerSensor

[docs]VIRTUAL_CLUSTER_ID = os.getenv("VIRTUAL_CLUSTER_ID", "test-cluster")
[docs]JOB_ROLE_ARN = os.getenv("JOB_ROLE_ARN", "arn:aws:iam::012345678912:role/emr_eks_default_role")
# [START howto_operator_emr_eks_config]
[docs]JOB_DRIVER_ARG = { "sparkSubmitJobDriver": { "entryPoint": "local:///usr/lib/spark/examples/src/main/python/pi.py", "sparkSubmitParameters": "--conf spark.executors.instances=2 --conf spark.executors.memory=2G --conf spark.executor.cores=2 --conf spark.driver.cores=1", # noqa: E501
} }
[docs]CONFIGURATION_OVERRIDES_ARG = { "applicationConfiguration": [ { "classification": "spark-defaults", "properties": { "spark.hadoop.hive.metastore.client.factory.class": "com.amazonaws.glue.catalog.metastore.AWSGlueDataCatalogHiveClientFactory", # noqa: E501 }, } ], "monitoringConfiguration": { "cloudWatchMonitoringConfiguration": { "logGroupName": "/aws/emr-eks-spark", "logStreamNamePrefix": "airflow",
} }, } # [END howto_operator_emr_eks_config] with DAG( dag_id='example_emr_eks', schedule_interval=None, start_date=datetime(2021, 1, 1), tags=['example'], catchup=False, ) as dag: # [START howto_operator_emr_container]
[docs] job_starter = EmrContainerOperator( task_id="start_job", virtual_cluster_id=VIRTUAL_CLUSTER_ID, execution_role_arn=JOB_ROLE_ARN, release_label="emr-6.3.0-latest", job_driver=JOB_DRIVER_ARG, configuration_overrides=CONFIGURATION_OVERRIDES_ARG, name="pi.py", wait_for_completion=False,
) # [END howto_operator_emr_container] # [START howto_sensor_emr_container] job_waiter = EmrContainerSensor( task_id="job_waiter", virtual_cluster_id=VIRTUAL_CLUSTER_ID, job_id=str(job_starter.output) ) # [END howto_sensor_emr_container] chain(job_starter, job_waiter)

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