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)