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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 (
EmrAddStepsOperator,
EmrCreateJobFlowOperator,
EmrModifyClusterOperator,
EmrTerminateJobFlowOperator,
)
from airflow.providers.amazon.aws.sensors.emr import EmrJobFlowSensor, EmrStepSensor
[docs]JOB_FLOW_ROLE = os.getenv('EMR_JOB_FLOW_ROLE', 'EMR_EC2_DefaultRole')
[docs]SERVICE_ROLE = os.getenv('EMR_SERVICE_ROLE', 'EMR_DefaultRole')
# [START howto_operator_emr_steps_config]
[docs]SPARK_STEPS = [
{
'Name': 'calculate_pi',
'ActionOnFailure': 'CONTINUE',
'HadoopJarStep': {
'Jar': 'command-runner.jar',
'Args': ['/usr/lib/spark/bin/run-example', 'SparkPi', '10'],
},
}
]
[docs]JOB_FLOW_OVERRIDES = {
'Name': 'PiCalc',
'ReleaseLabel': 'emr-5.29.0',
'Applications': [{'Name': 'Spark'}],
'Instances': {
'InstanceGroups': [
{
'Name': 'Primary node',
'Market': 'ON_DEMAND',
'InstanceRole': 'MASTER',
'InstanceType': 'm5.xlarge',
'InstanceCount': 1,
},
],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False,
},
'Steps': SPARK_STEPS,
'JobFlowRole': JOB_FLOW_ROLE,
'ServiceRole': SERVICE_ROLE,
}
# [END howto_operator_emr_steps_config]
with DAG(
dag_id='example_emr',
schedule_interval=None,
start_date=datetime(2021, 1, 1),
tags=['example'],
catchup=False,
) as dag:
# [START howto_operator_emr_create_job_flow]
[docs] job_flow_creator = EmrCreateJobFlowOperator(
task_id='create_job_flow',
job_flow_overrides=JOB_FLOW_OVERRIDES,
)
# [END howto_operator_emr_create_job_flow]
# [START howto_sensor_emr_job_flow]
job_sensor = EmrJobFlowSensor(
task_id='check_job_flow',
job_flow_id=job_flow_creator.output,
)
# [END howto_sensor_emr_job_flow]
# [START howto_operator_emr_modify_cluster]
cluster_modifier = EmrModifyClusterOperator(
task_id='modify_cluster', cluster_id=job_flow_creator.output, step_concurrency_level=1
)
# [END howto_operator_emr_modify_cluster]
# [START howto_operator_emr_add_steps]
step_adder = EmrAddStepsOperator(
task_id='add_steps',
job_flow_id=job_flow_creator.output,
steps=SPARK_STEPS,
)
# [END howto_operator_emr_add_steps]
# [START howto_sensor_emr_step]
step_checker = EmrStepSensor(
task_id='watch_step',
job_flow_id=job_flow_creator.output,
step_id="{{ task_instance.xcom_pull(task_ids='add_steps', key='return_value')[0] }}",
)
# [END howto_sensor_emr_step]
# [START howto_operator_emr_terminate_job_flow]
cluster_remover = EmrTerminateJobFlowOperator(
task_id='remove_cluster',
job_flow_id=job_flow_creator.output,
)
# [END howto_operator_emr_terminate_job_flow]
chain(
job_flow_creator,
job_sensor,
cluster_modifier,
step_adder,
step_checker,
cluster_remover,
)
