Python 2.7.12
boto3==1.3.1
How can I add a step to a running EMR cluster and have the cluster terminated after the step is complete, regardless of it fails or succeeds?
Create the cluster
response = client.run_job_flow(
Name=name,
LogUri='s3://mybucket/emr/',
ReleaseLabel='emr-5.9.0',
Instances={
'MasterInstanceType': instance_type,
'SlaveInstanceType': instance_type,
'InstanceCount': instance_count,
'KeepJobFlowAliveWhenNoSteps': True,
'Ec2KeyName': 'KeyPair',
'EmrManagedSlaveSecurityGroup': 'sg-1234',
'EmrManagedMasterSecurityGroup': 'sg-1234',
'Ec2SubnetId': 'subnet-1q234',
},
Applications=[
{'Name': 'Spark'},
{'Name': 'Hadoop'}
],
BootstrapActions=[
{
'Name': 'Install Python packages',
'ScriptBootstrapAction': {
'Path': 's3://mybucket/code/spark/bootstrap_spark_cluster.sh'
}
}
],
VisibleToAllUsers=True,
JobFlowRole='EMR_EC2_DefaultRole',
ServiceRole='EMR_DefaultRole',
Configurations=[
{
'Classification': 'spark',
'Properties': {
'maximizeResourceAllocation': 'true'
}
},
],
)
Add a step
response = client.add_job_flow_steps(
JobFlowId=cluster_id,
Steps=[
{
'Name': 'Run Step',
'ActionOnFailure': 'TERMINATE_CLUSTER',
'HadoopJarStep': {
'Args': [
'spark-submit',
'--deploy-mode', 'cluster',
'--py-files',
's3://mybucket/code/spark/spark_udfs.py',
's3://mybucket/code/spark/{}'.format(spark_script),
'--some-arg'
],
'Jar': 'command-runner.jar'
}
}
]
)
This successfully adds a step and runs, however, when the step completes successfully, I would like the cluster to auto-terminate as noted in the AWS CLI: http://docs.aws.amazon.com/cli/latest/reference/emr/create-cluster.html