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#
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from datetime import datetime
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from airflow.providers.amazon.aws.operators.emr import (
EmrServerlessCreateApplicationOperator,
EmrServerlessDeleteApplicationOperator,
EmrServerlessStartJobOperator,
)
from airflow.providers.amazon.aws.operators.s3 import S3CreateBucketOperator, S3DeleteBucketOperator
from airflow.providers.amazon.aws.sensors.emr import EmrServerlessApplicationSensor, EmrServerlessJobSensor
from airflow.utils.trigger_rule import TriggerRule
from tests.system.providers.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
[docs]DAG_ID = 'example_emr_serverless'
# Externally fetched variables:
[docs]ROLE_ARN_KEY = 'ROLE_ARN'
[docs]sys_test_context_task = SystemTestContextBuilder().add_variable(ROLE_ARN_KEY).build()
with DAG(
dag_id=DAG_ID,
schedule_interval='@once',
start_date=datetime(2021, 1, 1),
tags=['example'],
catchup=False,
) as dag:
[docs] test_context = sys_test_context_task()
env_id = test_context[ENV_ID_KEY]
role_arn = test_context[ROLE_ARN_KEY]
bucket_name = f'{env_id}-emr-serverless-bucket'
entryPoint = "s3://us-east-1.elasticmapreduce/emr-containers/samples/wordcount/scripts/wordcount.py"
create_s3_bucket = S3CreateBucketOperator(task_id='create_s3_bucket', bucket_name=bucket_name)
SPARK_JOB_DRIVER = {
"sparkSubmit": {
"entryPoint": entryPoint,
"entryPointArguments": [f"s3://{bucket_name}/output"],
"sparkSubmitParameters": "--conf spark.executor.cores=1 --conf spark.executor.memory=4g\
--conf spark.driver.cores=1 --conf spark.driver.memory=4g --conf spark.executor.instances=1",
}
}
SPARK_CONFIGURATION_OVERRIDES = {
"monitoringConfiguration": {"s3MonitoringConfiguration": {"logUri": f"s3://{bucket_name}/logs"}}
}
# [START howto_operator_emr_serverless_create_application]
emr_serverless_app = EmrServerlessCreateApplicationOperator(
task_id='create_emr_serverless_task',
release_label='emr-6.6.0',
job_type="SPARK",
config={'name': 'new_application'},
)
# [END howto_operator_emr_serverless_create_application]
# [START howto_sensor_emr_serverless_application]
wait_for_app_creation = EmrServerlessApplicationSensor(
task_id='wait_for_app_creation',
application_id=emr_serverless_app.output,
)
# [END howto_sensor_emr_serverless_application]
# [START howto_operator_emr_serverless_start_job]
start_job = EmrServerlessStartJobOperator(
task_id='start_emr_serverless_job',
application_id=emr_serverless_app.output,
execution_role_arn=role_arn,
job_driver=SPARK_JOB_DRIVER,
configuration_overrides=SPARK_CONFIGURATION_OVERRIDES,
)
# [END howto_operator_emr_serverless_start_job]
# [START howto_sensor_emr_serverless_job]
wait_for_job = EmrServerlessJobSensor(
task_id='wait_for_job', application_id=emr_serverless_app.output, job_run_id=start_job.output
)
# [END howto_sensor_emr_serverless_job]
# [START howto_operator_emr_serverless_delete_application]
delete_app = EmrServerlessDeleteApplicationOperator(
task_id='delete_application',
application_id=emr_serverless_app.output,
trigger_rule=TriggerRule.ALL_DONE,
)
# [END howto_operator_emr_serverless_delete_application]
delete_s3_bucket = S3DeleteBucketOperator(
task_id='delete_s3_bucket',
bucket_name=bucket_name,
force_delete=True,
trigger_rule=TriggerRule.ALL_DONE,
)
chain(
# TEST SETUP
test_context,
create_s3_bucket,
# TEST BODY
emr_serverless_app,
wait_for_app_creation,
start_job,
wait_for_job,
# TEST TEARDOWN
delete_app,
delete_s3_bucket,
)
from tests.system.utils.watcher import watcher
# This test needs watcher in order to properly mark success/failure
# when "tearDown" task with trigger rule is part of the DAG
list(dag.tasks) >> watcher()
from tests.system.utils import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)