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from __future__ import annotations
from datetime import datetime
import boto3
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from airflow.providers.amazon.aws.operators.emr import (
EmrServerlessCreateApplicationOperator,
EmrServerlessDeleteApplicationOperator,
EmrServerlessStartJobOperator,
EmrServerlessStopApplicationOperator,
)
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="@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"
region = boto3.session.Session().region_name
entryPoint = f"s3://{region}.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]
# EmrServerlessCreateApplicationOperator waits by default, setting as False to test the Sensor below.
emr_serverless_app.wait_for_completion = False
emr_serverless_app_id = emr_serverless_app.output
# [START howto_sensor_emr_serverless_application]
wait_for_app_creation = EmrServerlessApplicationSensor(
task_id="wait_for_app_creation",
application_id=emr_serverless_app_id,
)
# [END howto_sensor_emr_serverless_application]
wait_for_app_creation.poke_interval = 1
# [START howto_operator_emr_serverless_start_job]
start_job = EmrServerlessStartJobOperator(
task_id="start_emr_serverless_job",
application_id=emr_serverless_app_id,
execution_role_arn=role_arn,
job_driver=SPARK_JOB_DRIVER,
configuration_overrides=SPARK_CONFIGURATION_OVERRIDES,
)
# [END howto_operator_emr_serverless_start_job]
start_job.wait_for_completion = False
# [START howto_sensor_emr_serverless_job]
wait_for_job = EmrServerlessJobSensor(
task_id="wait_for_job",
application_id=emr_serverless_app_id,
job_run_id=start_job.output,
# the default is to wait for job completion, here we just wait for the job to be running.
target_states={"RUNNING"},
)
# [END howto_sensor_emr_serverless_job]
wait_for_job.poke_interval = 10
# [START howto_operator_emr_serverless_stop_application]
stop_app = EmrServerlessStopApplicationOperator(
task_id="stop_application",
application_id=emr_serverless_app_id,
force_stop=True,
)
# [END howto_operator_emr_serverless_stop_application]
stop_app.waiter_check_interval_seconds = 1
# [START howto_operator_emr_serverless_delete_application]
delete_app = EmrServerlessDeleteApplicationOperator(
task_id="delete_application",
application_id=emr_serverless_app_id,
)
# [END howto_operator_emr_serverless_delete_application]
delete_app.waiter_check_interval_seconds = 1
delete_app.trigger_rule = TriggerRule.ALL_DONE
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,
stop_app,
# 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)