Source code for

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from __future__ import annotations

from datetime import datetime

from airflow import DAG
from import (

# Name of the datacenter where Dataproc cluster will be created
from airflow.utils.trigger_rule import TriggerRule
from tests.system.utils import get_test_env_id

# should be filled with appropriate ids

[docs]AVAILABILITY_ZONE_ID = "ru-central1-c"
# Dataproc cluster will use this bucket as distributed storage
[docs]S3_BUCKET_NAME = ""
[docs]ENV_ID = get_test_env_id()
[docs]DAG_ID = "example_yandexcloud_dataproc_lightweight"
with DAG( DAG_ID, schedule=None, start_date=datetime(2021, 1, 1), tags=["example"], ) as dag:
[docs] create_cluster = DataprocCreateClusterOperator( task_id="create_cluster", zone=AVAILABILITY_ZONE_ID, s3_bucket=S3_BUCKET_NAME, computenode_count=1, datanode_count=0, services=("SPARK", "YARN"), )
create_spark_job = DataprocCreateSparkJobOperator( cluster_id=create_cluster.cluster_id, task_id="create_spark_job", main_jar_file_uri="file:///usr/lib/spark/examples/jars/spark-examples.jar", main_class="org.apache.spark.examples.SparkPi", args=["1000"], ) delete_cluster = DataprocDeleteClusterOperator( cluster_id=create_cluster.cluster_id, task_id="delete_cluster", trigger_rule=TriggerRule.ALL_DONE, ) create_spark_job >> delete_cluster 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/
[docs]test_run = get_test_run(dag)

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