Source code for tests.system.yandex.example_yandexcloud_dataproc_lightweight
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from __future__ import annotations
from datetime import datetime
from airflow import DAG
from airflow.providers.yandex.operators.dataproc import (
DataprocCreateClusterOperator,
DataprocCreateSparkJobOperator,
DataprocDeleteClusterOperator,
)
# Name of the datacenter where Dataproc cluster will be created
from airflow.utils.trigger_rule import TriggerRule
from tests_common.test_utils.system_tests 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]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_common.test_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_common.test_utils.system_tests 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)