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Example Airflow DAG for Dataproc batch operators.
from __future__ import annotations

import os
from datetime import datetime

from airflow import models
from import (
from import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "dataproc_batch_ps"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "")
[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
[docs]REGION = "europe-west1"
[docs]CLUSTER_NAME = f"dataproc-cluster-ps-{ENV_ID}"
[docs]BATCH_ID = f"batch-ps-{ENV_ID}"
[docs]CLUSTER_GENERATOR_CONFIG_FOR_PHS = ClusterGenerator( project_id=PROJECT_ID, region=REGION, master_machine_type="n1-standard-4", worker_machine_type="n1-standard-4", num_workers=0, properties={ "spark:spark.history.fs.logDirectory": f"gs://{BUCKET_NAME}/logging", }, enable_component_gateway=True,
[docs]BATCH_CONFIG_WITH_PHS = { "spark_batch": { "jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"], "main_class": "org.apache.spark.examples.SparkPi", }, "environment_config": { "peripherals_config": { "spark_history_server_config": { "dataproc_cluster": f"projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}"
} } }, } with models.DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "dataproc"], ) as dag:
[docs] create_bucket = GCSCreateBucketOperator( task_id="create_bucket", bucket_name=BUCKET_NAME, project_id=PROJECT_ID
) # [START how_to_cloud_dataproc_create_cluster_for_persistent_history_server] create_cluster = DataprocCreateClusterOperator( task_id="create_cluster_for_phs", project_id=PROJECT_ID, cluster_config=CLUSTER_GENERATOR_CONFIG_FOR_PHS, region=REGION, cluster_name=CLUSTER_NAME, ) # [END how_to_cloud_dataproc_create_cluster_for_persistent_history_server] # [START how_to_cloud_dataproc_create_batch_operator_with_persistent_history_server] create_batch = DataprocCreateBatchOperator( task_id="create_batch_with_phs", project_id=PROJECT_ID, region=REGION, batch=BATCH_CONFIG_WITH_PHS, batch_id=BATCH_ID, ) # [END how_to_cloud_dataproc_create_batch_operator_with_persistent_history_server] delete_cluster = DataprocDeleteClusterOperator( task_id="delete_cluster", project_id=PROJECT_ID, cluster_name=CLUSTER_NAME, region=REGION, trigger_rule=TriggerRule.ALL_DONE, ) delete_bucket = GCSDeleteBucketOperator( task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE ) create_bucket >> create_cluster >> create_batch >> delete_cluster >> delete_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/
[docs]test_run = get_test_run(dag)

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