Source code for tests.system.providers.google.cloud.dataproc.example_dataproc_batch

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

import os
from datetime import datetime

from google.api_core.retry import Retry

from airflow import models
from airflow.providers.google.cloud.operators.dataproc import (
    DataprocCancelOperationOperator,
    DataprocCreateBatchOperator,
    DataprocDeleteBatchOperator,
    DataprocGetBatchOperator,
    DataprocListBatchesOperator,
)
from airflow.providers.google.cloud.sensors.dataproc import DataprocBatchSensor
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "dataproc_batch"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]REGION = "europe-west1"
[docs]BATCH_ID = f"batch-{ENV_ID}-{DAG_ID}".replace("_", "-")
[docs]BATCH_ID_2 = f"batch-{ENV_ID}-{DAG_ID}-2".replace("_", "-")
[docs]BATCH_ID_3 = f"batch-{ENV_ID}-{DAG_ID}-3".replace("_", "-")
[docs]BATCH_ID_4 = f"batch-{ENV_ID}-{DAG_ID}-4".replace("_", "-")
[docs]BATCH_CONFIG = { "spark_batch": { "jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"], "main_class": "org.apache.spark.examples.SparkPi", }, }
with models.DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "dataproc"], ) as dag: # [START how_to_cloud_dataproc_create_batch_operator]
[docs] create_batch = DataprocCreateBatchOperator( task_id="create_batch", project_id=PROJECT_ID, region=REGION, batch=BATCH_CONFIG, batch_id=BATCH_ID, )
create_batch_2 = DataprocCreateBatchOperator( task_id="create_batch_2", project_id=PROJECT_ID, region=REGION, batch=BATCH_CONFIG, batch_id=BATCH_ID_2, result_retry=Retry(maximum=10.0, initial=10.0, multiplier=1.0), ) create_batch_3 = DataprocCreateBatchOperator( task_id="create_batch_3", project_id=PROJECT_ID, region=REGION, batch=BATCH_CONFIG, batch_id=BATCH_ID_3, asynchronous=True, ) # [END how_to_cloud_dataproc_create_batch_operator] # [START how_to_cloud_dataproc_batch_async_sensor] batch_async_sensor = DataprocBatchSensor( task_id="batch_async_sensor", region=REGION, project_id=PROJECT_ID, batch_id=BATCH_ID_3, poke_interval=10, ) # [END how_to_cloud_dataproc_batch_async_sensor] # [START how_to_cloud_dataproc_get_batch_operator] get_batch = DataprocGetBatchOperator( task_id="get_batch", project_id=PROJECT_ID, region=REGION, batch_id=BATCH_ID ) get_batch_2 = DataprocGetBatchOperator( task_id="get_batch_2", project_id=PROJECT_ID, region=REGION, batch_id=BATCH_ID_2 ) # [END how_to_cloud_dataproc_get_batch_operator] # [START how_to_cloud_dataproc_list_batches_operator] list_batches = DataprocListBatchesOperator( task_id="list_batches", project_id=PROJECT_ID, region=REGION, ) # [END how_to_cloud_dataproc_list_batches_operator] create_batch_4 = DataprocCreateBatchOperator( task_id="create_batch_4", project_id=PROJECT_ID, region=REGION, batch=BATCH_CONFIG, batch_id=BATCH_ID_4, asynchronous=True, ) # [START how_to_cloud_dataproc_cancel_operation_operator] cancel_operation = DataprocCancelOperationOperator( task_id="cancel_operation", project_id=PROJECT_ID, region=REGION, operation_name="{{ task_instance.xcom_pull('create_batch_4') }}", ) # [END how_to_cloud_dataproc_cancel_operation_operator] # [START how_to_cloud_dataproc_delete_batch_operator] delete_batch = DataprocDeleteBatchOperator( task_id="delete_batch", project_id=PROJECT_ID, region=REGION, batch_id=BATCH_ID ) delete_batch_2 = DataprocDeleteBatchOperator( task_id="delete_batch_2", project_id=PROJECT_ID, region=REGION, batch_id=BATCH_ID_2 ) delete_batch_3 = DataprocDeleteBatchOperator( task_id="delete_batch_3", project_id=PROJECT_ID, region=REGION, batch_id=BATCH_ID_3 ) delete_batch_4 = DataprocDeleteBatchOperator( task_id="delete_batch_4", project_id=PROJECT_ID, region=REGION, batch_id=BATCH_ID_4 ) # [END how_to_cloud_dataproc_delete_batch_operator] delete_batch.trigger_rule = TriggerRule.ALL_DONE delete_batch_2.trigger_rule = TriggerRule.ALL_DONE delete_batch_3.trigger_rule = TriggerRule.ALL_DONE delete_batch_4.trigger_rule = TriggerRule.ALL_DONE ( # TEST SETUP [create_batch, create_batch_2, create_batch_3] # TEST BODY >> batch_async_sensor >> [get_batch, get_batch_2, list_batches] >> create_batch_4 >> cancel_operation # TEST TEARDOWN >> [delete_batch, delete_batch_2, delete_batch_3, delete_batch_4] ) 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)

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