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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 import (
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"test-batch-id-{ENV_ID}"
[docs]BATCH_ID_2 = f"test-batch-id-{ENV_ID}-2"
[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), ) # [END how_to_cloud_dataproc_create_batch_operator] # [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] # [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.trigger_rule = TriggerRule.ALL_DONE delete_batch_2 = DataprocDeleteBatchOperator( task_id="delete_batch_2", project_id=PROJECT_ID, region=REGION, batch_id=BATCH_ID_2 ) # [END how_to_cloud_dataproc_delete_batch_operator] delete_batch.trigger_rule = TriggerRule.ALL_DONE ( create_batch >> create_batch_2 >> get_batch >> get_batch_2 >> list_batches >> delete_batch >> delete_batch_2 ) 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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