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"""
Example Airflow DAG for DataprocSubmitJobOperator with spark job
in deferrable mode.
"""
from __future__ import annotations
import os
from datetime import datetime, timedelta
from typing import Any
from google.api_core.exceptions import NotFound
from google.api_core.retry import Retry
from google.cloud.dataproc_v1.types import Batch
from airflow.models.dag import DAG
from airflow.providers.google.cloud.hooks.dataproc import DataprocHook
from airflow.providers.google.cloud.operators.dataproc import (
DataprocCreateBatchOperator,
DataprocDeleteBatchOperator,
DataprocGetBatchOperator,
)
try:
from airflow.sdk import TriggerRule
except ImportError:
# Compatibility for Airflow < 3.1
from airflow.utils.trigger_rule import TriggerRule # type: ignore[no-redef,attr-defined]
from system.google import DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
DAG_ID = "dataproc_batch_deferrable"
PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
REGION = "europe-north1"
BATCH_ID = f"batch-{ENV_ID}-{DAG_ID}".replace("_", "-")
BATCH_CONFIG = {
"spark_batch": {
"jar_file_uris": ["file:///usr/lib/spark/examples/jars/spark-examples.jar"],
"main_class": "org.apache.spark.examples.SparkPi",
},
}
def delete_batch_before_retry(context: dict[str, Any]) -> None:
task = context["task"]
hook = DataprocHook(
gcp_conn_id=task.gcp_conn_id,
impersonation_chain=task.impersonation_chain,
)
try:
batch = hook.get_batch(
batch_id=task.batch_id,
region=task.region,
project_id=task.project_id,
retry=task.retry,
timeout=task.timeout,
metadata=task.metadata,
)
except NotFound:
task.log.info("Batch %s does not exist. Nothing to clean up before retry.", task.batch_id)
return
if batch.state != Batch.State.FAILED:
task.log.info("Batch %s is not failed. Skipping cleanup before retry.", task.batch_id)
return
hook.delete_batch(
batch_id=task.batch_id,
region=task.region,
project_id=task.project_id,
retry=task.retry,
timeout=task.timeout,
metadata=task.metadata,
)
task.log.info("Requested deletion of failed batch %s before retry.", task.batch_id)
with DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "managed-spark", "batch", "deferrable"],
) as dag:
# [START how_to_cloud_dataproc_create_batch_operator_async]
create_batch = DataprocCreateBatchOperator(
task_id="create_batch",
project_id=PROJECT_ID,
region=REGION,
batch=BATCH_CONFIG,
batch_id=BATCH_ID,
deferrable=True,
retries=10,
retry_delay=timedelta(minutes=5),
on_retry_callback=delete_batch_before_retry,
result_retry=Retry(maximum=100.0, initial=10.0, multiplier=1.0),
num_retries_if_resource_is_not_ready=3,
)
# [END how_to_cloud_dataproc_create_batch_operator_async]
get_batch = DataprocGetBatchOperator(
task_id="get_batch", project_id=PROJECT_ID, region=REGION, batch_id=BATCH_ID
)
delete_batch = DataprocDeleteBatchOperator(
task_id="delete_batch",
project_id=PROJECT_ID,
region=REGION,
batch_id=BATCH_ID,
)
delete_batch.trigger_rule = TriggerRule.ALL_DONE
(
# TEST SETUP
create_batch
# TEST BODY
>> get_batch
# TEST TEARDOWN
>> delete_batch
)
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: contributing-docs/testing/system_tests.rst)
test_run = get_test_run(dag)