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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.models.dag import DAG
from airflow.providers.google.cloud.operators.dataproc import (
ClusterGenerator,
DataprocCreateBatchOperator,
DataprocCreateClusterOperator,
DataprocDeleteBatchOperator,
DataprocDeleteClusterOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
from airflow.utils.trigger_rule import TriggerRule
from providers.tests.system.google import DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]DAG_ID = "dataproc_batch_ps"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}".replace("-", "_")
[docs]CLUSTER_NAME_BASE = f"cluster-{DAG_ID}".replace("_", "-")
[docs]CLUSTER_NAME_FULL = CLUSTER_NAME_BASE + f"-{ENV_ID}".replace("_", "-")
[docs]CLUSTER_NAME = CLUSTER_NAME_BASE if len(CLUSTER_NAME_FULL) >= 33 else CLUSTER_NAME_FULL
[docs]BATCH_ID = f"batch-{ENV_ID}-{DAG_ID}".replace("_", "-")
[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,
).make()
[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 DAG(
DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example", "dataproc", "batch", "persistent"],
) 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,
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_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,
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_with_persistent_history_server]
delete_batch = DataprocDeleteBatchOperator(
task_id="delete_batch",
project_id=PROJECT_ID,
region=REGION,
batch_id=BATCH_ID,
trigger_rule=TriggerRule.ALL_DONE,
)
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
)
(
# TEST SETUP
create_bucket
>> create_cluster
# TEST BODY
>> create_batch
# TEST TEARDOWN
>> delete_batch
>> delete_cluster
>> delete_bucket
)
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)