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"""
Example Airflow DAG that show how to use various Dataproc Metastore
operators to manage a service.
"""
from __future__ import annotations
import datetime
import os
from google.protobuf.field_mask_pb2 import FieldMask
from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.dataproc_metastore import (
DataprocMetastoreCreateMetadataImportOperator,
DataprocMetastoreCreateServiceOperator,
DataprocMetastoreDeleteServiceOperator,
DataprocMetastoreExportMetadataOperator,
DataprocMetastoreGetServiceOperator,
DataprocMetastoreUpdateServiceOperator,
)
from airflow.providers.google.cloud.operators.gcs import (
GCSCreateBucketOperator,
GCSDeleteBucketOperator,
GCSSynchronizeBucketsOperator,
)
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
[docs]
DAG_ID = "dataproc_metastore"
[docs]
PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT") or DEFAULT_GCP_SYSTEM_TEST_PROJECT_ID
[docs]
ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]
SERVICE_ID = f"{DAG_ID}-service-{ENV_ID}".replace("_", "-")
[docs]
RESOURCE_DATA_BUCKET = "airflow-system-tests-resources"
[docs]
BUCKET_NAME = f"bucket_{DAG_ID}_{ENV_ID}"
[docs]
DESTINATION_GCS_FOLDER = f"gs://{BUCKET_NAME}/>"
[docs]
GCS_URI = f"gs://{BUCKET_NAME}/dataproc/{HIVE_FILE}"
# Service definition
# Docs: https://cloud.google.com/dataproc-metastore/docs/reference/rest/v1/projects.locations.services#Service
# [START how_to_cloud_dataproc_metastore_create_service]
[docs]
SERVICE = {
"name": "test-service",
}
# [END how_to_cloud_dataproc_metastore_create_service]
# [START how_to_cloud_dataproc_metastore_create_metadata_import]
# [END how_to_cloud_dataproc_metastore_create_metadata_import]
# Update service
# [START how_to_cloud_dataproc_metastore_update_service]
[docs]
SERVICE_TO_UPDATE = {
"labels": {
"mylocalmachine": "mylocalmachine",
"systemtest": "systemtest",
}
}
[docs]
UPDATE_MASK = FieldMask(paths=["labels"])
# [END how_to_cloud_dataproc_metastore_update_service]
with DAG(
DAG_ID,
start_date=datetime.datetime(2021, 1, 1),
schedule="@once",
catchup=False,
tags=["example", "dataproc", "metastore"],
) as dag:
[docs]
create_bucket = GCSCreateBucketOperator(
task_id="create_bucket", bucket_name=BUCKET_NAME, project_id=PROJECT_ID
)
move_file = GCSSynchronizeBucketsOperator(
task_id="move_file",
source_bucket=RESOURCE_DATA_BUCKET,
source_object="dataproc/hive",
destination_bucket=BUCKET_NAME,
destination_object="dataproc",
recursive=True,
)
# [START how_to_cloud_dataproc_metastore_create_service_operator]
create_service = DataprocMetastoreCreateServiceOperator(
task_id="create_service",
region=REGION,
project_id=PROJECT_ID,
service=SERVICE,
service_id=SERVICE_ID,
timeout=TIMEOUT,
)
# [END how_to_cloud_dataproc_metastore_create_service_operator]
# [START how_to_cloud_dataproc_metastore_get_service_operator]
get_service = DataprocMetastoreGetServiceOperator(
task_id="get_service",
region=REGION,
project_id=PROJECT_ID,
service_id=SERVICE_ID,
)
# [END how_to_cloud_dataproc_metastore_get_service_operator]
# [START how_to_cloud_dataproc_metastore_update_service_operator]
update_service = DataprocMetastoreUpdateServiceOperator(
task_id="update_service",
project_id=PROJECT_ID,
service_id=SERVICE_ID,
region=REGION,
service=SERVICE_TO_UPDATE,
update_mask=UPDATE_MASK,
timeout=TIMEOUT,
)
# [END how_to_cloud_dataproc_metastore_update_service_operator]
# [START how_to_cloud_dataproc_metastore_create_metadata_import_operator]
import_metadata = DataprocMetastoreCreateMetadataImportOperator(
task_id="import_metadata",
project_id=PROJECT_ID,
region=REGION,
service_id=SERVICE_ID,
metadata_import=METADATA_IMPORT,
metadata_import_id=METADATA_IMPORT_ID,
timeout=TIMEOUT,
)
# [END how_to_cloud_dataproc_metastore_create_metadata_import_operator]
# [START how_to_cloud_dataproc_metastore_export_metadata_operator]
export_metadata = DataprocMetastoreExportMetadataOperator(
task_id="export_metadata",
destination_gcs_folder=DESTINATION_GCS_FOLDER,
project_id=PROJECT_ID,
region=REGION,
service_id=SERVICE_ID,
timeout=TIMEOUT,
)
# [END how_to_cloud_dataproc_metastore_export_metadata_operator]
# [START how_to_cloud_dataproc_metastore_delete_service_operator]
delete_service = DataprocMetastoreDeleteServiceOperator(
task_id="delete_service",
region=REGION,
project_id=PROJECT_ID,
service_id=SERVICE_ID,
timeout=TIMEOUT,
)
# [END how_to_cloud_dataproc_metastore_delete_service_operator]
delete_service.trigger_rule = TriggerRule.ALL_DONE
delete_bucket = GCSDeleteBucketOperator(
task_id="delete_bucket", bucket_name=BUCKET_NAME, trigger_rule=TriggerRule.ALL_DONE
)
(
create_bucket
>> move_file
>> create_service
>> get_service
>> update_service
>> import_metadata
>> export_metadata
>> delete_service
>> 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: contributing-docs/testing/system_tests.rst)
[docs]
test_run = get_test_run(dag)