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"""
Example Airflow DAG that show how to check Hive partitions existence
using Dataproc Metastore Sensor.
Note that Metastore service must be configured to use gRPC endpoints.
"""
from __future__ import annotations
import datetime
import os
from airflow.decorators import task
from airflow.models.dag import DAG
from airflow.providers.google.cloud.hooks.gcs import _parse_gcs_url
from airflow.providers.google.cloud.operators.dataproc import (
DataprocCreateClusterOperator,
DataprocDeleteClusterOperator,
DataprocSubmitJobOperator,
)
from airflow.providers.google.cloud.operators.dataproc_metastore import (
DataprocMetastoreCreateServiceOperator,
DataprocMetastoreDeleteServiceOperator,
)
from airflow.providers.google.cloud.operators.gcs import GCSDeleteBucketOperator
from airflow.providers.google.cloud.sensors.dataproc_metastore import MetastoreHivePartitionSensor
from airflow.providers.google.cloud.transfers.gcs_to_gcs import GCSToGCSOperator
from airflow.utils.trigger_rule import TriggerRule
[docs]DAG_ID = "hive_partition_sensor"
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "demo-project")
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "demo-env")
[docs]DATAPROC_CLUSTER_NAME = f"cluster-{DAG_ID}".replace("_", "-")
[docs]DATAPROC_CLUSTER_CONFIG = {
"master_config": {
"num_instances": 1,
"machine_type_uri": "n1-standard-2",
"disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 1024},
},
"worker_config": {
"num_instances": 2,
"machine_type_uri": "n1-standard-2",
"disk_config": {"boot_disk_type": "pd-standard", "boot_disk_size_gb": 1024},
},
"metastore_config": {
"dataproc_metastore_service": METASTORE_SERVICE_QFN,
},
"gce_cluster_config": {
"service_account_scopes": [
"https://www.googleapis.com/auth/cloud-platform",
],
},
}
[docs]TABLE_NAME = "transactions_partitioned"
[docs]COLUMN = "TransactionType"
[docs]PARTITION_1 = f"{COLUMN}=credit".lower()
[docs]PARTITION_2 = f"{COLUMN}=debit".lower()
[docs]SOURCE_DATA_BUCKET = "airflow-system-tests-resources"
[docs]SOURCE_DATA_PATH = "dataproc/hive"
[docs]SOURCE_DATA_FILE_NAME = "part-00000.parquet"
[docs]EXTERNAL_TABLE_BUCKET = "{{task_instance.xcom_pull(task_ids='get_hive_warehouse_bucket_task', key='bucket')}}"
[docs]QUERY_CREATE_EXTERNAL_TABLE = f"""
CREATE EXTERNAL TABLE IF NOT EXISTS transactions
(SubmissionDate DATE, TransactionAmount DOUBLE, TransactionType STRING)
STORED AS PARQUET
LOCATION 'gs://{EXTERNAL_TABLE_BUCKET}/{SOURCE_DATA_PATH}';
"""
[docs]QUERY_CREATE_PARTITIONED_TABLE = f"""
CREATE EXTERNAL TABLE IF NOT EXISTS {TABLE_NAME}
(SubmissionDate DATE, TransactionAmount DOUBLE)
PARTITIONED BY ({COLUMN} STRING);
"""
[docs]QUERY_COPY_DATA_WITH_PARTITIONS = f"""
SET hive.exec.dynamic.partition.mode=nonstrict;
INSERT INTO TABLE {TABLE_NAME} PARTITION ({COLUMN})
SELECT SubmissionDate,TransactionAmount,TransactionType FROM transactions;
"""
with DAG(
DAG_ID,
start_date=datetime.datetime(2021, 1, 1),
schedule="@once",
catchup=False,
tags=["example", "dataproc", "metastore", "partition", "hive", "sensor"],
) as dag:
create_cluster = DataprocCreateClusterOperator(
task_id="create_cluster",
cluster_name=DATAPROC_CLUSTER_NAME,
project_id=PROJECT_ID,
cluster_config=DATAPROC_CLUSTER_CONFIG,
region=REGION,
)
@task(task_id="get_hive_warehouse_bucket_task")
def get_hive_warehouse_bucket(**kwargs):
"""Returns Hive Metastore Warehouse GCS bucket name."""
ti = kwargs["ti"]
metastore_service: dict = ti.xcom_pull(task_ids="create_metastore_service")
config_overrides: dict = metastore_service["hive_metastore_config"]["config_overrides"]
destination_dir: str = config_overrides["hive.metastore.warehouse.dir"]
bucket, _ = _parse_gcs_url(destination_dir)
ti.xcom_push(key="bucket", value=bucket)
get_hive_warehouse_bucket_task = get_hive_warehouse_bucket()
copy_source_data = GCSToGCSOperator(
task_id="copy_source_data",
source_bucket=SOURCE_DATA_BUCKET,
source_object=f"{SOURCE_DATA_PATH}/{SOURCE_DATA_FILE_NAME}",
destination_bucket=EXTERNAL_TABLE_BUCKET,
destination_object=f"{SOURCE_DATA_PATH}/{SOURCE_DATA_FILE_NAME}",
)
create_external_table = DataprocSubmitJobOperator(
task_id="create_external_table",
job={
"reference": {"project_id": PROJECT_ID},
"placement": {"cluster_name": DATAPROC_CLUSTER_NAME},
"hive_job": {"query_list": {"queries": [QUERY_CREATE_EXTERNAL_TABLE]}},
},
region=REGION,
project_id=PROJECT_ID,
)
create_partitioned_table = DataprocSubmitJobOperator(
task_id="create_partitioned_table",
job={
"reference": {"project_id": PROJECT_ID},
"placement": {"cluster_name": DATAPROC_CLUSTER_NAME},
"hive_job": {"query_list": {"queries": [QUERY_CREATE_PARTITIONED_TABLE]}},
},
region=REGION,
project_id=PROJECT_ID,
)
partition_data = DataprocSubmitJobOperator(
task_id="partition_data",
job={
"reference": {"project_id": PROJECT_ID},
"placement": {"cluster_name": DATAPROC_CLUSTER_NAME},
"hive_job": {"query_list": {"queries": [QUERY_COPY_DATA_WITH_PARTITIONS]}},
},
region=REGION,
project_id=PROJECT_ID,
)
# [START how_to_cloud_dataproc_metastore_hive_partition_sensor]
hive_partition_sensor = MetastoreHivePartitionSensor(
task_id="hive_partition_sensor",
service_id=METASTORE_SERVICE_ID,
region=REGION,
table=TABLE_NAME,
partitions=[PARTITION_1, PARTITION_2],
)
# [END how_to_cloud_dataproc_metastore_hive_partition_sensor]
delete_dataproc_cluster = DataprocDeleteClusterOperator(
task_id="delete_dataproc_cluster",
cluster_name=DATAPROC_CLUSTER_NAME,
project_id=PROJECT_ID,
region=REGION,
trigger_rule=TriggerRule.ALL_DONE,
)
delete_metastore_service = DataprocMetastoreDeleteServiceOperator(
task_id="delete_metastore_service",
service_id=METASTORE_SERVICE_ID,
project_id=PROJECT_ID,
region=REGION,
trigger_rule=TriggerRule.ALL_DONE,
)
delete_warehouse_bucket = GCSDeleteBucketOperator(
task_id="delete_warehouse_bucket",
bucket_name=EXTERNAL_TABLE_BUCKET,
trigger_rule=TriggerRule.ALL_DONE,
)
# TEST SETUP
(
create_metastore_service
>> create_cluster
>> get_hive_warehouse_bucket_task
>> copy_source_data
>> create_external_table
>> create_partitioned_table
>> partition_data
)
(
create_metastore_service
# TEST BODY
>> hive_partition_sensor
# TEST TEARDOWN
>> [delete_dataproc_cluster, delete_metastore_service, delete_warehouse_bucket]
)
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)