Source code for tests.system.providers.google.cloud.dataplex.example_dataplex_dq

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"""
Example Airflow DAG that shows how to use Dataplex Scan Data.
"""
from __future__ import annotations

import os
from datetime import datetime

from google.cloud import dataplex_v1
from google.protobuf.field_mask_pb2 import FieldMask

from airflow import models
from airflow.models.baseoperator import chain
from airflow.providers.google.cloud.operators.bigquery import (
    BigQueryCreateEmptyDatasetOperator,
    BigQueryCreateEmptyTableOperator,
    BigQueryDeleteDatasetOperator,
    BigQueryInsertJobOperator,
)
from airflow.providers.google.cloud.operators.dataplex import (
    DataplexCreateAssetOperator,
    DataplexCreateLakeOperator,
    DataplexCreateOrUpdateDataQualityScanOperator,
    DataplexCreateZoneOperator,
    DataplexDeleteAssetOperator,
    DataplexDeleteDataQualityScanOperator,
    DataplexDeleteLakeOperator,
    DataplexDeleteZoneOperator,
    DataplexGetDataQualityScanOperator,
    DataplexGetDataQualityScanResultOperator,
    DataplexRunDataQualityScanOperator,
)
from airflow.providers.google.cloud.sensors.dataplex import DataplexDataQualityJobStatusSensor
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
[docs]DAG_ID = "example_dataplex_data_quality"
[docs]LAKE_ID = f"test-lake-{ENV_ID}"
[docs]REGION = "us-central1"
[docs]DATASET_NAME = f"dataset_bq_{ENV_ID}"
[docs]TABLE_1 = "table0"
[docs]TABLE_2 = "table1"
[docs]SCHEMA = [ {"name": "value", "type": "INTEGER", "mode": "REQUIRED"}, {"name": "name", "type": "STRING", "mode": "NULLABLE"}, {"name": "dt", "type": "STRING", "mode": "NULLABLE"}, ]
[docs]DATASET = DATASET_NAME
[docs]INSERT_DATE = datetime.now().strftime("%Y-%m-%d")
[docs]INSERT_ROWS_QUERY = f"INSERT {DATASET}.{TABLE_1} VALUES (1, 'test test2', '{INSERT_DATE}');"
[docs]LOCATION = "us"
[docs]TRIGGER_SPEC_TYPE = "ON_DEMAND"
[docs]ZONE_ID = "test-zone-id"
[docs]DATA_SCAN_ID = "test-data-scan-id"
[docs]EXAMPLE_LAKE_BODY = { "display_name": "test_display_name", "labels": [], "description": "test_description", "metastore": {"service": ""}, }
# [START howto_dataplex_zone_configuration]
[docs]EXAMPLE_ZONE = { "type_": "RAW", "resource_spec": {"location_type": "SINGLE_REGION"}, }
# [END howto_dataplex_zone_configuration]
[docs]ASSET_ID = "test-asset-id"
# [START howto_dataplex_asset_configuration]
[docs]EXAMPLE_ASSET = { "resource_spec": {"name": f"projects/{PROJECT_ID}/datasets/{DATASET_NAME}", "type_": "BIGQUERY_DATASET"}, "discovery_spec": {"enabled": True}, }
# [END howto_dataplex_asset_configuration] # [START howto_dataplex_data_quality_configuration]
[docs]EXAMPLE_DATA_SCAN = dataplex_v1.DataScan()
EXAMPLE_DATA_SCAN.data.entity = ( f"projects/{PROJECT_ID}/locations/{REGION}/lakes/{LAKE_ID}/zones/{ZONE_ID}/entities/{TABLE_1}" ) EXAMPLE_DATA_SCAN.data.resource = ( f"//bigquery.googleapis.com/projects/{PROJECT_ID}/datasets/{DATASET}/tables/{TABLE_1}" ) EXAMPLE_DATA_SCAN.data_quality_spec = { "rules": [ { "range_expectation": { "min_value": "0", "max_value": "10000", }, "column": "value", "dimension": "VALIDITY", } ], } # [END howto_dataplex_data_quality_configuration]
[docs]UPDATE_MASK = FieldMask(paths=["data_quality_spec"])
[docs]ENTITY = f"projects/{PROJECT_ID}/locations/{REGION}/lakes/{LAKE_ID}/zones/{ZONE_ID}/entities/{TABLE_1}"
[docs]EXAMPLE_DATA_SCAN_UPDATE = { "data": { "entity": ENTITY, "resource": f"//bigquery.googleapis.com/projects/{PROJECT_ID}/datasets/{DATASET}/tables/{TABLE_1}", }, "data_quality_spec": { "rules": [ { "range_expectation": { "min_value": "1", "max_value": "50000", }, "column": "value", "dimension": "VALIDITY", } ], }, }
with models.DAG( DAG_ID, start_date=datetime(2021, 1, 1), schedule="@once", tags=["example", "dataplex", "data_quality"], ) as dag:
[docs] create_dataset = BigQueryCreateEmptyDatasetOperator(task_id="create_dataset", dataset_id=DATASET_NAME)
create_table_1 = BigQueryCreateEmptyTableOperator( task_id="create_table_1", dataset_id=DATASET_NAME, table_id=TABLE_1, schema_fields=SCHEMA, location=LOCATION, ) create_table_2 = BigQueryCreateEmptyTableOperator( task_id="create_table_2", dataset_id=DATASET_NAME, table_id=TABLE_2, schema_fields=SCHEMA, location=LOCATION, ) insert_query_job = BigQueryInsertJobOperator( task_id="insert_query_job", configuration={ "query": { "query": INSERT_ROWS_QUERY, "useLegacySql": False, } }, ) create_lake = DataplexCreateLakeOperator( task_id="create_lake", project_id=PROJECT_ID, region=REGION, body=EXAMPLE_LAKE_BODY, lake_id=LAKE_ID ) # [START howto_dataplex_create_zone_operator] create_zone = DataplexCreateZoneOperator( task_id="create_zone", project_id=PROJECT_ID, region=REGION, lake_id=LAKE_ID, body=EXAMPLE_ZONE, zone_id=ZONE_ID, ) # [END howto_dataplex_create_zone_operator] # [START howto_dataplex_create_asset_operator] create_asset = DataplexCreateAssetOperator( task_id="create_asset", project_id=PROJECT_ID, region=REGION, body=EXAMPLE_ASSET, lake_id=LAKE_ID, zone_id=ZONE_ID, asset_id=ASSET_ID, ) # [END howto_dataplex_create_asset_operator] # [START howto_dataplex_create_data_quality_operator] create_data_scan = DataplexCreateOrUpdateDataQualityScanOperator( task_id="create_data_scan", project_id=PROJECT_ID, region=REGION, body=EXAMPLE_DATA_SCAN, data_scan_id=DATA_SCAN_ID, ) # [END howto_dataplex_create_data_quality_operator] update_data_scan = DataplexCreateOrUpdateDataQualityScanOperator( task_id="update_data_scan", project_id=PROJECT_ID, region=REGION, update_mask=UPDATE_MASK, body=EXAMPLE_DATA_SCAN_UPDATE, data_scan_id=DATA_SCAN_ID, ) # [START howto_dataplex_get_data_quality_operator] get_data_scan = DataplexGetDataQualityScanOperator( task_id="get_data_scan", project_id=PROJECT_ID, region=REGION, data_scan_id=DATA_SCAN_ID, ) # [END howto_dataplex_get_data_quality_operator] run_data_scan_sync = DataplexRunDataQualityScanOperator( task_id="run_data_scan_sync", project_id=PROJECT_ID, region=REGION, data_scan_id=DATA_SCAN_ID, ) get_data_scan_job_result = DataplexGetDataQualityScanResultOperator( task_id="get_data_scan_job_result", project_id=PROJECT_ID, region=REGION, data_scan_id=DATA_SCAN_ID, ) # [START howto_dataplex_run_data_quality_operator] run_data_scan_async = DataplexRunDataQualityScanOperator( task_id="run_data_scan_async", project_id=PROJECT_ID, region=REGION, data_scan_id=DATA_SCAN_ID, asynchronous=True, ) # [END howto_dataplex_run_data_quality_operator] # [START howto_dataplex_data_scan_job_state_sensor] get_data_scan_job_status = DataplexDataQualityJobStatusSensor( task_id="get_data_scan_job_status", project_id=PROJECT_ID, region=REGION, data_scan_id=DATA_SCAN_ID, job_id="{{ task_instance.xcom_pull('run_data_scan_async') }}", ) # [END howto_dataplex_data_scan_job_state_sensor] # [START howto_dataplex_get_data_quality_job_operator] get_data_scan_job_result_2 = DataplexGetDataQualityScanResultOperator( task_id="get_data_scan_job_result_2", project_id=PROJECT_ID, region=REGION, data_scan_id=DATA_SCAN_ID, ) # [END howto_dataplex_get_data_quality_job_operator] # [START howto_dataplex_delete_asset_operator] delete_asset = DataplexDeleteAssetOperator( task_id="delete_asset", project_id=PROJECT_ID, region=REGION, lake_id=LAKE_ID, zone_id=ZONE_ID, asset_id=ASSET_ID, ) # [END howto_dataplex_delete_asset_operator] delete_asset.trigger_rule = TriggerRule.ALL_DONE # [START howto_dataplex_delete_zone_operator] delete_zone = DataplexDeleteZoneOperator( task_id="delete_zone", project_id=PROJECT_ID, region=REGION, lake_id=LAKE_ID, zone_id=ZONE_ID, ) # [END howto_dataplex_delete_zone_operator] delete_zone.trigger_rule = TriggerRule.ALL_DONE # [START howto_dataplex_delete_data_quality_operator] delete_data_scan = DataplexDeleteDataQualityScanOperator( task_id="delete_data_scan", project_id=PROJECT_ID, region=REGION, data_scan_id=DATA_SCAN_ID, ) # [END howto_dataplex_delete_data_quality_operator] delete_data_scan.trigger_rule = TriggerRule.ALL_DONE delete_lake = DataplexDeleteLakeOperator( project_id=PROJECT_ID, region=REGION, lake_id=LAKE_ID, task_id="delete_lake", trigger_rule=TriggerRule.ALL_DONE, ) delete_dataset = BigQueryDeleteDatasetOperator( task_id="delete_dataset", dataset_id=DATASET_NAME, project_id=PROJECT_ID, delete_contents=True, trigger_rule=TriggerRule.ALL_DONE, ) chain( # TEST SETUP create_dataset, [create_table_1, create_table_2], insert_query_job, create_lake, create_zone, create_asset, # TEST BODY create_data_scan, update_data_scan, get_data_scan, run_data_scan_sync, get_data_scan_job_result, run_data_scan_async, get_data_scan_job_status, get_data_scan_job_result_2, # TEST TEARDOWN delete_asset, delete_zone, delete_data_scan, [delete_lake, delete_dataset], ) 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)

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