Source code for tests.system.providers.google.cloud.bigquery.example_bigquery_queries

#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
"""
Example Airflow DAG for Google BigQuery service.
"""
from __future__ import annotations

import os
from datetime import datetime

from airflow import models
from airflow.operators.bash import BashOperator
from airflow.providers.google.cloud.operators.bigquery import (
    BigQueryCheckOperator,
    BigQueryColumnCheckOperator,
    BigQueryCreateEmptyDatasetOperator,
    BigQueryCreateEmptyTableOperator,
    BigQueryDeleteDatasetOperator,
    BigQueryGetDataOperator,
    BigQueryInsertJobOperator,
    BigQueryIntervalCheckOperator,
    BigQueryTableCheckOperator,
    BigQueryValueCheckOperator,
)
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]LOCATION = "us-east1"
[docs]QUERY_SQL_PATH = "resources/example_bigquery_query.sql"
[docs]TABLE_1 = "table1"
[docs]TABLE_2 = "table2"
[docs]SCHEMA = [ {"name": "value", "type": "INTEGER", "mode": "REQUIRED"}, {"name": "name", "type": "STRING", "mode": "NULLABLE"}, {"name": "ds", "type": "DATE", "mode": "NULLABLE"},
]
[docs]DAGS_LIST = []
[docs]locations = [None, LOCATION]
for index, location in enumerate(locations, 1):
[docs] DAG_ID = "bigquery_queries_location" if location else "bigquery_queries"
DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}" DATASET = f"{DATASET_NAME}{index}" INSERT_DATE = datetime.now().strftime("%Y-%m-%d") # [START howto_operator_bigquery_query] INSERT_ROWS_QUERY = ( f"INSERT {DATASET}.{TABLE_1} VALUES " f"(42, 'monty python', '{INSERT_DATE}'), " f"(42, 'fishy fish', '{INSERT_DATE}');" ) # [END howto_operator_bigquery_query] with models.DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "bigquery"], user_defined_macros={"DATASET": DATASET, "TABLE": TABLE_1, "QUERY_SQL_PATH": QUERY_SQL_PATH}, ) as dag: create_dataset = BigQueryCreateEmptyDatasetOperator( task_id="create_dataset", dataset_id=DATASET, location=location, ) create_table_1 = BigQueryCreateEmptyTableOperator( task_id="create_table_1", dataset_id=DATASET, table_id=TABLE_1, schema_fields=SCHEMA, location=location, ) create_table_2 = BigQueryCreateEmptyTableOperator( task_id="create_table_2", dataset_id=DATASET, table_id=TABLE_2, schema_fields=SCHEMA, location=location, ) # [START howto_operator_bigquery_insert_job] insert_query_job = BigQueryInsertJobOperator( task_id="insert_query_job", configuration={ "query": { "query": INSERT_ROWS_QUERY, "useLegacySql": False, } }, location=location, ) # [END howto_operator_bigquery_insert_job] # [START howto_operator_bigquery_select_job] select_query_job = BigQueryInsertJobOperator( task_id="select_query_job", configuration={ "query": { "query": "{% include QUERY_SQL_PATH %}", "useLegacySql": False, } }, location=location, ) # [END howto_operator_bigquery_select_job] execute_insert_query = BigQueryInsertJobOperator( task_id="execute_insert_query", configuration={ "query": { "query": INSERT_ROWS_QUERY, "useLegacySql": False, } }, location=location, ) execute_query_save = BigQueryInsertJobOperator( task_id="execute_query_save", configuration={ "query": { "query": f"SELECT * FROM {DATASET}.{TABLE_1}", "useLegacySql": False, "destinationTable": { 'projectId': PROJECT_ID, 'datasetId': DATASET, 'tableId': TABLE_2, }, } }, location=location, ) bigquery_execute_multi_query = BigQueryInsertJobOperator( task_id="execute_multi_query", configuration={ "query": { "query": [ f"SELECT * FROM {DATASET}.{TABLE_2}", f"SELECT COUNT(*) FROM {DATASET}.{TABLE_2}", ], "useLegacySql": False, } }, location=location, ) # [START howto_operator_bigquery_get_data] get_data = BigQueryGetDataOperator( task_id="get_data", dataset_id=DATASET, table_id=TABLE_1, max_results=10, selected_fields="value,name", location=location, ) # [END howto_operator_bigquery_get_data] get_data_result = BashOperator( task_id="get_data_result", bash_command=f"echo {get_data.output}", ) # [START howto_operator_bigquery_check] check_count = BigQueryCheckOperator( task_id="check_count", sql=f"SELECT COUNT(*) FROM {DATASET}.{TABLE_1}", use_legacy_sql=False, location=location, ) # [END howto_operator_bigquery_check] # [START howto_operator_bigquery_value_check] check_value = BigQueryValueCheckOperator( task_id="check_value", sql=f"SELECT COUNT(*) FROM {DATASET}.{TABLE_1}", pass_value=4, use_legacy_sql=False, location=location, ) # [END howto_operator_bigquery_value_check] # [START howto_operator_bigquery_interval_check] check_interval = BigQueryIntervalCheckOperator( task_id="check_interval", table=f"{DATASET}.{TABLE_1}", days_back=1, metrics_thresholds={"COUNT(*)": 1.5}, use_legacy_sql=False, location=location, ) # [END howto_operator_bigquery_interval_check] # [START howto_operator_bigquery_column_check] column_check = BigQueryColumnCheckOperator( task_id="column_check", table=f"{DATASET}.{TABLE_1}", column_mapping={"value": {"null_check": {"equal_to": 0}}}, ) # [END howto_operator_bigquery_column_check] # [START howto_operator_bigquery_table_check] table_check = BigQueryTableCheckOperator( task_id="table_check", table=f"{DATASET}.{TABLE_1}", checks={"row_count_check": {"check_statement": {"COUNT(*) = 4"}}}, ) # [END howto_operator_bigquery_table_check] delete_dataset = BigQueryDeleteDatasetOperator( task_id="delete_dataset", dataset_id=DATASET, delete_contents=True, trigger_rule=TriggerRule.ALL_DONE, ) # TEST SETUP create_dataset >> [create_table_1, create_table_2] # TEST BODY [create_table_1, create_table_2] >> insert_query_job >> [select_query_job, execute_insert_query] execute_insert_query >> get_data >> get_data_result >> delete_dataset execute_insert_query >> execute_query_save >> bigquery_execute_multi_query >> delete_dataset execute_insert_query >> [check_count, check_value, check_interval] >> 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() DAGS_LIST.append(dag) globals()[DAG_ID] = dag for dag in DAGS_LIST: from tests.system.utils import get_test_run # Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs] test_run = get_test_run(dag)

Was this entry helpful?