example_bigquery_queries.py

#
# 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

ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT")
LOCATION = "us-east1"
QUERY_SQL_PATH = "resources/example_bigquery_query.sql"

TABLE_1 = "table1"
TABLE_2 = "table2"

SCHEMA = [
    {"name": "value", "type": "INTEGER", "mode": "REQUIRED"},
    {"name": "name", "type": "STRING", "mode": "NULLABLE"},
    {"name": "ds", "type": "DATE", "mode": "NULLABLE"},
]

DAGS_LIST = []
locations = [None, LOCATION]
for index, location in enumerate(locations, 1):
    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,
                    "priority": "BATCH",
                }
            },
            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)
    test_run = get_test_run(dag)