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

#
# 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 Sensors.
"""

from __future__ import annotations

import os
from datetime import datetime

from airflow.models.dag import DAG
from airflow.providers.google.cloud.operators.bigquery import (
    BigQueryCreateEmptyDatasetOperator,
    BigQueryCreateEmptyTableOperator,
    BigQueryDeleteDatasetOperator,
    BigQueryInsertJobOperator,
)
from airflow.providers.google.cloud.sensors.bigquery import (
    BigQueryTableExistenceSensor,
    BigQueryTablePartitionExistenceSensor,
)
from airflow.utils.trigger_rule import TriggerRule

[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID", "default")
[docs]PROJECT_ID = os.environ.get("SYSTEM_TESTS_GCP_PROJECT", "default")
[docs]DAG_ID = "example_bigquery_sensors"
[docs]DATASET_NAME = f"dataset_{DAG_ID}_{ENV_ID}".replace("-", "_")
[docs]TABLE_NAME = f"partitioned_table_{DAG_ID}_{ENV_ID}".replace("-", "_")
[docs]INSERT_DATE = datetime.now().strftime("%Y-%m-%d")
[docs]PARTITION_NAME = "{{ ds_nodash }}"
[docs]INSERT_ROWS_QUERY = f"INSERT {DATASET_NAME}.{TABLE_NAME} VALUES (42, '{{{{ ds }}}}')"
[docs]SCHEMA = [ {"name": "value", "type": "INTEGER", "mode": "REQUIRED"}, {"name": "ds", "type": "DATE", "mode": "NULLABLE"}, ]
with DAG( DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "bigquery", "sensors"], user_defined_macros={"DATASET": DATASET_NAME, "TABLE": TABLE_NAME}, default_args={"project_id": PROJECT_ID}, ) as dag:
[docs] create_dataset = BigQueryCreateEmptyDatasetOperator( task_id="create_dataset", dataset_id=DATASET_NAME, project_id=PROJECT_ID )
create_table = BigQueryCreateEmptyTableOperator( task_id="create_table", dataset_id=DATASET_NAME, table_id=TABLE_NAME, schema_fields=SCHEMA, time_partitioning={ "type": "DAY", "field": "ds", }, ) # [START howto_sensor_bigquery_table] check_table_exists = BigQueryTableExistenceSensor( task_id="check_table_exists", project_id=PROJECT_ID, dataset_id=DATASET_NAME, table_id=TABLE_NAME ) # [END howto_sensor_bigquery_table] # [START howto_sensor_bigquery_table_defered] check_table_exists_def = BigQueryTableExistenceSensor( task_id="check_table_exists_def", project_id=PROJECT_ID, dataset_id=DATASET_NAME, table_id=TABLE_NAME, deferrable=True, ) # [END howto_sensor_bigquery_table_defered] # [START howto_sensor_async_bigquery_table] check_table_exists_async = BigQueryTableExistenceSensor( task_id="check_table_exists_async", project_id=PROJECT_ID, dataset_id=DATASET_NAME, table_id=TABLE_NAME, ) # [END howto_sensor_async_bigquery_table] execute_insert_query = BigQueryInsertJobOperator( task_id="execute_insert_query", configuration={ "query": { "query": INSERT_ROWS_QUERY, "useLegacySql": False, } }, ) # [START howto_sensor_bigquery_table_partition] check_table_partition_exists = BigQueryTablePartitionExistenceSensor( task_id="check_table_partition_exists", project_id=PROJECT_ID, dataset_id=DATASET_NAME, table_id=TABLE_NAME, partition_id=PARTITION_NAME, ) # [END howto_sensor_bigquery_table_partition] # [START howto_sensor_bigquery_table_partition_defered] check_table_partition_exists_def = BigQueryTablePartitionExistenceSensor( task_id="check_table_partition_exists_def", project_id=PROJECT_ID, dataset_id=DATASET_NAME, table_id=TABLE_NAME, partition_id=PARTITION_NAME, deferrable=True, ) # [END howto_sensor_bigquery_table_partition_defered] # [START howto_sensor_bigquery_table_partition_async] check_table_partition_exists_async = BigQueryTablePartitionExistenceSensor( task_id="check_table_partition_exists_async", partition_id=PARTITION_NAME, project_id=PROJECT_ID, dataset_id=DATASET_NAME, table_id=TABLE_NAME, ) # [END howto_sensor_bigquery_table_partition_async] delete_dataset = BigQueryDeleteDatasetOperator( task_id="delete_dataset", dataset_id=DATASET_NAME, delete_contents=True, trigger_rule=TriggerRule.ALL_DONE, ) ( create_dataset >> create_table >> [check_table_exists, check_table_exists_async, check_table_exists_def] >> execute_insert_query >> [ check_table_partition_exists, check_table_partition_exists_async, check_table_partition_exists_def, ] >> 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)

Was this entry helpful?