Source code for tests.system.providers.databricks.example_databricks_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
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations

import os
import textwrap
from datetime import datetime

from airflow import DAG
from airflow.providers.databricks.sensors.databricks_partition import DatabricksPartitionSensor
from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor

# [Env variable to be used from the OS]
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
# [DAG name to be shown on Airflow UI]
[docs]DAG_ID = "example_databricks_sensor"
with DAG( dag_id=DAG_ID, schedule="@daily", start_date=datetime(2021, 1, 1), tags=["example"], catchup=False, ) as dag: dag.doc_md = textwrap.dedent( """ This is an example DAG which uses the DatabricksSqlSensor sensor. The example task in the DAG executes the provided SQL query against the Databricks SQL warehouse and if a result is returned, the sensor returns True/succeeds. If no results are returned, the sensor returns False/ fails. """ ) # [START howto_sensor_databricks_connection_setup] # Connection string setup for Databricks workspace.
[docs] connection_id = "databricks_default"
sql_warehouse_name = "Starter Warehouse" # [END howto_sensor_databricks_connection_setup] # [START howto_sensor_databricks_sql] # Example of using the Databricks SQL Sensor to check existence of data in a table. sql_sensor = DatabricksSqlSensor( databricks_conn_id=connection_id, sql_warehouse_name=sql_warehouse_name, catalog="hive_metastore", task_id="sql_sensor_task", sql="select * from hive_metastore.temp.sample_table_3 limit 1", timeout=60 * 2, ) # [END howto_sensor_databricks_sql] # [START howto_sensor_databricks_partition] # Example of using the Databricks Partition Sensor to check the presence # of the specified partition(s) in a table. partition_sensor = DatabricksPartitionSensor( databricks_conn_id=connection_id, sql_warehouse_name=sql_warehouse_name, catalog="hive_metastore", task_id="partition_sensor_task", table_name="sample_table_2", schema="temp", partitions={"date": "2023-01-03", "name": ["abc", "def"]}, partition_operator="=", timeout=60 * 2, ) # [END howto_sensor_databricks_partition] # Task dependency between the SQL sensor and the partition sensor. # If the first task(sql_sensor) succeeds, the second task(partition_sensor) # runs, else all the subsequent DAG tasks and the DAG are marked as failed. (sql_sensor >> partition_sensor) from tests.system.utils.watcher import watcher # This example does not need a watcher in order to properly mark success/failure # since it is a single task, but it is given here as an example for users to # extend it to their use cases. # 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/
[docs]test_run = get_test_run(dag)

Was this entry helpful?