burakyilmaz321 commented on code in PR #23712:
URL: https://github.com/apache/airflow/pull/23712#discussion_r875320949


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airflow/providers/databricks/sensors/databricks.py:
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@@ -0,0 +1,103 @@
+#
+# 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.
+"""Databricks sensors"""
+
+from typing import TYPE_CHECKING, Any, Dict, Optional, Sequence, Union
+
+from airflow.exceptions import AirflowException
+from airflow.providers.databricks.hooks.databricks import DatabricksHook
+from airflow.sensors.base import BaseSensorOperator
+from airflow.utils.context import Context
+
+if TYPE_CHECKING:
+    from airflow.sensors.base import PokeReturnValue
+
+
+class DatabricksJobRunSensor(BaseSensorOperator):
+    """
+    Check for the state of a submitted Databricks job run or specific task of 
a job run.
+
+    :param run_id: Id of the submitted Databricks job run or specific task of 
a job run. (templated)
+    :param databricks_conn_id: Reference to the :ref:`Databricks connection 
<howto/connection:databricks>`.
+        By default and in the common case this will be ``databricks_default``. 
To use
+        token based authentication, provide the key ``token`` in the extra 
field for the
+        connection and create the key ``host`` and leave the ``host`` field 
empty.
+    :param retry_limit: Amount of times retry if the Databricks backend is
+        unreachable. Its value must be greater than or equal to 1.
+    :param retry_delay_seconds: Number of seconds to wait between retries (it
+            might be a floating point number).
+    :param databricks_retry_args: An optional dictionary with arguments passed 
to ``tenacity.Retrying`` class.
+    """
+
+    template_fields: Sequence[str] = ('run_id',)

Review Comment:
   I think this could be useful when we submit a multi-task job and listen each 
task separately from Airflow. I have a use case like this: I'm submitting 
multiple tasks to a single job cluster. I want to track each task's status from 
Airflow. I'm using this as following:
   
   ```python
   # Proof of concept dag that submits multiple tasks to a single
   # job cluster and watches every task's status separately
   @dag(schedule_interval=None, start_date=datetime(2021, 1, 1))
   def dbx_poc():
       tasks_keys = ["t1", "t2"]
   
       @task
       def submit_job_run_and_get_tasks(job_id: int) -> Dict[str, str]:
           hook = DatabricksHook()
           run_id = hook.run_now({"job_id": job_id})
           response = hook._do_api_call(GET_RUN_ENDPOINT, {"run_id": run_id})
           tasks = {task["task_key"]: task["run_id"] for task in 
response["tasks"]}
           return tasks
   
       tasks = submit_job_run_and_get_tasks(job_id=1234)
   
       for task_key in tasks_keys:
           tasks >> DatabricksJobRunSensor(task_id=f"wait_{task_key}", 
run_id=tasks[task_key])
   
   dag = dbx_poc()
   ```
   
   Basically, I'm submitting a multi-task job, get the run ids for each task 
and push them to XCOM, and create multiple sensors for each task using the 
templated run_id field.
   
   Does that make sense?



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