pankajkoti commented on code in PR #39110:
URL: https://github.com/apache/airflow/pull/39110#discussion_r1579863752
##########
airflow/providers/databricks/triggers/databricks.py:
##########
@@ -84,13 +84,30 @@ async def run(self):
async with self.hook:
while True:
run_state = await self.hook.a_get_run_state(self.run_id)
+ notebook_error = None
if run_state.is_terminal:
+ if run_state.result_state == "FAILED":
+ run_info = await self.hook.a_get_run(self.run_id)
+ task_run_id = None
+ if "tasks" in run_info:
+ for task in run_info["tasks"]:
+ if task.get("state", {}).get("result_state",
"") == "FAILED":
+ task_run_id = task["run_id"]
Review Comment:
task run id alone won't help much to trace the task itself, no? maybe
[task_key](https://docs.databricks.com/api/workspace/jobs/getrun#tasks-task_key)
would help identify the task too.
I think building a list of all failed tasks and outputting it might help.
The final list of failed tasks could be something like
```
failed_tasks = [
{
"task_key": ".....",
"run_id": "....",
"error": run_output["error"] or run_state.state_message # need to
construct this as per your currrent logic
},
{
"task_key": ".....",
"run_id": "....",
"error": run_output["error"] or run_state.state_message # need to
construct this as per your currrent logic
}
]
```
WDYT?
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
