We are getting the logs like
{local_executor.py:43} INFO - LocalWorker running airflow run
{models.py:1595} ERROR - Executor reports task instance %s finished (%s)
although the task says its %s. Was the task killed externally?
{models.py:1616} INFO - Marking task as UP_FOR_RETRY
It seems that
Hi,
I would like to know on how to get the status of a task & then based on that I
would like to pass the values to the next job as a value.
Example :
Task1 -- Run for 2 hours
Task2 - Check on task1, if complete - Then a message is sent saying task1 is
complete.
If Failed - Send a msg as
Hi Raman,
Does it happen only occasionally, or can it be easily reproduced?
What happens if you start it with "airflow run" or " airflow test"?
What is in the logs about it?
What is your user process limit ("ulimit -u") on that machine?
2018-08-17 15:39 GMT+02:00 ramandu...@gmail.com :
>
Thanks Taylor,
We are getting this issue even after restart. We are observing that task
instance state is transitioned from
scheduled->queued->up_for_retry and dag gets stuck in up_for_retry state.
Behind the scenes executor keep on retrying the dag's task exceeding the max
retry limit.
In
