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From "Hila Visan (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (AIRFLOW-366) SchedulerJob gets locked up when when child processes attempt to log to single file
Date Tue, 01 Nov 2016 09:11:58 GMT

    [ https://issues.apache.org/jira/browse/AIRFLOW-366?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15624870#comment-15624870
] 

Hila Visan commented on AIRFLOW-366:
------------------------------------

Bolke, 
where can I configure the use of sysLog? I wan't to try this workaround.
Thanks

> SchedulerJob gets locked up when when child processes attempt to log to single file
> -----------------------------------------------------------------------------------
>
>                 Key: AIRFLOW-366
>                 URL: https://issues.apache.org/jira/browse/AIRFLOW-366
>             Project: Apache Airflow
>          Issue Type: Bug
>          Components: scheduler
>            Reporter: Greg Neiheisel
>            Assignee: Bolke de Bruin
>
> After running the scheduler for a while (usually after 1 - 5 hours) it will eventually
lock up, and nothing will get scheduled.
> A `SchedulerJob` will end up getting stuck in the `while` loop around line 730 of `airflow/jobs.py`.
> From what I can tell this is related to logging from within a forked process using pythons
multiprocessing module.
> The job will fork off some child processes to process the DAGs but one (or more) will
end up getting suck and not terminating, resulting in the while loop getting hung up.  You
can `kill -9 PID` the child process manually, and the loop will end and the scheduler will
go on it's way, until it happens again.
> The issue is due to usage of the logging module from within the child processes.  From
what I can tell, logging to a file from multiple processes is not supported by the multiprocessing
module, but it is supported using python multithreading, using some sort of locking mechanism.
> I think a child process will somehow inherit a logger that is locked, right when it is
forked, resulting it the process completely locking up.
> I went in and commented out all the logging statements that could possibly be hit by
the child process (jobs.py, models.py), and was able to keep the scheduler alive.



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