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Posted to commits@airflow.apache.org by "Mike Perry (JIRA)" <ji...@apache.org> on 2017/07/02 18:25:03 UTC

[jira] [Commented] (AIRFLOW-366) SchedulerJob gets locked up when when child processes attempt to log to single file

    [ https://issues.apache.org/jira/browse/AIRFLOW-366?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16071748#comment-16071748 ] 

Mike Perry commented on AIRFLOW-366:
------------------------------------

We're still seeing this in airflow 1.8.1. Any other thoughts on a possible workaround? We've tried removing all log statements from jobs.py and models.py, and  replaced setup_logging per [~bolke]'s syslog suggestion above. 

> 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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