Hi,
we face the same issue with latest version.
*environment:*
*airflow* 1.7.1.3.
*postgress *9.2.13 (backend DB)
*OS*   Red Hat Enterprise Linux Server 7.2 (Maipo)
*python* 2.7.5
*celery* version 3.1.23
*kombu  *3.0.35
*rabbitMQ *3.3.5

airflow.config is attached

logs of scheduler and rabbitmq are too big, i can't attach them here.

do you want the end of the log?


i'll be happy to provide more info....







On Wed, Sep 7, 2016 at 8:40 AM, Bolke de Bruin <[email protected]> wrote:

> 1.6.2 is quite old and many updates to the scheduler have been made.
> Please make sure to use 1.7.1.3 or master.
>
> Also memory corruption requires more details as that indicates a problem
> with the interpreter itself. Then you would get a core dump and a SIGSEV.
> Did you get those?
>
> Bolke
>
> Sent from my iPhone
>
> > On 7 sep. 2016, at 02:45, Lance Norskog <[email protected]> wrote:
> >
> > Add your Airflow version and your Python & OS.
> > I'm on Py 2.7, Airflow 1.6.2 and have seen few different manifestions of
> > memory corruption.
> >
> >
> >> On Sun, Sep 4, 2016 at 1:38 PM, Bolke de Bruin <[email protected]>
> wrote:
> >>
> >> That would be interesting, but dying - are you sure you are not running
> >> with num_runs enabled?
> >>
> >> Yes please specify details.
> >>
> >> Verstuurd vanaf mijn iPad
> >>
> >> Op 4 sep. 2016 om 15:57 heeft Andrew Phillips <[email protected]> het
> >> volgende geschreven:
> >>
> >>>> First and foremost I am assuming that getting “stuck” is only
> >>>> happening when using a CeleryExecutor.
> >>>
> >>> We have seen repeated instanced of the scheduler "dying" - i.e. no more
> >> scheduler threads in a ps output - with LocalExecutor too. If you feel
> this
> >> fits the description of "getting stuck", happy to provide more detail to
> >> try to get to a reproducible situation.
> >>>
> >>> Regards
> >>>
> >>> ap
> >
> >
> >
> > --
> > Lance Norskog
> > [email protected]
> > Redwood City, CA
>

Reply via email to