Re: how to have good DAG+Kubernetes behavior on airflow crash/recovery?

[Grant Nicholas]

When you see the task being launched again on startup of the executor, does
the second launched task get killed when it tries to startup or does it
actually run the `execute` task instance method (and try to launch a pod on
kubernetes).

I ask because the latter should not happen if postgres is healthy(due to
row level locking in the ti table).

The kubernetes executor work is trying to iron out crash safety issues, as
it's super important to be able to tolerate failures when running the
scheduler in a container orchestrator. So surfacing these edge cases would
be super useful.

On Dec 17, 2017 2:38 PM, "Christopher Bockman" 
wrote:

> Hmm, perhaps we've just had a couple of bad/unlucky runs but, in general,
> the underlying task-kill process doesn't really seem to work, from what
> we've seen.  I would guess this is related to
> https://issues.apache.org/jira/browse/AIRFLOW-1623.
>
>
>
> On Sun, Dec 17, 2017 at 12:22 PM, Bolke de Bruin 
> wrote:
>
> > Shorter heartbeats, you might still have some tasks being scheduled
> > nevertheless due to the time window. However, if the tasks detects it is
> > running somewhere else, it should also terminate itself.
> >
> > [scheduler]
> > # Task instances listen for external kill signal (when you clear tasks
> > # from the CLI or the UI), this defines the frequency at which they
> should
> > # listen (in seconds).
> > job_heartbeat_sec = 5
> >
> > Bolke.
> >
> >
> > > On 17 Dec 2017, at 20:59, Christopher Bockman 
> > wrote:
> > >
> > >> P.S. I am assuming that you are talking about your scheduler going
> down,
> > > not workers
> > >
> > > Correct (and, in some unfortunate scenarios, everything else...)
> > >
> > >> Normally a task will detect (on the heartbeat interval) whether its
> > state
> > > was changed externally and will terminate itself.
> > >
> > > Hmm, that would be an acceptable solution, but this doesn't
> > (automatically,
> > > in our current configuration) occur.  How can we encourage this
> behavior
> > to
> > > happen?
> > >
> > >
> > > On Sun, Dec 17, 2017 at 11:47 AM, Bolke de Bruin 
> > wrote:
> > >
> > >> Quite important to know is, is that Airflow’s executors do not keep
> > state
> > >> after a restart. This particularly affects distributed executors
> > (celery,
> > >> dask) as the workers are independent from the scheduler. Thus at
> > restart we
> > >> reset all the tasks in the queued state that the executor does not
> know
> > >> about, which means all of them at the moment. Due to the distributed
> > nature
> > >> of the executors, tasks can still be running. Normally a task will
> > detect
> > >> (on the heartbeat interval) whether its state was changed externally
> and
> > >> will terminate itself.
> > >>
> > >> I have done some work some months ago to make the executor keep state
> > over
> > >> restarts, but never got around to finish it.
> > >>
> > >> So at the moment, to prevent requeuing, you need to make the airflow
> > >> scheduler no go down (as much).
> > >>
> > >> Bolke.
> > >>
> > >> P.S. I am assuming that you are talking about your scheduler going
> down,
> > >> not workers
> > >>
> > >>> On 17 Dec 2017, at 20:07, Christopher Bockman  >
> > >> wrote:
> > >>>
> > >>> Upon further internal discussion, we might be seeing the task cloning
> > >>> because the postgres DB is getting into a corrupted state...but
> > unclear.
> > >>> If consensus is we *shouldn't* be seeing this behavior, even as-is,
> > we'll
> > >>> push more on that angle.
> > >>>
> > >>> On Sun, Dec 17, 2017 at 10:45 AM, Christopher Bockman <
> > >> ch...@fathomhealth.co
> >  wrote:
> > >>>
> >  Hi all,
> > 
> >  We run DAGs, and sometimes Airflow crashes (for whatever
> reason--maybe
> >  something as simple as the underlying infrastructure going down).
> > 
> >  Currently, we run everything on Kubernetes (including Airflow), so
> the
> >  Airflow pods crashes generally will be detected, and then they will
> > >> restart.
> > 
> >  However, if we have, e.g., a DAG that is running task X when it
> > crashes,
> >  when Airflow comes back up, it apparently sees task X didn't
> complete,
> > >> so
> >  it restarts the task (which, in this case, means it spins up an
> > entirely
> >  new instance/pod).  Thus, both run "X_1" and "X_2" are fired off
> >  simultaneously.
> > 
> >  Is there any (out of the box) way to better connect up state between
> > >> tasks
> >  and Airflow to prevent this?
> > 
> >  (For additional context, we currently execute Kubernetes jobs via a
> > >> custom
> >  operator that basically layers on top of BashOperator...perhaps the
> > new
> >  Kubernetes operator will help address this?)
> > 
> >  Thank you in advance for any thoughts,
> > 
> >  Chris
> > 
> > >>
> > >>
> >
> >
>

Re: how to have good DAG+Kubernetes behavior on airflow crash/recovery?

[Christopher Bockman]

Hmm, perhaps we've just had a couple of bad/unlucky runs but, in general,
the underlying task-kill process doesn't really seem to work, from what
we've seen.  I would guess this is related to
https://issues.apache.org/jira/browse/AIRFLOW-1623.



On Sun, Dec 17, 2017 at 12:22 PM, Bolke de Bruin  wrote:

> Shorter heartbeats, you might still have some tasks being scheduled
> nevertheless due to the time window. However, if the tasks detects it is
> running somewhere else, it should also terminate itself.
>
> [scheduler]
> # Task instances listen for external kill signal (when you clear tasks
> # from the CLI or the UI), this defines the frequency at which they should
> # listen (in seconds).
> job_heartbeat_sec = 5
>
> Bolke.
>
>
> > On 17 Dec 2017, at 20:59, Christopher Bockman 
> wrote:
> >
> >> P.S. I am assuming that you are talking about your scheduler going down,
> > not workers
> >
> > Correct (and, in some unfortunate scenarios, everything else...)
> >
> >> Normally a task will detect (on the heartbeat interval) whether its
> state
> > was changed externally and will terminate itself.
> >
> > Hmm, that would be an acceptable solution, but this doesn't
> (automatically,
> > in our current configuration) occur.  How can we encourage this behavior
> to
> > happen?
> >
> >
> > On Sun, Dec 17, 2017 at 11:47 AM, Bolke de Bruin 
> wrote:
> >
> >> Quite important to know is, is that Airflow’s executors do not keep
> state
> >> after a restart. This particularly affects distributed executors
> (celery,
> >> dask) as the workers are independent from the scheduler. Thus at
> restart we
> >> reset all the tasks in the queued state that the executor does not know
> >> about, which means all of them at the moment. Due to the distributed
> nature
> >> of the executors, tasks can still be running. Normally a task will
> detect
> >> (on the heartbeat interval) whether its state was changed externally and
> >> will terminate itself.
> >>
> >> I have done some work some months ago to make the executor keep state
> over
> >> restarts, but never got around to finish it.
> >>
> >> So at the moment, to prevent requeuing, you need to make the airflow
> >> scheduler no go down (as much).
> >>
> >> Bolke.
> >>
> >> P.S. I am assuming that you are talking about your scheduler going down,
> >> not workers
> >>
> >>> On 17 Dec 2017, at 20:07, Christopher Bockman 
> >> wrote:
> >>>
> >>> Upon further internal discussion, we might be seeing the task cloning
> >>> because the postgres DB is getting into a corrupted state...but
> unclear.
> >>> If consensus is we *shouldn't* be seeing this behavior, even as-is,
> we'll
> >>> push more on that angle.
> >>>
> >>> On Sun, Dec 17, 2017 at 10:45 AM, Christopher Bockman <
> >> ch...@fathomhealth.co
>  wrote:
> >>>
>  Hi all,
> 
>  We run DAGs, and sometimes Airflow crashes (for whatever reason--maybe
>  something as simple as the underlying infrastructure going down).
> 
>  Currently, we run everything on Kubernetes (including Airflow), so the
>  Airflow pods crashes generally will be detected, and then they will
> >> restart.
> 
>  However, if we have, e.g., a DAG that is running task X when it
> crashes,
>  when Airflow comes back up, it apparently sees task X didn't complete,
> >> so
>  it restarts the task (which, in this case, means it spins up an
> entirely
>  new instance/pod).  Thus, both run "X_1" and "X_2" are fired off
>  simultaneously.
> 
>  Is there any (out of the box) way to better connect up state between
> >> tasks
>  and Airflow to prevent this?
> 
>  (For additional context, we currently execute Kubernetes jobs via a
> >> custom
>  operator that basically layers on top of BashOperator...perhaps the
> new
>  Kubernetes operator will help address this?)
> 
>  Thank you in advance for any thoughts,
> 
>  Chris
> 
> >>
> >>
>
>

Re: how to have good DAG+Kubernetes behavior on airflow crash/recovery?

[Bolke de Bruin]

Shorter heartbeats, you might still have some tasks being scheduled 
nevertheless due to the time window. However, if the tasks detects it is 
running somewhere else, it should also terminate itself.

[scheduler]
# Task instances listen for external kill signal (when you clear tasks
# from the CLI or the UI), this defines the frequency at which they should
# listen (in seconds).
job_heartbeat_sec = 5

Bolke.


> On 17 Dec 2017, at 20:59, Christopher Bockman  wrote:
> 
>> P.S. I am assuming that you are talking about your scheduler going down,
> not workers
> 
> Correct (and, in some unfortunate scenarios, everything else...)
> 
>> Normally a task will detect (on the heartbeat interval) whether its state
> was changed externally and will terminate itself.
> 
> Hmm, that would be an acceptable solution, but this doesn't (automatically,
> in our current configuration) occur.  How can we encourage this behavior to
> happen?
> 
> 
> On Sun, Dec 17, 2017 at 11:47 AM, Bolke de Bruin  wrote:
> 
>> Quite important to know is, is that Airflow’s executors do not keep state
>> after a restart. This particularly affects distributed executors (celery,
>> dask) as the workers are independent from the scheduler. Thus at restart we
>> reset all the tasks in the queued state that the executor does not know
>> about, which means all of them at the moment. Due to the distributed nature
>> of the executors, tasks can still be running. Normally a task will detect
>> (on the heartbeat interval) whether its state was changed externally and
>> will terminate itself.
>> 
>> I have done some work some months ago to make the executor keep state over
>> restarts, but never got around to finish it.
>> 
>> So at the moment, to prevent requeuing, you need to make the airflow
>> scheduler no go down (as much).
>> 
>> Bolke.
>> 
>> P.S. I am assuming that you are talking about your scheduler going down,
>> not workers
>> 
>>> On 17 Dec 2017, at 20:07, Christopher Bockman 
>> wrote:
>>> 
>>> Upon further internal discussion, we might be seeing the task cloning
>>> because the postgres DB is getting into a corrupted state...but unclear.
>>> If consensus is we *shouldn't* be seeing this behavior, even as-is, we'll
>>> push more on that angle.
>>> 
>>> On Sun, Dec 17, 2017 at 10:45 AM, Christopher Bockman <
>> ch...@fathomhealth.co
 wrote:
>>> 
 Hi all,
 
 We run DAGs, and sometimes Airflow crashes (for whatever reason--maybe
 something as simple as the underlying infrastructure going down).
 
 Currently, we run everything on Kubernetes (including Airflow), so the
 Airflow pods crashes generally will be detected, and then they will
>> restart.
 
 However, if we have, e.g., a DAG that is running task X when it crashes,
 when Airflow comes back up, it apparently sees task X didn't complete,
>> so
 it restarts the task (which, in this case, means it spins up an entirely
 new instance/pod).  Thus, both run "X_1" and "X_2" are fired off
 simultaneously.
 
 Is there any (out of the box) way to better connect up state between
>> tasks
 and Airflow to prevent this?
 
 (For additional context, we currently execute Kubernetes jobs via a
>> custom
 operator that basically layers on top of BashOperator...perhaps the new
 Kubernetes operator will help address this?)
 
 Thank you in advance for any thoughts,
 
 Chris
 
>> 
>> 

Re: how to have good DAG+Kubernetes behavior on airflow crash/recovery?

[Christopher Bockman]

> P.S. I am assuming that you are talking about your scheduler going down,
not workers

Correct (and, in some unfortunate scenarios, everything else...)

> Normally a task will detect (on the heartbeat interval) whether its state
was changed externally and will terminate itself.

Hmm, that would be an acceptable solution, but this doesn't (automatically,
in our current configuration) occur.  How can we encourage this behavior to
happen?


On Sun, Dec 17, 2017 at 11:47 AM, Bolke de Bruin  wrote:

> Quite important to know is, is that Airflow’s executors do not keep state
> after a restart. This particularly affects distributed executors (celery,
> dask) as the workers are independent from the scheduler. Thus at restart we
> reset all the tasks in the queued state that the executor does not know
> about, which means all of them at the moment. Due to the distributed nature
> of the executors, tasks can still be running. Normally a task will detect
> (on the heartbeat interval) whether its state was changed externally and
> will terminate itself.
>
> I have done some work some months ago to make the executor keep state over
> restarts, but never got around to finish it.
>
> So at the moment, to prevent requeuing, you need to make the airflow
> scheduler no go down (as much).
>
> Bolke.
>
> P.S. I am assuming that you are talking about your scheduler going down,
> not workers
>
> > On 17 Dec 2017, at 20:07, Christopher Bockman 
> wrote:
> >
> > Upon further internal discussion, we might be seeing the task cloning
> > because the postgres DB is getting into a corrupted state...but unclear.
> > If consensus is we *shouldn't* be seeing this behavior, even as-is, we'll
> > push more on that angle.
> >
> > On Sun, Dec 17, 2017 at 10:45 AM, Christopher Bockman <
> ch...@fathomhealth.co
> >> wrote:
> >
> >> Hi all,
> >>
> >> We run DAGs, and sometimes Airflow crashes (for whatever reason--maybe
> >> something as simple as the underlying infrastructure going down).
> >>
> >> Currently, we run everything on Kubernetes (including Airflow), so the
> >> Airflow pods crashes generally will be detected, and then they will
> restart.
> >>
> >> However, if we have, e.g., a DAG that is running task X when it crashes,
> >> when Airflow comes back up, it apparently sees task X didn't complete,
> so
> >> it restarts the task (which, in this case, means it spins up an entirely
> >> new instance/pod).  Thus, both run "X_1" and "X_2" are fired off
> >> simultaneously.
> >>
> >> Is there any (out of the box) way to better connect up state between
> tasks
> >> and Airflow to prevent this?
> >>
> >> (For additional context, we currently execute Kubernetes jobs via a
> custom
> >> operator that basically layers on top of BashOperator...perhaps the new
> >> Kubernetes operator will help address this?)
> >>
> >> Thank you in advance for any thoughts,
> >>
> >> Chris
> >>
>
>

Re: how to have good DAG+Kubernetes behavior on airflow crash/recovery?

[Bolke de Bruin]

Quite important to know is, is that Airflow’s executors do not keep state after 
a restart. This particularly affects distributed executors (celery, dask) as 
the workers are independent from the scheduler. Thus at restart we reset all 
the tasks in the queued state that the executor does not know about, which 
means all of them at the moment. Due to the distributed nature of the 
executors, tasks can still be running. Normally a task will detect (on the 
heartbeat interval) whether its state was changed externally and will terminate 
itself.

I have done some work some months ago to make the executor keep state over 
restarts, but never got around to finish it.

So at the moment, to prevent requeuing, you need to make the airflow scheduler 
no go down (as much).

Bolke.

P.S. I am assuming that you are talking about your scheduler going down, not 
workers

> On 17 Dec 2017, at 20:07, Christopher Bockman  wrote:
> 
> Upon further internal discussion, we might be seeing the task cloning
> because the postgres DB is getting into a corrupted state...but unclear.
> If consensus is we *shouldn't* be seeing this behavior, even as-is, we'll
> push more on that angle.
> 
> On Sun, Dec 17, 2017 at 10:45 AM, Christopher Bockman > wrote:
> 
>> Hi all,
>> 
>> We run DAGs, and sometimes Airflow crashes (for whatever reason--maybe
>> something as simple as the underlying infrastructure going down).
>> 
>> Currently, we run everything on Kubernetes (including Airflow), so the
>> Airflow pods crashes generally will be detected, and then they will restart.
>> 
>> However, if we have, e.g., a DAG that is running task X when it crashes,
>> when Airflow comes back up, it apparently sees task X didn't complete, so
>> it restarts the task (which, in this case, means it spins up an entirely
>> new instance/pod).  Thus, both run "X_1" and "X_2" are fired off
>> simultaneously.
>> 
>> Is there any (out of the box) way to better connect up state between tasks
>> and Airflow to prevent this?
>> 
>> (For additional context, we currently execute Kubernetes jobs via a custom
>> operator that basically layers on top of BashOperator...perhaps the new
>> Kubernetes operator will help address this?)
>> 
>> Thank you in advance for any thoughts,
>> 
>> Chris
>> 

Re: how to have good DAG+Kubernetes behavior on airflow crash/recovery?

[Christopher Bockman]

Upon further internal discussion, we might be seeing the task cloning
because the postgres DB is getting into a corrupted state...but unclear.
If consensus is we *shouldn't* be seeing this behavior, even as-is, we'll
push more on that angle.

On Sun, Dec 17, 2017 at 10:45 AM, Christopher Bockman  wrote:

> Hi all,
>
> We run DAGs, and sometimes Airflow crashes (for whatever reason--maybe
> something as simple as the underlying infrastructure going down).
>
> Currently, we run everything on Kubernetes (including Airflow), so the
> Airflow pods crashes generally will be detected, and then they will restart.
>
> However, if we have, e.g., a DAG that is running task X when it crashes,
> when Airflow comes back up, it apparently sees task X didn't complete, so
> it restarts the task (which, in this case, means it spins up an entirely
> new instance/pod).  Thus, both run "X_1" and "X_2" are fired off
> simultaneously.
>
> Is there any (out of the box) way to better connect up state between tasks
> and Airflow to prevent this?
>
> (For additional context, we currently execute Kubernetes jobs via a custom
> operator that basically layers on top of BashOperator...perhaps the new
> Kubernetes operator will help address this?)
>
> Thank you in advance for any thoughts,
>
> Chris
>

how to have good DAG+Kubernetes behavior on airflow crash/recovery?

[Christopher Bockman]

Hi all,

We run DAGs, and sometimes Airflow crashes (for whatever reason--maybe
something as simple as the underlying infrastructure going down).

Currently, we run everything on Kubernetes (including Airflow), so the
Airflow pods crashes generally will be detected, and then they will restart.

However, if we have, e.g., a DAG that is running task X when it crashes,
when Airflow comes back up, it apparently sees task X didn't complete, so
it restarts the task (which, in this case, means it spins up an entirely
new instance/pod).  Thus, both run "X_1" and "X_2" are fired off
simultaneously.

Is there any (out of the box) way to better connect up state between tasks
and Airflow to prevent this?

(For additional context, we currently execute Kubernetes jobs via a custom
operator that basically layers on top of BashOperator...perhaps the new
Kubernetes operator will help address this?)

Thank you in advance for any thoughts,

Chris