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From Garrett Barton <garrett.bar...@gmail.com>
Subject Re: Flink 1.5 Yarn Connection unexpectedly closed
Date Thu, 21 Jun 2018 17:43:12 GMT
Actually, random thought, could yarn preemption be causing this?  What is
the failure scenario should a working task manager go down in yarn that is
doing real work?  The docs make it sound like it should fire up another TM
and get back to work out of the box, but I'm not seeing that.

On Thu, Jun 21, 2018 at 1:20 PM Garrett Barton <garrett.barton@gmail.com>

> Thank you all for the reply!
> I am running batch jobs, I read in a handful of files from HDFS and output
> to HBase, HDFS, and Kafka.  I run into this when I have partial usage of
> the cluster as the job runs.  So right now I spin up 20 nodes with 3 slots,
> my job at peak uses all 60 slots, but by the end of it since my outputs are
> all forced parallel 1 while I work out kinks, that all typically ends up
> running in 1 or two task managers tops.  The other 18-19 task managers die
> off.  Problem is as soon as any task manager dies off, my client throws the
> above exception and the job fails.
> I cannot share logs, but I was thinking about writing a dirt simple
> mapreduce flow based on the wordcount example.  The example would have a
> wide map phase that generates data, and then I'd run it through a reducer
> that sleeps maybe 1 second every record.  I believe that will simulate my
> condition very well where I go from 100% used slots to only 1-2 used slots
> as I hit that timeout.  I'll do that today and let you know, if it works I
> can share the code in here as an example.
> On Thu, Jun 21, 2018 at 5:01 AM Till Rohrmann <trohrmann@apache.org>
> wrote:
>> Hi Garrett,
>> killing of idle TaskManager should not affect the execution of the job.
>> By definition a TaskManager only idles if it does not execute any tasks.
>> Could you maybe share the complete logs (of the cluster entrypoint and all
>> TaskManagers) with us?
>> Cheers,
>> Till
>> On Thu, Jun 21, 2018 at 10:26 AM Fabian Hueske <fhueske@gmail.com> wrote:
>>> Hi Garrett,
>>> I agree, there seems to be an issue and increasing the timeout should
>>> not be the right approach to solve it.
>>> Are you running streaming or batch jobs, i.e., do some of the tasks
>>> finish much earlier than others?
>>> I'm adding Till to this thread who's very familiar with scheduling and
>>> process communication.
>>> Best, Fabian
>>> 2018-06-19 0:03 GMT+02:00 Garrett Barton <garrett.barton@gmail.com>:
>>>> Hey all,
>>>>  My jobs that I am trying to write in Flink 1.5 are failing after a few
>>>> minutes.  I think its because the idle task managers are shutting down,
>>>> which seems to kill the client and the running job. The running job itself
>>>> was still going on one of the other task managers.  I get:
>>>> org.apache.flink.client.program.ProgramInvocationException:
>>>> org.apache.flink.runtime.io.network.netty.exception.RemoteTransportException:
>>>> Connection unexpectedly closed by remote task manager 'xxxx'. This might
>>>> indicate that the remote task manager was lost.
>>>> at org.apache.flink.runtime.io
>>>> .network.netty.CreditBasedPartitionRequestClientHandler.channelInactive(CreditBasedPartitionRequestClientHandler.java:143)
>>>> Now I happen to have the last part of the flow paralleled to 1 right
>>>> now for debugging, so the 4 task managers that are spun up, 3 of them hit
>>>> the timeout period (currently set to 240000).  I think as soon as the first
>>>> one goes the client throws up and the whole job dies as a result.
>>>>  Is this expected behavior and if so, is there another way around it?
>>>> Do I keep increasing the slotmanager.taskmanager-timeout to a really really
>>>> large number? I have verified setting the timeout to 840000 lets the job
>>>> complete without error.
>>>> Thank you!

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