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From Robert Schmidtke <ro.schmid...@gmail.com>
Subject Re: All but one TMs connect when JM has more than 16G of memory
Date Thu, 01 Oct 2015 09:24:30 GMT
Hi Robert,

I had a job failure yesterday with what I believe is the setup I have
described above. However when trying to reproduce now, the behavior is the
same: Flink waiting for resources to become available. So no hard error.

Ok, the looping makes sense then. I haven't thought about shared setups.
I'm still figuring out how all parameters play together, i.e. -yn, -yjm,
-ytm and the memory limits in yarn-site.xml. This will need some testing
and I'll come back with a proper description once I think I know what's
going on.

When running Flink on YARN, is it easily possible to place the Flink JM
where the YARN Resource Manager sits, and all the TMs with the remaining
Node Managers?

Robert

On Thu, Oct 1, 2015 at 10:53 AM, Robert Metzger <rmetzger@apache.org> wrote:

> Hi,
>
> It is interesting to note that when I set both yarn.nodemanager.resource.memory-mb
>> and yarn.scheduler.maximum-allocation-mb to 56G I get a proper error
>> when requesting 56G and 1M, but when setting yarn.nodemanager.resource.memory-mb
>> to 56G and yarn.scheduler.maximum-allocation-mb to 54G I don't get an
>> error but the aforementioned endless loop.
>
>
> is it a "hard error" (failing) you're getting or just "WARN" log messages.
> I'm asking because I've added some code some time ago to do some checks
> before deploying Flink on YARN. These checks will print WARN log messages
> if the requested YARN session/job does not fit onto the cluster.
> This "endless loop" exists because in many production environments Flink
> can just wait for resources to become available, for example when other
> containers are finishing.
>
>
> Robert
>
> On Wed, Sep 30, 2015 at 6:33 PM, Robert Schmidtke <ro.schmidtke@gmail.com>
> wrote:
>
>> Hi Robert,
>>
>> thanks for your reply. It got me digging into my setup and I discovered
>> that one TM was scheduled next to the JM. When specifying -yn 7 the
>> documentation suggests that this is the number of TMs (of which I wanted
>> 7), and I thought an additional container would be used for the JM (my YARN
>> cluster has 8 containers). Anyway with this setup the memory added up to
>> 56G and 1M (40G per TM and 16G 1M for the JM), but I set a hard maximum of
>> 56G in my yarn-site.xml which is why the request could not be fulfilled. It
>> is interesting to note that when I set
>> both yarn.nodemanager.resource.memory-mb
>> and yarn.scheduler.maximum-allocation-mb to 56G I get a proper error when
>> requesting 56G and 1M, but when setting yarn.nodemanager.resource.memory-mb
>> to 56G and yarn.scheduler.maximum-allocation-mb to 54G I don't get an error
>> but the aforementioned endless loop. Note I
>> have yarn.nodemanager.vmem-check-enabled set to false. This is probably a
>> YARN issue then / my bad configuration.
>>
>> I'm in a rush now (to get to the Flink meetup) and thus will check the
>> documentation later to see how to deploy the TMs and JM on separate
>> machines each, since that is not what's happening at the moment, but this
>> is what I'd like to have. Thanks again and see you in an hour.
>>
>> Cheers
>> Robert
>>
>> On Wed, Sep 30, 2015 at 5:19 PM, Robert Metzger <rmetzger@apache.org>
>> wrote:
>>
>>> Hi Robert,
>>>
>>> the problem here is that YARN's scheduler (there are different
>>> schedulers in YARN: FIFO, CapacityScheduler, ...) is not giving Flink's
>>> ApplicationMaster/JobManager all the containers it is requesting. By
>>> increasing the size of the AM/JM container, there is probably no memory
>>> left to fit the last TaskManager container.
>>> I also experienced this issue, when I wanted to run a Flink job on YARN
>>> and the containers were fitting theoretically, but YARN was not giving me
>>> all the containers I requested.
>>> Back then, I asked on the yarn-dev list [1] (there were also some
>>> off-list emails) but we could not resolve the issue.
>>>
>>> Can you check the resource manager logs? Maybe there is a log message
>>> which explains why the container request of Flink's AM is not fulfilled.
>>>
>>>
>>> [1]
>>> http://search-hadoop.com/m/AsBtCilK5r1pKLjf1&subj=Re+QUESTION+Allocating+a+full+YARN+cluster
>>>
>>> On Wed, Sep 30, 2015 at 5:02 PM, Robert Schmidtke <
>>> ro.schmidtke@gmail.com> wrote:
>>>
>>>> It's me again. This is a strange issue, I hope I managed to find the
>>>> right keywords. I got 8 machines, 1 for the JM, the other 7 are TMs with
>>>> 64G of memory each.
>>>>
>>>> When running my job like so:
>>>>
>>>> $FLINK_HOME/bin/flink run -m yarn-cluster -yjm 16384 -ytm 40960 -yn 7
>>>> .....
>>>>
>>>> The job completes without any problems. When running it like so:
>>>>
>>>> $FLINK_HOME/bin/flink run -m yarn-cluster -yjm 16385 -ytm 40960 -yn 7
>>>> .....
>>>>
>>>> (note the one more M of memory for the JM), the execution stalls,
>>>> continuously reporting:
>>>>
>>>> .....
>>>> TaskManager status (6/7)
>>>> TaskManager status (6/7)
>>>> TaskManager status (6/7)
>>>> .....
>>>>
>>>> I did some poking around, but I couldn't find any direct correlation
>>>> with the code.
>>>>
>>>> The JM log says:
>>>>
>>>> .....
>>>> 16:49:01,893 INFO  org.apache.flink.yarn.ApplicationMaster$
>>>>          -  JVM Options:
>>>> 16:49:01,893 INFO  org.apache.flink.yarn.ApplicationMaster$
>>>>          -     -Xmx12289M
>>>> .....
>>>>
>>>> but then continues to report
>>>>
>>>> .....
>>>> 16:52:59,311 INFO
>>>>  org.apache.flink.yarn.ApplicationMaster$$anonfun$2$$anon$1    - The user
>>>> requested 7 containers, 6 running. 1 containers missing
>>>> 16:52:59,831 INFO
>>>>  org.apache.flink.yarn.ApplicationMaster$$anonfun$2$$anon$1    - The user
>>>> requested 7 containers, 6 running. 1 containers missing
>>>> 16:53:00,351 INFO
>>>>  org.apache.flink.yarn.ApplicationMaster$$anonfun$2$$anon$1    - The user
>>>> requested 7 containers, 6 running. 1 containers missing
>>>> .....
>>>>
>>>> forever until I cancel the job.
>>>>
>>>> If you have any ideas I'm happy to try them out. Thanks in advance for
>>>> any hints! Cheers.
>>>>
>>>> Robert
>>>> --
>>>> My GPG Key ID: 336E2680
>>>>
>>>
>>>
>>
>>
>> --
>> My GPG Key ID: 336E2680
>>
>
>


-- 
My GPG Key ID: 336E2680

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