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From Gary Yao <g...@ververica.com>
Subject Re: Flink 1.6 Yarn Session behavior
Date Sun, 17 Feb 2019 18:03:44 GMT
Hi Jins George,

Every TM brings additional overhead, e.g., more heartbeat messages.
However, a
cluster with 28 TMs would not be considered big as there are users that are
running Flink applications on thousands of cores [1][2].

Best,
Gary

[1]
https://flink.apache.org/flink-architecture.html#run-applications-at-any-scale
[2]
https://de.slideshare.net/FlinkForward/flink-forward-sf-2017-stephan-ewen-experiences-running-flink-at-very-large-scale

On Thu, Feb 14, 2019 at 6:59 PM Jins George <Jins.George@aeris.net> wrote:

> Thanks Gary. Understood the behavior.
>
> I am leaning towards running 7 TM on each machine(8 core), I have 4 nodes,
> that will end up 28 taskmanagers and 1 job manager. I was wondering if this
> can bring additional burden on jobmanager? Is it recommended?
>
> Thanks,
>
> Jins George
> On 2/14/19 8:49 AM, Gary Yao wrote:
>
> Hi Jins George,
>
> This has been asked before [1]. The bottom line is that you currently
> cannot
> pre-allocate TMs and distribute your tasks evenly. You might be able to
> achieve a better distribution across hosts by configuring fewer slots in
> your
> TMs.
>
> Best,
> Gary
>
> [1]
> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Flink-1-5-job-distribution-over-cluster-nodes-td21588.html
>
>
> On Wed, Feb 13, 2019 at 6:20 AM Tzu-Li (Gordon) Tai <tzulitai@apache.org>
> wrote:
>
>> Hi,
>>
>> I'm forwarding this question to Gary (CC'ed), who most likely would have
>> an answer for your question here.
>>
>> Cheers,
>> Gordon
>>
>> On Wed, Feb 13, 2019 at 8:33 AM Jins George <Jins.George@aeris.net>
>> wrote:
>>
>>> Hello community,
>>>
>>> I am trying to  upgrade a  Flink Yarn session cluster running BEAM
>>> pipelines  from version 1.2.0 to 1.6.3.
>>>
>>> Here is my session start command: yarn-session.sh -d *-n 4*  -jm 1024
>>> -tm 3072 *-s 7*
>>>
>>> Because of the dynamic resource allocation,  no taskmanager gets created
>>> initially. Now once I submit a job with parallelism 5, I see that 1
>>> task-manager gets created and all 5 parallel instances are scheduled on the
>>> same taskmanager( because I have 7 slots).  This can create hot spot as
>>> only one physical node ( out of 4 in my case) is utilized for processing.
>>>
>>> I noticed the legacy mode, which would provision all task managers at
>>> cluster creation, but since legacy mode is expected to go away soon, I
>>> didn't want to try that route.
>>>
>>> Is there a way I can configure the multiple jobs or parallel instances
>>> of same job spread across all the available Yarn nodes and continue using
>>> the 'new' mode ?
>>>
>>> Thanks,
>>>
>>> Jins George
>>>
>>

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