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From Sunil G <sun...@apache.org>
Subject Re: [DISCUSS] Merge Absolute resource configuration support in Capacity Scheduler (YARN-5881) to trunk
Date Thu, 30 Nov 2017 08:22:22 GMT
Thanks everyone for the feedback!

Based on positive feedback, we started voting thread in
http://mail-archives.apache.org/mod_mbox/hadoop-yarn-dev/201711.mbox/%3CCACYiTuhzMrd_kFRT7_f4VBHejrajbCnVB1wmgHLMLXRr58y0MA%40mail.gmail.com%3E

@Carlo: Yes, this change should be straight forward except some minor
conflicts.

- Sunil



On Thu, Nov 30, 2017 at 9:34 AM Carlo Aldo Curino <carlo.curino@gmail.com>
wrote:

> I haven't tested this, but I support the merge as the patch is very much
> needed for MS usecases as well... Can this be cherry-picked on 2.9 easily?
>
> Thanks for this contribution!
>
> Cheers,
> Carlo
>
> On Nov 29, 2017 6:34 PM, "Weiwei Yang" <cheersyang@hotmail.com> wrote:
>
>> Hi Sunil
>>
>> +1 from my side.
>> Actually we have applied some of these patches to our production cluster
>> since Sep this year, on over 2000+ nodes and it works nicely. +1 for the
>> merge. I am pretty sure this feature will help a lot of users, especially
>> those on cloud. Thanks for getting this done, great job!
>>
>> --
>> Weiwei
>>
>> On 29 Nov 2017, 9:23 PM +0800, Rohith Sharma K S <
>> rohithsharmaks@apache.org>, wrote:
>> +1, thanks Sunil for working on this feature!
>>
>> -Rohith Sharma K S
>>
>> On 24 November 2017 at 23:19, Sunil G <sunilg@apache.org> wrote:
>>
>> Hi All,
>>
>> We would like to bring up the discussion of merging “absolute min/max
>> resources support in capacity scheduler” branch (YARN-5881) [2] into trunk
>> in a few weeks. The goal is to get it in for Hadoop 3.1.
>>
>> *Major work happened in this branch*
>>
>> - YARN-6471. Support to add min/max resource configuration for a queue
>> - YARN-7332. Compute effectiveCapacity per each resource vector
>> - YARN-7411. Inter-Queue preemption's computeFixpointAllocation need to
>> handle absolute resources.
>>
>> *Regarding design details*
>>
>> Please refer [1] for detailed design document.
>>
>> *Regarding to testing:*
>>
>> We did extensive tests for the feature in the last couple of months.
>> Comparing to latest trunk.
>>
>> - For SLS benchmark: We didn't see observable performance gap from
>> simulated test based on 8K nodes SLS traces (1 PB memory). We got 3k+
>> containers allocated per second.
>>
>> - For microbenchmark: We use performance test cases added by YARN 6775, it
>> did not show much performance regression comparing to trunk.
>>
>> *YARN-5881* <https://issues.apache.org/jira/browse/YARN-5881
>>
>> #ResourceTypes = 2. Avg of fastest 20: 55294.52
>> #ResourceTypes = 2. Avg of fastest 20: 55401.66
>>
>> *trunk*
>> #ResourceTypes = 2. Avg of fastest 20: 55865.92
>> #ResourceTypes = 2. Avg of fastest 20: 55096.418
>>
>> *Regarding to API stability:*
>>
>> All newly added @Public APIs are @Unstable.
>>
>> Documentation jira [3] could help to provide detailed configuration
>> details. This feature works from end-to-end and we are running this in our
>> development cluster for last couple of months and undergone good amount of
>> testing. Branch code is run against trunk and tracked via [4].
>>
>> We would love to get your thoughts before opening a voting thread.
>>
>> Special thanks to a team of folks who worked hard and contributed towards
>> this efforts including design discussion / patch / reviews, etc.: Wangda
>> Tan, Vinod Kumar Vavilappali, Rohith Sharma K S.
>>
>> [1] :
>> https://issues.apache.org/jira/secure/attachment/
>> 12855984/YARN-5881.Support.Absolute.Min.Max.Resource.In.
>> Capacity.Scheduler.design-doc.v1.pdf
>> [2] : https://issues.apache.org/jira/browse/YARN-5881
>>
>> [3] : https://issues.apache.org/jira/browse/YARN-7533
>>
>> [4] : https://issues.apache.org/jira/browse/YARN-7510
>>
>> Thanks,
>>
>> Sunil G and Wangda Tan
>>
>>

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