@Yikun, Please add me to the contributors' list. Happy to help.
Regards, Mich view my Linkedin profile <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/> *Disclaimer:* Use it at your own risk. Any and all responsibility for any loss, damage or destruction of data or any other property which may arise from relying on this email's technical content is explicitly disclaimed. The author will in no case be liable for any monetary damages arising from such loss, damage or destruction. On Wed, 1 Dec 2021 at 02:49, Yikun Jiang <yikunk...@gmail.com> wrote: > @Weiwei @Chenya > > > Thanks for bringing this up. This is quite interesting, we definitely > should participate more in the discussions. > > Thanks for your reply and welcome to join the discussion, I think the > input from Yunikorn is very critical. > > > The main thing here is, the Spark community should make Spark pluggable > in order to support other schedulers, not just for Volcano. It looks like > this proposal is pushing really hard for adopting PodGroup, which isn't > part of K8s yet, that to me is problematic. > > Definitely yes, we are on the same page. > > I think we have the same goal: propose a general and reasonable mechanism > to make spark on k8s with a custom scheduler more usable. > > But for the PodGroup, just allow me to do a brief introduction: > - The PodGroup definition has been approved by Kubernetes officially in > KEP-583. [1] > - It can be regarded as a general concept/standard in Kubernetes rather > than a specific concept in Volcano, there are also others to implement it, > such as [2][3]. > - Kubernetes recommends using CRD to do more extension to implement what > they want. [4] > - Volcano as extension provides an interface to maintain the life cycle > PodGroup CRD and use volcano-scheduler to complete the scheduling. > > [1] > https://github.com/kubernetes/enhancements/tree/master/keps/sig-scheduling/583-coscheduling > [2] > https://github.com/kubernetes-sigs/scheduler-plugins/tree/master/pkg/coscheduling#podgroup > [3] https://github.com/kubernetes-sigs/kube-batch > [4] > https://kubernetes.io/docs/tasks/extend-kubernetes/custom-resources/custom-resource-definitions/ > > Regards, > Yikun > > > Weiwei Yang <w...@apache.org> 于2021年12月1日周三 上午5:57写道： > >> Hi Chenya >> >> Thanks for bringing this up. This is quite interesting, we definitely >> should participate more in the discussions. >> The main thing here is, the Spark community should make Spark pluggable >> in order to support other schedulers, not just for Volcano. It looks like >> this proposal is pushing really hard for adopting PodGroup, which isn't >> part of K8s yet, that to me is problematic. >> >> On Tue, Nov 30, 2021 at 9:21 AM Prasad Paravatha < >> prasad.parava...@gmail.com> wrote: >> >>> This is a great feature/idea. >>> I'd love to get involved in some form (testing and/or documentation). >>> This could be my 1st contribution to Spark! >>> >>> On Tue, Nov 30, 2021 at 10:46 PM John Zhuge <jzh...@apache.org> wrote: >>> >>>> +1 Kudos to Yikun and the community for starting the discussion! >>>> >>>> On Tue, Nov 30, 2021 at 8:47 AM Chenya Zhang < >>>> chenyazhangche...@gmail.com> wrote: >>>> >>>>> Thanks folks for bringing up the topic of natively integrating Volcano >>>>> and other alternative schedulers into Spark! >>>>> >>>>> +Weiwei, Wilfred, Chaoran. We would love to contribute to the >>>>> discussion as well. >>>>> >>>>> From our side, we have been using and improving on one alternative >>>>> resource scheduler, Apache YuniKorn (https://yunikorn.apache.org/), >>>>> for Spark on Kubernetes in production at Apple with solid results in the >>>>> past year. It is capable of supporting Gang scheduling (similar to >>>>> PodGroups), multi-tenant resource queues (similar to YARN), FIFO, and >>>>> other >>>>> handy features like bin packing to enable efficient autoscaling, etc. >>>>> >>>>> Natively integrating with Spark would provide more flexibility for >>>>> users and reduce the extra cost and potential inconsistency of maintaining >>>>> different layers of resource strategies. One interesting topic we hope to >>>>> discuss more about is dynamic allocation, which would benefit from native >>>>> coordination between Spark and resource schedulers in K8s & >>>>> cloud environment for an optimal resource efficiency. >>>>> >>>>> >>>>> On Tue, Nov 30, 2021 at 8:10 AM Holden Karau <hol...@pigscanfly.ca> >>>>> wrote: >>>>> >>>>>> Thanks for putting this together, I’m really excited for us to add >>>>>> better batch scheduling integrations. >>>>>> >>>>>> On Tue, Nov 30, 2021 at 12:46 AM Yikun Jiang <yikunk...@gmail.com> >>>>>> wrote: >>>>>> >>>>>>> Hey everyone, >>>>>>> >>>>>>> I'd like to start a discussion on "Support Volcano/Alternative >>>>>>> Schedulers Proposal". >>>>>>> >>>>>>> This SPIP is proposed to make spark k8s schedulers provide more YARN >>>>>>> like features (such as queues and minimum resources before scheduling >>>>>>> jobs) >>>>>>> that many folks want on Kubernetes. >>>>>>> >>>>>>> The goal of this SPIP is to improve current spark k8s scheduler >>>>>>> implementations, add the ability of batch scheduling and support >>>>>>> volcano as >>>>>>> one of implementations. >>>>>>> >>>>>>> Design doc: >>>>>>> https://docs.google.com/document/d/1xgQGRpaHQX6-QH_J9YV2C2Dh6RpXefUpLM7KGkzL6Fg >>>>>>> JIRA: https://issues.apache.org/jira/browse/SPARK-36057 >>>>>>> Part of PRs: >>>>>>> Ability to create resources >>>>>>> https://github.com/apache/spark/pull/34599 >>>>>>> Add PodGroupFeatureStep: https://github.com/apache/spark/pull/34456 >>>>>>> >>>>>>> Regards, >>>>>>> Yikun >>>>>>> >>>>>> -- >>>>>> Twitter: https://twitter.com/holdenkarau >>>>>> Books (Learning Spark, High Performance Spark, etc.): >>>>>> https://amzn.to/2MaRAG9 <https://amzn.to/2MaRAG9> >>>>>> YouTube Live Streams: https://www.youtube.com/user/holdenkarau >>>>>> >>>>> >>>> >>>> -- >>>> John Zhuge >>>> >>> >>> >>> -- >>> Regards, >>> Prasad Paravatha >>> >>
