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Posted to general@incubator.apache.org by BLAST <12...@qq.com.INVALID> on 2022/05/26 03:41:07 UTC
回复: [DISCUSSION] Incubating Proposal of Uniffle
+1, Good Luck!
------------------ 原始邮件 ------------------
发件人: "general" <wander4096@gmail.com>;
发送时间: 2022年5月25日(星期三) 下午2:26
收件人: "Incubator"<general@incubator.apache.org>;
主题: Re: [DISCUSSION] Incubating Proposal of Uniffle
+1 (binding)
An interesting project. Good luck!
Best,
tison.
Jungtaek Lim <kabhwan.opensource@gmail.com> 于2022年5月25日周三 14:22写道:
> +1 (non-binding)
>
> Good luck!
>
> On Wed, May 25, 2022 at 2:42 PM Daniel Widdis <widdis@gmail.com> wrote:
>
> > This was stated in the other thread: Unified/Universal Shuffle
> >
> > On 5/24/22, 10:04 PM, "XiaoYu" <xiaoyu@apache.org> wrote:
> >
> > Hi
> >
> > Uniffle as a project name, What does he mean~
> >
> > thanks
> >
> > Weiwei Yang <wwei@apache.org> 于2022年5月25日周三 12:57写道:
> > >
> > > +1 (binding)
> > > Good luck!
> > >
> > > On Tue, May 24, 2022 at 8:49 PM Ye Xianjin <advancedxy@gmail.com>
> > wrote:
> > >
> > > > +1 (non-binding).
> > > >
> > > > Sent from my iPhone
> > > >
> > > > > On May 25, 2022, at 9:59 AM, Goson zhang <
> gosonzhang@apache.org>
> > wrote:
> > > > >
> > > > > +1 (non-binding)
> > > > >
> > > > > Good luck!
> > > > >
> > > > > Daniel Widdis <widdis@gmail.com> 于2022年5月25日周三 09:53写道:
> > > > >
> > > > >> +1 (non-binding) from me! Good luck!
> > > > >>
> > > > >> On 5/24/22, 9:05 AM, "Jerry Shao" <jshao@apache.org> wrote:
> > > > >>
> > > > >> Hi all,
> > > > >>
> > > > >> Due to the name issue in thread (
> > > > >>
> > https://lists.apache.org/thread/y07xjkqzvpchncym9zr1hgm3c4l4ql0f),
> > > > we
> > > > >> figured out a new project name "Uniffle" and created a new
> > Thread.
> > > > >> Please
> > > > >> help to discuss.
> > > > >>
> > > > >> We would like to propose Uniffle[1] as a new Apache
> incubator
> > > > project,
> > > > >> you
> > > > >> can find the proposal here [2] for more details.
> > > > >>
> > > > >> Uniffle is a high performance, general purpose Remote
> > Shuffle Service
> > > > >> for
> > > > >> distributed compute engines like Apache Spark
> > > > >> <https://spark.apache.org/>, Apache
> > > > >> Hadoop MapReduce <https://hadoop.apache.org/>, Apache
> Flink
> > > > >> <https://flink.apache.org/> and so on. We are aiming to
> make
> > > > >> Firestorm a
> > > > >> universal shuffle service for distributed compute engines.
> > > > >>
> > > > >> Shuffle is the key part for a distributed compute engine to
> > exchange
> > > > >> the
> > > > >> data between distributed tasks, the performance and
> > stability of
> > > > >> shuffle
> > > > >> will directly affect the whole job. Current “local file
> > pull-like
> > > > >> shuffle
> > > > >> style” has several limitations:
> > > > >>
> > > > >> 1. Current shuffle is hard to support super large
> > workloads,
> > > > >> especially
> > > > >> in a high load environment, the major problem is IO
> > problem
> > > > (random
> > > > >> disk IO
> > > > >> issue, network congestion and timeout).
> > > > >> 2. Current shuffle is hard to deploy on the
> disaggregated
> > compute
> > > > >> storage environment, as disk capacity is quite limited
> on
> > compute
> > > > >> nodes.
> > > > >> 3. The constraint of storing shuffle data locally makes
> > it hard to
> > > > >> scale
> > > > >> elastically.
> > > > >>
> > > > >> Remote Shuffle Service is the key technology for
> enterprises
> > to build
> > > > >> big
> > > > >> data platforms, to expand big data applications to
> > disaggregated,
> > > > >> online-offline hybrid environments, and to solve above
> > problems.
> > > > >>
> > > > >> The implementation of Remote Shuffle Service - “Uniffle”
> -
> > is
> > > > heavily
> > > > >> adopted in Tencent, and shows its advantages in production.
> > Other
> > > > >> enterprises also adopted or prepared to adopt Firestorm in
> > their
> > > > >> environments.
> > > > >>
> > > > >> Uniffle's key idea is brought from Salfish shuffle
> > > > >> <
> > > > >>
> > > >
> >
> https://www.researchgate.net/publication/262241541_Sailfish_a_framework_for_large_scale_data_processing
> > > > >>> ,
> > > > >> it has several key design goals:
> > > > >>
> > > > >> 1. High performance. Firestorm’s performance is close
> > enough to
> > > > >> local
> > > > >> file based shuffle style for small workloads. For large
> > workloads,
> > > > >> it is
> > > > >> far better than the current shuffle style.
> > > > >> 2. Fault tolerance. Firestorm provides high availability
> > for
> > > > >> Coordinated
> > > > >> nodes, and failover for Shuffle nodes.
> > > > >> 3. Pluggable. Firestorm is highly pluggable, which could
> > be suited
> > > > >> to
> > > > >> different compute engines, different backend storages,
> and
> > > > different
> > > > >> wire-protocols.
> > > > >>
> > > > >> We believe that Uniffle project will provide the great
> value
> > for the
> > > > >> community if it is accepted by the Apache incubator.
> > > > >>
> > > > >> I will help this project as champion and many thanks to
> the 3
> > > > mentors:
> > > > >>
> > > > >> -
> > > > >>
> > > > >> Felix Cheung (felixcheung@apache.org)
> > > > >> - Junping du (junping_du@apache.org)
> > > > >> - Weiwei Yang (wwei@apache.org)
> > > > >> - Xun liu (liuxun@apache.org)
> > > > >> - Zhankun Tang (ztang@apache.org)
> > > > >>
> > > > >>
> > > > >> [1] https://github.com/Tencent/Firestorm
> > > > >> [2]
> > > > >>
> > https://cwiki.apache.org/confluence/display/INCUBATOR/UniffleProposal
> > > > >>
> > > > >> Best regards,
> > > > >> Jerry
> > > > >>
> > > > >>
> > > > >>
> > > > >>
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