+1。

On Mon, May 16, 2022 at 10:13 PM Goson zhang <gosonzh...@apache.org> wrote:

> +1
> Good luck!
>
>
> Jerry Shao <js...@apache.org> 于2022年5月16日周一 21:44写道:
>
> > Hi all,
> >
> > We would like to propose Firestorm[1] as a new Apache incubator project,
> > you can find the proposal here [2] for more details.
> >
> > Firestorm 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 -  “Firestorm”  - is heavily
> > adopted in Tencent, and shows its advantages in production. Other
> > enterprises also adopted or prepared to adopt Firestorm in their
> > environments.
> >
> > Firestorm’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 Firestorm 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:
> >
> >    - Junping du (junping...@apache.org)
> >    - Xun liu (liu...@apache.org)
> >    - Zhankun Tang (zt...@apache.org)
> >
> >
> > [1] https://github.com/Tencent/Firestorm
> > [2]
> > https://cwiki.apache.org/confluence/display/INCUBATOR/FirestormProposal
> >
> > Best regards,
> > Jerry
> >
>

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