+1 (non-binding) Good luck!
Daniel Widdis <wid...@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" <js...@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 (felixche...@apache.org) > - Junping du (junping...@apache.org) > - Weiwei Yang (w...@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/UniffleProposal > > Best regards, > Jerry > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > For additional commands, e-mail: general-h...@incubator.apache.org > >
