You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@beam.apache.org by "Beam JIRA Bot (Jira)" <ji...@apache.org> on 2020/09/02 17:08:28 UTC

[jira] [Updated] (BEAM-3783) Streaming Beam SQL benchmarks on all of our runners

     [ https://issues.apache.org/jira/browse/BEAM-3783?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Beam JIRA Bot updated BEAM-3783:
--------------------------------
    Labels: SQL bigdata cloud gsoc2018 java  (was: SQL bigdata cloud gsoc2018 java stale-P2)

> Streaming Beam SQL benchmarks on all of our runners
> ---------------------------------------------------
>
>                 Key: BEAM-3783
>                 URL: https://issues.apache.org/jira/browse/BEAM-3783
>             Project: Beam
>          Issue Type: New Feature
>          Components: testing-nexmark
>            Reporter: Kenneth Knowles
>            Priority: P3
>              Labels: SQL, bigdata, cloud, gsoc2018, java
>
> Beam has a number of classic streaming SQL benchmarks known as "Nexmark" coded up in both raw Java and also Beam SQL.
> So far, expanding functionality has been the focus of Beam SQL so there is little known about performance - we know only that it is a pretty straightforward mapping from SQL to Beam that should work OK a lot of the time. It would be interesting to see where the bottlenecks are when these SQL benchmarks are translated via Beam SQL into a Beam pipeline and then again translated to the native capabilities of e.g. Spark and Flink.
> This project will require the ability to read, write, and run Java and SQL.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)