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From "Kenneth Knowles (JIRA)" <>
Subject [jira] [Updated] (BEAM-3783) Streaming Beam SQL benchmarks on all of our runners
Date Tue, 06 Mar 2018 04:43:00 GMT


Kenneth Knowles updated BEAM-3783:
    Labels: SQL bigdata cloud gsoc2018 java  (was: gsoc2018)

> Streaming Beam SQL benchmarks on all of our runners
> ---------------------------------------------------
>                 Key: BEAM-3783
>                 URL:
>             Project: Beam
>          Issue Type: New Feature
>          Components: examples-nexmark
>            Reporter: Kenneth Knowles
>            Assignee: Kenneth Knowles
>            Priority: Major
>              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.

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