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https://issues.apache.org/jira/browse/FLINK-13053?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Stephan Ewen updated FLINK-13053:
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Priority: Minor (was: Critical)
> Vectorization Support in Flink
> ------------------------------
>
> Key: FLINK-13053
> URL: https://issues.apache.org/jira/browse/FLINK-13053
> Project: Flink
> Issue Type: New Feature
> Components: Table SQL / Runtime
> Reporter: Liya Fan
> Assignee: Liya Fan
> Priority: Minor
> Attachments: image-2019-07-02-15-26-39-550.png
>
>
> Vectorization is a popular technique in SQL engines today. Compared with
> traditional row-based approach, it has some distinct advantages, for example:
>
> * Better use of CPU resources (e.g. SIMD)
> * More compact memory layout
> * More friendly to compressed data format.
>
> Currently, Flink is based on a row-based SQL engine for both stream and batch
> workloads. To enjoy the above benefits, we want to bring vectorization to
> Flink. This involves substantial changes to the existing code base.
> Therefore, we give a plan to carry out such changes in small, incremental
> steps, in order not to affect existing features. We want to apply it to batch
> workload first. The details can be found in our
> [proposal|https://docs.google.com/document/d/1cUHb-_Pbe4NMU3Igwt4tytEmI66jQxev00IL99e2wFY/edit#heading=h.50xdeg1htedb]
> .
>
> For the past months, we have developed an initial implementation of the above
> ideas. Initial performance evaluations on TPC-H benchmarks show that
> substantial performance improvements can be obtained by vectorization (see
> the figure below). More details can be found in our
> [proposal|https://docs.google.com/document/d/1cUHb-_Pbe4NMU3Igwt4tytEmI66jQxev00IL99e2wFY/edit#heading=h.50xdeg1htedb].
> !image-2019-07-02-15-26-39-550.png!
> Special thanks to @Kurt Young’s team for all the kind help.
> Special thanks to @Piotr Nowojski for all the valuable feedback and help
> suggestions.
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