[jira] [Updated] (ARROW-16138) [C++] Improve performance of ExecuteScalarExpression

["Tobias Zagorni (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-16138?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Tobias Zagorni updated ARROW-16138:
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    Attachment: Flamegraph.png

> [C++] Improve performance of ExecuteScalarExpression
> ----------------------------------------------------
>
>                 Key: ARROW-16138
>                 URL: https://issues.apache.org/jira/browse/ARROW-16138
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: C++
>            Reporter: Weston Pace
>            Assignee: Tobias Zagorni
>            Priority: Major
>         Attachments: Flamegraph.png
>
>
> One of the things we want to be able to do in the streaming execution engine is process data in small L2 sized batches.  Based on literature we might like to use batches somewhere in the range of 1k to 16k rows.  In ARROW-16014 we created a benchmark to measure the performance of ExecuteScalarExpression as the size of our batches got smaller.  There are two things we observed:
>  * Something is causing thread contention.  We should be able to get pretty close to perfect linear speedup when we are evaluating scalar expressions and the batch size fits entirely into L2.  We are not seeing that.
>  * The overhead of ExecuteScalarExpression is too high when processing small batches.  Even when the expression is doing real work (e.g. copies, comparisons) the execution time starts to be dominated by overhead when we have 10k sized batches.



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