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https://issues.apache.org/jira/browse/ARROW-10026?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17198579#comment-17198579
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Wes McKinney commented on ARROW-10026:
--------------------------------------

That seems like a good start. I'd like to look at writing a patch to use a 
simpler data structure that doesn't involve a variant nor heap-allocating 
{{ArrayData}} objects. See for example the {{PrimitiveArg}} data structure that 
is being used in the selection kernels

https://github.com/apache/arrow/blob/d0f3b5f3c74f67c7ca941c98bd60148e9a9e94f0/cpp/src/arrow/compute/kernels/util_internal.h#L30

It seems like some evolved version of that which satisfies the needs of kernels 
would make sense. 

> [C++] Improve kernel performance on small batches
> -------------------------------------------------
>
>                 Key: ARROW-10026
>                 URL: https://issues.apache.org/jira/browse/ARROW-10026
>             Project: Apache Arrow
>          Issue Type: Task
>          Components: C++
>            Reporter: Antoine Pitrou
>            Priority: Major
>
> It seems that invoking some kernels on smallish batches has quite an overhead:
> {code}
> ArrayArrayKernel<Add, Int32Type>/32768/100                      2860 ns       
>   2859 ns       245195 bytes_per_second=10.6727G/s 
> items_per_second=2.86494G/s null_percent=1 size=32.768k
> ArrayArrayKernel<Add, Int32Type>/32768/0                        2752 ns       
>   2751 ns       249316 bytes_per_second=11.093G/s items_per_second=2.97775G/s 
> null_percent=0 size=32.768k
> ArrayArrayKernel<Add, Int32Type>/524288/100                    18633 ns       
>  18630 ns        36548 bytes_per_second=26.2097G/s 
> items_per_second=7.03561G/s null_percent=1 size=524.288k
> ArrayArrayKernel<Add, Int32Type>/524288/0                      18260 ns       
>  18257 ns        38245 bytes_per_second=26.7451G/s 
> items_per_second=7.17933G/s null_percent=0 size=524.288k
> {code}
> We should investigate and try to lighten the overhead.



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