[jira] [Comment Edited] (ARROW-12751) [C++] Add variadic row-wise min/max kernels (least/greatest)

["Ian Cook (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-12751?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17349490#comment-17349490 ] 

Ian Cook edited comment on ARROW-12751 at 5/21/21, 10:34 PM:
-------------------------------------------------------------

In principle this should behave the same as the min/max aggregate kernels, I think.

Can we use {{ScalarAggregateOptions}} or something like it to control whether to propagate vs. ignore?

With zero arguments it should return null.


was (Author: icook):
In principle this should behave the same as the min/max aggregate kernels, I think.

Can we use {{ScalarAggregateOptions}} or something like to control whether to propagate vs. ignore?

With zero arguments it should return null.

> [C++] Add variadic row-wise min/max kernels (least/greatest)
> ------------------------------------------------------------
>
>                 Key: ARROW-12751
>                 URL: https://issues.apache.org/jira/browse/ARROW-12751
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: C++
>            Reporter: Ian Cook
>            Assignee: David Li
>            Priority: Major
>
> Add a pair of variadic functions equivalent to SQL's {{least}}/{{greatest}} or R's {{pmin}}/{{pmax}}. Should take 0, 1, 2, ... same-length numeric arrays as input and return an array giving the minimum/maximum of the values found in each position of the input arrays. For example, in the case of these 2 input arrays:
> {code:java}
> Array<double>        Array<double>
> [                    [
>   1,                   2,
>   4                    3
> ]                    ]
> {code}
> {{least}} would return:
> {code:java}
> Array<double>
> [ 
>   1,
>   3
> ] 
> {code}
> and {{greatest}} would return
> {code:java}
> Array<double>
> [ 
>   2,
>   4
> ] 
> {code}
> The returned array should have the same data type as the input arrays, or follow promotion rules if the numeric types of the input arrays differ.
> Should also accept scalar numeric inputs and recycle their values.



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