[jira] [Assigned] (ARROW-4124) [C++] Abstract aggregation kernel API

["Francois Saint-Jacques (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-4124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Francois Saint-Jacques reassigned ARROW-4124:
---------------------------------------------

    Assignee: Francois Saint-Jacques

> [C++] Abstract aggregation kernel API
> -------------------------------------
>
>                 Key: ARROW-4124
>                 URL: https://issues.apache.org/jira/browse/ARROW-4124
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: C++
>            Reporter: Wes McKinney
>            Assignee: Francois Saint-Jacques
>            Priority: Major
>             Fix For: 0.13.0
>
>
> Related to the particular details of implementing various aggregation types, we should first put a bit of energy into the abstract API for aggregating data in a multi-threaded setting
> Aggregators must support both hash/group (e.g. "group by" in SQL or data frame libraries) modes and non-group modes. 
> Aggregations ideally should also support filter pushdown. For example:
> {code}
> select $AGG($EXPR)
> from $TABLE
> where $PREDICATE
> {code}
> Some systems might materialize the post-predicate / filtered version of {{$EXPR}}, then aggregate that. pandas does this for example. Vectorized performance can be much improved by filtering inside the aggregation kernel. How the predicate true/false values are handled may depend on the implementation details of the kernel (e.g. SUM or MEAN will be a bit different from PRODUCT)



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