[jira] [Resolved] (HIVE-7328) Refactoring: make Hive reduce side data processing reusable [Spark Branch]

["Shohei Okumiya (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HIVE-7328?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Shohei Okumiya resolved HIVE-7328.
----------------------------------
    Fix Version/s: NA
       Resolution: Won't Fix

We have discontinued Hive on Spark and EoLed Hive 3. HIVE-26134

> Refactoring: make Hive reduce side data processing reusable [Spark Branch]
> --------------------------------------------------------------------------
>
>                 Key: HIVE-7328
>                 URL: https://issues.apache.org/jira/browse/HIVE-7328
>             Project: Hive
>          Issue Type: Sub-task
>    Affects Versions: 0.13.0
>            Reporter: Xuefu Zhang
>            Assignee: Xuefu Zhang
>            Priority: Major
>             Fix For: NA
>
>
> ExecReducer is Hive's reducer implementation for MapReduce. Table rows are shuffled by MR framework to ExecReducer and further processed by ExecReducer.reduce() method, which invokes Hive's reduce-side operator tree starting. This task is to extract the reduce-side data processing offered by the operator tree so that it can be reused by other execution engine such as Spark. This is purely refactoring the existing code.



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