[jira] [Resolved] (HIVE-7327) Refactoring: make Hive map side data processing reusable [Spark Branch]

["Xuefu Zhang (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HIVE-7327?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Xuefu Zhang resolved HIVE-7327.
-------------------------------
    Resolution: Not a Problem

Since Hive on Spark doesn't use ExecMapper directly now, this is no longer an issue. Closed this for now.

> Refactoring: make Hive map side data processing reusable [Spark Branch]
> -----------------------------------------------------------------------
>
>                 Key: HIVE-7327
>                 URL: https://issues.apache.org/jira/browse/HIVE-7327
>             Project: Hive
>          Issue Type: Sub-task
>    Affects Versions: 0.13.0
>            Reporter: Xuefu Zhang
>            Assignee: Xuefu Zhang
>              Labels: Spark-M1
>
> ExecMapper is Hive's mapper implementation for MapReduce. Table rows are read by MR framework and processed by ExecMapper.map() method, which invokes Hive's map-side operator tree starting from MapOperator. This task is to extract the map-side data processing offered by the operator tree so that it can be used by other execution engine such as Spark. This is purely refactoring the existing code.



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