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From "Xiao Li (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-21422) Depend on Apache ORC 1.4.0
Date Wed, 16 Aug 2017 06:09:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-21422?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xiao Li resolved SPARK-21422.
-----------------------------
       Resolution: Fixed
         Assignee: Dongjoon Hyun
    Fix Version/s: 2.3.0

> Depend on Apache ORC 1.4.0
> --------------------------
>
>                 Key: SPARK-21422
>                 URL: https://issues.apache.org/jira/browse/SPARK-21422
>             Project: Spark
>          Issue Type: Bug
>          Components: Build
>    Affects Versions: 2.3.0
>            Reporter: Dongjoon Hyun
>            Assignee: Dongjoon Hyun
>             Fix For: 2.3.0
>
>
> Like Parquet, this issue aims to depend on the latest Apache ORC 1.4 for Apache Spark
2.3. There are key benefits for now.
> - Stability: Apache ORC 1.4.0 has many fixes and we can depend on ORC community more.
> - Maintainability: Reduce the Hive dependency and can remove old legacy code later.
> Later, we can get the following two key benefits by adding new ORCFileFormat in SPARK-20728,
too.
> - Usability: User can use ORC data sources without hive module, i.e, -Phive.
> - Speed: Use both Spark ColumnarBatch and ORC RowBatch together. This is faster than
the current implementation in Spark.



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