[jira] [Resolved] (SPARK-13664) Simplify and Speedup HadoopFSRelation

["Michael Armbrust (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-13664?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Michael Armbrust resolved SPARK-13664.
--------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.0.0

Issue resolved by pull request 11646
[https://github.com/apache/spark/pull/11646]

> Simplify and Speedup HadoopFSRelation
> -------------------------------------
>
>                 Key: SPARK-13664
>                 URL: https://issues.apache.org/jira/browse/SPARK-13664
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>            Reporter: Michael Armbrust
>            Assignee: Michael Armbrust
>            Priority: Blocker
>             Fix For: 2.0.0
>
>
> A majority of Spark SQL queries likely run though {{HadoopFSRelation}}, however there are currently several complexity and performance problems with this code path:
>  - The class mixes the concerns of file management, schema reconciliation, scan building, bucketing, partitioning, and writing data.
>  - For very large tables, we are broadcasting the entire list of files to every executor. [SPARK-11441]
>  - For partitioned tables, we always do an extra projection.  This results not only in a copy, but undoes much of the performance gains that we are going to get from vectorized reads.
> This is an umbrella ticket to track a set of improvements to this codepath.



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