You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2016/03/15 19:26:33 UTC
[jira] [Reopened] (SPARK-13664) Simplify and Speedup
HadoopFSRelation
[ https://issues.apache.org/jira/browse/SPARK-13664?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Michael Armbrust reopened SPARK-13664:
--------------------------------------
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org