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Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2016/03/04 03:44:40 UTC

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

Michael Armbrust created SPARK-13664:
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             Summary: 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


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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