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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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