[HIVE-8621] Dump small table join data for map-join [Spark Branch]

• Type: Sub-task
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Fix Version/s: 1.1.0
• Assignee: Jimmy Xiang
• Reporter: Suhas Satish
• Created: 27/Oct/14 22:06
• Updated: 29/May/15 02:27
• Resolved: 10/Nov/14 13:54

Description

This jira aims to re-use a slightly modified approach of map-reduce distributed cache in spark to dump map-joined small tables as hash tables onto spark DFS cluster.
This is a sub-task of map-join for spark
https://issues.apache.org/jira/browse/HIVE-7613

This can use the baseline patch for map-join
https://issues.apache.org/jira/browse/HIVE-8616

The original thought process was to use broadcast variable concept in spark, for the small tables.
The number of broadcast variables that must be created is m x n where
'm' is the number of small tables in the (m+1) way join and n is the number of buckets of tables. If unbucketed, n=1

But it was discovered that objects compressed with kryo serialization on disk, can occupy 20X or more when deserialized in-memory. For bucket join, the spark Driver has to hold all the buckets (for bucketed tables) in-memory (to provide for fault-tolerance against Executor failures) although the executors only need individual buckets in their memory. So the broadcast variable approach may not be the right approach.

Issue Links

• is related to: HIVE-7613 Research optimization of auto convert join to map join [Spark branch]