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From "Namit Jain (JIRA)" <>
Subject [jira] Commented: (HIVE-562) join does not work well if there is a very large skew in keys
Date Mon, 15 Jun 2009 22:58:07 GMT


Namit Jain commented on HIVE-562:

It can be handled in a couple of ways - 

1. create another level of indirection, and then swap those units independently. For eg, instead
of storing 'N' values with a key 'k', store that 'k' maps to 'k1', 'k2'.....'kn'
    and then read all keys when needed.

2. the query is rewritten to a bunch of independent queries - at some layer. So instead of
joining L and S:
  a.  S is broken into S1..Sn
  b.  Join L with S1..Sn
  c.  Merge the above results.

This can be done by the compiler or at the query specification time.

> join does not work well if there is a very large skew in keys
> -------------------------------------------------------------
>                 Key: HIVE-562
>                 URL:
>             Project: Hadoop Hive
>          Issue Type: Improvement
>          Components: Query Processor
>    Affects Versions: 0.4.0
>            Reporter: Namit Jain
> Only the last table is streamed in case of regular joins.
> So, for any other table, or for any small table (in case of map-joins), if the number
of values for a given key are very large, it does not scale.

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