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From "Namit Jain (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-4440) SMB Operator spills to disk like it's 1999
Date Tue, 30 Apr 2013 02:54:16 GMT

    [ https://issues.apache.org/jira/browse/HIVE-4440?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13645178#comment-13645178
] 

Namit Jain commented on HIVE-4440:
----------------------------------

I really like the title of the jira.

Changing the parameter name is backward incompatible.
Can you support both the current parameter and the proposed parameter for now ?
Document it clearly, and say that the current parameter hive.mapjoin.bucket.cache.size will
not be supported
for this from 0.13 or something like that.
                
> SMB Operator spills to disk like it's 1999
> ------------------------------------------
>
>                 Key: HIVE-4440
>                 URL: https://issues.apache.org/jira/browse/HIVE-4440
>             Project: Hive
>          Issue Type: Bug
>            Reporter: Gunther Hagleitner
>            Assignee: Gunther Hagleitner
>         Attachments: HIVE-4440.1.patch
>
>
> I was recently looking into some performance issue with a query that used SMB join and
was running really slow. Turns out that the SMB join by default caches only 100 values per
key before spilling to disk. That seems overly conservative to me. Changing the parameter
resulted in a ~5x speedup - quite significant.
> The parameter is: hive.mapjoin.bucket.cache.size
> Which right now is only used the SMB Operator as far as I can tell.
> The parameter was introduced originally (3 yrs ago) for the map join operator (looks
like pre-SMB) and set to 100 to avoid OOM. That seems to have been in a different context
though where you had to avoid running out of memory with the cached hash table in the same
process, I think.
> Two things I'd like to propose:
> a) Rename it to what it does: hive.smbjoin.cache.rows
> b) Set it to something less restrictive: 10000
> If you string together a 5 table smb join with a map join and a map-side group by aggregation
you might still run out of memory, but the renamed parameter should be easier to find and
reduce. For most queries, I would think that 10000 is still a reasonable number to cache (On
the reduce side we use 25000 for shuffle joins).

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