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From "Todd Lipcon (Commented) (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-1639) Grouping using hashing instead of sorting
Date Thu, 20 Oct 2011 01:46:11 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-1639?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13131259#comment-13131259
] 

Todd Lipcon commented on MAPREDUCE-1639:
----------------------------------------

The JNI cost makes sense, but the linked HBase JIRA doesn't use JNI. It uses sun.misc.unsafe
calls which are actually JVM intrinsics (ie they get directly compiled into assembly, rather
than going through the whole calling-convention + safepoint shenanigans that JNI does)
                
> Grouping using hashing instead of sorting
> -----------------------------------------
>
>                 Key: MAPREDUCE-1639
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1639
>             Project: Hadoop Map/Reduce
>          Issue Type: New Feature
>            Reporter: Joydeep Sen Sarma
>
> most applications of map-reduce care about grouping and not sorting. Sorting is a (relatively
expensive) way to achieve grouping. In order to achieve just grouping - one can:
> - replace the sort on the Mappers with a HashTable - and maintain lists of key-values
against each hash-bucket.
> - key-value tuples inside each hash bucket are sorted - before spilling or sending to
Reducer. Anytime this is done - Combiner can be invoked.
> - HashTable is serialized by hash-bucketid. So merges (of either spills or Map Outputs)
works similar to today (at least there's no change in overall compute complexity of merge)
> Of course this hashtable has nothing to do with partitioning. it's just a replacement
for map-side sort.
> --
> this is (pretty much) straight from the MARS project paper: http://www.cse.ust.hk/catalac/papers/mars_pact08.pdf.
They report a 45% speedup in inverted index calculation using hashing instead of sorting (reference
implementation is NOT against Hadoop though).

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