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Posted to mapreduce-issues@hadoop.apache.org by "Jerry Chen (JIRA)" <ji...@apache.org> on 2012/12/11 02:49:28 UTC
[jira] [Commented] (MAPREDUCE-1639) Grouping using hashing instead
of sorting
[ https://issues.apache.org/jira/browse/MAPREDUCE-1639?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13528596#comment-13528596 ]
Jerry Chen commented on MAPREDUCE-1639:
---------------------------------------
+1 I think this feature is valuable and I would take time to work on this. The hash based algorithm can both used for group by and for join. Both of them are not requiring a global sort.
> 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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