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From "Shashikant Kore (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAHOUT-165) Using better primitives hash for sparse vector for performance gains
Date Thu, 10 Sep 2009 11:58:57 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12753583#action_12753583
] 

Shashikant Kore commented on MAHOUT-165:
----------------------------------------

The attached patch uses integer to double map. I was wondering if precision of float is good
enough for us. That reduces the memory consumption by one-third.  (int+float instead of int+double)


> Using better primitives hash for sparse vector for performance gains
> --------------------------------------------------------------------
>
>                 Key: MAHOUT-165
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-165
>             Project: Mahout
>          Issue Type: Improvement
>          Components: Matrix
>    Affects Versions: 0.2
>            Reporter: Shashikant Kore
>             Fix For: 0.2
>
>         Attachments: colt.jar, mahout-165-trove.patch, MAHOUT-165.patch, mahout-165.patch
>
>
> In SparseVector, we need primitives hash map for index and values. The present implementation
of this hash map is not as efficient as some of the other implementations in non-Apache projects.

> In an experiment, I found that, for get/set operations, the primitive hash of  Colt performance
an order of magnitude better than OrderedIntDoubleMapping. For iteration it is 2x slower,
though. 
> Using Colt in Sparsevector improved performance of canopy generation. For an experimental
dataset, the current implementation takes 50 minutes. Using Colt, reduces this duration to
19-20 minutes. That's 60% reduction in the delay. 

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