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https://issues.apache.org/jira/browse/MAHOUT-165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12781427#action_12781427
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Grant Ingersoll commented on MAHOUT-165:
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OK, I am committing the Matrix module. Once done, I am going to move our
Matrix stuff out of core and into the Matrix module. Then, Shashi, if you can
update your patch, that would be great. From there, refactoring Vector to not
have a Writable dependency (etc.) would be great, but let's handle that on a
separate issue.
> 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
> Assignee: Grant Ingersoll
> Fix For: 0.3
>
> Attachments: colt.jar, mahout-165-18nov-updated.patch,
> mahout-165-18nov.patch, MAHOUT-165-colt.patch, mahout-165-trove.patch,
> MAHOUT-165-updated.patch, MAHOUT-165-with-colt-module.patch,
> MAHOUT-165-with-colt.patch, mahout-165.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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