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https://issues.apache.org/jira/browse/MAHOUT-165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12781165#action_12781165
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Jake Mannix commented on MAHOUT-165:
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bq. +1 yes the order of dependency makes the most sense; also makes it easy for
others to reuse who are interested in only the matrix library.
+1 from me as well. This also makes it easier to keep decomposer decoupled -
it can depend on mahout-matrix, and not need mahout-core.
But what about Vector? Vector coming out of Core and moving into another
module, well, everything depends on Vector, doesn't it? In what way does this
help?
> 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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