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https://issues.apache.org/jira/browse/MAHOUT-165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12760898#action_12760898
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Grant Ingersoll commented on MAHOUT-165:
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There are some thoughts on equals, etc. in the archives and other JIRA issues.
Here's what I recall:
1. We want DenseVectors and SparseVectors with the same names to be equal in
the equals() sense. The implementations of equals in SparseVector and
DenseVector are the equivalent, AFAICT, as the implementations in equals(), but
for #2:
2. We don't just defer to strictEquivalence b/c the thinking is that we can do
much faster equals comparison if we know what type of vector it is, which is
why SparseVector checks to see if "that" is a SparseVector, otherwise deferring
to equivalent (since names have already been checked). I haven't validated
whether they truly are faster.
> 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: 0.2
>
> 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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