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https://issues.apache.org/jira/browse/MAHOUT-165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12754154#action_12754154
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Ted Dunning commented on MAHOUT-165:
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If we need something more than small integers, it is likely that we will need
doubles. Floats are just tooo easy to get into trouble with round-off with
large numerical operations. Even something as simple as adding up a list of
numbers can be difficult without enough resolution. Since we generally can't
afford the time and effort to do detailed numerical stability analysis, we
should probably stick with doubles for most floating point work.
> 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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