[jira] Updated: (MAHOUT-165) Using better primitives hash for sparse vector for performance gains

["Grant Ingersoll (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MAHOUT-165?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Grant Ingersoll updated MAHOUT-165:
-----------------------------------

    Attachment: mahout-165.patch

This gets the VectorTest testEquals to pass.  Also fixes an instanceof check in the equals of OrderedIntDoubleVector.

Still a failure in VectorTest testHashCode due to the fact that the HashVector doesn't gracefully handle missing index items.

> 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-updated.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. 

-- 
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.