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Posted to dev@mahout.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2011/08/21 21:34:27 UTC

[jira] [Updated] (MAHOUT-767) Improve RowSimilarityJob performance for count-based distance measures

     [ https://issues.apache.org/jira/browse/MAHOUT-767?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen updated MAHOUT-767:
-----------------------------

          Component/s: Collaborative Filtering
    Affects Version/s: 0.5
             Assignee: Sebastian Schelter

> Improve RowSimilarityJob performance for count-based distance measures
> ----------------------------------------------------------------------
>
>                 Key: MAHOUT-767
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-767
>             Project: Mahout
>          Issue Type: Improvement
>          Components: Collaborative Filtering
>    Affects Versions: 0.5
>            Reporter: Grant Ingersoll
>            Assignee: Sebastian Schelter
>             Fix For: 0.6
>
>         Attachments: MAHOUT-767.patch
>
>
> (See http://www.lucidimagination.com/search/document/40c4f124795c6b5/rowsimilarity_s#42ab816c27c6a9e7 for background)
> Currently, the RowSimilarityJob defers the calculation of the similarity metric until the reduce phase, while emitting many Cooccurrence objects.  For similarity metrics that are algebraic (http://pig.apache.org/docs/r0.8.1/udf.html#Aggregate+Functions) we should be able to do much of the computation during the Mapper part of this phase and also take advantage of a Combiner.  
> We should use a marker interface to know whether a similarity metric is algebraic and then make use of an appropriate Mapper implementation, otherwise we can fall back on our existing implementation.

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