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https://issues.apache.org/jira/browse/MAHOUT-974?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13676816#comment-13676816
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Sebastian Schelter commented on MAHOUT-974:
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Hi Saikat,
The first two jobs create two versions of the ratings matrix, one partitioned
by items, the other partitioned by users. The most elegant solution for this
issue would be to make these jobs write out the mapping of ints to long ids via
an emulation of MultipleOutputs such as used in
org.apache.mahout.math.hadoop.stochasticsvd.ABtJob
I suggest we add an argument "usesLongIDs" to the job that the user can set to
trigger the mapping.
> org.apache.mahout.cf.taste.hadoop.als.ParallelALSFactorizationJob use
> integer as userId and itemId
> ---------------------------------------------------------------------------------------------------
>
> Key: MAHOUT-974
> URL: https://issues.apache.org/jira/browse/MAHOUT-974
> Project: Mahout
> Issue Type: Wish
> Components: Collaborative Filtering
> Affects Versions: 0.8
> Reporter: Han Hui Wen
> Assignee: Sebastian Schelter
> Labels: CF,recommendation,als
> Fix For: 0.8
>
> Original Estimate: 2h
> Remaining Estimate: 2h
>
> org.apache.mahout.cf.taste.hadoop.als.ParallelALSFactorizationJob uses
> integer as userId and itemId,but
> org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob and
> org.apache.mahout.cf.taste.hadoop.item.RecommenderJob .use Long as userId and
> ItemId.
> It's best that ParallelALSFactorizationJob also uses Long as userId and
> itemId ,so that same dataset can use all the recommendation arithrmetic
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