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https://issues.apache.org/jira/browse/SPARK-10802?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16002343#comment-16002343
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Nick Pentreath commented on SPARK-10802:
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Hey folks - since the {{ALSModel}} in the ML API now supports "recommend-all"
methods, this functionality will be implemented there (see SPARK-20679). Unless
there are major objections, I advocate closing this one as "Wont Fix" once
SPARK-20679 is done, since MLlib API is in maintenance mode.
> Let ALS recommend for subset of data
> ------------------------------------
>
> Key: SPARK-10802
> URL: https://issues.apache.org/jira/browse/SPARK-10802
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.5.0
> Reporter: Tomasz Bartczak
> Priority: Minor
>
> Currently MatrixFactorizationModel allows to get recommendations for
> - single user
> - single product
> - all users
> - all products
> recommendation for all users/products do a cartesian join inside.
> It would be useful in some cases to get recommendations for subset of
> users/products by providing an RDD with which MatrixFactorizationModel could
> do an intersection before doing a cartesian join. This would make it much
> faster in situation where recommendations are needed only for subset of
> users/products, and when the subset is still too large to make it feasible to
> recommend one-by-one.
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