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Posted to issues@spark.apache.org by "Tomasz Bartczak (JIRA)" <ji...@apache.org> on 2015/09/24 18:08:04 UTC

[jira] [Created] (SPARK-10802) Let ALS recommend for subset of data

Tomasz Bartczak created SPARK-10802:
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             Summary: 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


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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