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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