Hai created SPARK-15504:
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Summary: Could MatrixFactorizationModel support recommend for some users only
?
Key: SPARK-15504
URL: https://issues.apache.org/jira/browse/SPARK-15504
Project: Spark
Issue Type: Wish
Components: MLlib
Affects Versions: 1.6.1, 1.6.0
Environment: Spark 1.6.1
Reporter: Hai
Priority: Trivial
I have used the ALS algorithm training a model, and I want to recommend products for some
users not all in model, so the way I can use the API of MatrixFactorizationModel is the one
-> recommendProducts(user: Int, num: Int): Array[Rating] which I should recommend the product
one by one in spark driver, or the one -> recommendProductsForUsers(num: Int): RDD[(Int,
Array[Rating])] which could run in spark cluster but it take some unused time calculate the
user that I don't want to recommend products for. So I think if there could have an API such
as -> recommendProductsForUsers(users: RDD[Int], num: Int): RDD[(Int, Array[Rating])],
so it best match my case.
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