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  1. Spark
  2. SPARK-15504

Could MatrixFactorizationModel support recommend for some users only ?

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    Details

    • Type: Wish
    • Status: Resolved
    • Priority: Trivial
    • Resolution: Duplicate
    • Affects Version/s: 1.6.0, 1.6.1
    • Fix Version/s: None
    • Component/s: MLlib
    • Environment:

      Spark 1.6.1

      Description

      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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              • Assignee:
                Unassigned
                Reporter:
                ImagicHai Hai
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                  Updated:
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