Github user mpjlu commented on the issue:
https://github.com/apache/spark/pull/18748
Thanks @MLnick . I have double checked my test.
Since there is no recommendForUserSubset , my previous test is MLLIB
MatrixFactorizationModel::predict(RDD(Int, Int)), which predicts the rating of
many users for many products. The performance of this function is low comparing
with recommendForAll.
This PR calls recommendForAll with a subset of the users, I agree with your
test results. Thanks.
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