Github user mengxr commented on a diff in the pull request: https://github.com/apache/spark/pull/3098#discussion_r24955680 --- Diff: mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala --- @@ -103,13 +109,106 @@ class MatrixFactorizationModel private[mllib] ( recommend(productFeatures.lookup(product).head, userFeatures, num) .map(t => Rating(t._1, product, t._2)) + /** + * Recommends topK users/products. + * + * @param num how many users to return. The number returned may be less than this. + * @return [Array[Rating]] objects, each of which contains a userID, the given productID and a + * "score" in the rating field. Each represents one recommended user, and they are sorted + * by score, decreasing. The first returned is the one predicted to be most strongly + * recommended to the product. The score is an opaque value that indicates how strongly + * recommended the user is. + */ + + /** + * Recommend topK products for all users + */ + def recommendProductsForUsers(num: Int): RDD[(Int, Array[Rating])] = { + val topK = userFeatures.map { x => (x._1, num) } + recommendProductsForUsers(topK) + } + + /** + * Recommend topK users for all products + */ + def recommendUsersForProducts(num: Int): RDD[(Int, Array[Rating])] = { + val topK = productFeatures.map { x => (x._1, num) } + recommendUsersForProducts(topK) + } + + val ord = Ordering.by[Rating, Double](x => x.rating) --- End diff -- These become public members. Please move them to the companion object and mark them package private.
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