Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1687#discussion_r15645443
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
---
@@ -66,6 +66,42 @@ class MatrixFactorizationModel private[mllib] (
}
/**
+ * Recommends products to users.
+ *
+ * @param user the user to recommend products to
+ * @param howMany how many products to return. The number returned may
be less than this.
+ * @return product ID and score tuples, sorted descending by score. The
first product returned
+ * is the one predicted to be most strongly recommended to the user.
The score is an opaque
+ * value that indicates how strongly recommended the product is.
+ */
+ def recommendProducts(user: Int, howMany: Int = 10): Array[(Int,Double)]
=
--- End diff --
The default value is not Java friendly. It should be okay if we don't set a
default here.
`howMany` -> `num`? This is similar to `RDD.top`, where we used `num` as
the argument name.
Add a space after `Int,`
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