Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/10152#discussion_r47548255
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -534,8 +577,15 @@ class Word2VecModel private[spark] (
// Need not divide with the norm of the given vector since it is
constant.
val cosVec = cosineVec.map(_.toDouble)
var ind = 0
+ var vecNorm = 1f
+ if (norm) {
--- End diff --
You only need to normalize the top K values that are returned, at the end.
If speed is important here, then this implementation should probably be
changed to use a heap or something rather than needlessly sort the whole thing.
That's a much bigger bottleneck.
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