Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/15150#discussion_r79638858
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala ---
@@ -580,10 +581,14 @@ class Word2VecModel private[spark] (
ind += 1
}
- val scored = wordList.zip(cosVec).toSeq.sortBy(-_._2)
+ val pq = new BoundedPriorityQueue[(String, Double)](num +
1)(Ordering.by(_._2))
+
+ pq ++= wordList.zip(cosVec)
--- End diff --
I also don't know... when I've used it it has been with vocabs of tens of
thousands of words. From others' emails I think some people do use it with very
large vocabs. If you have a minute, while we're here, might as well take it one
more step towards optimized?
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