Github user karlhigley commented on a diff in the pull request:
https://github.com/apache/spark/pull/9843#discussion_r46017996
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/IDF.scala ---
@@ -211,14 +213,17 @@ private object IDFModel {
val n = v.size
v match {
case SparseVector(size, indices, values) =>
+ val newElements = new ArrayBuffer[(Int, Double)]
val nnz = indices.size
- val newValues = new Array[Double](nnz)
var k = 0
while (k < nnz) {
- newValues(k) = values(k) * idf(indices(k))
+ val newValue = values(k) * idf(indices(k))
--- End diff --
As the diff shows, the existing code is already calling `idf(indices(k))`.
That call may indeed be expensive and represent a potential optimization, but
it's distinct from the problem this PR is intended to address. Seems like there
might be room for a second JIRA/PR to handle the issue you identified.
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