Github user karlhigley commented on a diff in the pull request:
https://github.com/apache/spark/pull/9843#discussion_r46013493
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/feature/IDF.scala ---
@@ -211,14 +213,16 @@ private object IDFModel {
val n = v.size
v match {
case SparseVector(size, indices, values) =>
- val nnz = indices.size
- val newValues = new Array[Double](nnz)
+ val newElements = new ArrayBuffer[(Int, Double)]
var k = 0
- while (k < nnz) {
- newValues(k) = values(k) * idf(indices(k))
+ while (k < indices.size) {
+ val newValue = values(k) * idf(indices(k))
--- End diff --
Good point about `indices.size`, I've added a commit to move that outside
the loop.
The purpose of this ticket and PR is to remove explicit zeros from the
output of `IDFModel.transform`. There may be further performance optimizations
to be done in this section of code (e.g. the four cases as you suggest). It's
not clear to me that the code in this PR is significantly less performant than
what was already there, or that the suggested optimized code addresses the
original issue. Maybe I'm missing something?
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