kiszk commented on a change in pull request #25178: [SPARK-28421][ML]
SparseVector.apply performance optimization
URL: https://github.com/apache/spark/pull/25178#discussion_r305080682
##########
File path: mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
##########
@@ -603,6 +603,19 @@ class SparseVector @Since("2.0.0") (
private[spark] override def asBreeze: BV[Double] = new BSV[Double](indices,
values, size)
+ override def apply(i: Int): Double = {
+ if (i < 0 || i >= size) {
+ throw new IndexOutOfBoundsException(s"Index $i out of bounds [0, $size)")
+ }
+
+ if (indices.isEmpty || i < indices(0) || i > indices(indices.length - 1)) {
Review comment:
I see. This performance improvement comes from avoiding to walk a binary
tree if a `key` is not included in a given sorted array. It makes sense to me .
One question. What do you mean `avoiding internal conversion` in the
description?
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
With regards,
Apache Git Services
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
