[GitHub] [spark] kiszk commented on a change in pull request #25178: [SPARK-28421][ML] SparseVector.apply performance optimization

[GitBox <gi...@apache.org>]

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
 
 

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 File path: mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
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 @@ -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?

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