[GitHub] [spark] zhengruifeng commented on a change in pull request #31394: [SPARK-34291][ML] LSH hashDistance optimization

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

zhengruifeng commented on a change in pull request #31394:
URL: https://github.com/apache/spark/pull/31394#discussion_r568419326



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File path: mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala
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@@ -97,7 +97,19 @@ class BucketedRandomProjectionLSHModel private[ml](
   @Since("2.1.0")
   override protected[ml] def hashDistance(x: Seq[Vector], y: Seq[Vector]): Double = {
     // Since it's generated by hashing, it will be a pair of dense vectors.
-    x.zip(y).map(vectorPair => Vectors.sqdist(vectorPair._1, vectorPair._2)).min
+    // Currently each hash vector (generated by hashFunction) only has one element, this equals to:

Review comment:
       It is possible that a hash vector has length>1, but in current impl (since 2.1), each vector has only one value.




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