srowen commented on a change in pull request #27052: [SPARK-30390][MLLIB] Avoid
double caching in mllib.KMeans#runWithWeights.
URL: https://github.com/apache/spark/pull/27052#discussion_r362234083
##########
File path: mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
##########
@@ -232,7 +232,10 @@ class KMeans private (
val zippedData = data.zip(norms).map { case ((v, w), norm) =>
(new VectorWithNorm(v, norm), w)
}
- zippedData.persist(StorageLevel.MEMORY_AND_DISK)
+
+ if (data.getStorageLevel == StorageLevel.NONE) {
+ zippedData.persist(StorageLevel.MEMORY_AND_DISK)
+ }
Review comment:
Yeah I thought that was your point. If zippedData were expensive, I'd agree
that caching the intermediate values too is worthwhile, and we do that in some
places. Here it's not, and the original behavior was to always cache
internally, so I guess this is less of a change. This at least skips it where
it can be inexpensively computed
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