Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/12432#discussion_r60324307
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala ---
@@ -209,9 +211,10 @@ class KMeans private (
/**
* Train a K-means model on the given set of points; `data` should be
cached for high
* performance, because this is an iterative algorithm.
+ * `instr` is used to log instrumentation parameters.
*/
@Since("0.8.0")
- def run(data: RDD[Vector]): KMeansModel = {
+ def run(data: RDD[Vector], instr: Instrumentation[clustering.KMeans] =
null): KMeansModel = {
--- End diff --
Default arguments are not Java friendly. You'll need to do this:
```
def run(data: RDD[Vector]): KMeansModel = {
run(data, None)
}
private[spark] def run(data: RDD[Vector], instr:
Option[Instrumentation[clustering.KMeans]]): KMeansModel = ...
```
That way, we will not change the public API. Note: I'd also use Option
instead of null.
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