Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/15428#discussion_r83911542
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/QuantileDiscretizerSuite.scala
---
@@ -83,10 +83,20 @@ class QuantileDiscretizerSuite
.setOutputCol("result")
.setNumBuckets(numBuckets)
- // Reserve extra one bucket for NaN
- val expectedNumBuckets = discretizer.fit(df).getSplits.length - 1
- val result = discretizer.fit(df).transform(df)
- val observedNumBuckets = result.select("result").distinct.count
+ // Reserve extra one bucket for NaN values
+ discretizer.setHandleInvalid("keep")
+ var expectedNumBuckets = discretizer.fit(df).getSplits.length - 1
+ var result = discretizer.fit(df).transform(df)
+ var observedNumBuckets = result.select("result").distinct.count
+ assert(observedNumBuckets == expectedNumBuckets,
+ s"Observed number of buckets are not correct." +
+ s" Expected $expectedNumBuckets but found $observedNumBuckets")
+
+ // Remove NaN values
+ discretizer.setHandleInvalid("skip")
+ expectedNumBuckets = discretizer.fit(df).getSplits.length - 2
--- End diff --
Same here; I'd also recommend directly testing the values of the splits.
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