viirya commented on a change in pull request #20442: [SPARK-23265][ML]Update
multi-column error handling logic in QuantileDiscretizer
URL: https://github.com/apache/spark/pull/20442#discussion_r321925219
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File path:
mllib/src/main/scala/org/apache/spark/ml/feature/QuantileDiscretizer.scala
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@@ -171,25 +171,38 @@ final class QuantileDiscretizer @Since("1.6.0")
(@Since("1.6.0") override val ui
@Since("2.3.0")
def setOutputCols(value: Array[String]): this.type = set(outputCols, value)
- private[feature] def getInOutCols: (Array[String], Array[String]) = {
- require((isSet(inputCol) && isSet(outputCol) && !isSet(inputCols) &&
!isSet(outputCols)) ||
- (!isSet(inputCol) && !isSet(outputCol) && isSet(inputCols) &&
isSet(outputCols)),
- "QuantileDiscretizer only supports setting either inputCol/outputCol or"
+
- "inputCols/outputCols."
- )
+ @Since("1.6.0")
+ override def transformSchema(schema: StructType): StructType = {
+ ParamValidators.checkSingleVsMultiColumnParams(this, Seq(outputCol),
Review comment:
`checkSingleVsMultiColumnParams` can used like
`ParamValidators.checkSingleVsMultiColumnParams(this, Seq(outputCol, splits),
Seq(outputCols, splitsArray))`.
If we want `numBuckets ` and `numBucketsArray` to be exclusively set, you
can use `checkSingleVsMultiColumnParams` like that.
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