Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/11218#discussion_r60185694
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/ElementwiseProduct.scala ---
@@ -55,6 +55,11 @@ class ElementwiseProduct(override val uid: String)
elemScaler.transform
}
+ override protected def validateInputType(inputType: DataType): Unit = {
+ super.validateInputType(inputType)
+ require(inputType.isInstanceOf[VectorUDT], s"Input type must be
VectorUDT but got $inputType.")
--- End diff --
This same pattern occurs in multiple places now. We have
`SchemaUtils.checkColumnType`, so I think we should create a new method
`SchemaUtils.checkDataType` in a similar manner, to harmonize the functionality
and in particular the default error message across all present and future
usages.
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