srowen commented on a change in pull request #23275: [SPARK-26323][SQL] Scala
UDF should still check input types even if some inputs are of type Any
URL: https://github.com/apache/spark/pull/23275#discussion_r245652117
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
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@@ -882,7 +882,18 @@ object TypeCoercion {
case udf: ScalaUDF if udf.inputTypes.nonEmpty =>
val children = udf.children.zip(udf.inputTypes).map { case (in,
expected) =>
- implicitCast(in, udfInputToCastType(in.dataType,
expected)).getOrElse(in)
+ // Currently Scala UDF will only expect `AnyDataType` at top level,
so this trick works.
+ // In the future we should create types like `AbstractArrayType`, so
that Scala UDF can
+ // accept inputs of array type of arbitrary element type.
Review comment:
Yeah I think we should make this change. For better or worse we have several
like this in MLlib that are trying to handle things like `Double` and instance
types at the same time. We might have user code that does the same. If we can
keep some functionality in these cases, I think it's worth it.
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