[GitHub] 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

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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
 
 

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 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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