Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/5279#discussion_r27837485
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala
---
@@ -80,6 +80,90 @@ trait ScalaReflection {
case (other, _) => other
}
+ /**
+ * Creates a converter function that will convert Scala objects to the
specified catalyst type.
+ */
+ private[sql] def createCatalystConverter(dataType: DataType): Any => Any
= {
+ def extractOption(item: Any): Any = item match {
+ case o: Some[_] => o.get
+ case other => other
+ }
+
+ dataType match {
+ // Check UDT first since UDTs can override other types
+ case udt: UserDefinedType[_] =>
+ (item) => {
+ if (item == None) null else udt.serialize(extractOption(item))
--- End diff --
If `item` is `null`, it will call `udf.serialize(null)`, do we really need
UserDefinedType to handle `null`?
Also, why not put `None` case in `extractOption` ?
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