Github user maryannxue commented on a diff in the pull request:
https://github.com/apache/spark/pull/22732#discussion_r225587391
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUDF.scala
---
@@ -31,6 +31,7 @@ import org.apache.spark.sql.types.DataType
* null. Use boxed type or [[Option]] if you wanna do the
null-handling yourself.
* @param dataType Return type of function.
* @param children The input expressions of this UDF.
+ * @param handleNullForInputs Whether the inputs need null-value handling
respectively.
--- End diff --
Yes, it needs a little explanation here regarding the primitive types.
Since the types are not nullable, when the values are null, it usually ends up
being represented as a zero value.
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