Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/17848#discussion_r115251937
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUDF.scala
---
@@ -36,17 +36,25 @@ import org.apache.spark.sql.types.DataType
* better to use Option of Seq[DataType] so we can use
"None" as the case for no
* type coercion. However, that would require more
refactoring of the codebase.
* @param udfName The user-specified name of this UDF.
+ * @param udfDeterministic True if the UDF is deterministic.
Deterministic UDF returns same result
+ * each time it is invoked with a particular
input.
+ * @param distinctLike A UDF is considered distinctLike if the UDF can be
evaluated on just the
+ * distinct values of a column.
--- End diff --
Hive UDFs ignores `distinctLike` and AFAIK there is no optimisation rules
for `distinctLike` though, do we need this `param` now?
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