[GitHub] [spark] gatorsmile commented on a change in pull request #27488: [SPARK-31010][SQL][ML][FOLLOW-UP] Throw exception when use untyped UDF by default

[GitBox <gi...@apache.org>]

gatorsmile commented on a change in pull request #27488: [SPARK-31010][SQL][ML][FOLLOW-UP] Throw exception when use untyped UDF by default
URL: https://github.com/apache/spark/pull/27488#discussion_r390032075
 
 

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 File path: sql/core/src/main/scala/org/apache/spark/sql/functions.scala
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 @@ -4732,6 +4732,15 @@ object functions {
    * @since 2.0.0
    */
   def udf(f: AnyRef, dataType: DataType): UserDefinedFunction = {
+    if (!SQLConf.get.getConf(SQLConf.LEGACY_ALLOW_UNTYPED_SCALA_UDF)) {
+      val errorMsg = "You're using untyped Scala UDF, which does not have the input type " +
+        "information. Spark may blindly pass null to the Scala closure with primitive-type " +
+        "argument, and the closure will see the default value of the Java type for the null " +
+        "argument, e.g. `udf((x: Int) => x, IntegerType)`, the result is 0 for null input. " +
+        "You could use other typed Scala UDF APIs to avoid this problem, or set " +
 
 Review comment:
   In the error message, we should give an example to show how to use the typed Scala UDF for implementing "udf((x: Int) => x, IntegerType)"

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