cloud-fan commented on a change in pull request #27488:
[SPARK-26580][SQL][ML][FOLLOW-UP] Throw exception when use untyped UDF by
default
URL: https://github.com/apache/spark/pull/27488#discussion_r376306898
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/functions.scala
##########
@@ -4732,6 +4733,15 @@ object functions {
* @since 2.0.0
*/
def udf(f: AnyRef, dataType: DataType): UserDefinedFunction = {
+ if (!SQLConf.get.getConf(SQLConf.LEGACY_USE_UNTYPED_UDF)) {
+ val errorMsg = "You're using untyped udf, which does not have the input
type information. " +
+ "So, 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 udf APIs to avoid this problem, or set " +
+ "spark.sql.legacy.useUnTypedUdf.enabled to true to insistently use
this."
Review comment:
let's not hardcode config names.
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