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https://issues.apache.org/jira/browse/SPARK-34583?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17296751#comment-17296751
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Hyukjin Kwon commented on SPARK-34583:
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cc [~Ngone51] [~cloud_fan] FYI
> typed udf fails when it refers to type member in abstract class
> ---------------------------------------------------------------
>
> Key: SPARK-34583
> URL: https://issues.apache.org/jira/browse/SPARK-34583
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.1
> Reporter: kondziolka9ld
> Priority: Minor
>
> Please consider a following scenario:
> {code:java}
> scala> abstract class SomeAbstractClass {
> | type SomeTypeMember
> | }
> defined class SomeAbstractClassscala> class SomeSpecificClass extends
> SomeAbstractClass {
> | override type SomeTypeMember = Int
> | }
> defined class SomeSpecificClassscala> def someFunction(someInstance:
> SomeAbstractClass): Any = {
> | udf { _: someInstance.SomeTypeMember => 42 }
> | }
> someFunction: (someInstance: SomeAbstractClass)Any
> scala> someFunction(new SomeSpecificClass)
> java.lang.NoClassDefFoundError: no Java class corresponding to
> someInstance.SomeTypeMember found
> at
> scala.reflect.runtime.JavaMirrors$JavaMirror.typeToJavaClass(JavaMirrors.scala:1354)
> at
> scala.reflect.runtime.JavaMirrors$JavaMirror.runtimeClass(JavaMirrors.scala:227)
> at
> scala.reflect.runtime.JavaMirrors$JavaMirror.runtimeClass(JavaMirrors.scala:68)
> at
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$.apply(ExpressionEncoder.scala:56)
> at org.apache.spark.sql.functions$.$anonfun$udf$1(functions.scala:4509)
> at scala.util.Try$.apply(Try.scala:213)
> at org.apache.spark.sql.functions$.udf(functions.scala:4509)
> at someFunction(<console>:25)
> ... 47 elided
> {code}
> On *spark-2.4.7* it works. I guess that it is related to:
> {code:java}
> In Spark 3.0, using org.apache.spark.sql.functions.udf(AnyRef, DataType) is
> not allowed by default. Remove the return type parameter to automatically
> switch to typed Scala udf is recommended, or set
> spark.sql.legacy.allowUntypedScalaUDF to true to keep using it. In Spark
> version 2.4 and below, if org.apache.spark.sql.functions.udf(AnyRef,
> DataType) gets a Scala closure with primitive-type argument, the returned UDF
> returns null if the input values is null. However, in Spark 3.0, the UDF
> returns the default value of the Java type if the input value is null. For
> example, val f = udf((x: Int) => x, IntegerType), f($"x") returns null in
> Spark 2.4 and below if column x is null, and return 0 in Spark 3.0. This
> behavior change is introduced because Spark 3.0 is built with Scala 2.12 by
> default.
> {code}
> [https://spark.apache.org/docs/latest/sql-migration-guide.html#udfs-and-built-in-functions]
> Does spark try to do some type inferation? When it refers to
> `SomeAbstractClass.SomeTypeMember` it really does not exist.
> Some workaround could be runtime type casting, something like:
> {code:java}
> udf { param: Any => {
> ...
> param.asInstanceOf[someInstance.SomeTypeMember]
> ...
> } {code}
> ----
> I classified it as bug since on previous versions of spark it worked.
> However, I believe that it can work as designed.
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