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https://issues.apache.org/jira/browse/SPARK-38042?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17482963#comment-17482963
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Johan Nyström-Persson commented on SPARK-38042:
-----------------------------------------------
A similar issue was solved in SPARK-21567.
> Encoder cannot be found when a tuple component is a type alias for an Array
> ---------------------------------------------------------------------------
>
> Key: SPARK-38042
> URL: https://issues.apache.org/jira/browse/SPARK-38042
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.1.2, 3.2.0
> Reporter: Johan Nyström-Persson
> Priority: Major
>
> ScalaReflection.dataTypeFor fails when Array[T] has been aliased for some T,
> and then the alias is being used as a component of e.g. a product.
> Minimal example, tested in version 3.1.2:
> {code:java}
> type Data = Array[Long]
> val xs:List[(Data,Int)] = List((Array(1),1), (Array(2),2))
> sc.parallelize(xs).toDF("a", "b"){code}
> This gives the following exception:
> {code:java}
> scala.MatchError: Data (of class
> scala.reflect.internal.Types$AliasNoArgsTypeRef)
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.$anonfun$dataTypeFor$1(ScalaReflection.scala:104)
>
> at
> scala.reflect.internal.tpe.TypeConstraints$UndoLog.undo(TypeConstraints.scala:69)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection.cleanUpReflectionObjects(ScalaReflection.scala:904)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection.cleanUpReflectionObjects$(ScalaReflection.scala:903)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.cleanUpReflectionObjects(ScalaReflection.scala:49)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.dataTypeFor(ScalaReflection.scala:88)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.$anonfun$serializerFor$6(ScalaReflection.scala:573)
>
> at
> scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:238)
> at scala.collection.immutable.List.foreach(List.scala:392)
> at scala.collection.TraversableLike.map(TraversableLike.scala:238)
> at scala.collection.TraversableLike.map$(TraversableLike.scala:231)
> at scala.collection.immutable.List.map(List.scala:298)
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.$anonfun$serializerFor$1(ScalaReflection.scala:562)
>
> at
> scala.reflect.internal.tpe.TypeConstraints$UndoLog.undo(TypeConstraints.scala:69)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection.cleanUpReflectionObjects(ScalaReflection.scala:904)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection.cleanUpReflectionObjects$(ScalaReflection.scala:903)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.cleanUpReflectionObjects(ScalaReflection.scala:49)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.serializerFor(ScalaReflection.scala:432)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.$anonfun$serializerForType$1(ScalaReflection.scala:421)
>
> at
> scala.reflect.internal.tpe.TypeConstraints$UndoLog.undo(TypeConstraints.scala:69)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection.cleanUpReflectionObjects(ScalaReflection.scala:904)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection.cleanUpReflectionObjects$(ScalaReflection.scala:903)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.cleanUpReflectionObjects(ScalaReflection.scala:49)
>
> at
> org.apache.spark.sql.catalyst.ScalaReflection$.serializerForType(ScalaReflection.scala:413)
>
> at
> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder$.apply(ExpressionEncoder.scala:55)
>
> at org.apache.spark.sql.Encoders$.product(Encoders.scala:285)
> at
> org.apache.spark.sql.LowPrioritySQLImplicits.newProductEncoder(SQLImplicits.scala:251)
>
> at
> org.apache.spark.sql.LowPrioritySQLImplicits.newProductEncoder$(SQLImplicits.scala:251)
>
> at
> org.apache.spark.sql.SQLImplicits.newProductEncoder(SQLImplicits.scala:32)
> ... 48 elided{code}
> Off the top of my head, I think this could be fixed by changing e.g.
> {code:java}
> getClassNameFromType(tpe) to
> getClassNameFromType(tpe.dealias)
> {code}
> in ScalaReflection.dataTypeFor. I will try to test that and submit a pull
> request shortly.
>
>
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