Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/9726#discussion_r45426470
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/encoders/ExpressionEncoder.scala
---
@@ -44,20 +44,21 @@ import org.apache.spark.sql.types.{NullType,
StructField, ObjectType, StructType
* to the name `value`.
*/
object ExpressionEncoder {
- def apply[T : TypeTag](flat: Boolean = false): ExpressionEncoder[T] = {
+ def apply[T : TypeTag](): ExpressionEncoder[T] = {
// We convert the not-serializable TypeTag into StructType and
ClassTag.
val mirror = typeTag[T].mirror
val cls = mirror.runtimeClass(typeTag[T].tpe)
+ val flat = !classOf[Product].isAssignableFrom(cls)
--- End diff --
But we need a way to detect flatness automatically, sometimes we only have
the type `T` and nothing else, like when we wanna use encoders for `ScalaUDF`.
How about `flat = !ScalaReflection.schemaFor[T].isInstanceOf[StructType])`?
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