ahshahid commented on code in PR #48252:
URL: https://github.com/apache/spark/pull/48252#discussion_r1844722744


##########
sql/api/src/main/scala/org/apache/spark/sql/catalyst/JavaTypeInference.scala:
##########
@@ -148,34 +163,180 @@ object JavaTypeInference {
       // TODO: we should only collect properties that have getter and setter. 
However, some tests
       //   pass in scala case class as java bean class which doesn't have 
getter and setter.
       val properties = getJavaBeanReadableProperties(c)
-      // add type variables from inheritance hierarchy of the class
-      val classTV = JavaTypeUtils.getTypeArguments(c, 
classOf[Object]).asScala.toMap ++
-        typeVariables
-      // Note that the fields are ordered by name.
-      val fields = properties.map { property =>
-        val readMethod = property.getReadMethod
-        val encoder = encoderFor(readMethod.getGenericReturnType, seenTypeSet 
+ c, classTV)
-        // The existence of `javax.annotation.Nonnull`, means this field is 
not nullable.
-        val hasNonNull = readMethod.isAnnotationPresent(classOf[Nonnull])
-        EncoderField(
-          property.getName,
-          encoder,
-          encoder.nullable && !hasNonNull,
-          Metadata.empty,
-          Option(readMethod.getName),
-          Option(property.getWriteMethod).map(_.getName))
+
+      // if the properties is empty and this is not a top level enclosing 
class, then we
+      // should not consider class as bean, as otherwise it will be treated as 
empty schema
+      // and loose the data on deser.
+      if (properties.isEmpty && seenTypeSet.nonEmpty) {
+        findBestEncoder(Seq(c), seenTypeSet, typeVariables, None, 
serializableEncodersOnly = true)

Review Comment:
   will revert on this.. by going through the code.



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