pang-wu commented on code in PR #41498:
URL: https://github.com/apache/spark/pull/41498#discussion_r1222252120


##########
connector/protobuf/src/main/scala/org/apache/spark/sql/protobuf/ProtobufDeserializer.scala:
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@@ -247,12 +247,86 @@ private[sql] class ProtobufDeserializer(
           updater.setLong(ordinal, micros + 
TimeUnit.NANOSECONDS.toMicros(nanoSeconds))
 
       case (MESSAGE, StringType)
-          if protoType.getMessageType.getFullName == "google.protobuf.Any" =>
+        if protoType.getMessageType.getFullName == "google.protobuf.Any" =>
         (updater, ordinal, value) =>
           // Convert 'Any' protobuf message to JSON string.
           val jsonStr = jsonPrinter.print(value.asInstanceOf[DynamicMessage])
           updater.set(ordinal, UTF8String.fromString(jsonStr))
 
+      // Handle well known wrapper types. We unpack the value field instead of 
keeping

Review Comment:
   > Better for Spark to preserve the same information, right?
   
   I would say no, the issue here is after converting these data type to struct 
spark erase the original type info, i.e. all user see is a struct, but this 
struct could be a custom struct from the user rather than wrapper types. In 
that case, we provide no additional information for a user to decide whether 
special action needs to take, it adds the burden of understanding the original 
schema to data consumer  -- remember the data consumer may not have the 
original schema at hand.
   The idea behind wrapper type are these are structures defined to have 
special meaning, so deserializers can leverage these type information to get 
presence information and generate data that is more intuitive, thus the 
implementaion in libraries like jsonpb.



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