[GitHub] [spark] xkrogen commented on a diff in pull request #36506: [SPARK-25050][SQL] Avro: writing complex unions

[GitBox <gi...@apache.org>]

xkrogen commented on code in PR #36506:
URL: https://github.com/apache/spark/pull/36506#discussion_r948268086


##########
connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala:
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@@ -218,6 +218,17 @@ private[sql] class AvroSerializer(
         val numFields = st.length
         (getter, ordinal) => structConverter(getter.getStruct(ordinal, numFields))
 
+      case (st: StructType, UNION) =>
+        val unionConvertor = newComplexUnionConverter(st, avroType, catalystPath, avroPath)
+        val numFields = st.length
+        (getter, ordinal) => unionConvertor(getter.getStruct(ordinal, numFields))
+
+      case (DoubleType, UNION) if nonNullUnionTypes(avroType) == Set(FLOAT, DOUBLE) =>
+        (getter, ordinal) => getter.getDouble(ordinal)
+
+      case (LongType, UNION) if nonNullUnionTypes(avroType) == Set(INT, LONG) =>
+        (getter, ordinal) => getter.getLong(ordinal)

Review Comment:
   This does imply some loss of information if you were to do a round-trip from Avro to SQL to Avro, since all records written out would have double/long values even if the input was a float/int.
   
   The representation chosen on the read path is inherently lossy, since we discard the information about which union branch the datum originated from, so I don't think there's anything we can do here to avoid this behavior. Just wanted to point it out.



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