[GitHub] [spark] viirya commented on a change in pull request #28833: [SPARK-20680][SQL] Spark-sql do not support for creating table with void column datatype

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

viirya commented on a change in pull request #28833:
URL: https://github.com/apache/spark/pull/28833#discussion_r449788503



##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Util.scala
##########
@@ -346,4 +346,23 @@ private[sql] object CatalogV2Util {
       }
     }
   }
+
+  def failNullType(dt: DataType): Unit = {
+    def containsNullType(dt: DataType): Boolean = dt match {
+      case ArrayType(et, _) => containsNullType(et)
+      case MapType(kt, vt, _) => containsNullType(kt) || containsNullType(vt)
+      case StructType(fields) => fields.exists(f => containsNullType(f.dataType))
+      case _ => dt.isInstanceOf[NullType]
+    }
+    if (containsNullType(dt)) {
+      throw new AnalysisException(
+        "Cannot create tables with VOID type.")

Review comment:
       So basically, looks like current change allows to parse `void` as `NullType`, but if it is used in a command like creating table, we throw exception?
   
   
   One question, if we don't allow void/unknown type, is there good reason to accept in parser?
   
   Because we don't have real `void` data type, to say "unknown" type in error message looks okay.




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