Github user maropu commented on a diff in the pull request:
https://github.com/apache/spark/pull/16886#discussion_r100539896
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala ---
@@ -218,22 +220,33 @@ private[hive] trait HiveInspectors {
case c: Class[_] if c == java.lang.Float.TYPE => FloatType
case c: Class[_] if c == java.lang.Boolean.TYPE => BooleanType
- case c: Class[_] if c.isArray =>
ArrayType(javaClassToDataType(c.getComponentType))
+ case c: Class[_] if c.isArray =>
ArrayType(javaTypeToDataType(c.getComponentType))
// Hive seems to return this for struct types?
case c: Class[_] if c == classOf[java.lang.Object] => NullType
- // java list type unsupported
+ // raw java list type unsupported
case c: Class[_] if c == classOf[java.util.List[_]] =>
throw new AnalysisException(
- "List type in java is unsupported because " +
- "JVM type erasure makes spark fail to catch a component type in
List<>")
+ "Raw list type in java is unsupported because Spark cannot infer
the element type.")
--- End diff --
Do we need this error handling? `"Unsupported java type interface
java.util.List"` thrown in the bottom entry is not enough?
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