Github user jaceklaskowski commented on a diff in the pull request: https://github.com/apache/spark/pull/15257#discussion_r80663732 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala --- @@ -52,13 +53,51 @@ object Literal { case t: Timestamp => Literal(DateTimeUtils.fromJavaTimestamp(t), TimestampType) case d: Date => Literal(DateTimeUtils.fromJavaDate(d), DateType) case a: Array[Byte] => Literal(a, BinaryType) + case a: Array[_] => + val elementType = componentTypeToDataType(a.getClass.getComponentType()) + val dataType = ArrayType(elementType) + val convert = CatalystTypeConverters.createToCatalystConverter(dataType) + Literal(convert(a), dataType) case i: CalendarInterval => Literal(i, CalendarIntervalType) case null => Literal(null, NullType) case v: Literal => v case _ => throw new RuntimeException("Unsupported literal type " + v.getClass + " " + v) } + private def componentTypeToDataType(clz: Class[_]): DataType = clz match { --- End diff -- It looks so similar to the other cases where Spark has to map from Scala types to Spark SQL's, like https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala#L65. When comparing them I noticed that `CalendarInterval` is not included in your list. Why?
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