Github user yjshen commented on a diff in the pull request:
https://github.com/apache/spark/pull/8132#discussion_r36957526
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala
---
@@ -270,6 +271,18 @@ private[sql] object PartitioningUtils {
private val upCastingOrder: Seq[DataType] =
Seq(NullType, IntegerType, LongType, FloatType, DoubleType, StringType)
+ def checkPartitionColumnOfValidDataType(
+ schema: StructType,
+ partitionColumns: Array[String]): Unit = {
+
+ ResolvedDataSource.partitionColumnsSchema(schema,
partitionColumns).foreach { field =>
+ field.dataType match {
+ case _: AtomicType | NullType => // OK
--- End diff --
I have `NullType` here because I think it's possible the schema was
inferred from existing partition columns . For example,
`DataFrameWriter.insert` into a `HadoopFsRelation`, in this case, it's possible
that the column type can be `NullType`. Is this possible?
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