cloud-fan commented on a change in pull request #35265:
URL: https://github.com/apache/spark/pull/35265#discussion_r802623812
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DescribeTableExec.scala
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@@ -80,13 +81,23 @@ case class DescribeTableExec(
}
private def addPartitioning(rows: ArrayBuffer[InternalRow]): Unit = {
- rows += emptyRow()
- rows += toCatalystRow("# Partitioning", "", "")
- if (table.partitioning.isEmpty) {
- rows += toCatalystRow("Not partitioned", "", "")
- } else {
- rows ++= table.partitioning.zipWithIndex.map {
- case (transform, index) => toCatalystRow(s"Part $index",
transform.describe(), "")
+ if (table.partitioning.nonEmpty) {
+ val partitionColumnsOnly = table.partitioning.forall(t =>
t.isInstanceOf[IdentityTransform])
+ if (partitionColumnsOnly) {
+ val nameToField = table.schema.map(f => (f.name, f)).toMap
+ rows += toCatalystRow("# Partition Information", "", "")
+ rows += toCatalystRow(s"# ${output(0).name}", output(1).name,
output(2).name)
+ rows ++= table.partitioning.sortBy(_.describe).map {
+ case t =>
+ val field = nameToField(t.describe)
Review comment:
we should cast v2 partitioning to `IdentityTransform` and get the column
names
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