Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/16655#discussion_r97189276
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
---
@@ -199,31 +199,52 @@ case class AnalyzeCreateTable(sparkSession:
SparkSession) extends Rule[LogicalPl
// * can't use all table columns as partition columns.
// * partition columns' type must be AtomicType.
// * sort columns' type must be orderable.
+ // * reorder table schema or output of query plan, to put partition
columns at the end.
case c @ CreateTable(tableDesc, _, query) =>
- val analyzedQuery = query.map { q =>
- // Analyze the query in CTAS and then we can do the normalization
and checking.
- val qe = sparkSession.sessionState.executePlan(q)
+ if (query.isDefined) {
+ val qe = sparkSession.sessionState.executePlan(query.get)
qe.assertAnalyzed()
- qe.analyzed
- }
- val schema = if (analyzedQuery.isDefined) {
- analyzedQuery.get.schema
- } else {
- tableDesc.schema
- }
+ val analyzedQuery = qe.analyzed
+
+ val normalizedTable = normalizeCatalogTable(analyzedQuery.schema,
tableDesc)
+
+ val output = analyzedQuery.output
+ val partitionAttrs = normalizedTable.partitionColumnNames.map {
partCol =>
+ output.find(_.name == partCol).get
+ }
+ val newOutput = output.filterNot(partitionAttrs.contains) ++
partitionAttrs
+ val reorderedQuery = if (newOutput == output) {
+ analyzedQuery
+ } else {
+ Project(newOutput, analyzedQuery)
+ }
- val columnNames = if
(sparkSession.sessionState.conf.caseSensitiveAnalysis) {
- schema.map(_.name)
+ c.copy(tableDesc = normalizedTable, query = Some(reorderedQuery))
--- End diff --
this should be guaranteed by the parser, but we can check it again here.
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