Github user gatorsmile commented on a diff in the pull request: https://github.com/apache/spark/pull/16655#discussion_r97189247 --- 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 -- How about adding one more check here? ```Scala assert(normalizedTable.schema.isEmpty, "Schema may not be specified in a Create Table As Select (CTAS) statement") ```
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