Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/12313#discussion_r65822835
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -505,6 +506,117 @@ class Analyzer(
}
}
+ object ResolveOutputColumns extends Rule[LogicalPlan] {
+ def apply(plan: LogicalPlan): LogicalPlan = plan.transform {
+ case ins @ InsertIntoTable(relation: LogicalPlan, partition, _, _,
_, _)
+ if relation.resolved && !ins.resolved =>
+ resolveOutputColumns(ins, expectedColumns(relation, partition),
relation.toString)
+ }
+
+ private def resolveOutputColumns(
+ insertInto: InsertIntoTable,
+ columns: Seq[Attribute],
+ relation: String) = {
+ val resolved = if (insertInto.isMatchByName) {
+ projectAndCastOutputColumns(columns, insertInto.child, relation)
+ } else {
+ castAndRenameOutputColumns(columns, insertInto.child, relation)
+ }
+
+ if (resolved == insertInto.child.output) {
+ insertInto
+ } else {
+ insertInto.copy(child = Project(resolved, insertInto.child))
+ }
+ }
+
+ /**
+ * Resolves output columns by input column name, adding casts if
necessary.
+ */
+ private def projectAndCastOutputColumns(
+ output: Seq[Attribute],
+ data: LogicalPlan,
+ relation: String): Seq[NamedExpression] = {
+ output.map { col =>
+ data.resolveQuoted(col.name, resolver) match {
+ case Some(inCol) if col.dataType != inCol.dataType =>
+ Alias(UpCast(inCol, col.dataType, Seq()), col.name)()
+ case Some(inCol) => inCol
+ case None =>
+ throw new AnalysisException(
+ s"Cannot resolve ${col.name} in
${data.output.mkString(",")}")
+ }
+ }
+ }
+
+ private def castAndRenameOutputColumns(
+ output: Seq[Attribute],
+ data: LogicalPlan,
+ relation: String): Seq[NamedExpression] = {
+ val outputNames = output.map(_.name)
+ // incoming expressions may not have names
+ val inputNames = data.output.flatMap(col => Option(col.name))
+ if (output.size > data.output.size) {
+ // always a problem
+ throw new AnalysisException(
+ s"""Not enough data columns to write into $relation:
+ |Data columns: ${data.output.mkString(",")}
+ |Table columns: ${outputNames.mkString(",")}""".stripMargin)
+ } else if (output.size < data.output.size) {
+ if (outputNames.toSet.subsetOf(inputNames.toSet)) {
+ throw new AnalysisException(
+ s"""Table column names are a subset of the input data columns:
+ |Data columns: ${inputNames.mkString(",")}
+ |Table columns: ${outputNames.mkString(",")}""".stripMargin)
+ } else {
+ // be conservative and fail if there are too many columns
+ throw new AnalysisException(
+ s"""Extra data columns to write into $relation:
+ |Data columns: ${data.output.mkString(",")}
+ |Table columns: ${outputNames.mkString(",")}""".stripMargin)
+ }
+ } else {
+ // check for reordered names and warn. this may be on purpose, so
it isn't an error.
+ if (outputNames.toSet == inputNames.toSet && outputNames !=
inputNames) {
+ logWarning(
+ s"""Data column names match the table in a different order:
+ |Data columns: ${inputNames.mkString(",")}
+ |Table columns: ${outputNames.mkString(",")}""".stripMargin)
+ }
+ }
+
+ data.output.zip(output).map {
+ case (in, out) if !in.dataType.sameType(out.dataType) =>
+ Alias(Cast(in, out.dataType), out.name)()
+ case (in, out) if in.name != out.name =>
+ Alias(in, out.name)()
+ case (in, _) => in
+ }
+ }
+
+ private def expectedColumns(
+ data: LogicalPlan,
+ partitionData: Map[String, Option[String]]): Seq[Attribute] = {
+ data match {
+ case partitioned: CatalogRelation =>
+ val tablePartitionNames =
partitioned.catalogTable.partitionColumns.map(_.name)
+ val (inputPartCols, dataColumns) = data.output.partition { attr
=>
+ tablePartitionNames.contains(attr.name)
+ }
+ // Get the dynamic partition columns in partition order
+ val dynamicNames = tablePartitionNames.filter(
+ name => partitionData.getOrElse(name, None).isEmpty)
--- End diff --
`partitionData.contains`?
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