cloud-fan commented on code in PR #36150:
URL: https://github.com/apache/spark/pull/36150#discussion_r922266752
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/errors/QueryCompilationErrors.scala:
##########
@@ -92,6 +92,19 @@ private[sql] object QueryCompilationErrors extends
QueryErrorsBase {
pivotVal.toString, pivotVal.dataType.simpleString,
pivotCol.dataType.catalogString))
}
+ def unpivotRequiresValueColumns(ids: Seq[NamedExpression]): Throwable = {
+ new AnalysisException(
+ errorClass = "UNPIVOT_REQUIRES_VALUE_COLUMNS",
+ messageParameters = Array(ids.map(id =>
toSQLId(id.toString)).mkString(", ")))
+ }
+
+ def unpivotValDataTypeMismatchError(values: Seq[NamedExpression]): Throwable
= {
+ val dataTypes = values.map(_.dataType).toSet.map((dt: DataType) =>
toSQLType(dt))
Review Comment:
`toSet` removes duplicated types, but I think it's easier for users to find
out which value column is problematic, if they can match type and columns by
ordinal.
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