EnricoMi commented on code in PR #36150:
URL: https://github.com/apache/spark/pull/36150#discussion_r923128053


##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala:
##########
@@ -1245,6 +1245,44 @@ case class Pivot(
   override protected def withNewChildInternal(newChild: LogicalPlan): Pivot = 
copy(child = newChild)
 }
 
+/**
+ * A constructor for creating an Unpivot, which will later be converted to an 
[[Expand]]
+ * during the query analysis.
+ *
+ * An empty values array will be replaced during analysis with all resolved 
outputs of child except
+ * the ids. This expansion allows to easily unpivot all non-id columns.
+ *
+ * @see `org.apache.spark.sql.catalyst.analysis.Analyzer.ResolveUnpivot`
+ *
+ * The type of the value column is derived from all value columns during 
analysis once all values
+ * are resolved. All values' types have to be compatible, otherwise the result 
value column cannot
+ * be assigned the individual values and an AnalysisException is thrown.
+ *
+ * @see 
`org.apache.spark.sql.catalyst.analysis.TypeCoercionBase.UnpivotCoercion`
+ *
+ * @param ids                Id columns
+ * @param values             Value columns to unpivot
+ * @param variableColumnName Name of the variable column
+ * @param valueColumnName    Name of the value column
+ * @param valueType          Type of value column once known
+ * @param child              Child operator
+ */
+case class Unpivot(
+    ids: Seq[NamedExpression],
+    values: Seq[NamedExpression],
+    variableColumnName: String,
+    valueColumnName: String,
+    valueType: Option[DataType],

Review Comment:
   Right, the valueType is not needed as it can be derived from 
`values.head.dataType` as `values` is never empty once resolved. I have 
reworked that: 
https://github.com/apache/spark/pull/36150/commits/61c8a3b36ddbbb05e8c066c05b78724eaae201cf



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