EnricoMi commented on code in PR #36150:
URL: https://github.com/apache/spark/pull/36150#discussion_r881780193
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sql/core/src/test/scala/org/apache/spark/sql/MeltSuite.scala:
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@@ -0,0 +1,297 @@
+/*
Review Comment:
Partially! Pivot has an aggregation part, which aggregates values if
multiple values exist for the same groupby and pivot values (see (dotNET,2012)
below). From that aggregated Dataset, you cannot recreate the input.
Formally, the melting of a pivoted Dataset is identical the grouped and
aggregated input Dataset:
```
val courseSales
+------+----+--------+
|course|year|earnings|
+------+----+--------+
|dotNET|2012| 10000.0|
|dotNET|2012| 5000.0|
|dotNET|2013| 48000.0|
| Java|2012| 20000.0|
| Java|2013| 30000.0|
+------+----+--------+
val pivoted = courseSales.groupBy("year").pivot("course", Seq("dotNET",
"Java")).agg(sum($"earnings"))
+----+-------+-------+
|year| dotNET| Java|
+----+-------+-------+
|2012|15000.0|20000.0|
|2013|48000.0|30000.0|
+----+-------+-------+
val melted = pivoted.melt(Array("year"))
+----+--------+-------+
|year|variable| value|
+----+--------+-------+
|2012| dotNET|15000.0|
|2012| Java|20000.0|
|2013| dotNET|48000.0|
|2013| Java|30000.0|
+----+--------+-------+
val expected = courseSales.groupBy("year", "course").sum("earnings")
checkAnswer(melted, expected)
```
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