cloud-fan commented on code in PR #36150:
URL: https://github.com/apache/spark/pull/36150#discussion_r922269010
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sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala:
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@@ -2013,6 +2013,143 @@ class Dataset[T] private[sql](
@scala.annotation.varargs
def agg(expr: Column, exprs: Column*): DataFrame = groupBy().agg(expr, exprs
: _*)
+ /**
+ * Unpivot a DataFrame from wide format to long format, optionally leaving
identifier columns set.
+ * This is the reverse to `groupBy(...).pivot(...).agg(...)`, except for the
aggregation,
+ * which cannot be reversed.
+ *
+ * This function is useful to massage a DataFrame into a format where some
+ * columns are identifier columns ("ids"), while all other columns ("values")
+ * are "unpivoted" to the rows, leaving just two non-id columns, named as
given
+ * by `variableColumnName` and `valueColumnName`.
+ *
+ * {{{
+ * val df = Seq((1, 11, 12L), (2, 21, 22L)).toDF("id", "int", "long")
+ * df.show()
+ * // output:
+ * // +---+---+----+
+ * // | id|int|long|
+ * // +---+---+----+
+ * // | 1| 11| 12|
+ * // | 2| 21| 22|
+ * // +---+---+----+
+ *
+ * df.unpivot(Array($"id"), Array($"int", $"long"), "variable",
"value").show()
+ * // output:
+ * // +---+--------+-----+
+ * // | id|variable|value|
+ * // +---+--------+-----+
+ * // | 1| int| 11|
+ * // | 1| long| 12|
+ * // | 2| int| 21|
+ * // | 2| long| 22|
+ * // +---+--------+-----+
+ * // schema:
+ * //root
+ * // |-- id: integer (nullable = false)
+ * // |-- variable: string (nullable = false)
+ * // |-- value: long (nullable = true)
+ * }}}
+ *
+ * When no "id" columns are given, the unpivoted DataFrame consists of only
the
+ * "variable" and "value" columns.
+ *
+ * All "value" columns must share a least common data type. Unless they are
the same data type,
+ * all "value" columns are cast to the nearest common data type. For
instance,
+ * types `IntegerType` and `LongType` are cast to `LongType`, while
`IntegerType` and `StringType`
+ * do not have a common data type and `unpivot` fails.
+ *
+ * @param ids Id columns
+ * @param values Value columns to unpivot
+ * @param variableColumnName Name of the variable column
Review Comment:
Is this naming from pandas? `variable` is a bit weird to me, as this column
contains the type string of each value column.
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