Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/7841#discussion_r44500928
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala ---
@@ -273,6 +280,60 @@ class GroupedData protected[sql](
def sum(colNames: String*): DataFrame = {
aggregateNumericColumns(colNames : _*)(Sum)
}
+
+ /**
+ * (Scala-specific) Pivots a column of the current [[DataFrame]] and
preform the specified
+ * aggregation.
+ * {{{
+ * // Compute the sum of earnings for each year by course with each
course as a separate column
+ * df.groupBy($"year").pivot($"course", "dotNET",
"Java").agg(sum($"earnings"))
+ * // Or without specifying column values
+ * df.groupBy($"year").pivot($"course").agg(sum($"earnings"))
+ * }}}
+ * @param pivotColumn Column to pivot
+ * @param values Optional list of values of pivotColumn that will be
translated to columns in the
+ * output data frame. If values are not provided the
method with do an immediate
+ * call to .distinct() on the pivot column.
+ * @since 1.6.0
+ */
+ @scala.annotation.varargs
+ def pivot(pivotColumn: Column, values: String*): GroupedData = groupType
match {
+ case _: GroupedData.PivotType =>
+ throw new UnsupportedOperationException("repeated pivots are not
supported")
+ case GroupedData.GroupByType =>
+ val pivotValues = if (values.nonEmpty) {
+ values
+ } else {
+ // Get the distinct values of the column and sort them so its
consistent
+ df.select(pivotColumn.cast(StringType))
+ .distinct()
+ .map(_.getString(0))
+ .collect().sorted.toSeq
+ }
+ new GroupedData(df, groupingExprs,
GroupedData.PivotType(pivotColumn.expr, pivotValues))
+ case _ =>
+ throw new UnsupportedOperationException("pivot is only supported
after a groupBy")
+ }
+
+ /**
+ * Pivots a column of the current [[DataFrame]] and preform the
specified aggregation.
+ * {{{
+ * // Compute the sum of earnings for each year by course with each
course as a separate column
+ * df.groupBy("year").pivot("course", "dotNET",
"Java").sum("earnings")
+ * // Or without specifying column values
+ * df.groupBy("year").pivot("course").sum("earnings")
+ * }}}
+ * @param pivotColumn Column to pivot
+ * @param values Optional list of values of pivotColumn that will be
translated to columns in the
+ * output data frame. If values are not provided the
method with do an immediate
+ * call to .distinct() on the pivot column.
+ * @since 1.6.0
+ */
+ @scala.annotation.varargs
+ def pivot(pivotColumn: String, values: String*): GroupedData = {
+ val resolvedPivotColumn = Column(df.resolve(pivotColumn))
+ pivot(resolvedPivotColumn, values: _*)
+ }
--- End diff --
For the first version, maybe we can just have the API using `Column` as the
argument type? (I am thinking about the type of values. I am not sure String is
the right type).
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