Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/7841#discussion_r44500555
--- 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"))
+ * }}}
--- End diff --
How about we let users know that if no pivot values are provided, we will
launch a job to find all distinct values of the pivot column?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
