Github user jaceklaskowski commented on a diff in the pull request:
https://github.com/apache/spark/pull/13526#discussion_r69986532
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala ---
@@ -65,6 +65,46 @@ class KeyValueGroupedDataset[K, V] private[sql](
groupingAttributes)
/**
+ * Returns a new [[KeyValueGroupedDataset]] where the given function has
been applied to the
+ * data. The grouping key is unchanged by this.
+ *
+ * {{{
+ * // Create values grouped by key from a Dataset[(K, V)]
+ * ds.groupByKey(_._1).mapValues(_._2) // Scala
+ * }}}
+ * @since 2.0.0
+ */
+ def mapValues[W: Encoder](func: V => W): KeyValueGroupedDataset[K, W] = {
+ val withNewData = AppendColumns(func, dataAttributes, logicalPlan)
+ val projected = Project(withNewData.newColumns ++ groupingAttributes,
withNewData)
+ val executed = sparkSession.sessionState.executePlan(projected)
+
+ new KeyValueGroupedDataset(
+ encoderFor[K],
+ encoderFor[W],
+ executed,
+ withNewData.newColumns,
+ groupingAttributes)
+ }
+
+ /**
+ * Returns a new [[KeyValueGroupedDataset]] where the given function has
been applied to the
+ * data. The grouping key is unchanged by this.
+ *
+ * {{{
+ * // Create Integer values grouped by String key from a
Dataset<Tuple2<String, Integer>>
+ * Dataset<Tuple2<String, Integer>> ds = ...;
+ * KeyValueGroupedDataset<String, Integer> grouped =
+ * ds.groupByKey(t -> t._1, Encoders.STRING()).mapValues(t -> t._2,
Encoders.INT()); // Java 8
+ * }}}
+ * @since 2.0.0
+ */
+ def mapValues[W](func: MapFunction[V, W], encoder: Encoder[W]):
KeyValueGroupedDataset[K, W] = {
+ implicit val uEnc = encoder
+ mapValues{ (v: V) => func.call(v) }
--- End diff --
A space before `{`?
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