Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/13345#discussion_r64859326
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala
---
@@ -376,6 +376,38 @@ class SparkSession private(
Dataset.ofRows(self, LogicalRelation(baseRelation))
}
+ /* ------------------------------- *
+ | Methods for creating DataSets |
+ * ------------------------------- */
+
+ /**
+ * Creates a [[Dataset]] from a local Seq of data of a given type. This
method requires an
+ * encoder (to convert a JVM object of type `T` to and from the internal
Spark SQL representation)
+ * that is generally created automatically through implicits from a
`SparkSession`, or can be
+ * created explicitly by calling static methods on [[Encoders]].
+ *
+ * == Example ==
+ *
+ * {{{
+ *
+ * import spark.implicits._
+ * case class Person(name: String, age: Long)
+ * val data = Seq(Person("Michael", 29), Person("Andy", 30),
Person("Justin", 19))
+ * val ds = spark.createDataset(data)
+ *
+ * ds.show()
+ * // +-------+---+
+ * // | name|age|
+ * // +-------+---+
+ * // |Michael| 29|
+ * // | Andy| 30|
+ * // | Justin| 19|
+ * // +-------+---+
+ * }}}
+ *
+ * @since 2.0.0
+ * @group dataset
+ */
def createDataset[T : Encoder](data: Seq[T]): Dataset[T] = {
--- End diff --
can you add experimental to all 3?
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