Github user liancheng commented on a diff in the pull request:
https://github.com/apache/spark/pull/11443#discussion_r73107764
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala ---
@@ -745,6 +825,80 @@ class DataFrame private[sql](
}
/**
+ * Returns a new [[Dataset]] by computing the given [[Column]]
expression for each element.
+ *
+ * {{{
+ * val ds = Seq(1, 2, 3).toDS()
+ * val newDS = ds.select(expr("value + 1").as[Int])
+ * }}}
+ * @since 1.6.0
+ */
+ def select[U1: Encoder](c1: TypedColumn[T, U1]): Dataset[U1] = {
--- End diff --
@vlad17 The reason why the snippet in your Gist fails is that `(1 to
10).toDS` is a `Dataset[Int]`, while `agg.toColumn` is a `TypedColumn[Long,
Long]`. Thus the `select` call is dispatched to the untyped one. The following
one works:
```
scala> spark.range(10).as[Long].select(agg.toColumn).show()
+---------------+
|$anon$1(bigint)|
+---------------+
| 10|
+---------------+
```
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