cloud-fan commented on a change in pull request #27499: [SPARK-30590][SQL] 
Untyped select API cannot take typed column expression
URL: https://github.com/apache/spark/pull/27499#discussion_r377575371
 
 

 ##########
 File path: 
sql/core/src/test/scala/org/apache/spark/sql/DatasetAggregatorSuite.scala
 ##########
 @@ -394,4 +403,21 @@ class DatasetAggregatorSuite extends QueryTest with 
SharedSparkSession {
     checkAnswer(group, Row("bob", Row(true, 3)) :: Nil)
     checkDataset(group.as[OptionBooleanIntData], OptionBooleanIntData("bob", 
Some((true, 3))))
   }
+
+  test("SPARK-30590: select multiple typed column expressions") {
+    val df = Seq((1, 2, 3, 4, 5, 6)).toDF("a", "b", "c", "d", "e", "f")
+    val fooAgg = (i: Int) => FooAgg(i).toColumn.name(s"foo_agg_$i")
+
+    val agg1 = df.select(fooAgg(1), fooAgg(2), fooAgg(3), fooAgg(4), fooAgg(5))
+    checkDataset(agg1, (3, 5, 7, 9, 11))
+
+    val agg2 = df.selectUntyped(fooAgg(1), fooAgg(2), fooAgg(3), fooAgg(4), 
fooAgg(5), fooAgg(6))
+      .asInstanceOf[Dataset[(Int, Int, Int, Int, Int, Int)]]
 
 Review comment:
   is this really a good use case? It looks to me `selectUntyped` is a bad 
user-facing API that is hard to use. Maybe we should follow other places and 
add more overloads that take up to 22 columns?

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