[SPARK-7687] [SQL] DataFrame.describe() should cast all aggregates to String

In `DataFrame.describe()`, the `count` aggregate produces an integer, the `avg` and `stdev` aggregates produce doubles, and `min` and `max` aggregates can produce varying types depending on what type of column they're applied to.  As a result, we should cast all aggregate results to String so that `describe()`'s output types match its declared output schema.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #6218 from JoshRosen/SPARK-7687 and squashes the following commits:

146b615 [Josh Rosen] Fix R test.
2974bd5 [Josh Rosen] Cast to string type instead
f206580 [Josh Rosen] Cast to double to fix SPARK-7687
307ecbf [Josh Rosen] Add failing regression test for SPARK-7687

2 files changed, 14 insertions, 9 deletions

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
index 27e9af49f0..adad85806d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
@@ -1063,7 +1063,7 @@ class DataFrame private[sql](
 
     val ret: Seq[Row] = if (outputCols.nonEmpty) {
       val aggExprs = statistics.flatMap { case (_, colToAgg) =>
-        outputCols.map(c => Column(colToAgg(Column(c).expr)).as(c))
+        outputCols.map(c => Column(Cast(colToAgg(Column(c).expr), StringType)).as(c))
       }
 
       val row = agg(aggExprs.head, aggExprs.tail: _*).head().toSeq
@@ -1077,9 +1077,9 @@ class DataFrame private[sql](
       statistics.map { case (name, _) => Row(name) }
     }
 
-    // The first column is string type, and the rest are double type.
+    // All columns are string type
     val schema = StructType(
-      StructField("summary", StringType) :: outputCols.map(StructField(_, DoubleType))).toAttributes
+      StructField("summary", StringType) :: outputCols.map(StructField(_, StringType))).toAttributes
     LocalRelation(schema, ret)
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
index f05d059d44..0dcba80ef2 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
@@ -370,14 +370,14 @@ class DataFrameSuite extends QueryTest {
       ("Amy",   24, 180)).toDF("name", "age", "height")
 
     val describeResult = Seq(
-      Row("count",   4,               4),
-      Row("mean",    33.0,            178.0),
-      Row("stddev",  16.583123951777, 10.0),
-      Row("min",     16,              164),
-      Row("max",     60,              192))
+      Row("count",   "4",               "4"),
+      Row("mean",    "33.0",            "178.0"),
+      Row("stddev",  "16.583123951777", "10.0"),
+      Row("min",     "16",              "164"),
+      Row("max",     "60",              "192"))
 
     val emptyDescribeResult = Seq(
-      Row("count",   0,    0),
+      Row("count",   "0",  "0"),
       Row("mean",    null, null),
       Row("stddev",  null, null),
       Row("min",     null, null),
@@ -388,6 +388,11 @@ class DataFrameSuite extends QueryTest {
     val describeTwoCols = describeTestData.describe("age", "height")
     assert(getSchemaAsSeq(describeTwoCols) === Seq("summary", "age", "height"))
     checkAnswer(describeTwoCols, describeResult)
+    // All aggregate value should have been cast to string
+    describeTwoCols.collect().foreach { row =>
+      assert(row.get(1).isInstanceOf[String], "expected string but found " + row.get(1).getClass)
+      assert(row.get(2).isInstanceOf[String], "expected string but found " + row.get(2).getClass)
+    }
 
     val describeAllCols = describeTestData.describe()
     assert(getSchemaAsSeq(describeAllCols) === Seq("summary", "age", "height"))