[SPARK-1947] [SQL] Child of SumDistinct or Average should be widened to prevent overflows the same as Sum.

Child of `SumDistinct` or `Average` should be widened to prevent overflows the same as `Sum`.

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #902 from ueshin/issues/SPARK-1947 and squashes the following commits:

99c3dcb [Takuya UESHIN] Insert Cast for SumDistinct and Average.

1 files changed, 13 insertions, 1 deletions

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala
index 4557d77160..326feea6fe 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala
@@ -264,10 +264,22 @@ trait HiveTypeCoercion {
       // Skip nodes who's children have not been resolved yet.
       case e if !e.childrenResolved => e
 
-      // Promote SUM to largest types to prevent overflows.
+      // Promote SUM, SUM DISTINCT and AVERAGE to largest types to prevent overflows.
       case s @ Sum(e @ DecimalType()) => s // Decimal is already the biggest.
       case Sum(e @ IntegralType()) if e.dataType != LongType => Sum(Cast(e, LongType))
       case Sum(e @ FractionalType()) if e.dataType != DoubleType => Sum(Cast(e, DoubleType))
+
+      case s @ SumDistinct(e @ DecimalType()) => s // Decimal is already the biggest.
+      case SumDistinct(e @ IntegralType()) if e.dataType != LongType =>
+        SumDistinct(Cast(e, LongType))
+      case SumDistinct(e @ FractionalType()) if e.dataType != DoubleType =>
+        SumDistinct(Cast(e, DoubleType))
+
+      case s @ Average(e @ DecimalType()) => s // Decimal is already the biggest.
+      case Average(e @ IntegralType()) if e.dataType != LongType =>
+        Average(Cast(e, LongType))
+      case Average(e @ FractionalType()) if e.dataType != DoubleType =>
+        Average(Cast(e, DoubleType))
     }
   }
 }