diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala
index a8983df208318..6a32244bd03b3 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala
@@ -17,7 +17,7 @@
 
 package org.apache.spark.sql.catalyst.expressions
 
-import org.apache.spark.sql.types.{StructType, NativeType}
+import org.apache.spark.sql.types.{DataType, StructType, NativeType}
 
 
 /**
@@ -232,3 +232,10 @@ class RowOrdering(ordering: Seq[SortOrder]) extends Ordering[Row] {
     return 0
   }
 }
+
+object RowOrdering {
+  def getOrderingFromDataTypes(dataTypes: Seq[DataType]): RowOrdering =
+    new RowOrdering(dataTypes.zipWithIndex.map {
+      case(dt, index) => new SortOrder(BoundReference(index, dt, nullable = true), Ascending)
+    })
+}
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala
index a1f0805a0ab92..048251c4c1f91 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/SortMergeJoin.scala
@@ -46,11 +46,8 @@ case class SortMergeJoin(
   override def requiredChildDistribution: Seq[Distribution] =
     ClusteredDistribution(leftKeys) :: ClusteredDistribution(rightKeys) :: Nil
 
-  private val orders: Seq[SortOrder] = leftKeys.zipWithIndex.map {
-    case(expr, index) => SortOrder(BoundReference(index, expr.dataType, expr.nullable), Ascending)
-  }
   // this is to manually construct an ordering that can be used to compare keys from both sides
-  private val keyOrdering: RowOrdering = new RowOrdering(orders)
+  private val keyOrdering: RowOrdering = RowOrdering.getOrderingFromDataTypes(leftKeys.map(_.dataType))
 
   private def requiredOrders(keys: Seq[Expression], side: SparkPlan): Ordering[Row] =
     newOrdering(keys.map(SortOrder(_, Ascending)), side.output)