diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
index 3d071df493cec..a52f5f4ac94ae 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingSymmetricHashJoinExec.scala
@@ -56,8 +56,8 @@ import org.apache.spark.util.{CompletionIterator, SerializableConfiguration}
  * - Apply the optional condition to filter the joined rows as the final output.
  *
  * If a timestamp column with event time watermark is present in the join keys or in the input
- * data, then the it uses the watermark figure out which rows in the buffer will not join with
- * and the new data, and therefore can be discarded. Depending on the provided query conditions, we
+ * data, then it uses the watermark to figure out which rows in the buffer will not join with
+ * the new data, and therefore can be discarded. Depending on the provided query conditions, we
  * can define thresholds on both state key (i.e. joining keys) and state value (i.e. input rows).
  * There are three kinds of queries possible regarding this as explained below.
  * Assume that watermark has been defined on both `leftTime` and `rightTime` columns used below.
@@ -134,7 +134,7 @@ case class StreamingSymmetricHashJoinExec(
     stateWatermarkPredicates: JoinStateWatermarkPredicates,
     stateFormatVersion: Int,
     left: SparkPlan,
-    right: SparkPlan) extends SparkPlan with BinaryExecNode with StateStoreWriter {
+    right: SparkPlan) extends BinaryExecNode with StateStoreWriter {
 
   def this(
       leftKeys: Seq[Expression],
@@ -157,14 +157,16 @@ case class StreamingSymmetricHashJoinExec(
       " the checkpoint and rerun the query. See SPARK-26154 for more details.")
   }
 
+  private lazy val errorMessageForJoinType =
+    s"${getClass.getSimpleName} should not take $joinType as the JoinType"
+
   private def throwBadJoinTypeException(): Nothing = {
-    throw new IllegalArgumentException(
-      s"${getClass.getSimpleName} should not take $joinType as the JoinType")
+    throw new IllegalArgumentException(errorMessageForJoinType)
   }
 
   require(
     joinType == Inner || joinType == LeftOuter || joinType == RightOuter,
-    s"${getClass.getSimpleName} should not take $joinType as the JoinType")
+    errorMessageForJoinType)
   require(leftKeys.map(_.dataType) == rightKeys.map(_.dataType))
 
   private val storeConf = new StateStoreConf(sqlContext.conf)
@@ -189,11 +191,9 @@ case class StreamingSymmetricHashJoinExec(
   override def outputPartitioning: Partitioning = joinType match {
     case _: InnerLike =>
       PartitioningCollection(Seq(left.outputPartitioning, right.outputPartitioning))
-    case LeftOuter => PartitioningCollection(Seq(left.outputPartitioning))
-    case RightOuter => PartitioningCollection(Seq(right.outputPartitioning))
-    case x =>
-      throw new IllegalArgumentException(
-        s"${getClass.getSimpleName} should not take $x as the JoinType")
+    case LeftOuter => left.outputPartitioning
+    case RightOuter => right.outputPartitioning
+    case _ => throwBadJoinTypeException()
   }
 
   override def shouldRunAnotherBatch(newMetadata: OffsetSeqMetadata): Boolean = {
@@ -246,13 +246,14 @@ case class StreamingSymmetricHashJoinExec(
 
     //  Join one side input using the other side's buffered/state rows. Here is how it is done.
     //
-    //  - `leftJoiner.joinWith(rightJoiner)` generates all rows from matching new left input with
-    //    stored right input, and also stores all the left input
+    //  - `leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner)` generates all rows from
+    //    matching new left input with stored right input, and also stores all the left input
     //
-    //  - `rightJoiner.joinWith(leftJoiner)` generates all rows from matching new right input with
-    //    stored left input, and also stores all the right input. It also generates all rows from
-    //    matching new left input with new right input, since the new left input has become stored
-    //    by that point. This tiny asymmetry is necessary to avoid duplication.
+    //  - `rightSideJoiner.storeAndJoinWithOtherSide(leftSideJoiner)` generates all rows from
+    //    matching new right input with stored left input, and also stores all the right input.
+    //    It also generates all rows from matching new left input with new right input, since
+    //    the new left input has become stored by that point. This tiny asymmetry is necessary
+    //    to avoid duplication.
     val leftOutputIter = leftSideJoiner.storeAndJoinWithOtherSide(rightSideJoiner) {
       (input: InternalRow, matched: InternalRow) => joinedRow.withLeft(input).withRight(matched)
     }
@@ -459,8 +460,9 @@ case class StreamingSymmetricHashJoinExec(
      */
     def storeAndJoinWithOtherSide(
         otherSideJoiner: OneSideHashJoiner)(
-        generateJoinedRow: (InternalRow, InternalRow) => JoinedRow):
-    Iterator[InternalRow] = {
+        generateJoinedRow: (InternalRow, InternalRow) => JoinedRow)
+      : Iterator[InternalRow] = {
+
       val watermarkAttribute = inputAttributes.find(_.metadata.contains(delayKey))
       val nonLateRows =
         WatermarkSupport.watermarkExpression(watermarkAttribute, eventTimeWatermark) match {
@@ -471,6 +473,14 @@ case class StreamingSymmetricHashJoinExec(
             inputIter
         }
 
+      val generateFilteredJoinedRow: InternalRow => Iterator[InternalRow] = joinSide match {
+        case LeftSide if joinType == LeftOuter =>
+          (row: InternalRow) => Iterator(generateJoinedRow(row, nullRight))
+        case RightSide if joinType == RightOuter =>
+          (row: InternalRow) => Iterator(generateJoinedRow(row, nullLeft))
+        case _ => (_: InternalRow) => Iterator.empty
+      }
+
       nonLateRows.flatMap { row =>
         val thisRow = row.asInstanceOf[UnsafeRow]
         // If this row fails the pre join filter, that means it can never satisfy the full join
@@ -483,13 +493,7 @@ case class StreamingSymmetricHashJoinExec(
             .getJoinedRows(key, thatRow => generateJoinedRow(thisRow, thatRow), postJoinFilter)
           new AddingProcessedRowToStateCompletionIterator(key, thisRow, outputIter)
         } else {
-          joinSide match {
-            case LeftSide if joinType == LeftOuter =>
-              Iterator(generateJoinedRow(thisRow, nullRight))
-            case RightSide if joinType == RightOuter =>
-              Iterator(generateJoinedRow(thisRow, nullLeft))
-            case _ => Iterator()
-          }
+          generateFilteredJoinedRow(thisRow)
         }
       }
     }