diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
index e3d28388c547..ad95879d86f4 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
@@ -17,6 +17,7 @@
 
 package org.apache.spark.sql.execution.exchange
 
+import scala.collection.mutable
 import scala.collection.mutable.ArrayBuffer
 
 import org.apache.spark.sql.catalyst.expressions._
@@ -227,9 +228,16 @@ case class EnsureRequirements(conf: SQLConf) extends Rule[SparkPlan] {
       currentOrderOfKeys: Seq[Expression]): (Seq[Expression], Seq[Expression]) = {
     val leftKeysBuffer = ArrayBuffer[Expression]()
     val rightKeysBuffer = ArrayBuffer[Expression]()
+    val pickedIndexes = mutable.Set[Int]()
+    val keysAndIndexes = currentOrderOfKeys.zipWithIndex
 
     expectedOrderOfKeys.foreach(expression => {
-      val index = currentOrderOfKeys.indexWhere(e => e.semanticEquals(expression))
+      val index = keysAndIndexes.find { case (e, idx) =>
+        // As we may have the same key used many times, we need to filter out its occurrence we
+        // have already used.
+        e.semanticEquals(expression) && !pickedIndexes.contains(idx)
+      }.map(_._2).get
+      pickedIndexes += index
       leftKeysBuffer.append(leftKeys(index))
       rightKeysBuffer.append(rightKeys(index))
     })
@@ -270,7 +278,7 @@ case class EnsureRequirements(conf: SQLConf) extends Rule[SparkPlan] {
    * partitioning of the join nodes' children.
    */
   private def reorderJoinPredicates(plan: SparkPlan): SparkPlan = {
-    plan.transformUp {
+    plan match {
       case BroadcastHashJoinExec(leftKeys, rightKeys, joinType, buildSide, condition, left,
         right) =>
         val (reorderedLeftKeys, reorderedRightKeys) =
@@ -288,6 +296,8 @@ case class EnsureRequirements(conf: SQLConf) extends Rule[SparkPlan] {
         val (reorderedLeftKeys, reorderedRightKeys) =
           reorderJoinKeys(leftKeys, rightKeys, left.outputPartitioning, right.outputPartitioning)
         SortMergeJoinExec(reorderedLeftKeys, reorderedRightKeys, joinType, condition, left, right)
+
+      case other => other
     }
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala
index 8fa747465cb1..44767dfc9249 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala
@@ -882,4 +882,15 @@ class JoinSuite extends QueryTest with SharedSQLContext {
       checkAnswer(df, Row(3, 8, 7, 2) :: Row(3, 8, 4, 2) :: Nil)
     }
   }
+
+  test("SPARK-24495: Join may return wrong result when having duplicated equal-join keys") {
+    withSQLConf(SQLConf.SHUFFLE_PARTITIONS.key -> "1",
+      SQLConf.CONSTRAINT_PROPAGATION_ENABLED.key -> "false",
+      SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "-1") {
+      val df1 = spark.range(0, 100, 1, 2)
+      val df2 = spark.range(100).select($"id".as("b1"), (- $"id").as("b2"))
+      val res = df1.join(df2, $"id" === $"b1" && $"id" === $"b2").select($"b1", $"b2", $"id")
+      checkAnswer(res, Row(0, 0, 0))
+    }
+  }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala
index ed0ff1be476c..37d468739c61 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala
@@ -680,6 +680,23 @@ class PlannerSuite extends SharedSQLContext {
     assert(rangeExecInZeroPartition.head.outputPartitioning == UnknownPartitioning(0))
   }
 
+  test("SPARK-24495: EnsureRequirements can return wrong plan when reusing the same key in join") {
+    val plan1 = DummySparkPlan(outputOrdering = Seq(orderingA),
+      outputPartitioning = HashPartitioning(exprA :: exprA :: Nil, 5))
+    val plan2 = DummySparkPlan(outputOrdering = Seq(orderingB),
+      outputPartitioning = HashPartitioning(exprB :: Nil, 5))
+    val smjExec = SortMergeJoinExec(
+      exprA :: exprA :: Nil, exprB :: exprC :: Nil, Inner, None, plan1, plan2)
+
+    val outputPlan = EnsureRequirements(spark.sessionState.conf).apply(smjExec)
+    outputPlan match {
+      case SortMergeJoinExec(leftKeys, rightKeys, _, _, _, _) =>
+        assert(leftKeys == Seq(exprA, exprA))
+        assert(rightKeys == Seq(exprB, exprC))
+      case _ => fail()
+    }
+  }
+
   test("SPARK-24500: create union with stream of children") {
     val df = Union(Stream(
       Range(1, 1, 1, 1),