diff --git a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
index 25973348a7837..1901330d8b188 100644
--- a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
@@ -274,37 +274,42 @@ class RDDSuite extends FunSuite with SharedSparkContext {
   test("coalesced RDDs with locality, large scale (10K partitions)") {
     // large scale experiment
     import collection.mutable
-    val rnd = scala.util.Random
     val partitions = 10000
     val numMachines = 50
     val machines = mutable.ListBuffer[String]()
-    (1 to numMachines).foreach(machines += "m"+_)
-
-    val blocks = (1 to partitions).map(i =>
-    { (i, Array.fill(3)(machines(rnd.nextInt(machines.size))).toList) } )
-
-    val data2 = sc.makeRDD(blocks)
-    val coalesced2 = data2.coalesce(numMachines*2)
-
-    // test that you get over 90% locality in each group
-    val minLocality = coalesced2.partitions
-      .map(part => part.asInstanceOf[CoalescedRDDPartition].localFraction)
-      .foldLeft(1.0)((perc, loc) => math.min(perc,loc))
-    assert(minLocality >= 0.90, "Expected 90% locality but got " + (minLocality*100.0).toInt + "%")
-
-    // test that the groups are load balanced with 100 +/- 20 elements in each
-    val maxImbalance = coalesced2.partitions
-      .map(part => part.asInstanceOf[CoalescedRDDPartition].parents.size)
-      .foldLeft(0)((dev, curr) => math.max(math.abs(100-curr),dev))
-    assert(maxImbalance <= 20, "Expected 100 +/- 20 per partition, but got " + maxImbalance)
-
-    val data3 = sc.makeRDD(blocks).map(i => i*2) // derived RDD to test *current* pref locs
-    val coalesced3 = data3.coalesce(numMachines*2)
-    val minLocality2 = coalesced3.partitions
-      .map(part => part.asInstanceOf[CoalescedRDDPartition].localFraction)
-      .foldLeft(1.0)((perc, loc) => math.min(perc,loc))
-    assert(minLocality2 >= 0.90, "Expected 90% locality for derived RDD but got " +
-      (minLocality2*100.0).toInt + "%")
+    (1 to numMachines).foreach(machines += "m" + _)
+    val rnd = scala.util.Random
+    for (seed <- 1 to 5) {
+      rnd.setSeed(seed)
+
+      val blocks = (1 to partitions).map { i =>
+        (i, Array.fill(3)(machines(rnd.nextInt(machines.size))).toList)
+      }
+
+      val data2 = sc.makeRDD(blocks)
+      val coalesced2 = data2.coalesce(numMachines * 2)
+
+      // test that you get over 90% locality in each group
+      val minLocality = coalesced2.partitions
+        .map(part => part.asInstanceOf[CoalescedRDDPartition].localFraction)
+        .foldLeft(1.0)((perc, loc) => math.min(perc, loc))
+      assert(minLocality >= 0.90, "Expected 90% locality but got " +
+        (minLocality * 100.0).toInt + "%")
+
+      // test that the groups are load balanced with 100 +/- 20 elements in each
+      val maxImbalance = coalesced2.partitions
+        .map(part => part.asInstanceOf[CoalescedRDDPartition].parents.size)
+        .foldLeft(0)((dev, curr) => math.max(math.abs(100 - curr), dev))
+      assert(maxImbalance <= 20, "Expected 100 +/- 20 per partition, but got " + maxImbalance)
+
+      val data3 = sc.makeRDD(blocks).map(i => i * 2) // derived RDD to test *current* pref locs
+      val coalesced3 = data3.coalesce(numMachines * 2)
+      val minLocality2 = coalesced3.partitions
+        .map(part => part.asInstanceOf[CoalescedRDDPartition].localFraction)
+        .foldLeft(1.0)((perc, loc) => math.min(perc, loc))
+      assert(minLocality2 >= 0.90, "Expected 90% locality for derived RDD but got " +
+        (minLocality2 * 100.0).toInt + "%")
+    }
   }
 
   test("zipped RDDs") {