Added a test for sorting using MutablePair's.

core/src/test/scala/spark/ShuffleSuite.scala

@@ -20,9 +20,10 @@ package spark
 import org.scalatest.FunSuite
 import org.scalatest.matchers.ShouldMatchers
 
-import spark.rdd.ShuffledRDD
 import spark.SparkContext._
 import spark.ShuffleSuite.NonJavaSerializableClass
+import spark.rdd.OrderedRDDFunctions
+import spark.rdd.ShuffledRDD
 import spark.util.MutablePair
 
 
@@ -137,12 +138,27 @@ class ShuffleSuite extends FunSuite with ShouldMatchers with LocalSparkContext {
     sc = new SparkContext("local-cluster[2,1,512]", "test")
     def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2)
     val data = Array(p(1, 1), p(1, 2), p(1, 3), p(2, 1))
-    val pairs: RDD[MutablePair[Int, Int]] = sc.parallelize(data)
+    val pairs: RDD[MutablePair[Int, Int]] = sc.parallelize(data, 2)
     val results = new ShuffledRDD[Int, Int, MutablePair[Int, Int]](pairs, new HashPartitioner(2))
       .collect()
 
     data.foreach { pair => results should contain (pair) }
   }
+
+  test("sorting using mutable pairs") {
+    // This is not in SortingSuite because of the local cluster setup.
+    // Use a local cluster with 2 processes to make sure there are both local and remote blocks
+    sc = new SparkContext("local-cluster[2,1,512]", "test")
+    def p[T1, T2](_1: T1, _2: T2) = MutablePair(_1, _2)
+    val data = Array(p(1, 11), p(3, 33), p(100, 100), p(2, 22))
+    val pairs: RDD[MutablePair[Int, Int]] = sc.parallelize(data, 2)
+    val results = new OrderedRDDFunctions[Int, Int, MutablePair[Int, Int]](pairs)
+      .sortByKey().collect()
+    results(0) should be (p(1, 11))
+    results(1) should be (p(2, 22))
+    results(2) should be (p(3, 33))
+    results(3) should be (p(100, 100))
+  }
 }
 
 object ShuffleSuite {