Move zero-length partition testing from JavaAPISuite.java to PartitioningSuite.scala

core/src/test/scala/spark/JavaAPISuite.java

@@ -314,28 +314,6 @@ public class JavaAPISuite implements Serializable {
     List<Double> take = rdd.take(5);
   }
 
-  @Test
-  public void zeroLengthPartitions() {
-    // Create RDD with some consecutive empty partitions (including the "first" one)
-    JavaDoubleRDD rdd = sc
-        .parallelizeDoubles(Arrays.asList(-1.0, -1.0, -1.0, -1.0, 2.0, 4.0, -1.0, -1.0), 8)
-        .filter(new Function<Double, Boolean>() {
-          @Override
-          public Boolean call(Double x) {
-            return x > 0.0;
-          }
-        });
-    
-    // Run the partitions, including the consecutive empty ones, through StatCounter
-    StatCounter stats = rdd.stats();
-    Assert.assertEquals(6.0, stats.sum(), 0.01);
-    Assert.assertEquals(6.0/2, rdd.mean(), 0.01);
-    Assert.assertEquals(1.0, rdd.variance(), 0.01);
-    Assert.assertEquals(1.0, rdd.stdev(), 0.01);
-    
-    // Add other tests here for classes that should be able to handle empty partitions correctly
-  }
-
   @Test
   public void map() {
     JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5));

core/src/test/scala/spark/PartitioningSuite.scala

 package spark
 
 import org.scalatest.FunSuite
-
 import scala.collection.mutable.ArrayBuffer
-
 import SparkContext._
+import spark.util.StatCounter
+import scala.math._
 
 class PartitioningSuite extends FunSuite with LocalSparkContext {
   
@@ -120,4 +120,21 @@ class PartitioningSuite extends FunSuite with LocalSparkContext {
     assert(intercept[SparkException]{ arrPairs.reduceByKeyLocally(_ + _) }.getMessage.contains("array"))
     assert(intercept[SparkException]{ arrPairs.reduceByKey(_ + _) }.getMessage.contains("array"))
   }
+  
+  test("Zero-length partitions should be correctly handled") {
+    // Create RDD with some consecutive empty partitions (including the "first" one)
+    sc = new SparkContext("local", "test")
+    val rdd: RDD[Double] = sc
+        .parallelize(Array(-1.0, -1.0, -1.0, -1.0, 2.0, 4.0, -1.0, -1.0), 8)
+        .filter(_ >= 0.0)
+    
+    // Run the partitions, including the consecutive empty ones, through StatCounter
+    val stats: StatCounter = rdd.stats();
+    assert(abs(6.0 - stats.sum) < 0.01);
+    assert(abs(6.0/2 - rdd.mean) < 0.01);
+    assert(abs(1.0 - rdd.variance) < 0.01);
+    assert(abs(1.0 - rdd.stdev) < 0.01);
+    
+    // Add other tests here for classes that should be able to handle empty partitions correctly
+  }
 }