Spark 1165 rdd.intersection in python and java

core/src/main/scala/org/apache/spark/api/java/JavaDoubleRDD.scala

@@ -140,6 +140,14 @@ class JavaDoubleRDD(val srdd: RDD[scala.Double]) extends JavaRDDLike[JDouble, Ja
    */
   def union(other: JavaDoubleRDD): JavaDoubleRDD = fromRDD(srdd.union(other.srdd))
 
+  /**
+   * Return the intersection of this RDD and another one. The output will not contain any duplicate
+   * elements, even if the input RDDs did.
+   *
+   * Note that this method performs a shuffle internally.
+   */
+  def intersection(other: JavaDoubleRDD): JavaDoubleRDD = fromRDD(srdd.intersection(other.srdd))
+
   // Double RDD functions
 
   /** Add up the elements in this RDD. */

core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala

@@ -126,6 +126,16 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])
   def union(other: JavaPairRDD[K, V]): JavaPairRDD[K, V] =
     new JavaPairRDD[K, V](rdd.union(other.rdd))
 
+  /**
+   * Return the intersection of this RDD and another one. The output will not contain any duplicate
+   * elements, even if the input RDDs did.
+   *
+   * Note that this method performs a shuffle internally.
+   */
+  def intersection(other: JavaPairRDD[K, V]): JavaPairRDD[K, V] =
+    new JavaPairRDD[K, V](rdd.intersection(other.rdd))
+
+
   // first() has to be overridden here so that the generated method has the signature
   // 'public scala.Tuple2 first()'; if the trait's definition is used,
   // then the method has the signature 'public java.lang.Object first()',

core/src/main/scala/org/apache/spark/api/java/JavaRDD.scala

@@ -106,6 +106,15 @@ class JavaRDD[T](val rdd: RDD[T])(implicit val classTag: ClassTag[T])
    */
   def union(other: JavaRDD[T]): JavaRDD[T] = wrapRDD(rdd.union(other.rdd))
 
+
+  /**
+   * Return the intersection of this RDD and another one. The output will not contain any duplicate
+   * elements, even if the input RDDs did.
+   *
+   * Note that this method performs a shuffle internally.
+   */
+  def intersection(other: JavaRDD[T]): JavaRDD[T] = wrapRDD(rdd.intersection(other.rdd))
+
   /**
    * Return an RDD with the elements from `this` that are not in `other`.
    *

core/src/test/java/org/apache/spark/JavaAPISuite.java

@@ -110,6 +110,37 @@ public void sparkContextUnion() {
     Assert.assertEquals(4, pUnion.count());
   }
 
+  @SuppressWarnings("unchecked")
+  @Test
+  public void intersection() {
+    List<Integer> ints1 = Arrays.asList(1, 10, 2, 3, 4, 5);
+    List<Integer> ints2 = Arrays.asList(1, 6, 2, 3, 7, 8);
+    JavaRDD<Integer> s1 = sc.parallelize(ints1);
+    JavaRDD<Integer> s2 = sc.parallelize(ints2);
+
+    JavaRDD<Integer> intersections = s1.intersection(s2);
+    Assert.assertEquals(3, intersections.count());
+
+    ArrayList<Integer> list = new ArrayList<Integer>();
+    JavaRDD<Integer> empty = sc.parallelize(list);
+    JavaRDD<Integer> emptyIntersection = empty.intersection(s2);
+    Assert.assertEquals(0, emptyIntersection.count());
+
+    List<Double> doubles = Arrays.asList(1.0, 2.0);
+    JavaDoubleRDD d1 = sc.parallelizeDoubles(doubles);
+    JavaDoubleRDD d2 = sc.parallelizeDoubles(doubles);
+    JavaDoubleRDD dIntersection = d1.intersection(d2);
+    Assert.assertEquals(2, dIntersection.count());
+
+    List<Tuple2<Integer, Integer>> pairs = new ArrayList<Tuple2<Integer, Integer>>();
+    pairs.add(new Tuple2<Integer, Integer>(1, 2));
+    pairs.add(new Tuple2<Integer, Integer>(3, 4));
+    JavaPairRDD<Integer, Integer> p1 = sc.parallelizePairs(pairs);
+    JavaPairRDD<Integer, Integer> p2 = sc.parallelizePairs(pairs);
+    JavaPairRDD<Integer, Integer> pIntersection = p1.intersection(p2);
+    Assert.assertEquals(2, pIntersection.count());
+  }
+
   @Test
   public void sortByKey() {
     List<Tuple2<Integer, Integer>> pairs = new ArrayList<Tuple2<Integer, Integer>>();

python/pyspark/rdd.py

@@ -319,6 +319,23 @@ def union(self, other):
             return RDD(self_copy._jrdd.union(other_copy._jrdd), self.ctx,
                        self.ctx.serializer)
 
+    def intersection(self, other):
+        """
+        Return the intersection of this RDD and another one. The output will not 
+        contain any duplicate elements, even if the input RDDs did.
+
+        Note that this method performs a shuffle internally.
+
+        >>> rdd1 = sc.parallelize([1, 10, 2, 3, 4, 5])
+        >>> rdd2 = sc.parallelize([1, 6, 2, 3, 7, 8])
+        >>> rdd1.intersection(rdd2).collect()
+        [1, 2, 3]
+        """
+        return self.map(lambda v: (v, None)) \
+            .cogroup(other.map(lambda v: (v, None))) \
+            .filter(lambda x: (len(x[1][0]) != 0) and (len(x[1][1]) != 0)) \
+            .keys()
+
     def _reserialize(self):
         if self._jrdd_deserializer == self.ctx.serializer:
             return self