fall back to filter-map-collect when calling lookup() on an RDD without a partitioner

core/src/main/scala/spark/PairRDDFunctions.scala

@@ -438,7 +438,7 @@ class PairRDDFunctions[K: ClassManifest, V: ClassManifest](
         val res = self.context.runJob(self, process _, Array(index), false)
         res(0)
       case None =>
-        throw new UnsupportedOperationException("lookup() called on an RDD without a partitioner")
+        self.filter(_._1 == key).map(_._2).collect
     }
   }
 

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

@@ -130,6 +130,17 @@ public class JavaAPISuite implements Serializable {
     Assert.assertEquals(2, foreachCalls);
   }
 
+  @Test
+  public void lookup() {
+    JavaPairRDD<String, String> categories = sc.parallelizePairs(Arrays.asList(
+      new Tuple2<String, String>("Apples", "Fruit"),
+      new Tuple2<String, String>("Oranges", "Fruit"),
+      new Tuple2<String, String>("Oranges", "Citrus")
+      ));
+    Assert.assertEquals(2, categories.lookup("Oranges").size());
+    Assert.assertEquals(2, categories.groupByKey().lookup("Oranges").get(0).size());
+  }
+
   @Test
   public void groupBy() {
     JavaRDD<Integer> rdd = sc.parallelize(Arrays.asList(1, 1, 2, 3, 5, 8, 13));