JavaKafkaWordCount not working under Spark Streaming

[Something Something]

I am embarrassed to admit but I can't get a basic 'word count' to work
under Kafka/Spark streaming.  My code looks like this.  I  don't see any
word counts in console output.  Also, don't see any output in UI.  Needless
to say, I am newbie in both 'Spark' as well as 'Kafka'.

Please help.  Thanks.

Here's the code:

    public static void main(String[] args) {
        if (args.length < 4) {
            System.err.println("Usage: JavaKafkaWordCount <zkQuorum>
<group> <topics> <numThreads>");
            System.exit(1);
        }

//        StreamingExamples.setStreamingLogLevels();
//        SparkConf sparkConf = new
SparkConf().setAppName("JavaKafkaWordCount");

        // Location of the Spark directory
        String sparkHome = "/opt/mapr/spark/spark-1.0.2/";

        // URL of the Spark cluster
        String sparkUrl = "spark://mymachine:7077";

        // Location of the required JAR files
        String jarFiles =
"./spark-streaming-kafka_2.10-1.1.0.jar,./DlSpark-1.0-SNAPSHOT.jar,./zkclient-0.3.jar,./kafka_2.10-0.8.1.1.jar,./metrics-core-2.2.0.jar";

        SparkConf sparkConf = new SparkConf();
        sparkConf.setAppName("JavaKafkaWordCount");
        sparkConf.setJars(new String[]{jarFiles});
        sparkConf.setMaster(sparkUrl);
        sparkConf.set("spark.ui.port", "2348");
        sparkConf.setSparkHome(sparkHome);

        Map<String, String> kafkaParams = new HashMap<String, String>();
        kafkaParams.put("zookeeper.connect", "myedgenode:2181");
        kafkaParams.put("group.id", "1");
        kafkaParams.put("metadata.broker.list", "myedgenode:9092");
        kafkaParams.put("serializer.class",
"kafka.serializer.StringEncoder");
        kafkaParams.put("request.required.acks", "1");

        // Create the context with a 1 second batch size
        JavaStreamingContext jssc = new JavaStreamingContext(sparkConf, new
Duration(2000));

        int numThreads = Integer.parseInt(args[3]);
        Map<String, Integer> topicMap = new HashMap<String, Integer>();
        String[] topics = args[2].split(",");
        for (String topic: topics) {
            topicMap.put(topic, numThreads);
        }

//        JavaPairReceiverInputDStream<String, String> messages =
//                KafkaUtils.createStream(jssc, args[0], args[1], topicMap);
        JavaPairDStream<String, String> messages =
KafkaUtils.createStream(jssc,
                String.class,
                String.class,
                StringDecoder.class,
                StringDecoder.class,
                kafkaParams,
                topicMap,
                StorageLevel.MEMORY_ONLY_SER());


        JavaDStream<String> lines = messages.map(new
Function<Tuple2<String, String>, String>() {
            @Override
            public String call(Tuple2<String, String> tuple2) {
                return tuple2._2();
            }
        });

        JavaDStream<String> words = lines.flatMap(new
FlatMapFunction<String, String>() {
            @Override
            public Iterable<String> call(String x) {
                return Lists.newArrayList(SPACE.split(x));
            }
        });

        JavaPairDStream<String, Integer> wordCounts = words.mapToPair(
                new PairFunction<String, String, Integer>() {
                    @Override
                    public Tuple2<String, Integer> call(String s) {
                        return new Tuple2<String, Integer>(s, 1);
                    }
                }).reduceByKey(new Function2<Integer, Integer, Integer>() {
            @Override
            public Integer call(Integer i1, Integer i2) {
                return i1 + i2;
            }
        });

        wordCounts.print();
        jssc.start();
        jssc.awaitTermination();