Here's a simple working version.


import com.google.common.collect.Lists;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.streaming.Duration;
import org.apache.spark.streaming.api.java.JavaDStream;
import org.apache.spark.streaming.api.java.JavaPairDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;
import org.apache.spark.streaming.kafka.KafkaUtils;
import scala.Tuple2;

import java.util.HashMap;
import java.util.Map;

/**
 * Created by akhld on 11/11/14.
 */

public class KafkaWordcount {

    public static void main(String[] args) {

        // Location of the Spark directory
        String sparkHome = "/home/akhld/mobi/localcluster/spark-1";

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

        // Location of the required JAR files
        String jarFiles = "/home/akhld/mobi/temp/kafkwc.jar,/home/akhld/.ivy2/cache/org.apache.spark/spark-streaming-kafka_2.10/jars/spark-streaming-kafka_2.10-1.1.0.jar,/home/akhld/.ivy2/cache/com.101tec/zkclient/jars/zkclient-0.3.jar,/home/akhld/.ivy2/cache/org.apache.kafka/kafka_2.10/jars/kafka_2.10-0.8.0.jar,/home/akhld/.ivy2/cache/com.yammer.metrics/metrics-core/jars/metrics-core-2.2.0.jar";

        SparkConf sparkConf = new SparkConf();
        sparkConf.setAppName("JavaKafkaWordCount");
        sparkConf.setJars(new String[]{jarFiles});
        sparkConf.setMaster(sparkUrl);
        sparkConf.setSparkHome(sparkHome);

        //These are the minimal things that are required
        Map<String, Integer> topicMap = new HashMap<String, Integer>();
        topicMap.put("test", 1);
        String kafkaGroup = "groups";
        String zkQuorum = "localhost:2181";

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

        JavaPairDStream<String, String> messages = KafkaUtils.createStream(jssc, zkQuorum,
                kafkaGroup, topicMap);


        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(x.split(" "));
            }
        });

        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();


    }

}

Inline image 1 

Thanks
Best Regards

On Tue, Nov 11, 2014 at 5:37 AM, Something Something <mailinglists19@gmail.com> wrote:
I am not running locally.  The Spark master is:

"spark://<machine name>:7077"



On Mon, Nov 10, 2014 at 3:47 PM, Tathagata Das <tathagata.das1565@gmail.com> wrote:
What is the Spark master that you are using. Use local[4], not local
if you are running locally.

On Mon, Nov 10, 2014 at 3:01 PM, Something Something
<mailinglists19@gmail.com> wrote:
> 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();
>