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();
}
}
[image: Inline image 1]
Thanks
Best Regards
On Tue, Nov 11, 2014 at 5:37 AM, Something Something <
[email protected]> 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 <
> [email protected]> 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
>> <[email protected]> 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();
>> >
>>
>
>
