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package com.myspark;
import com.google.common.collect.Lists;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.*;
import org.apache.spark.streaming.Duration;
import org.apache.spark.streaming.api.java.*;
import org.apache.spark.streaming.kafka.KafkaUtils;
import scala.Tuple2;
import java.util.HashMap;
import java.util.Map;
import java.util.regex.Pattern;
/**
* Consumes messages from one or more topics in Kafka and does wordcount.
*
* Usage: JavaKafkaWordCount <zkQuorum> <group> <topics> <numThreads>
* <zkQuorum> is a list of one or more zookeeper servers that make quorum
* <group> is the name of kafka consumer group
* <topics> is a list of one or more kafka topics to consume from
* <numThreads> is the number of threads the kafka consumer should use
*
* To run this example:
* `$ bin/run-example org.apache.spark.examples.streaming.JavaKafkaWordCount zoo01,zoo02, \
* zoo03 my-consumer-group topic1,topic2 1`
*/
public final class JavaKafkaWordCount {
private static final Pattern SPACE = Pattern.compile(" ");
private JavaKafkaWordCount() {
}
public static void main(String[] args) {
if (args.length < 4) {
System.err.println("Usage: JavaKafkaWordCount <zkQuorum> <group> <topics> <numThreads>");
System.exit(1);
}
LoggerTools.setStreamingLogLevels();
SparkConf sparkConf = new SparkConf().setAppName("JavaKafkaWordCount");
sparkConf.setMaster("local[2]"); //set master server
sparkConf.set("com.couchbase.bucket.travel-sample", "");
// Create the context with 2 seconds 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);
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();
}
}
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