/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.streaming.examples;
import java.util.Map;
import java.util.HashMap;
import java.util.regex.Pattern;
import com.google.common.collect.Lists;
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;
/**
* Consumes messages from one or more topics in Kafka and does wordcount.
* Usage: JavaKafkaWordCount <master> <zkQuorum> <group> <topics> <numThreads>
* <master> is the Spark master URL. In local mode, <master> should be 'local[n]' with n > 1.
* <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
*
* Example:
* `./bin/run-example org.apache.spark.streaming.examples.JavaKafkaWordCount local[2] 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 < 5) {
System.err.println("Usage: KafkaWordCount <master> <zkQuorum> <group> <topics> <numThreads>");
System.exit(1);
}
StreamingExamples.setStreamingLogLevels();
// Create the context with a 1 second batch size
JavaStreamingContext jssc = new JavaStreamingContext(args[0], "KafkaWordCount",
new Duration(2000), System.getenv("SPARK_HOME"),
JavaStreamingContext.jarOfClass(JavaKafkaWordCount.class));
int numThreads = Integer.parseInt(args[4]);
Map<String, Integer> topicMap = new HashMap<String, Integer>();
String[] topics = args[3].split(",");
for (String topic: topics) {
topicMap.put(topic, numThreads);
}
JavaPairDStream<String, String> messages = KafkaUtils.createStream(jssc, args[1], args[2], 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();
}
}