/* * 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.examples.streaming; import java.util.HashMap; import java.util.HashSet; import java.util.Arrays; import java.util.Iterator; import java.util.Map; import java.util.Set; import java.util.regex.Pattern; import scala.Tuple2; import kafka.serializer.StringDecoder; import org.apache.spark.SparkConf; import org.apache.spark.api.java.function.*; import org.apache.spark.streaming.api.java.*; import org.apache.spark.streaming.kafka.KafkaUtils; import org.apache.spark.streaming.Durations; /** * Consumes messages from one or more topics in Kafka and does wordcount. * Usage: JavaDirectKafkaWordCount <brokers> <topics> * <brokers> is a list of one or more Kafka brokers * <topics> is a list of one or more kafka topics to consume from * * Example: * $ bin/run-example streaming.JavaDirectKafkaWordCount broker1-host:port,broker2-host:port \ * topic1,topic2 */ public final class JavaDirectKafkaWordCount { private static final Pattern SPACE = Pattern.compile(" "); public static void main(String[] args) throws Exception { if (args.length < 2) { System.err.println("Usage: JavaDirectKafkaWordCount <brokers> <topics>\n" + " <brokers> is a list of one or more Kafka brokers\n" + " <topics> is a list of one or more kafka topics to consume from\n\n"); System.exit(1); } StreamingExamples.setStreamingLogLevels(); String brokers = args[0]; String topics = args[1]; // Create context with a 2 seconds batch interval SparkConf sparkConf = new SparkConf().setAppName("JavaDirectKafkaWordCount"); JavaStreamingContext jssc = new JavaStreamingContext(sparkConf, Durations.seconds(2)); Set<String> topicsSet = new HashSet<>(Arrays.asList(topics.split(","))); Map<String, String> kafkaParams = new HashMap<>(); kafkaParams.put("metadata.broker.list", brokers); // Create direct kafka stream with brokers and topics JavaPairInputDStream<String, String> messages = KafkaUtils.createDirectStream( jssc, String.class, String.class, StringDecoder.class, StringDecoder.class, kafkaParams, topicsSet ); // Get the lines, split them into words, count the words and print 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 Iterator<String> call(String x) { return Arrays.asList(SPACE.split(x)).iterator(); } }); JavaPairDStream<String, Integer> wordCounts = words.mapToPair( new PairFunction<String, String, Integer>() { @Override public Tuple2<String, Integer> call(String s) { return new Tuple2<>(s, 1); } }).reduceByKey( new Function2<Integer, Integer, Integer>() { @Override public Integer call(Integer i1, Integer i2) { return i1 + i2; } }); wordCounts.print(); // Start the computation jssc.start(); jssc.awaitTermination(); } }