storm集成kafka实例

storm是流式计算框架，而kafka是一个消息队列，在生产环境中两者经常配合使用，kafka缓存消息，storm可以从kafka中读取消息。因为流式消息的产生可能是不均匀的，经过kafka缓存之后，可以将不均匀的消息流变为均匀的传给storm用于计算。
下面的代码实现了将kafka的“test”topic产生的消息传给storm，然后storm将输出导入kafka的“test2”topic，因为是示例，所以在storm中没有做任何处理，实际场景中数据会在storm被处理。

WordCountTopology.java

import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.StormSubmitter;
import org.apache.storm.kafka.*;
import org.apache.storm.kafka.bolt.KafkaBolt;
import org.apache.storm.spout.Scheme;
import org.apache.storm.spout.SchemeAsMultiScheme;
import org.apache.storm.topology.TopologyBuilder;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Values;

import java.io.UnsupportedEncodingException;
import java.nio.ByteBuffer;
import java.util.*;

public class WordCountTopology {
    private static final String SENTENCE_SPOUT_ID = "sentence-spout";
    private static final String SPLIT_BOLT_ID = "split-bolt";
    private static final String COUNT_BOLT_ID = "count-bolt";
    private static final String REPORT_BOLT_ID = "report-bolt";
    private static final String TOPOLOGY_NAME = "word-count-topology";
    public static void main(String[] args) throws Exception {
        BrokerHosts brokerHosts = new ZkHosts("localhost:2181","/kafka/brokers");
        SpoutConfig spoutConfig = new SpoutConfig(brokerHosts, "test", "/kafka", "word-count-topology");
        Config conf = new Config();
        Properties properties = new Properties();
        properties.put("bootstrap.servers", "localhost:9092");
        properties.put("serializer.class", "kafka.serializer.StringEncoder");
        properties.put("value.serializer","org.apache.kafka.common.serialization.StringSerializer");
        properties.put("key.serializer","org.apache.kafka.common.serialization.StringSerializer");
        conf.put("kafka.broker.properties", properties);
        conf.put("bootstrap.servers", "localhost:9092");
        conf.put("topic", "test2");
        spoutConfig.scheme = new SchemeAsMultiScheme(new StringScheme());
        TopologyBuilder builder = new TopologyBuilder();
        builder.setSpout("kafka-reader", new KafkaSpout(spoutConfig));
        builder.setBolt(SPLIT_BOLT_ID, new TopicMsgBolt()).shuffleGrouping("kafka-reader");
        KafkaBolt kafkaBolt = new KafkaBolt();
        kafkaBolt.withProducerProperties(properties);
        builder.setBolt("msgKafkaBolt", kafkaBolt).shuffleGrouping(SPLIT_BOLT_ID);
        StormSubmitter.submitTopology("ttt", conf, builder.createTopology());
        Thread.sleep(1000);
    }
}

TopicMsgBolt.java

import org.apache.storm.topology.BasicOutputCollector;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.base.BaseBasicBolt;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;

public class TopicMsgBolt extends BaseBasicBolt {

@Override
public void execute(Tuple input, BasicOutputCollector collector) {
    String word = (String) input.getValue(0);
    String out = "Message got is '" + word + "'!";
    collector.emit(new Values(out));
  }

@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
    declarer.declare(new Fields("message"));
  }
}

本来我是想将“kafka-reader”kafkaSpout产生的消息直接发给“msgKafkaBolt”kafkaBolt，但是会报一个“java.lang.IllegalArgumentException: message does not exist”的异常，必须在两者之间加一个bolt，且该bolt的declareOutputFields需要声明“message”field，待研究。。