Kafka实战－Kafka到Storm

2017-11-17 1327

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简介：

1.概述

　　在《Kafka实战－Flume到Kafka》一文中给大家分享了Kafka的数据源生产，今天为大家介绍如何去实时消费Kafka中的数据。这里使用实时计算的模型——Storm。下面是今天分享的主要内容，如下所示：

数据消费
Storm计算
预览截图

　　接下来，我们开始分享今天的内容。

2.数据消费

　　Kafka的数据消费，是由Storm去消费，通过KafkaSpout将数据输送到Storm，然后让Storm安装业务需求对接受的数据做实时处理，下面给大家介绍数据消费的流程图，如下图所示：

　　从图可以看出，Storm通过KafkaSpout获取Kafka集群中的数据，在经过Storm处理后，结果会被持久化到DB库中。

3.Storm计算

　　接着，我们使用Storm去计算，这里需要体检搭建部署好Storm集群，若是未搭建部署集群，大家可以参考我写的《Kafka实战－Storm Cluster》。这里就不多做赘述搭建的过程了，下面给大家介绍实现这部分的代码，关于KafkaSpout的代码如下所示：

KafkaSpout类：

package cn.hadoop.hdfs.storm;

import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import cn.hadoop.hdfs.conf.ConfigureAPI.KafkaProperties;
import kafka.consumer.Consumer;
import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
import backtype.storm.spout.SpoutOutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.IRichSpout;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Values;

/**
 * @Date Jun 10, 2015
 *
 * @Author dengjie
 *
 * @Note Data sources using KafkaSpout to consume Kafka
 */
public class KafkaSpout implements IRichSpout {

    /**
     * 
     */
    private static final long serialVersionUID = -7107773519958260350L;
    private static final Logger LOGGER = LoggerFactory.getLogger(KafkaSpout.class);

    SpoutOutputCollector collector;
    private ConsumerConnector consumer;
    private String topic;

    private static ConsumerConfig createConsumerConfig() {
        Properties props = new Properties();
        props.put("zookeeper.connect", KafkaProperties.ZK);
        props.put("group.id", KafkaProperties.GROUP_ID);
        props.put("zookeeper.session.timeout.ms", "40000");
        props.put("zookeeper.sync.time.ms", "200");
        props.put("auto.commit.interval.ms", "1000");
        return new ConsumerConfig(props);
    }

    public KafkaSpout(String topic) {
        this.topic = topic;
    }

    public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) {
        this.collector = collector;
    }

    public void close() {
        // TODO Auto-generated method stub

    }

    public void activate() {
        this.consumer = Consumer.createJavaConsumerConnector(createConsumerConfig());
        Map<String, Integer> topickMap = new HashMap<String, Integer>();
        topickMap.put(topic, new Integer(1));
        Map<String, List<KafkaStream<byte[], byte[]>>> streamMap = consumer.createMessageStreams(topickMap);
        KafkaStream<byte[], byte[]> stream = streamMap.get(topic).get(0);
        ConsumerIterator<byte[], byte[]> it = stream.iterator();
        while (it.hasNext()) {
            String value = new String(it.next().message());
            LOGGER.info("(consumer)==>" + value);
            collector.emit(new Values(value), value);
        }
    }

    public void deactivate() {
        // TODO Auto-generated method stub

    }

    public void nextTuple() {
        // TODO Auto-generated method stub

    }

    public void ack(Object msgId) {
        // TODO Auto-generated method stub

    }

    public void fail(Object msgId) {
        // TODO Auto-generated method stub

    }

    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        declarer.declare(new Fields("KafkaSpout"));
    }

    public Map<String, Object> getComponentConfiguration() {
        // TODO Auto-generated method stub
        return null;
    }

}

KafkaTopology类：

package cn.hadoop.hdfs.storm.client;

import cn.hadoop.hdfs.storm.FileBlots;
import cn.hadoop.hdfs.storm.KafkaSpout;
import cn.hadoop.hdfs.storm.WordsCounterBlots;
import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.StormSubmitter;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.tuple.Fields;

/**
 * @Date Jun 10, 2015
 *
 * @Author dengjie
 *
 * @Note KafkaTopology Task
 */
public class KafkaTopology {
    public static void main(String[] args) {
        TopologyBuilder builder = new TopologyBuilder();
        builder.setSpout("testGroup", new KafkaSpout("test"));
        builder.setBolt("file-blots", new FileBlots()).shuffleGrouping("testGroup");
        builder.setBolt("words-counter", new WordsCounterBlots(), 2).fieldsGrouping("file-blots", new Fields("words"));
        Config config = new Config();
        config.setDebug(true);
        if (args != null && args.length > 0) {
            // online commit Topology
            config.put(Config.NIMBUS_HOST, args[0]);
            config.setNumWorkers(3);
            try {
                StormSubmitter.submitTopologyWithProgressBar(KafkaTopology.class.getSimpleName(), config,
                        builder.createTopology());
            } catch (Exception e) {
                e.printStackTrace();
            }
        } else {
            // Local commit jar
            LocalCluster local = new LocalCluster();
            local.submitTopology("counter", config, builder.createTopology());
            try {
                Thread.sleep(60000);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            local.shutdown();
        }
    }
}