Storm的WordCount案例（spout bolt详细总结）

spout介绍

一个spout是由流组成的数据源在storm的拓扑里，通常情况下会读取外部的数据源 
然后emit（发射）到拓扑里面，比如是kafka，MySQL或者redis等等，Spout有两种实现一种是可靠的消息实现，如果发送失败则会重试，另外一种是不可靠的消息实现可能会出现消息丢失，spout可以一次声明多个数据流通过OutputFieldsDeclarer类的declareStream方法，当然前提是你的SpoutOutputCollector里的emit也是多个流 

Spout里面主要的方法是nextTuple，它里面可以发射新的tuple到拓扑，或者当没有消息的时候就return，需要注意，这个方法里面不能阻塞，因为storm调用spout方法是单线程的，其他的主要方法是ack和fail，如果使用了可靠的spout，可以使用ack和fail来确定消息发送状态 

相关扩展： 
IRichSpout：spout类必须实现的接口 
BaseRichSpout ：可靠的spout有ack确保 
BaseBasicSpout ：不可靠的spout

1.Spout组件：创建Spout（WordCountSpout）组件采集数据，作为整个Topology的数据源

WordCountSpout：

package storm;

import lombok.SneakyThrows;
import org.apache.storm.spout.SpoutOutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.IRichSpout;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Values;

import java.util.Map;
import java.util.Random;
import java.util.concurrent.TimeUnit;

/**
 * @author: wtl
 * @License: (C) Copyright 2020, wtl Corporation Limited.
 * @Contact: 1050100468@qq.com
 * @Date: 2020/11/27 5:14
 * @Version: 1.0
 * @Description:
 */
public class WordCountSpout implements IRichSpout {

    private SpoutOutputCollector spoutOutputCollector;
    private String [] lines = {"I love you","hello world","hello kitty","nihao beijing"};
    private Random random = new Random();

    @Override
    public void open(Map<String, Object> map, TopologyContext topologyContext, SpoutOutputCollector spoutOutputCollector) {
        this.spoutOutputCollector = spoutOutputCollector;
    }

    @Override
    public void close() {

    }

    @Override
    public void activate() {

    }

    @Override
    public void deactivate() {

    }

    @SneakyThrows
    @Override
    public void nextTuple() {
        int nextInt = random.nextInt(lines.length);
        spoutOutputCollector.emit(new Values(lines[nextInt]));
        TimeUnit.SECONDS.sleep(1);
    }

    @Override
    public void ack(Object o) {

    }

    @Override
    public void fail(Object o) {

    }

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

    @Override
    public Map<String, Object> getComponentConfiguration() {
        return null;
    }
}

bolt介绍

Bolts 业务处理单元 
所有的拓扑处理都会在bolt中进行，bolt里面可以做任何etl，比如过滤，函数，聚合，连接，写入数据库系统或缓存等，一个bolt可以做简单的事件流转换，如果是复杂的流转化，往往需要多个bolt参与，这就是流计算，每个bolt都进行一个业务逻辑处理，bolt也可以emit多个流到下游，通过declareStream方法声明输出的schema。 

Bolt里面主要的方法是execute方法，每次处理一个输入的tuple，bolt里面也可以发射新的tuple使用OutputCollector类，bolt里面每处理一个tuple必须调用ack方法以便于storm知道某个tuple何时处理完成。Strom里面的IBasicBolt接口可以自动 
调用ack。 

相关拓展： 
IRichBolt：bolts的通用接口 
IBasicBolt：扩展的bolt接口，可以自动处理ack 
OutputCollector：bolt发射tuple到下游bolt里面 

2.Bolt组件1：创建Bolt（WordCountSplitBolt）组件进行分词操作

SplitBolt：

package storm;

import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.IRichBolt;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;

import java.util.Map;
import java.util.stream.Stream;

/**
 * @author: wtl
 * @License: (C) Copyright 2020, wtl Corporation Limited.
 * @Contact: 1050100468@qq.com
 * @Date: 2020/11/27 5:41
 * @Version: 1.0
 * @Description:
 */
public class SplitBolt implements IRichBolt {

    private TopologyContext topologyContext;
    private OutputCollector outputCollector;

    @Override
    public void prepare(Map<String, Object> map, TopologyContext topologyContext, OutputCollector outputCollector) {
        this.topologyContext = topologyContext;
        this.outputCollector = outputCollector;
    }

    @Override
    public void execute(Tuple tuple) {
        String line = tuple.getStringByField("line");
        String[] splits = line.split(" ");

        Stream.of(splits).forEach(word -> {
            outputCollector.emit(new Values(word,1));
        });
    }

    @Override
    public void cleanup() {

    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer outputFieldsDeclarer) {
        outputFieldsDeclarer.declare(new Fields("word","count"));
    }

    @Override
    public Map<String, Object> getComponentConfiguration() {
        return null;
    }
}

3.Bolt组件2：创建Bolt（WordCountTotalBolt）组件进行单词统计操作

TotalBolt：

package storm;

import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.IRichBolt;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;

import java.util.HashMap;
import java.util.Map;

/**
 * @author: wtl
 * @License: (C) Copyright 2020, wtl Corporation Limited.
 * @Contact: 1050100468@qq.com
 * @Date: 2020/11/27 5:57
 * @Version: 1.0
 * @Description:
 */
public class TotalBolt implements IRichBolt {
    private TopologyContext topologyContext;
    private OutputCollector outputCollector;
    private Map<String,Integer> map;

    @Override
    public void prepare(Map<String, Object> map, TopologyContext topologyContext, OutputCollector outputCollector) {
        this.topologyContext = topologyContext;
        this.outputCollector = outputCollector;
        this.map = new HashMap<>();
    }

    @Override
    public void execute(Tuple tuple) {
        String word = tuple.getStringByField("word");
        Integer count = tuple.getIntegerByField("count");
        if (!map.containsKey(word)){
            map.put(word,count);
        }
        else{
            map.put(word,map.get(word) + count);
        }

        map.forEach((key, value) -> {
            System.out.println(key + ": " + value);
        });
    }

    @Override
    public void cleanup() {
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer outputFieldsDeclarer) {
        outputFieldsDeclarer.declare(new Fields("word","total"));
    }

    @Override
    public Map<String, Object> getComponentConfiguration() {
        return null;
    }
}

4.Topology主程序:

WordCountTopology:

package storm;

import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.generated.StormTopology;
import org.apache.storm.topology.TopologyBuilder;
import org.apache.storm.tuple.Fields;

/**
 * @author: wtl
 * @License: (C) Copyright 2020, wtl Corporation Limited.
 * @Contact: 1050100468@qq.com
 * @Date: 2020/11/27 6:06
 * @Version: 1.0
 * @Description:
 */
public class WordCountTopology {
    public static void main(String[] args) throws Exception {
        TopologyBuilder topologyBuilder = new TopologyBuilder();

        topologyBuilder.setSpout("wcSpout",new WordCountSpout(),1);
        topologyBuilder.setBolt("wcSplitBolt",new SplitBolt(),1).shuffleGrouping("wcSpout");

        topologyBuilder.setBolt("wcTotalBolt",new TotalBolt(),1).fieldsGrouping("wcSplitBolt",new Fields("word"));

        //创建任务
        StormTopology job = topologyBuilder.createTopology();

        Config config = new Config();

        //运行任务有两种模式
        //1 本地模式   2 集群模式

        //1、本地模式
        LocalCluster localCluster = new LocalCluster();
        localCluster.submitTopology("MyWordCount",config,job);
    }
}

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