Storm之WordCount初探

　　刚接触Strom，记录下执行过程

1、pom.xml

<?xml version="1.0" encoding="UTF-8"?>

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
  <modelVersion>4.0.0</modelVersion>

  <groupId>org.toda.demo</groupId>
  <artifactId>demo</artifactId>
  <version>1.0-SNAPSHOT</version>

  <name>demo</name>
  <!-- FIXME change it to the project's website -->
  <url>http://www.example.com</url>

  <properties>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <maven.compiler.source>1.7</maven.compiler.source>
    <maven.compiler.target>1.7</maven.compiler.target>
  </properties>

  <dependencies>
    <dependency>
      <groupId>junit</groupId>
      <artifactId>junit</artifactId>
      <version>4.11</version>
      <scope>test</scope>
    </dependency>

    <dependency>
      <groupId>org.apache.storm</groupId>
      <artifactId>storm-core</artifactId>
      <version>0.9.6</version>
     <!-- <scope>provided</scope>-->
    </dependency>

    <dependency>
      <groupId>org.apache.thrift</groupId>
      <artifactId>libthrift</artifactId>
      <version>0.9.3</version>
    </dependency>
  </dependencies>

  <build>
    <pluginManagement><!-- lock down plugins versions to avoid using Maven defaults (may be moved to parent pom) -->
      <plugins>
        <!-- clean lifecycle, see https://maven.apache.org/ref/current/maven-core/lifecycles.html#clean_Lifecycle -->
        <plugin>
          <artifactId>maven-clean-plugin</artifactId>
          <version>3.1.0</version>
        </plugin>
        <!-- default lifecycle, jar packaging: see https://maven.apache.org/ref/current/maven-core/default-bindings.html#Plugin_bindings_for_jar_packaging -->
        <plugin>
          <artifactId>maven-resources-plugin</artifactId>
          <version>3.0.2</version>
        </plugin>
        <plugin>
          <artifactId>maven-compiler-plugin</artifactId>
          <version>3.8.0</version>
        </plugin>
        <plugin>
          <artifactId>maven-surefire-plugin</artifactId>
          <version>2.22.1</version>
        </plugin>
        <plugin>
          <artifactId>maven-jar-plugin</artifactId>
          <version>3.0.2</version>
        </plugin>
        <plugin>
          <artifactId>maven-install-plugin</artifactId>
          <version>2.5.2</version>
        </plugin>
        <plugin>
          <artifactId>maven-deploy-plugin</artifactId>
          <version>2.8.2</version>
        </plugin>
        <!-- site lifecycle, see https://maven.apache.org/ref/current/maven-core/lifecycles.html#site_Lifecycle -->
        <plugin>
          <artifactId>maven-site-plugin</artifactId>
          <version>3.7.1</version>
        </plugin>
        <plugin>
          <artifactId>maven-project-info-reports-plugin</artifactId>
          <version>3.0.0</version>
        </plugin>
      </plugins>
    </pluginManagement>
  </build>
</project>

2、WordCountSpout.java文件

package org.toda.demo.wordcout;

import java.util.Map;
import java.util.Random;
import backtype.storm.spout.SpoutOutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseRichSpout;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Values;
import backtype.storm.utils.Utils;
//执行顺序：open() --> nextTuple() -->declareOutputFields()
public class WordCountSpout extends BaseRichSpout {
    private Map map;
    private TopologyContext context;
    private SpoutOutputCollector collector;

    String text[]={
            "你好 谢谢 再见",
            "哈哈 再见 吃饭",
            "再见 你好 睡觉",
            "上班 谢谢 辛苦",
            "开心"
    };
    Random random=new Random();
    @Override
    public void nextTuple() {
        Values line = new Values(text[random.nextInt(text.length)]);
        //发送tuple消息,并返回起发送任务的task的序列号集合
        collector.emit(line);
        Utils.sleep(1000);
        System.err.println("splot-----     emit-------   "+line);
    }

    @Override
    public void open(Map map, TopologyContext context, SpoutOutputCollector collector) {
        //数据初始化
        this.map=map;
        this.context=context;
        this.collector=collector;
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        //定义元组中变量结构的名字
        declarer.declare(new Fields("newFields"));
    }
}

3\WordCountBolt.java文件

package org.toda.demo.wordcout;

import java.util.List;
import java.util.Map;

import backtype.storm.task.OutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseRichBolt;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values;
//执行顺序： prepare() -->  execute() --> declareOutputFields()
public class WordCountBolt extends BaseRichBolt {
    private OutputCollector collector;

    @Override
    public void execute(Tuple input) {
        //随机获取单行数据,
        //String line = input.getString(0);
        //也可以用下面的代码通过field获取，这里0是返回这个String的0号位置
        String line=input.getStringByField("newFields");
        //切分字符串单词
        String[] words = line.split(" ");
        //向后发送tuple
        for(String word : words){
            List w=new Values(word);
            collector.emit(w);
        }
    }

    @Override
    public void prepare(Map stormConf, TopologyContext context, OutputCollector collector) {
        //数据初始化
        this.collector=collector;
    }

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

}

4\WordFinalBolt.java文件

package org.toda.demo.wordcout;

import java.util.HashMap;
import java.util.Map;
import backtype.storm.task.OutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseRichBolt;
import backtype.storm.tuple.Tuple;

public class WordFinalBolt extends BaseRichBolt {
    private OutputCollector collector;
    Map<String, Integer> map=new HashMap<String,Integer>();

    @Override
    public void prepare(Map stormConf, TopologyContext context, OutputCollector collector){
        this.collector=collector;
    }

    @Override
    public void execute(Tuple input) {
        int count =1;
        //获取切分后的每一个单词
        String word = input.getStringByField("word");
        if(map.containsKey(word)) {
            count=(int) map.get(word)+1;
        }
        map.put(word, count);
        //输出
        System.err.println(word+"============="+count);
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {
    }

}

5、Test.java文件(main函数)

package org.toda.demo.wordcout;

import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.tuple.Fields;

public class Test {

    public static void main(String[] args) {
                //创建一个拓扑
                TopologyBuilder tb=new TopologyBuilder();
                //拓扑设置 喷嘴以及个数
                tb.setSpout("ws", new WordCountSpout());
                //拓扑设置 Bolt以及个数,shuffleGrouping表示随机分组
                tb.setBolt("wordcountbolt", new WordCountBolt(),3).shuffleGrouping("ws");
                //fieldsGrouping表示按照字段分组，即是同一个单词只能发送给一个Bolt
                tb.setBolt("wc", new WordFinalBolt(),3).fieldsGrouping("wordcountbolt",new Fields("word") );
                //本地模式,测试
                LocalCluster localCluster = new LocalCluster();
                localCluster.submitTopology("wordconut",new Config(), tb.createTopology());
            }
}

总结：

　　从代码可看出，Spout是将数据源封装成Tuple,而Bolt主要是对Tuple进行逻辑处理，可以有多个Bolt执行，最后一个Bolt是最后所需数据。

执行过程：