<?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>com.player3</groupId>
<artifactId>storm-wordcount</artifactId>
<version>1.0-SNAPSHOT</version>
<dependencies>
<dependency>
<groupId>org.apache.storm</groupId>
<artifactId>storm-core</artifactId>
<version>1.1.0</version>
</dependency>
<dependency>
<groupId>commons-collections</groupId>
<artifactId>commons-collections</artifactId>
<version>3.2.1</version>
</dependency>
</dependencies>
<build>
<sourceDirectory>src/main/java</sourceDirectory>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<configuration>
<createDependencyReducedPom>true</createDependencyReducedPom>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.sf</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.dsa</exclude>
<exclude>META-INF/*.RSA</exclude>
<exclude>META-INF/*.rsa</exclude>
<exclude>META-INF/*.EC</exclude>
<exclude>META-INF/*.ec</exclude>
<exclude>META-INF/MSFTSIG.SF</exclude>
<exclude>META-INF/MSFTSIG.RSA</exclude>
</excludes>
</filter>
</filters>
</configuration>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<transformers>
<transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
</transformer>
</transformers>
</configuration>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.codehaus.mojo</groupId>
<artifactId>exec-maven-plugin</artifactId>
<version>1.2.1</version>
<executions>
<execution>
<goals>
<goal>exec</goal>
</goals>
</execution>
</executions>
<configuration>
<executable>java</executable>
<includeProjectDependencies>true</includeProjectDependencies>
<includePluginDependencies>false</includePluginDependencies>
<classpathScope>compile</classpathScope>
<mainClass>com.player3.storm.WordCountTopology</mainClass>
</configuration>
</plugin>
</plugins>
</build>
</project>
package com.player3.storm;
import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.StormSubmitter;
import org.apache.storm.spout.SpoutOutputCollector;
import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.TopologyBuilder;
import org.apache.storm.topology.base.BaseRichBolt;
import org.apache.storm.topology.base.BaseRichSpout;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;
import org.apache.storm.utils.Utils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.HashMap;
import java.util.Map;
import java.util.Random;
/**
* 单词计数拓扑
*
* 我认识很多java工程师，都是会一些大数据的技术的，不会太精通，没有那么多的时间去研究
* storm的课程，我就只是讲到，最基本的开发，就够了，java开发广告计费系统，大量的流量的引入和接入，就是用storm做得
* 用storm，主要是用它的成熟的稳定的易于扩容的分布式系统的特性
* java工程师，来说，做一些简单的storm开发，掌握到这个程度差不多就够了
*
* @author Administrator
*
*/
public class WordCountTopology {
/**
* spout
*
* spout，继承一个基类，实现接口，这个里面主要是负责从数据源获取数据
*
* 我们这里作为一个简化，就不从外部的数据源去获取数据了，只是自己内部不断发射一些句子
*
* @author Administrator
*
*/
public static class RandomSentenceSpout extends BaseRichSpout {
private static final long serialVersionUID = 3699352201538354417L;
private static final Logger LOGGER = LoggerFactory.getLogger(RandomSentenceSpout.class);
private SpoutOutputCollector collector;
private Random random;
/**
* open方法
*
* open方法，是对spout进行初始化的
*
* 比如说，创建一个线程池，或者创建一个数据库连接池，或者构造一个httpclient
*
*/
@SuppressWarnings("rawtypes")
public void open(Map conf, TopologyContext context,
SpoutOutputCollector collector) {
// 在open方法初始化的时候，会传入进来一个东西，叫做SpoutOutputCollector
// 这个SpoutOutputCollector就是用来发射数据出去的
this.collector = collector;
// 构造一个随机数生产对象
this.random = new Random();
}
/**
* nextTuple方法
*
* 这个spout类，之前说过，最终会运行在task中，某个worker进程的某个executor线程内部的某个task中
* 那个task会负责去不断的无限循环调用nextTuple()方法
* 只要的话呢，无限循环调用，可以不断发射最新的数据出去，形成一个数据流
*
*/
public void nextTuple() {
Utils.sleep(100);
String[] sentences = new String[]{"the cow jumped over the moon", "an apple a day keeps the doctor away",
"four score and seven years ago", "snow white and the seven dwarfs", "i am at two with nature"};
String sentence = sentences[random.nextInt(sentences.length)];
LOGGER.info("【发射句子】sentence=" + sentence);
// 这个values，你可以认为就是构建一个tuple
// tuple是最小的数据单位，无限个tuple组成的流就是一个stream
collector.emit(new Values(sentence));
}
/**
* declareOutputFielfs这个方法
*
* 很重要，这个方法是定义一个你发射出去的每个tuple中的每个field的名称是什么
*
*/
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("sentence"));
}
}
/**
* 写一个bolt，直接继承一个BaseRichBolt基类
*
* 实现里面的所有的方法即可，每个bolt代码，同样是发送到worker某个executor的task里面去运行
*
* @author Administrator
*
*/
public static class SplitSentence extends BaseRichBolt {
private static final long serialVersionUID = 6604009953652729483L;
private OutputCollector collector;
/**
* 对于bolt来说，第一个方法，就是prepare方法
*
* OutputCollector，这个也是Bolt的这个tuple的发射器
*
*/
@SuppressWarnings("rawtypes")
public void prepare(Map conf, TopologyContext context, OutputCollector collector) {
this.collector = collector;
}
/**
* execute方法
*
* 就是说，每次接收到一条数据后，就会交给这个executor方法来执行
*
*/
public void execute(Tuple tuple) {
String sentence = tuple.getStringByField("sentence");
String[] words = sentence.split(" ");
for(String word : words) {
collector.emit(new Values(word));
}
}
/**
* 定义发射出去的tuple，每个field的名称
*/
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("word"));
}
}
public static class WordCount extends BaseRichBolt {
private static final long serialVersionUID = 7208077706057284643L;
private static final Logger LOGGER = LoggerFactory.getLogger(WordCount.class);
private OutputCollector collector;
private Map<String, Long> wordCounts = new HashMap<String, Long>();
@SuppressWarnings("rawtypes")
public void prepare(Map conf, TopologyContext context, OutputCollector collector) {
this.collector = collector;
}
public void execute(Tuple tuple) {
String word = tuple.getStringByField("word");
Long count = wordCounts.get(word);
if(count == null) {
count = 0L;
}
count++;
wordCounts.put(word, count);
LOGGER.info("【单词计数】" + word + "出现的次数是" + count);
collector.emit(new Values(word, count));
}
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("word", "count"));
}
}
public static void main(String[] args) {
// 在main方法中，会去将spout和bolts组合起来，构建成一个拓扑
TopologyBuilder builder = new TopologyBuilder();
// 这里的第一个参数的意思，就是给这个spout设置一个名字
// 第二个参数的意思，就是创建一个spout的对象
// 第三个参数的意思，就是设置spout的executor有几个
builder.setSpout("RandomSentence", new RandomSentenceSpout(), 2);
builder.setBolt("SplitSentence", new SplitSentence(), 5)
.setNumTasks(10)
.shuffleGrouping("RandomSentence");
// 这个很重要，就是说，相同的单词，从SplitSentence发射出来时，一定会进入到下游的指定的同一个task中
// 只有这样子，才能准确的统计出每个单词的数量
// 比如你有个单词，hello，下游task1接收到3个hello，task2接收到2个hello
// 5个hello，全都进入一个task
builder.setBolt("WordCount", new WordCount(), 10)
.setNumTasks(20)
.fieldsGrouping("SplitSentence", new Fields("word"));
Config config = new Config();
// 说明是在命令行执行，打算提交到storm集群上去
if(args != null && args.length > 0) {
config.setNumWorkers(3);
try {
StormSubmitter.submitTopology(args[0], config, builder.createTopology());
} catch (Exception e) {
e.printStackTrace();
}
} else {
// 说明是在eclipse里面本地运行
config.setMaxTaskParallelism(20);
LocalCluster cluster = new LocalCluster();
cluster.submitTopology("WordCountTopology", config, builder.createTopology());
Utils.sleep(60000);
cluster.shutdown();
}
}
}