zoukankan html css js c++ java

Storm WordCount Topology学习

1，分布式单词计数的流程

首先要有数据源，在SentenceSpout中定义了一个字符串数组sentences来模拟数据源。字符串数组中的每句话作为一个tuple发射。其实，SplitBolt接收SentenceSpout发射的tuple，它将每句话分割成每个单词，并将每个单词作为tuple发射。再次，WordCountBolt接收SplitBolt发送的tuple，它将接收到的每一个单词统计计数，并将 <单词：出现次数> 作为tuple发射。最后，ReportBolt接收WordCountBolt发送的tuple，将统计的结果存入HashMap中，并打印出结果。

流程图如下：

2，Topology的组成类

ISpout、IComponent、IBolt三个接口定义了一些最基本的方法，BaseRichSpout、BaseRichBolt是接口的实现类，自定义的Spout与Bolt通过继承实现类来完成工作。

详细解释参考代码里面的注释。参考《Storm分布式实时计算模式》第一章中的例子。

1， SentenceSpou.java分析：

private String[] sentences = { "my dog has fleas", "i like cold beverages",
             "the dog ate my homework", "don't have a cow man",
             "i don't think i like fleas" };

定义了待发射的数据源。Spout从该字符串数组一次取一个字符串生成tuple进行发射。

32     public void open(@SuppressWarnings("rawtypes") Map conf,
33             TopologyContext context, SpoutOutputCollector collector) {
34         // TODO Auto-generated method stub
35         this.collector = collector;
36     }

open函数，在ISpout接口中定义，所有的Spout组件在初始化时调用这个方法。在open()中初始化了发射器。

55     public void declareOutputFields(OutputFieldsDeclarer declarer) {
56         // TODO Auto-generated method stub
57         declarer.declare(new Fields("sentence"));// 标记SentenceSpout发送的tuple的键为
58                                                     // sentence
59     }

declareOutputFields函数标记了该Spout发射的tuple的(字段值)键值。下游的Bolt可以通过该键值来接收它发出的tuple

41     public void nextTuple() {
42         // TODO Auto-generated method stub
43         // 以字符串数组sentences 中的每个字符串 作为参数 构造tuple
44         this.collector.emit(new Values(sentences[index]));// 通过emit方法将构造好的tuple发送出去
45         index++;
46         if (index >= sentences.length) {
47             index = 0;
48         }
49         Utils.sleep(100);
50     }

nextTuple()是所有Spout的核心方法。Storm通过调用这个方法向collector发射tuple。Values.java 继承了ArrayList，new Values(...)构造了一个List对象，并将之作为emit的参数通过collector发射出去。

这里的发射规则是：每次发射其中一个字符串，阻塞100ms。当发射完整个字符串数组时，将索引(index)重新置0。可以继续发射。除非显示终止Topology，否则它不会停止。

SentenceSpou.java代码如下：

 1 package org.apache.storm.storm_core;
 2 
 3 import java.util.Map;
 4 
 5 import backtype.storm.spout.SpoutOutputCollector;
 6 import backtype.storm.task.TopologyContext;
 7 import backtype.storm.topology.OutputFieldsDeclarer;
 8 import backtype.storm.topology.base.BaseRichSpout;
 9 import backtype.storm.tuple.Fields;
10 import backtype.storm.tuple.Values;
11 import backtype.storm.utils.Utils;
12 
13 public class SentenceSpout extends BaseRichSpout {
14     /**
15      * 
16      */
17     private static final long serialVersionUID = 3444934973982660864L;
18     private SpoutOutputCollector collector;// 用来向其他Spout发射tuple
19     private String[] sentences = { "my dog has fleas", "i like cold beverages",
20             "the dog ate my homework", "don't have a cow man",
21             "i don't think i like fleas" };
22 
23     private int index = 0;
24 
25     /*
26      * open() 方法在所有的Spout组件初始化时被调用
27      * 
28      * @param Map conf storm 配置信息
29      * 
30      * @context TopologyContext topology 组件信息
31      */
32     public void open(@SuppressWarnings("rawtypes") Map conf,
33             TopologyContext context, SpoutOutputCollector collector) {
34         // TODO Auto-generated method stub
35         this.collector = collector;
36     }
37 
38     /*
39      * Values.java extends ArrayList Storm 调用该方法向输出的collector发射tuple
40      */
41     public void nextTuple() {
42         // TODO Auto-generated method stub
43         // 以字符串数组sentences 中的每个字符串 作为参数 构造tuple
44         this.collector.emit(new Values(sentences[index]));// 通过emit方法将构造好的tuple发送出去
45         index++;
46         if (index >= sentences.length) {
47             index = 0;
48         }
49         Utils.sleep(100);
50     }
51 
52     /*
53      * SentenceSpout 发送的tuple它是一个包含键值对的List，该方法声明了List中包含的键值对的键为 sentence
54      */
55     public void declareOutputFields(OutputFieldsDeclarer declarer) {
56         // TODO Auto-generated method stub
57         declarer.declare(new Fields("sentence"));// 标记SentenceSpout发送的tuple的键为
58                                                     // sentence
59     }
60 }

SplitBolt.java代码如下：

 1 package org.apache.storm.storm_core;
 2 
 3 import java.util.Map;
 4 
 5 import backtype.storm.task.OutputCollector;
 6 import backtype.storm.task.TopologyContext;
 7 import backtype.storm.topology.OutputFieldsDeclarer;
 8 import backtype.storm.topology.base.BaseRichBolt;
 9 import backtype.storm.tuple.Fields;
10 import backtype.storm.tuple.Tuple;
11 import backtype.storm.tuple.Values;
12 
13 public class SplitSentenceBolt extends BaseRichBolt {
14     /**
15      * 
16      */
17     private static final long serialVersionUID = -2107029392155190729L;
18     private OutputCollector collector;// 用来向其他Spout发射tuple的发射器
19 
20     /*
21      * (non-Javadoc) prepare方法类似于open方法，prepare在bolt初始化时被调用
22      */
23     public void prepare(Map stormConf, TopologyContext context,
24             OutputCollector collector) {
25         // TODO Auto-generated method stub
26         this.collector = collector;// 发射器初始化
27 
28     }
29 
30     public void execute(Tuple input) {
31         // TODO Auto-generated method stub
32         // 接收从SentenceSpout的发射器发射过来的tuple,因为SentenceSpout中声明的tuple字段为sentence,故getStringByField方法的参数为sentence
33         String sentence = input.getStringByField("sentence");// 该tuple是一个包含
34                                                                 // 键为sentence
35                                                                 // 值为字符串
36                                                                 // 的列表List<Map<sentence,String>>
37         String[] words = sentence.split(" ");// 将字符串分解成一个个的单词
38         for (String word : words)
39             this.collector.emit(new Values(word));// 将每个单词构造成tuple并发送给下一个Spout
40     }
41 
42     public void declareOutputFields(OutputFieldsDeclarer declarer) {
43         // TODO Auto-generated method stub
44         declarer.declare(new Fields("word"));// 定义SplitSentenceBolt发送的tuple的字段("键值")为 word
45     }
46 }

WordCountBolt.java

 1 package org.apache.storm.storm_core;
 2 
 3 import java.util.HashMap;
 4 import java.util.Map;
 5 
 6 import backtype.storm.task.OutputCollector;
 7 import backtype.storm.task.TopologyContext;
 8 import backtype.storm.topology.OutputFieldsDeclarer;
 9 import backtype.storm.topology.base.BaseRichBolt;
10 import backtype.storm.tuple.Fields;
11 import backtype.storm.tuple.Tuple;
12 import backtype.storm.tuple.Values;
13 
14 public class WordCountBolt extends BaseRichBolt{
15 
16     private OutputCollector collector;
17     private HashMap<String, Long>counts = null;//统计每个单词出现的次数,放到HashMap中保存起来
18     
19     public void prepare(Map stormConf, TopologyContext context,
20             OutputCollector collector) {
21         // TODO Auto-generated method stub
22         this.collector = collector;
23         this.counts = new HashMap<String, Long>();//初始化HashMap,因为prepare会被自动调用的
24     }
25 
26     public void execute(Tuple input) {
27         // TODO Auto-generated method stub
28         String word = input.getStringByField("word");
29         Long count = this.counts.get(word);
30         if(count == null)//HashMap中没有word这个单词
31             count = 0L;
32         count++;
33         this.counts.put(word, count);//更新该单词在HashMap中的统计次数
34         //此处发射的tuple包含了两个元素:单词和计数，它每次发送的是一个长度为2的List，
35         //可理解为：List.add(new HashMap("word",word)); List.add(new HashMap(("count",count));
36         this.collector.emit(new Values(word, count));//第一个元素的键为 "word"，值为该单词(a string)，第二个键为 "count",值为单词的计数
37     }
38 
39     public void declareOutputFields(OutputFieldsDeclarer declarer) {
40         // TODO Auto-generated method stub
41         declarer.declare(new Fields("word", "count"));
42     }
43 }

ReportBolt.java如下：

package org.apache.storm.storm_core;

import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
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.Tuple;

public class ReportBolt extends BaseRichBolt{
/**
     * 
     */
    private static final long serialVersionUID = 4921144902730095910L;
    //    private OutputCollector collector; ReportBolt不需要发射tuple了
    private HashMap<String, Long> counts = null;
    
    public void prepare(Map stormConf, TopologyContext context,
            OutputCollector collector) {
        // TODO Auto-generated method stub
        this.counts = new HashMap<String, Long>();
    }

    public void execute(Tuple input) {
        // TODO Auto-generated method stub
        String word = input.getStringByField("word");
        Long count = input.getLongByField("count");
        this.counts.put(word, count);
    }

    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        // TODO Auto-generated method stub
        //不需要发出任何数据流
    }
    
    //Topology在storm集群中运行时，cleanup方法是不可靠的,并不能保证它一定会执行
    public void cleanup(){
        System.out.println("------ print counts ------");
        List<String> keys = new ArrayList<String>();
        keys.addAll(counts.keySet());//将HashMap中所有的键都添加到一个集合中
        Collections.sort(keys);//对键(单词)进行排序
        for(String key : keys)//输出排好序的每个单词的出现次数
            System.out.println(key + " : " + this.counts.get(key));
        System.out.println("--------bye----------");
    }
}

WordCountTopology.java如下：

 1 package org.apache.storm.storm_core;
 2 
 3 import backtype.storm.Config;
 4 import backtype.storm.LocalCluster;
 5 import backtype.storm.topology.TopologyBuilder;
 6 import backtype.storm.tuple.Fields;
 7 import backtype.storm.utils.Utils;
 8 
 9 public class WordCountTopology {
10     private static final String SENTENCE_SPOUT_ID = "sentence-spout";
11     private static final String SPLIT_BOLT_ID = "split-bolt";
12     private static final String COUNT_BOLT_ID = "count-bolt";
13     private static final String REPORT_BOLT_ID = "report-bolt";
14     private static final String TOPOLOGY_NAME = "word-count-topology";
15     
16     public static void main(String[] args) throws Exception{
17         SentenceSpout spout = new SentenceSpout();
18         SplitSentenceBolt splitBolt = new SplitSentenceBolt();
19         WordCountBolt countBolt = new WordCountBolt();
20         ReportBolt reportBolt = new ReportBolt();
21         
22         TopologyBuilder builder = new TopologyBuilder();
23         builder.setSpout(SENTENCE_SPOUT_ID, spout);
24         builder.setBolt(SPLIT_BOLT_ID, splitBolt).shuffleGrouping(SENTENCE_SPOUT_ID);
25         builder.setBolt(COUNT_BOLT_ID, countBolt).fieldsGrouping(SPLIT_BOLT_ID, new Fields("word"));
26         builder.setBolt(REPORT_BOLT_ID, reportBolt).globalGrouping(COUNT_BOLT_ID);
27         
28         Config config = new Config();
29         LocalCluster cluster = new LocalCluster();
30         
31         cluster.submitTopology(TOPOLOGY_NAME, config, builder.createTopology());
32         Utils.sleep(1000);
33         cluster.killTopology(TOPOLOGY_NAME);
34         cluster.shutdown();
35         
36     }
37 }

查看全文

相关阅读:
WebService出错 Maximum message size quota for incoming messages (65536) has been exceeded.已超过传入消息(65536)的最大消息大小配额
 php 获取系统时间
 JavaSctipt 控制网页前进，后退
 放A片的文件夹的名字
 玩玩独轮车
 3月18日周六骑行三水大旗头村——广东名镇之一
 叫春的猫
 抓紧锻炼身体噢！
使用Zend Framework中的 Zend_Pdf来创建pdf文档
 虚拟主机示例

原文地址：https://www.cnblogs.com/hapjin/p/4588413.html