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  • 【hadoop】看懂WordCount例子

    前言:今天刚开始看到map和reduce类里面的内容时,说实话一片迷茫,who are you?,最后实在没办法,上B站看别人的解说视频,再加上自己去网上查java的包的解释,终于把WordCount例子看懂,准备后面自己写一遍!实话说,现在实在肝不动了,每天只有晚上有点时间来学习,代码贴上来,睡觉!

    正文:实在不想写太多,解释都在代码的注释里面,饶了我吧!

    贴一个讲的比较好的网址:https://www.cnblogs.com/houji/p/7161468.html

    代码如下:

    /**
     * Licensed to the Apache Software Foundation (ASF) under one
     * or more contributor license agreements.  See the NOTICE file
     * distributed with this work for additional information
     * regarding copyright ownership.  The ASF licenses this file
     * to you under the Apache License, Version 2.0 (the
     * "License"); you may not use this file except in compliance
     * with the License.  You may obtain a copy of the License at
     *
     *     http://www.apache.org/licenses/LICENSE-2.0
     *
     * Unless required by applicable law or agreed to in writing, software
     * distributed under the License is distributed on an "AS IS" BASIS,
     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     * See the License for the specific language governing permissions and
     * limitations under the License.
     */
    package com.hadoop;
    
    import java.io.IOException;
    import java.util.StringTokenizer;
    
    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.io.IntWritable;
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Job;
    import org.apache.hadoop.mapreduce.Mapper;
    import org.apache.hadoop.mapreduce.Reducer;
    import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
    import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
    import org.apache.hadoop.util.GenericOptionsParser;
    
    public class WordCount {//WordCount是类名,要用public class进行修饰,java程序由类(class)组成,一个源文件可以包含多个类
    
      public static class TokenizerMapper 
           extends Mapper<Object, Text, Text, IntWritable>{
    /***
                   Mapper<KEYIN, VALUEIN, KEYOUT, VALUEOUT>
                          行偏移量 输入值  输出key  输出值
    ***/
        
        private final static IntWritable one = new IntWritable(1);
        private Text word = new Text();
          
        public void map(Object key, Text value, Context context
                        ) throws IOException, InterruptedException {
          StringTokenizer itr = new StringTokenizer(value.toString());//value.toString()获取输入值,并用StringTokenizer进行分隔(默认空格)
          while (itr.hasMoreTokens()) { //判断itr是否还有字符串,返回true或false
            word.set(itr.nextToken()); //set方法给word赋值,nextToken()返回下一个标记
            context.write(word, one);//输出<'word',1>
          }
        }
      }
      
      public static class IntSumReducer 
           extends Reducer<Text,IntWritable,Text,IntWritable> {
        private IntWritable result = new IntWritable();
    
        public void reduce(Text key, Iterable<IntWritable> values,  //values 里面存储着map输出数据,格式为 'word list<1,1,1,1,1>'
                           Context context
                           ) throws IOException, InterruptedException {
    
          int sum = 0;//自定义一个计数器
          for (IntWritable val : values) { //循环list里面的值
            sum += val.get();//求和
          }
          result.set(sum);//赋值给result
          context.write(key, result);
        }
      }
    
      public static void main(String[] args) throws Exception { //1、Java程序的入口,public static void main(String[] args){}是固定用法,public static void都是关键字。2、throws:声明一个异常可能被抛出
        /*** 
        Create a new Job
        ***/
        Configuration conf = new Configuration();  //实例化Configuration,读取Hadoop配置信息
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs(); //读取Hadoop的argument填入地址信息  
        if (otherArgs.length < 2) {//若填入的地址小于2,报错并输出"Usage: wordcount <in> [<in>...] <out>"
          System.err.println("Usage: wordcount <in> [<in>...] <out>");
          System.exit(2);
        }
        Job job = Job.getInstance(conf, "word count");//单例模式getInstance(),在主函数开始时调用,返回一个实例化对象,此对象是static的,在内存中保留着它的引用
        job.setJarByClass(WordCount.class);
        //设置Job处理的Map(拆分)、Combiner(中间结果合并)以及Reduce(合并)的相关处理类
        job.setMapperClass(TokenizerMapper.class);
        job.setCombinerClass(IntSumReducer.class);
        job.setReducerClass(IntSumReducer.class);
        //设置job输出结果<key,value>的中key和value数据类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        /***
        调用addInputPath()和setOutputPath()设置输入输出路径置
        InputFormat()方法是用来生成可供map处理的<key,value>对的
        ***/
        for (int i = 0; i < otherArgs.length - 1; ++i) {
          FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
        }
        FileOutputFormat.setOutputPath(job,
          new Path(otherArgs[otherArgs.length - 1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1); //运行job
      }
    }
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  • 原文地址:https://www.cnblogs.com/CQ-LQJ/p/11504072.html
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