MapReduce实例

1.WordCount（统计单词）

经典的运用MapReuce编程模型的实例

1.1 Description

给定一系列的单词/数据，输出每个单词/数据的数量

1.2 Sample

a is b is not c
b is a is not d

1.3 Output

a:2
b:2
c:1
d:1
is:4
not:2

1.4 Solution

/**
 *  Licensed 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 org.apache.hadoop.examples;

import java.io.File;
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 {
    
  //map输出的<key,value>为<输入的单词/数据,1>即<Text,IntWritable>
  public static class TokenizerMapper 
       extends Mapper<Object, Text, Text, IntWritable>{
    //value为封装好的int即IntWritable
    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());
      while (itr.hasMoreTokens()) {
        word.set(itr.nextToken());//word为每个单词/数据,以空格为分隔符识别
        context.write(word, one);
      }
    }
  }
  
  //reduce输入的<key,value>为<输入的单词/数据,各个值的1相加即sum(实际是一个list)>
  //即<Text,IntWrite>
  public static class IntSumReducer 
       extends Reducer<Text,IntWritable,Text,IntWritable> {  
    private IntWritable result = new IntWritable();

    public void reduce(Text key, Iterable<IntWritable> values, 
                       Context context
                       ) throws IOException, InterruptedException {
      int sum = 0;
      for (IntWritable val : values) {
        sum += val.get();
      }
      result.set(sum);
      context.write(key, result);
    }
  }

  public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
    if (otherArgs.length != 2) {
      System.err.println("Usage: wordcount <in> <out>");
      System.exit(2);
    }
    //删除已存在的输出文件夹
    judgeFileExist(otherArgs[1]);
    Job job = new Job(conf, "word count");
    job.setJarByClass(WordCount.class);
    job.setMapperClass(TokenizerMapper.class);
    job.setCombinerClass(IntSumReducer.class);
    job.setReducerClass(IntSumReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);
    FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
    FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
  
  //删除文件夹及其目录下的文件
  public static void judgeFileExist(String path){
      File file = new File(path);
      if( file.exists() ){
          deleteFileDir(file);
      }
  }
  
  public static void deleteFileDir(File path){
      if( path.isDirectory() ){
          String[] files = path.list();
          for( int i=0;i<files.length;i++ ){
              deleteFileDir( new File(path,files[i]) );
          }
      }
      path.delete();
  }
  
}

 

2. 数据去重

2.1 Description

针对给定一系列的数据去重并输出

2.2 Sample

3-1 a
3-2 b
3-3 c
3-4 d
3-5 a
3-6 b
3-7 c
3-3 c
3-1 b
3-2 a
3-3 b
3-4 d
3-5 a
3-6 c
3-7 d
3-3 c

2.3 Output

3-1 a
3-1 b
3-2 a
3-2 b
3-3 b
3-3 c
3-4 d
3-5 a
3-6 b
3-6 c
3-7 c
3-7 d

2.4 Solution

/**
 *  Licensed 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 org.apache.hadoop.examples;

import java.io.File;
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 {
    
 public static class Map extends Mapper<Object,Text,Text,Text>{//map最后一个指定Text
     public static Text lineWords= new Text();
     
     //map输出为<Text,Text>,因为只涉及到是否Key存在的问题，故value可任意
     public void map(Object key,Text value,Context context) 
             throws IOException, InterruptedException{
         lineWords = value;
         context.write(lineWords, new Text(""));//<Text,Text>
     }
 }
 
 public static class Reduce extends Reducer<Text,Text,Text,Text>{
     public void reduce(Text key,Iterable<Text> values,Context context) 
             throws IOException, InterruptedException{
         context.write(key,new Text(""));
     }
 }
 
 public static void main(String args[]) 
         throws IOException, ClassNotFoundException, InterruptedException{
     Configuration conf = new Configuration();
     
     String[] otherArgs = new GenericOptionsParser(conf,args).getRemainingArgs();
     if( otherArgs.length!=2 ){
         System.err.println("Usage: Data Deduplication <in> <out>");
         System.exit(2);
     }
     
     //删除已存在的输出文件夹
     judgeFileExist(otherArgs[1]);
     Job job = new Job(conf,"Data Dup");
     job.setJarByClass(WordCount.class);
     //设置map combine reduce处理类
     job.setMapperClass(Map.class);
     job.setCombinerClass(Reduce.class);
     job.setReducerClass(Reduce.class);
     //设置key value的类型
     job.setOutputKeyClass(Text.class);
     job.setOutputValueClass(Text.class);
     //设置输入和输出目录
     FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
     FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
     System.exit(job.waitForCompletion(true) ? 0 : 1);
 }
  
  //删除文件夹及其目录下的文件
  public static void judgeFileExist(String path){
      File file = new File(path);
      if( file.exists() ){
          deleteFileDir(file);
      }
  }
  
  public static void deleteFileDir(File path){
      if( path.isDirectory() ){
          String[] files = path.list();
          for( int i=0;i<files.length;i++ ){
              deleteFileDir( new File(path,files[i]) );
          }
      }
      path.delete();
  }
  
}

 

 

3. 数据排序

 3.1 Description

给多个文件的数据排序，每个文件中的每个数据占一行

3.2 Sample

1
12
31
123
21
31
12

3.3 Output

8       1
9       2
10      3
11      4
12      5
13      6
14      7

3.4 Solution

/**
 *  Licensed 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 org.apache.hadoop.example;

import java.io.File;
import java.io.IOException;

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 dataSort{
    
    public static class map extends Mapper<Object,Text,IntWritable,IntWritable>{
        private static IntWritable data = new IntWritable();
        String lineWords = new String();
        //map
        public void map(Object key,Text value,Context context) 
                throws IOException, InterruptedException{
            lineWords = value.toString();
            data.set(Integer.parseInt(lineWords));
            context.write(data,new IntWritable(1));
        }
    }
    
    public static class reduce extends Reducer<IntWritable, IntWritable,IntWritable,IntWritable>{
        private static IntWritable lineNum = new IntWritable(1);
        public void reduce(IntWritable key,Iterable<IntWritable> values,Context context) 
                throws IOException, InterruptedException{
            for(IntWritable val:values){
                context.write(lineNum,key);
                lineNum = new IntWritable(lineNum.get()+1);
            }
        }
    }
    
    public static void main(String args[]) 
            throws IOException, ClassNotFoundException, InterruptedException{
        Configuration conf = new Configuration();
         
         String[] otherArgs = new GenericOptionsParser(conf,args).getRemainingArgs();
         if( otherArgs.length!=2 ){
             System.err.println("Usage: Data Deduplication <in> <out>");
             System.exit(2);
         }
         
         //删除已存在的输出文件夹
         judgeFileExist(otherArgs[1]);
         Job job = new Job(conf,"Data Dup");
         job.setJarByClass(dataSort.class);
         //设置map combine reduce处理类
         job.setMapperClass(map.class);
         job.setCombinerClass(reduce.class);
         job.setReducerClass(reduce.class);
         //设置key value的类型
         job.setOutputKeyClass(IntWritable.class);
         job.setOutputValueClass(IntWritable.class);
         //设置输入和输出目录
         FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
         FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
         System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
    //删除文件夹及其目录下的文件
      public static void judgeFileExist(String path){
          File file = new File(path);
          if( file.exists() ){
              deleteFileDir(file);
          }
      }
      
      public static void deleteFileDir(File path){
          if( path.isDirectory() ){
              String[] files = path.list();
              for( int i=0;i<files.length;i++ ){
                  deleteFileDir( new File(path,files[i]) );
              }
          }
          path.delete();
      }
}