Hadop案例之WordCount

 

代码如下：

package hadopp_wordCount;

 

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.LongWritable;

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

   public static class Map extends Mapper<LongWritable, Text, Text, IntWritable>

   {

     private static final IntWritable one =new IntWritable(1);

     private Text word = new Text();

    

     @Override

     protected void map(LongWritable key, Textvalue, Contextcontext)

          throwsIOException, InterruptedException {

        StringTokenizer iter = new StringTokenizer(value.toString());

        while (iter.hasMoreTokens()) {

         

          word.set(iter.nextToken());

          context.write(word,one);

         

        }

     }

   }

  

   //reduce

   public static class reduce extends Reducer<Text, IntWritable, Text, IntWritable>

   {

     private IntWritable result = new IntWritable();

     @Override

     protected void reduce(Text key,Iterable<IntWritable>value,

          Contextcont) throwsIOException, InterruptedException {

        int sum = 0;

        for (IntWritablei : value) {

          sum += i.get();

        }

        result.set(sum);

        cont.write(key,result);

     }

   }

  

   //main

   public static void main(Stringargs[]) throwsException

   {

     Configuration conf =new Configuration();

     String[] otherArgs =new GenericOptionsParser(conf,args).getRemainingArgs();

     if (otherArgs.length <2) {

        System.out.println("Usage:wordcount <in> [<in>...] <out>");

        System.exit(2);

     }

    

     Job job =new Job(conf,"wordCount");

     job.setJarByClass(WordCount.class);

     job.setMapperClass(Map.class);

     job.setCombinerClass(reduce.class);

     job.setReducerClass(reduce.class);

     job.setOutputKeyClass(Text.class);

     job.setOutputValueClass(IntWritable.class);

    

     for(inti = 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);

         

   }

  

  

}

 

 

代码比较简单，网上也有很多介绍，本文不再详细描述。

需要注意的一点是命名空间问题：

如果按照如下方式执行WordCount，会报错：

root@node1:/usr/local/hadoop/hadoop-2.5.2/myJar#hadoop jar WordCount.jar WordCount  /usr/local/hadooptempdata/input/wc/usr/local/hadooptempdata/output/wc

Exception in thread "main"java.lang.ClassNotFoundException: WordCount

         atjava.net.URLClassLoader.findClass(URLClassLoader.java:381)

         atjava.lang.ClassLoader.loadClass(ClassLoader.java:424)

         atjava.lang.ClassLoader.loadClass(ClassLoader.java:357)

         atjava.lang.Class.forName0(Native Method)

         atjava.lang.Class.forName(Class.java:348)

         atorg.apache.hadoop.util.RunJar.main(RunJar.java:205)

 

原因是默认命名空间问题，本文中使用的包是package hadopp_wordCount;

按照如下方式执行就没问题：

hadoop jar WordCount.jarhadopp_wordCount.WordCount /usr/local/hadooptempdata/input/wc    /usr/local/hadooptempdata/output/wc