1.导入hadoop需要用到的包

hadoop-2.4.2/share/hadoop/mapreduce/*.jar

hadoop-2.4.2/share/hadoop/mapreduce/lib/*.jar

hadoop-2.4.2/share/hadoop/common/*.jar

hadoop-2.4.2/share/hadoop/common/lib/*.jar

2.编写java程序

package demo;

import java.io.IOException;

import java.util.*;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.*;

import org.apache.hadoop.mapred.*;

public class WordCount {

public static class Map extends MapReduceBase implements Mapper{

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

private Text word=new Text();

@Override

public void map(LongWritable key,  Text value,

OutputCollector output, Reporter reporter)

throws IOException {

// TODO Auto-generated method stub

String line=value.toString();

StringTokenizer tokenizer=new StringTokenizer(line);

while (tokenizer.hasMoreTokens()){

word.set(tokenizer.nextToken());

output.collect(word,one);

}

}

}

//旧版本

public static class Reduce extends MapReduceBase implements Reducer{

@Override

public void reduce(Text key, Iterator values,

OutputCollector output, Reporter reporter)

throws IOException {

// TODO Auto-generated method stub

int sum=0;

while(values.hasNext()){

sum+=values.next().get();

}

output.collect(key, new IntWritable(sum));

}

}

public static void main(String[] args) throws Exception{

// TODO Auto-generated method stub

//System.setProperty("HADOOP_USER_NAME","root");

JobConf conf=new JobConf(WordCount.class);

//conf.set("fs.defaultFS","hdfs://192.168.1.120:9000");

conf.setJobName("wordcount");

conf.setOutputKeyClass(Text.class);

conf.setOutputValueClass(IntWritable.class);

conf.setMapperClass(Map.class);

conf.setReducerClass(Reduce.class);

conf.setInputFormat(TextInputFormat.class);

conf.setOutputFormat(TextOutputFormat.class);

FileInputFormat.setInputPaths(conf,new Path(args[0]));

FileOutputFormat.setOutputPath(conf,new Path(args[1]));

JobClient.runJob(conf);

}

}

3.导出为jar文件

4.上传到linux系统中。

5.新建input目录，如果有output目录，先删除

6.上传jar包后，到jar包的目录下，执行

hadoop jar WordCount.jar demo.WordCount /input/* /output/

7.如果执行时不带“/”，会在hadoop目录中新建/user/root下新建两个文件夹，会提示

Exception in thread "main" org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: file:  /input  Exception in thread "main"

org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not

exist: hdfs://master:9000/user/root/input

只需要在执行的时候带上“/”就行。

8.获取分离后的文件

hadoop fs -get /output/* output/