Hadoop示例程序之单词统计MapReduce

在eclipse下新建一个map/reduce Project

1,新建文件MyMap.java

import java.io.IOException; 
import java.util.StringTokenizer; 
 
import org.apache.Hadoop.io.IntWritable; 
import org.apache.hadoop.io.Text; 
import org.apache.hadoop.mapreduce.Mapper; 
 
public class MyMap extends Mapper<Object, Text, Text, IntWritable> { 
    private final static IntWritable one = new IntWritable(1); 
 
    private Text word; 
 
    public void map(Object key, Text value, Context context) 
            throws IOException, InterruptedException { 
 
        String line = value.toString(); 
        StringTokenizer tokenizer = new StringTokenizer(line); 
        while (tokenizer.hasMoreTokens()) { 
            word = new Text(); 
            word.set(tokenizer.nextToken()); 
            context.write(word, one); 
        } 
    } 
} 

2，新建文件MyReduce.java:

import java.io.IOException; 
 
import org.apache.hadoop.io.IntWritable; 
import org.apache.hadoop.io.Text; 
import org.apache.hadoop.mapreduce.Reducer; 
 
public class MyReduce extends 
        Reducer<Text, IntWritable, Text, IntWritable> { 
    public void reduce(Text key, Iterable<IntWritable> values, Context context) 
            throws IOException, InterruptedException { 
        int sum = 0; 
        for (IntWritable val : values) { 
            sum += val.get(); 
        } 
        context.write(key, new IntWritable(sum)); 
    } 
} 

3，新建一个文件MyDriver.java

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.lib.input.FileInputFormat; 
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; 
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; 
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat; 
 
public class MyDriver { 
 
     
    public static void main(String[] args) throws Exception,InterruptedException { 
        Configuration conf=new Configuration(); 
         
      Job job=new Job(conf,"Hello Hadoop World"); 
       
      job.setJarByClass(MyDriver.class);         
       
      job.setMapOutputKeyClass(Text.class);     
      job.setMapOutputValueClass(IntWritable.class); 
       
      job.setOutputKeyClass(Text.class); 
      job.setOutputValueClass(IntWritable.class); 
       
      job.setMapperClass(MyMap.class); 
        job.setCombinerClass(MyReduce.class); 
        job.setReducerClass(MyReduce.class); 
         
        job.setInputFormatClass(TextInputFormat.class);           
        job.setOutputFormatClass(TextOutputFormat.class);         
         
        FileInputFormat.setInputPaths(job, new Path("./input/555.txt")); 
         
        FileOutputFormat.setOutputPath(job, new Path("./input/out.txt")); 

      job.waitForCompletion(true); 
      } 
 
} 
好了，见证奇迹的时刻到了，先在工程目录下创建一个目录input,并在下面新建文件555.txt,

Hello World 555  hahaha

Hello World

保存，运行java应用程序

在input下多了个文件目录:out.txt，该目录下有个文件part-r-0000文件，

打开后文件的内容是：

555    1
Hello    2
World    2
hahaha    1

算是搞定了。。。

运行中碰到包错：

org.apache.hadoop.fs.ChecksumException: Checksum error:

这个好办 只要将工程文件下的CRC数据校验文件删除就可以了