mapreduce程序来实现分类

文件的内容例如以下所看到的：

5

45

8

876

6

45

要求最后的输出格式：

1    5

2    6

3    8

4    45

5    45

5    876

首先，这个题目是须要对文件的内容进行排序操作。我们都知道在mapper阶段是会对key进行排序的，我们就利用这个出发，把输入一行的数据转换成int，再把该int做mapper的key输出，而value的输出随便，我们这里输出1；然后在reduce阶段我们把mapper的key做为reduce的value输出，而key仅仅需定义一个全局的静态变量，每次输出自增就可以。

package cn.lmj.mapreduce;


import java.io.IOException;
import java.util.Iterator;


import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;


public class Sort
{
public static class SortMapper extends MapReduceBase implements
Mapper<Object, Text, IntWritable, IntWritable>
{
@Override
public void map(Object key, Text value,
OutputCollector<IntWritable, IntWritable> output,
Reporter reporter) throws IOException
{
String line = value.toString();
int i = Integer.parseInt(line.toString());
output.collect(new IntWritable(i), new IntWritable(1));
}
}


public static class SortReducer extends MapReduceBase implements
Reducer<IntWritable, IntWritable, IntWritable, IntWritable>
{

//必须是全局的静态变量，由于reduce的实例在开发中可能会有非常多个，必须让多个对象共享同一个变量
private static IntWritable linenum = new IntWritable(1);


@Override
public void reduce(IntWritable key, Iterator<IntWritable> values,
OutputCollector<IntWritable, IntWritable> output,
Reporter reporter) throws IOException
{
while (values.hasNext())
{
values.next();
output.collect(linenum, key);

//每次输出让linenum加1
linenum = new IntWritable(linenum.get() + 1);
}
}
}


public static void main(String[] args) throws Exception
{
JobConf conf = new JobConf(Sort.class);
conf.setJobName("cccccc");


conf.setOutputKeyClass(IntWritable.class);
conf.setOutputValueClass(IntWritable.class);


conf.setMapperClass(SortMapper.class);

//注意，这个题目不能够设置Combiner对mapper之后的数据进行预先合拼
conf.setReducerClass(SortReducer.class);


conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);


FileInputFormat.setInputPaths(conf, new Path("/zuoye/file1/"));
FileOutputFormat.setOutputPath(conf, new Path("/zuoye/file1/output"));


JobClient.runJob(conf);
}
}