MapReduce编程实例：
MapReduce编程实例（一）,详细介绍在集成环境中运行第一个MapReduce程序 WordCount及代码分析
MapReduce编程实例（五），MapReduce实现单表关联
排序，比较简单，上代码，代码中有注释，欢迎交流。
总体是利用MapReduce本身对Key进行排序的特性和按key值有序的分配到不同的partition。Mapreduce默认会对每个reduce按text类型key按字母顺序排序，对intwritable类型按大小进行排序。
输入：
2013-11-01 aa
2013-11-02 bb
2013-11-03 cc
2013-11-04 aa
2013-11-05 dd
2013-11-06 dd
2013-11-07 aa
2013-11-09 cc
2013-11-10 ee
2013-11-01 bb
2013-11-02 33
2013-11-03 cc
2013-11-04 bb
2013-11-05 23
2013-11-06 dd
2013-11-07 99
2013-11-09 99
2013-11-10 ee
数据重复，map中每一行做为一个key，value值任意，经过shuffle之后输入到reduce中利用key的唯一性直接输出key
代码太简单，不解释，上代码：
package com.t.hadoop;
import java.io.IOException;
import java.util.HashSet;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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;
/**
* 数据去重
* @author daT dev.tao@gmail.com
*
*/
public class Dedup {
public static class MyMapper extends Mapper<Object, Text, Text, Text>{
@Override
protected void map(Object key, Text value, Context context)
throws IOException, InterruptedException {
context.write(value, new Text(""));
}
}
public static class MyReducer extends Reducer<Text, Text, Text, Text>{
@Override
protected void reduce(Text key, Iterable<Text> value,
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.out.println("parameter errors!");
System.exit(2);
}
Job job = new org.apache.hadoop.mapreduce.Job(conf, "Dedup");
job.setJarByClass(Dedup.class);
job.setMapperClass(MyMapper.class);
job.setCombinerClass(MyReducer.class);
job.setReducerClass(MyReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true)?0:1);
}
}
输出结果
2013-11-01 aa
2013-11-01 bb
2013-11-02 33
2013-11-02 bb
2013-11-03 cc
2013-11-03 cc
2013-11-04 98
2013-11-04 aa
2013-11-04 bb
2013-11-05 23
2013-11-05 93
2013-11-05 dd
2013-11-06 99
2013-11-06 dd
2013-11-07 92
2013-11-07 99
2013-11-07 aa
2013-11-09 99
2013-11-09 aa
2013-11-09 cc
2013-11-10 ee