Hadoop2.4.1 MapReduce通过Map端shuffle（Combiner）完成数据去重

package com.bank.service;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
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;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

/**
 * 将清洗后的数据通过Map端Shuffle（Job.setCombinerClass）去除重复值
 * @author mengyao
 *
 */
public class CnyDataFormatReplition extends Configured implements Tool {

    /**
     * Map端将行内容通过key输出到Reduce，这样会按照字典顺序对key进行排序，输出的value则为空，空值使用Hadoop提供的NullWritable类，该类是Hadoop的序列化后的类型
     * @author mengyao
     *
     */
    static class CnyDataFormatReplitionMapper extends Mapper<LongWritable, Text, Text, NullWritable> {
        @Override
        protected void map(LongWritable key, Text value, Context context)
                throws IOException, InterruptedException {
            context.write(value, NullWritable.get());
        }
    }

    /**
     * 在Map端Combiner后作为Reduce接收的key，Reduce端将key写入到HDFS，value则无需输出，使用NullWritable表示不输出
     * @author mengyao
     *
     */
    static class CnyDataFormatReplitionReduce extends Reducer<Text, NullWritable, Text, NullWritable> {
        @Override
        protected void reduce(Text key, Iterable<NullWritable> value, Context context)
                throws IOException, InterruptedException {
            context.write(key, NullWritable.get());        
        }
    }
    
    @Override
    public int run(String[] arg0) throws Exception {
        Job job = Job.getInstance(getConf(), CnyDataFormatReplition.class.getSimpleName());
        //指定运行作业类的主函数入口
        job.setJarByClass(CnyDataFormatReplition.class);
        
        FileInputFormat.setInputPaths(job, new Path(arg0[0]));
        job.setMapperClass(CnyDataFormatReplitionMapper.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(NullWritable.class);
        
        //在Map端进行shuffle，先写入缓冲区预排序（达到缓冲区默认100m后系统起后台线程spill到本地磁盘，写入磁盘前会进行二次快速排序），减少到Reduce的网络开销
        job.setCombinerClass(CnyDataFormatReplitionReduce.class);
        
        FileOutputFormat.setOutputPath(job, new Path(arg0[1]));
        job.setReducerClass(CnyDataFormatReplitionReduce.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(NullWritable.class);
        
        //提交作业并打印作业的进度详情，true打印，false为不打印
        return job.waitForCompletion(true) ? 0 : 1;
    }
    
    
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        String[] otherArgs = new GenericOptionsParser(conf,args).getRemainingArgs();
        if (otherArgs.length != 2) {
            System.err.println(" ERROR: <inputDir> <outputDir>");
            System.exit(2);
        }
        int status = ToolRunner.run(new CnyDataFormatReplition(), otherArgs);
        System.exit(status);
    }


}