java写hadoop全局排序

发布时间:2019-05-01 | 分类:Hadoop

标签: map-reduce 全局排序demo

前言:

一直不会用java,都是streaming的方式用C或者python写mapper或者reducer的可执行程序。但是有些情况,如全排序等等用streaming的方式往往不好处理,于是乎用原生语言来写map-reduce;

开发环境eclipse,windows,把hadoop相关的jar附加到程序中,打包后放回linux虚机执行;

输入数据

 1 haha    10
  2 haha    9
  3 haha    100
  4 haha    1
  5 haha    1
  6 haha    2
  7 haha    3
  8 haha    1000
  9 haha    1000
 10 haha    999
 11 haha    888
 12 haha    10000

输出数据 cat part*-*>o.txt

1 haha    1                                                                                                        
  2 haha    1
  3 haha    2
  4 haha    3
  5 haha    9
  6 haha    10
  7 haha    100
  8 haha    888
  9 haha    999
10 haha    1000
11 haha    1000
12 haha    10000

代码 MyMapper

package com.globalsort;
import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
 

public class MyMapper extends
 
   Mapper<LongWritable, Text, LongWritable, Text> {
 
        @Override
        protected void map(LongWritable  key, Text value, Context context)
                        throws IOException, InterruptedException {
        		String temp=value.toString();
        		String[] segs = temp.split("\t"); 
        		if (segs.length!=2)
        		{
        			return;
        		}
        		int newval = Integer.parseInt(segs[1]);
                context.write(new LongWritable(newval),
                                new Text(segs[0]));
 

        }
 

}

重写reducer

 

package com.globalsort;

import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.util.Iterator;  

public class MyReducer extends
 
                Reducer<LongWritable, Text,Text,LongWritable > {

        @Override
 
        protected void reduce(LongWritable key, Iterable<Text> values,
 
                        Context context) throws IOException, InterruptedException {
 
        	Iterator<Text> it = values.iterator(); 
        	while (it.hasNext()) 
        	{
        		String data = it.next().toString();
                context.write(new Text(data),key);
 
        	}
        }
 

}

 重写patitioner

package com.globalsort;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Partitioner;
public class MyPartitioner extends Partitioner<LongWritable, Text> {
 

        @Override
 
        public int getPartition(LongWritable key, Text value, int numPartitions) {
                long tmp = key.get();
                if (tmp <= 100) { 
                        return 0 % numPartitions;
 
                } else if (tmp <= 1000) { 
                        return 1 % numPartitions;
 
                } else {
                        return 2 % numPartitions;
 
                }  
 
        }
       
 

}

  runer

 

package com.globalsort;
 
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.compress.CompressionCodec;
import org.apache.hadoop.io.compress.GzipCodec;
import org.apache.hadoop.mapreduce.Job;
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;

import java.io.IOException;  

public class GlobalSortMain implements Tool {
	
	private Configuration conf;
	
	@Override 
	public Configuration getConf() {
		return conf;
	}
	
    @Override
    public void setConf (Configuration conf){
    	this.conf=conf;
    }
    @Override
    public int run(String[] args) throws Exception {
    	String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
    	if (otherArgs.length != 3) {                                                    
    		 System.err.println("Usage:  must contain <in> <out>");  
    	 }
    		Job job = configureJob(otherArgs);
    	 return (job.waitForCompletion(true) ? 0 : 1);
    }
    
    private Job configureJob(String[] args) throws IOException {
    	
    	conf.set("mapred.job.priority", "VERY_HIGH");
    //	conf.setBoolean("mapred.compress.map.output", true);
    	//conf.setClass("mapred.map.output.compression.codec", GzipCodec.class, CompressionCodec.class);
     //	conf.setBoolean("mapred.compress.reduce.output", true);
    	//conf.setClass("mapred.reduce.output.compression.codec", GzipCodec.class, CompressionCodec.class);
        Job job = new Job(conf, "global sort liuyu");
        job.setJarByClass(GlobalSortMain.class);
        job.setMapperClass(MyMapper.class);
        job.setReducerClass(MyReducer.class);
        job.setPartitionerClass(MyPartitioner.class);
        job.setNumReduceTasks(3);
        job.setMapOutputKeyClass(LongWritable.class);
        job.setMapOutputValueClass(Text.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);
        FileInputFormat.addInputPath(job, new Path(args[1]));
        FileOutputFormat.setOutputPath(job, new Path(args[2]));  
    	return job;
    }
    

        public static void main(String[] args) throws Exception {
 
                Configuration conf = new Configuration();
                ToolRunner.run(conf, new GlobalSortMain(), args);
        }
 
}

  

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