hadoop sort 自定义排序(三个数比较写法)

0 目的:

将文件,第一列相同时,第二列升序;第二列相同时,第三列升序

3,3,3
3,2,4
3,2,0
2,2,1
2,1,4
1,1,0

mapreduce中:

1.在map和reduce阶段进行排序时,比较的是k2。v2是不参与排序比较的。如果要想让v2也进行排序,需要把k2和v2组装成新的类,作为k2,才能参与比较。
 
2.分组时也是按照k2进行比较的。
 

1 代码: 核心就是将 hadoop map output的key自定义,里面写好比较写法

package sort;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.net.URI;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
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.io.WritableComparable;
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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

public class MyThreeSortApp {
	
	// 0 定义操作地址
	static final String FILE_ROOT = "hdfs://master:9000/";
	static final String INPUT_PATH = "hdfs://master:9000/hello";
	static final String OUT_PATH = "hdfs://master:9000/out";

	/**
	 * @param args
	 */
	public static void main(String[] args) throws Exception{
			
			Configuration conf = new Configuration();
			FileSystem fileSystem = FileSystem.get(new URI(FILE_ROOT),conf);
			Path outpath = new Path(OUT_PATH);
			if(fileSystem.exists(outpath)){
				fileSystem.delete(outpath, true);
			}
			
			// 0 定义干活的人
			Job job = new Job(conf);
			// 1.1 告诉干活的人 输入流位置     读取hdfs中的文件。每一行解析成一个<k,v>。每一个键值对调用一次map函数
			FileInputFormat.setInputPaths(job, INPUT_PATH);
			// 指定如何对输入文件进行格式化,把输入文件每一行解析成键值对
			job.setInputFormatClass(TextInputFormat.class); //用户在启动MapReduce的时候需要指定一个InputFormat的implement
			
			//1.2 指定自定义的map类
			job.setMapperClass(MyMapper3.class);
			job.setMapOutputKeyClass(NewKey3.class);
			job.setMapOutputValueClass(NullWritable.class);
			
			
			//1.3 分区
			job.setNumReduceTasks(1);
			
			//1.4 TODO 分组    目前按照默认方式执行
			//1.5 TODO 规约
			
			//2.2 指定自定义reduce类
			job.setReducerClass(MyReducer3.class);
			job.setOutputKeyClass(Text.class);
			job.setOutputValueClass(NullWritable.class);
			
			//2.3 指定写出到哪里
			FileOutputFormat.setOutputPath(job, outpath);
			job.setOutputFormatClass(TextOutputFormat.class);
			
			// 让干活的人干活
			job.waitForCompletion(true);
			
		}
}

class MyMapper3 extends Mapper<LongWritable, Text, NewKey3, NullWritable>{

	
	@Override
	protected void map(LongWritable k1, Text v1, Context context)throws IOException, InterruptedException {
		String lineStr = v1.toString();
		System.out.println("map the line: " + lineStr);
		String[] split = lineStr.split(",");
		NewKey3 newKey3 = new NewKey3(Long.parseLong(split[0]),Long.parseLong(split[1]),Long.parseLong(split[2]));
		context.write(newKey3, NullWritable.get());
	}
	
}

class MyReducer3 extends Reducer<NewKey3, NullWritable, Text, NullWritable>{

	protected void reduce(NewKey3 k2, Iterable<NullWritable> v2s, org.apache.hadoop.mapreduce.Reducer.Context context)
			throws IOException, InterruptedException {
		System.out.println("reduce the key is: " + k2.toString());
		context.write(new Text(k2.toString()), NullWritable.get());
	}

	
	
}


// 核心就是将 hadoop map output的key自定义,里面写好比较写法
class NewKey3 implements WritableComparable<NewKey3>{
	
	private long first;
	private long second;
	private long third;
	
	public NewKey3(){}
	
	public NewKey3(long first,long second,long third){
		this.first = first;
		this.second = second;
		this.third = third;
	}
	
	@Override
	public int hashCode() {
		final int prime = 31;
		int result = 1;
		result = prime * result + (int) (first ^ (first >>> 32));
		result = prime * result + (int) (second ^ (second >>> 32));
		result = prime * result + (int) (third ^ (third >>> 32));
		return result;
	}

	@Override
	public boolean equals(Object obj) {
		if (this == obj)
			return true;
		if (obj == null)
			return false;
		if (getClass() != obj.getClass())
			return false;
		NewKey3 other = (NewKey3) obj;
		if (first != other.first)
			return false;
		if (second != other.second)
			return false;
		if (third != other.third)
			return false;
		return true;
	}

	@Override
	public String toString() {
		return first + " " + second + " " + third ;
	}

	@Override
	public void write(DataOutput out) throws IOException {
		out.writeLong(this.first);
		out.writeLong(this.second);
		out.writeLong(this.third);
	}

	@Override
	public void readFields(DataInput in) throws IOException {
		this.first = in.readLong();
		this.second = in.readLong();
		this.third = in.readLong();
	}

	@Override
	public int compareTo(NewKey3 other) {
		long result;
		result = this.first - other.first;
		if(result == 0){
			result = this.second - other.second;
			if(result == 0){
				result = this.third - other.third;
			}
		}
		return (int)result;
	}
	
}

2 运行结果:

[root@master local]# hadoop fs -text /out/part-r-00000
Warning: $HADOOP_HOME is deprecated.

1 1 0
2 1 4
2 2 1
3 2 0
3 2 4
3 3 3

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