Hadoop demo 找出共同好友

需求

以下是qq的好友列表数据，冒号前是一个用，冒号后是该用户的所有好友（数据中的好友关系是单向的）

A:B,C,D,F,E,O

B:A,C,E,K

C:F,A,D,I

D:A,E,F,L

E:B,C,D,M,L

F:A,B,C,D,E,O,M

G:A,C,D,E,F

H:A,C,D,E,O

I:A,O

J:B,O

K:A,C,D

L:D,E,F

M:E,F,G

O:A,H,I,J

 

求出哪些人两两之间有共同好友，及他俩的共同好友都有谁？

第一步  

map

读一行   A:B,C,D,F,E,O

输出    

在读一行   B:A,C,E,K

输出   

 

 

REDUCE

拿到的数据比如......

输出：  

.....

 

 

 

第二步

map

读入一行

直接输出

 

reduce

读入数据  .......

输出： A-B  C,F,G,.....

第一步

package com.asin.hdp.commfriend;

import java.io.IOException;

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.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;

public class CommFriendDemo {

	public static void main(String[] args) throws Exception {
		Configuration conf = new Configuration();
		Job job = Job.getInstance(conf);
		job.setJarByClass(CommFriendDemo.class);

		job.setMapperClass(CommFriendMapper.class);
		job.setReducerClass(CommFriendReduce.class);

		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(Text.class);

		FileInputFormat.addInputPath(job, new Path("F:/friend.txt"));
		FileOutputFormat.setOutputPath(job, new Path("F:/outputFriend1"));

		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}

}

class CommFriendMapper extends Mapper {

	@Override
	protected void map(LongWritable key, Text value, Mapper.Context context)
			throws IOException, InterruptedException {
		String line = value.toString();
		String[] split = line.split(":");
		String user = split[0];
		String[] friends = split[1].split(",");
		for (String friend : friends) {
			context.write(new Text(friend), new Text(user));
		}
	}
}

class CommFriendReduce extends Reducer {

	@Override
	protected void reduce(Text key, Iterable value, Reducer.Context context)
			throws IOException, InterruptedException {

		String users = "";
		for (Text text : value) {
			users += text + ",";
		}
		context.write(key, new Text(users));
	}
}

部分结果

A	I,K,C,B,G,F,H,O,D,
B	A,F,J,E,
C	A,E,B,H,F,G,K,
D	G,C,K,A,L,F,E,H,
E	G,M,L,H,A,F,B,D,
F	L,M,D,C,G,A,

第二步

package com.asin.hdp.commfriend;

import java.io.IOException;
import java.util.Arrays;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.util.IterableUtils;
import org.apache.hadoop.io.LongWritable;
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;

public class CommFriendDemo2 {

	public static void main(String[] args) throws Exception {
		Configuration conf = new Configuration();
		Job job = Job.getInstance(conf);
		job.setJarByClass(CommFriendDemo2.class);

		job.setMapperClass(CommFriendMapperS.class);
		job.setReducerClass(CommFriendReduceS.class);

		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(Text.class);

		FileInputFormat.addInputPath(job, new Path("F:/outputFriend1/part-r-00000"));
		FileOutputFormat.setOutputPath(job, new Path("F:/outputFriend2"));

		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}

}

class CommFriendMapperS extends Mapper {

	@Override
	protected void map(LongWritable key, Text value, Mapper.Context context)
			throws IOException, InterruptedException {
		String line = value.toString();
		String[] split = line.split("\t");
		String friend = split[0];
		String users = split[1];
		String[] userArr = users.split(",");
		Arrays.sort(userArr);
		for (int i = 0; i < userArr.length - 2; i++) {
			for (int j = i + 1; j < userArr.length - 1; j++) {
				String user_user = userArr[i] + "-" + userArr[j];
				context.write(new Text(user_user), new Text(friend));
			}
		}
	}
}

class CommFriendReduceS extends Reducer {

	@Override
	protected void reduce(Text key, Iterable value, Reducer.Context context)
			throws IOException, InterruptedException {
		String user = "";
		for (Text text : value) {
			user += text + ",";
		}
		context.write(key, new Text(user));
	}
}

部分结果

A-B	C,E,
A-C	F,D,
A-D	E,F,
A-E	B,C,D,
A-F	C,D,B,E,O,
A-G	D,E,F,C,