数据准备：
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
需求：
1.先求出A、B、C、….等是谁的好友
2.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？
需求解读：
1.有题目可得，该关系为单项关系可以理解为关注，即A关注的为BCDEF，B关注的为AK，所以求A B C...是谁的关注，即需要将冒号后边的作为key，前边的作为value进行map，在reduce的时候在合并即可。
2.求两两之间的共同关注，这时我们需要借助1题产生的结果文件，map是从后边的value值两两组合生成两两关系。作为新的key值输入，新的value为1题的key。
reduce的时候，将结果合并即可
源代码如下
第一题：
package Demo5;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
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.Reducer.Context;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
/**
* @author 星际毁灭
* 找出ABC等人的好友
* */
import Demo4.Log1;
public class Friend1 {
public static class Map extends Mapper<Object , Text , Text , Text>{
private static Text newKey=new Text();
private static final IntWritable one = new IntWritable(1);
public void map(Object key,Text value,Mapper<Object, Text, Text, Text>.Context context) throws IOException, InterruptedException{
String line=value.toString();
String[] array=line.split(":"); //数据实例 A:B,C,D,F,E,O
String first=array[0]; //冒号前边部分
String second=array[1]; //冒号后边部分
String[] friend=second.split(","); //冒号后边部分在切割
System.out.println(first+"\t"+second);
for(int i=0;i<friend.length;i++) {
context.write(new Text(friend[i]),new Text(first)); //好友关系，即源文件的反向
}
}
}
public static class Reduce extends Reducer<Text, Text, Text, Text>{
public void reduce(Text key,Iterable<Text> values,Context context) throws IOException, InterruptedException{
String res="";
for(Text val:values) {
res+=val.toString()+","; //将结果合并
}
context.write(key,new Text(res));
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException{
System.setProperty("hadoop.home.dir", "H:\\文件\\hadoop\\hadoop-2.6.4");
Configuration conf=new Configuration();
Path in=new Path("hdfs://192.168.6.132:9000/wys/in/friend1.txt");
Path out=new Path("hdfs://192.168.6.132:9000/wys/out/friend1");
Job job =new Job(conf,"OneSort");
FileInputFormat.addInputPath(job,in);
FileOutputFormat.setOutputPath(job,out);
job.setJarByClass(Friend1.class);
job.setMapperClass(Friend1.Map.class);
job.setReducerClass(Friend1.Reduce.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
job.waitForCompletion(true);
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
第二题：
package Demo5;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
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.Reducer.Context;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
/**
* @author 王翌淞
*
* 求出他们的共同好友
* */
public class Friend2 {
public static class Map extends Mapper<Object , Text , Text , Text>{
private static Text newKey=new Text();
private static final IntWritable one = new IntWritable(1);
public void map(Object key,Text value,Mapper<Object, Text, Text, Text>.Context context) throws IOException, InterruptedException{
String line=value.toString();
String[] array=line.split("\t");
String first=array[0];
String second=array[1];
String[] friend=second.split(",");
System.out.println(first+"\t"+second);
//通过两层的for循环，A的好友进行组合，有顺序
for(int i=0;i<friend.length;i++) {
for(int j=i+1;j<friend.length;j++) {
context.write(new Text(friend[i]+"-"+friend[j]),new Text(first)); //正序关系
context.write(new Text(friend[j]+"-"+friend[i]),new Text(first)); //倒序关系
}
}
//context.write(new Text(friend[i]),new Text(first));
}
}
public static class Reduce extends Reducer<Text, Text, Text, Text>{
public void reduce(Text key,Iterable<Text> values,Context context) throws IOException, InterruptedException{
String res="";
for(Text val:values) {
res+=val.toString()+" ";
}
context.write(key,new Text(res));
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException{
System.setProperty("hadoop.home.dir", "H:\\文件\\hadoop\\hadoop-2.6.4");
Configuration conf=new Configuration();
Path in=new Path("hdfs://192.168.6.132:9000/wys/out/friend1/part-r-00000");
Path out=new Path("hdfs://192.168.6.132:9000/wys/out/friend2");
Job job =new Job(conf,"OneSort");
FileInputFormat.addInputPath(job,in);
FileOutputFormat.setOutputPath(job,out);
job.setJarByClass(Friend2.class);
job.setMapperClass(Friend2.Map.class);
job.setReducerClass(Friend2.Reduce.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
job.waitForCompletion(true);
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
来源：https://www.cnblogs.com/wys-373/p/11455624.html