mapreduce系列（7）--查找共同好友
一、概述
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是谁
比如:
a-b : c ,e思路：
首先可以第一步可以把朋友作为key，人作为value，形成：友–>人，人，人。这样的中间结果
第二把，把（人，人，人）进行排序，避免重复，然后进行两两匹配形成：(人-人）–>友。这样的键值对，进行mr统计，最后结果就是两两的共同好友了
第一步代码：
SharedFriendsStepOne.java
package friends;
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.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 java.io.IOException;
import java.net.URI;
import java.net.URISyntaxException;
/**
* Created by tianjun on 2017/3/20.
*/
public class SharedFriendsStepOne {
static class SharedFriendsStepOneMapper extends Mapper {
Text k = new Text();
Text v = new Text();
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String line = value.toString();
String[] person_friends = line.split(":");
String person = person_friends[0];
String[] friends = person_friends[1].split(",");
for(String friend : friends){
k.set(friend);
v.set(person);
//<好友，人>
context.write(k,v);
}
}
}
static class SharedFriendsStepOneReduce extends Reducer{
@Override
protected void reduce(Text friend, Iterable persons, Context context) throws IOException, InterruptedException {
StringBuffer sb = new StringBuffer();
for(Text person : persons){
if(sb.length()!=0){
sb.append(",");
}
sb.append(person);
}
context.write(friend,new Text(sb.toString()));
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException, URISyntaxException {
String os = System.getProperty("os.name").toLowerCase();
if (os.contains("windows")) {
System.setProperty("HADOOP_USER_NAME", "root");
}
Configuration conf = new Configuration();
conf.set("mapreduce.framework.name","yarn");
conf.set("yarn.resourcemanager.hostname","mini01");
conf.set("fs.defaultFS","hdfs://mini01:9000/");
// 默认就是local模式
// conf.set("mapreduce.framework.name","local");
// conf.set("mapreduce.jobtracker.address","local");
// conf.set("fs.defaultFS","file:///");
Job wcjob = Job.getInstance(conf);
wcjob.setJar("F:/myWorkPlace/java/dubbo/demo/dubbo-demo/mr-demo1/target/mr.demo-1.0-SNAPSHOT.jar");
//如果从本地拷贝，是不行的，这时需要使用setJar
// wcjob.setJarByClass(Rjoin.class);
wcjob.setMapperClass(SharedFriendsStepOneMapper.class);
wcjob.setReducerClass(SharedFriendsStepOneReduce.class);
//设置我们的业务逻辑Mapper类的输出key和value的数据类型
wcjob.setMapOutputKeyClass(Text.class);
wcjob.setMapOutputValueClass(Text.class);
//设置我们的业务逻辑Reducer类的输出key和value的数据类型
wcjob.setOutputKeyClass(Text.class);
wcjob.setOutputValueClass(Text.class);
//如果不设置InputFormat，默认就是使用TextInputFormat.class
// wcjob.setInputFormatClass(CombineFileInputFormat.class);
// CombineFileInputFormat.setMaxInputSplitSize(wcjob,4194304);
// CombineFileInputFormat.setMinInputSplitSize(wcjob,2097152);
FileSystem fs = FileSystem.get(new URI("hdfs://mini01:9000"), new Configuration(), "root");
Path path = new Path("hdfs://mini01:9000/wc/friends/stepone");
if (fs.exists(path)) {
fs.delete(path, true);
}
//指定要处理的数据所在的位置
FileInputFormat.setInputPaths(wcjob, new Path("hdfs://mini01:9000/input/friends"));
//指定处理完成之后的结果所保存的位置
FileOutputFormat.setOutputPath(wcjob, new Path("hdfs://mini01:9000/wc/friends/stepone"));
boolean res = wcjob.waitForCompletion(true);
System.exit(res ? 0 : 1);
}
}
计算结果：
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
G M
H O
I O,C
J O
K B
L D,E
M E,F
O A,H,I,J,F为了防止b–>c和c–>b这样同一对朋友的重复，所以，下面基于这个结果处理的时候，需要进行排序，这样就能达到没有重复朋友对的出现。
第二步：
SharedFriendsStepTwo.java
package friends;
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.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 java.io.IOException;
import java.net.URI;
import java.net.URISyntaxException;
import java.util.Arrays;
/**
* Created by tianjun on 2017/3/20.
*/
public class SharedFriendsStepTwo {
static class SharedFriendsStepTwoMapper extends Mapper {
Text k = new Text();
Text v = new Text();
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
String line = value.toString();
String[] friend_persons = line.split("\t");
String friend = friend_persons[0];
String[] persons = friend_persons[1].split(",");
//排序
Arrays.sort(persons);
for(int i = 0 ; i
for(int j=i+1;j
//<人-人,好友> ,这样相同的“人-人”对好友发到一起了
context.write(new Text(persons[i]+"-"+persons[j]),new Text(friend));
}
}
}
}
static class SharedFriendsStepTwoReduce extends Reducer{
@Override
protected void reduce(Text person_person, Iterable friends, Context context) throws IOException, InterruptedException {
StringBuffer sb = new StringBuffer();
for(Text friend : friends){
sb.append(friend).append(" ");
}
context.write(person_person,new Text(sb.toString()));
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException, URISyntaxException {
String os = System.getProperty("os.name").toLowerCase();
if (os.contains("windows")) {
System.setProperty("HADOOP_USER_NAME", "root");
}
Configuration conf = new Configuration();
conf.set("mapreduce.framework.name","yarn");
conf.set("yarn.resourcemanager.hostname","mini01");
conf.set("fs.defaultFS","hdfs://mini01:9000/");
// 默认就是local模式
// conf.set("mapreduce.framework.name","local");
// conf.set("mapreduce.jobtracker.address","local");
// conf.set("fs.defaultFS","file:///");
Job wcjob = Job.getInstance(conf);
wcjob.setJar("F:/myWorkPlace/java/dubbo/demo/dubbo-demo/mr-demo1/target/mr.demo-1.0-SNAPSHOT.jar");
//如果从本地拷贝，是不行的，这时需要使用setJar
// wcjob.setJarByClass(Rjoin.class);
wcjob.setMapperClass(SharedFriendsStepTwoMapper.class);
wcjob.setReducerClass(SharedFriendsStepTwoReduce.class);
//设置我们的业务逻辑Mapper类的输出key和value的数据类型
wcjob.setMapOutputKeyClass(Text.class);
wcjob.setMapOutputValueClass(Text.class);
//设置我们的业务逻辑Reducer类的输出key和value的数据类型
wcjob.setOutputKeyClass(Text.class);
wcjob.setOutputValueClass(Text.class);
//如果不设置InputFormat，默认就是使用TextInputFormat.class
// wcjob.setInputFormatClass(CombineFileInputFormat.class);
// CombineFileInputFormat.setMaxInputSplitSize(wcjob,4194304);
// CombineFileInputFormat.setMinInputSplitSize(wcjob,2097152);
FileSystem fs = FileSystem.get(new URI("hdfs://mini01:9000"), new Configuration(), "root");
Path path = new Path("hdfs://mini01:9000/wc/friends/steptwo");
if (fs.exists(path)) {
fs.delete(path, true);
}
//指定要处理的数据所在的位置
FileInputFormat.setInputPaths(wcjob, new Path("hdfs://mini01:9000/wc/friends/stepone"));
//指定处理完成之后的结果所保存的位置
FileOutputFormat.setOutputPath(wcjob, new Path("hdfs://mini01:9000/wc/friends/steptwo"));
boolean res = wcjob.waitForCompletion(true);
System.exit(res ? 0 : 1);
}
}
最后计算得出的两俩好友如下：
[root@mini03 ~]# hdfs dfs -cat /wc/friends/steptwo/*
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
A-H E O C D
A-I O
A-K D
A-L F E
B-C A
B-D E A
B-E C
B-F E A C
B-G C E A
B-H E C A
B-I A
B-K A
B-L E
C-D F A
C-E D
C-F D A
C-G F A D
C-H A D
C-I A
C-K D A
C-L F
D-F E A
D-G A E F
D-H A E
D-I A
D-K A
D-L F E
E-F C D B
E-G D C
E-H D C
E-K D
F-G C E D A
F-H C A D E O
F-I A O
F-K D A
F-L E
G-H D E C A
G-I A
G-K A D
G-L F E
H-I A O
H-K A D
H-L E
I-K A