【Hadoop离线基础总结】MapReduce 社交粉丝数据分析 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？
MapReduce 社交粉丝数据分析
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？
- 用户及好友数据
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
- java代码
需要两步完成需求
首先先创建第一步的package
在package中定义main、Mapper、Reducer三个类
定义一个Mapper类
package cn.itcast.demo1.step1;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
public class Step1Mapper extends Mapper<LongWritable, Text, Text, Text> {
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//输入数据如下格式 A:B,C,D,E,O
//将用户和好友列表分开
String[] split = value.toString().split(":");
//将好友列表分开，放到一个数组中去
String[] friendList = split[1].split(",");
//循环遍历，输出的k2,v2格式为 B [A,E]
for (String friend : friendList) {
context.write(new Text(friend), new Text(split[0]));
}
}
}
定义一个Reducer类
package cn.itcast.demo1.step1;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class Step1Reducer extends Reducer<Text,Text,Text,Text> {
/*
reduce接收到数据是 B [A,E]
B是好友，集合里面装的是多个用户
将数据最终转换成这样的形式进行输出 A-B-E-F-G-H-K- C
*/
@Override
protected void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
//创建StringBuffer对象
StringBuffer sb = new StringBuffer();
//循环遍历得到v2并拼接成字符串
for (Text value : values) {
sb.append(value.toString()).append("-");
}
context.write(new Text(sb.toString()),key);
}
}
程序main函数入口
package cn.itcast.demo1.step1;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
public class Step1Main extends Configured implements Tool {
@Override
public int run(String[] args) throws Exception {
//创建job对象
Job job = Job.getInstance(super.getConf(), "step1");
//输入数据，设置输入路径
job.setInputFormatClass(TextInputFormat.class);
TextInputFormat.setInputPaths(job, new Path("file:////Volumes/赵壮备份/大数据离线课程资料/5.大数据离线第五天/共同好友/input/friends.txt"));
//自定义map逻辑
job.setMapperClass(Step1Mapper.class);
//设置k2,v2输出类型
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
//自定义reduce逻辑
job.setReducerClass(Step1Reducer.class);
//设置k3,v3输出类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
//输出数据，设置输出路径
job.setOutputFormatClass(TextOutputFormat.class);
TextOutputFormat.setOutputPath(job, new Path("file:////Volumes/赵壮备份/大数据离线课程资料/5.大数据离线第五天/共同好友/step1_output"));
//将任务提交至集群
boolean b = job.waitForCompletion(true);
return b ? 0 : 1;
}
public static void main(String[] args) throws Exception {
int run = ToolRunner.run(new Configuration(), new Step1Main(), args);
System.exit(run);
}
}
运行完成后，得到第一步的数据
F-D-O-I-H-B-K-G-C- A
E-A-J-F- B
K-A-B-E-F-G-H- C
G-K-C-A-E-L-F-H- D
G-F-M-B-H-A-L-D- E
M-D-L-A-C-G- F
M- G
O- H
C-O- I
O- J
B- K
E-D- L
F-E- M
J-I-H-A-F- O
创建第二步的package
在package中定义main、Mapper、Reducer三个类
定义一个Mapper类
package cn.itcast.demo1.step2;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
import java.util.Arrays;
public class Step2Mapper extends Mapper<LongWritable, Text, Text, Text> {
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//对拿到的数据进行分割，得到用户列表和好友
String[] split = value.toString().split("\t");
//再对用户列表进行分割，得到用户列表数组
String[] userList = split[0].split("-");
//因为文件中的数据并不是按照字典顺序进行排序，所以有可能会出来A-E E-A的情况，reduceTask是无法将这种情况视为key相同的
//所以需要进行排序
Arrays.sort(userList);
for (int i = 0; i < userList.length - 1; i++) {
for (int j = i + 1; j < userList.length; j++) {
String userTwo = userList[i] + "-" + userList[j];
context.write(new Text(userTwo), new Text(split[1]));
}
}
}
}
定义一个reducer类
package cn.itcast.demo1.step2;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class Step2Reducer extends Reducer<Text, Text, Text, Text> {
@Override
protected void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
//创建StringBuffer对象
StringBuffer sb = new StringBuffer();
for (Text value : values) {
//获取共同好友列表
sb.append(value.toString()).append("-");
}
context.write(key, new Text(sb.toString()));
}
}
程序main函数入口
package cn.itcast.demo1.step2;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
public class Step2Main extends Configured implements Tool {
@Override
public int run(String[] args) throws Exception {
//创建job对象
Job job = Job.getInstance(super.getConf(), "step2");
//输入数据，设置输入路径
job.setInputFormatClass(TextInputFormat.class);
TextInputFormat.setInputPaths(job, new Path("file:////Volumes/赵壮备份/大数据离线课程资料/5.大数据离线第五天/共同好友/step1_output"));
//自定义map逻辑
job.setMapperClass(Step2Mapper.class);
//设置k2,v2输出类型
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
//自定义reduce逻辑
job.setReducerClass(Step2Reducer.class);
//设置k3,v3输出类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
//输出数据，设置输出路径
job.setOutputFormatClass(TextOutputFormat.class);
TextOutputFormat.setOutputPath(job, new Path("file:////Volumes/赵壮备份/大数据离线课程资料/5.大数据离线第五天/共同好友/step2_output"));
//提交任务至集群
boolean b = job.waitForCompletion(true);
return b ? 0 : 1;
}
public static void main(String[] args) throws Exception {
int run = ToolRunner.run(new Configuration(), new Step2Main(), args);
System.exit(run);
}
}
运行结果为
A-B C-E-
A-C D-F-
A-D F-E-
A-E C-B-D-
A-F D-O-E-B-C-
A-G C-D-F-E-
A-H E-C-O-D-
A-I O-
A-J O-B-
A-K C-D-
A-L E-D-F-
A-M F-E-
B-C A-
B-D E-A-
B-E C-
B-F E-A-C-
B-G A-E-C-
B-H E-C-A-
B-I A-
B-K A-C-
B-L E-
B-M E-
B-O A-
C-D F-A-
C-E D-
C-F A-D-
C-G F-D-A-
C-H D-A-
C-I A-
C-K A-D-
C-L D-F-
C-M F-
C-O I-A-
D-E L-
D-F A-E-
D-G F-A-E-
D-H A-E-
D-I A-
D-K A-
D-L F-E-
D-M F-E-
D-O A-
E-F M-C-B-D-
E-G C-D-
E-H C-D-
E-J B-
E-K C-D-
E-L D-
F-G A-D-E-C-
F-H D-O-C-E-A-
F-I O-A-
F-J B-O-
F-K A-D-C-
F-L D-E-
F-M E-
F-O A-
G-H E-A-C-D-
G-I A-
G-K C-D-A-
G-L D-E-F-
G-M E-F-
G-O A-
H-I O-A-
H-J O-
H-K D-A-C-
H-L E-D-
H-M E-
H-O A-
I-J O-
I-K A-
I-O A-
K-L D-
K-O A-
L-M F-E-
