mapreduce求共同好友案例示例

案例需求:
求出两两之间的共同好友

一:案例分析图解

------------------------------------------------------------第一阶段----------------------------------------------------------------------------

1.导入pom.xml依赖,特别留意打包插件,他可以把依赖的jar包全部打包,保证可以在hadoop集群上运行
 <dependencies>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>2.7.5</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>2.7.5</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-hdfs</artifactId>
            <version>2.7.5</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-mapreduce-client-core</artifactId>
            <version>2.7.5</version>
        </dependency>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>RELEASE</version>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.1</version>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                    <encoding>UTF-8</encoding>
                    <!--    <verbal>true</verbal>-->
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-shade-plugin</artifactId>
                <version>2.4.3</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>shade</goal>
                        </goals>
                        <configuration>
                            <minimizeJar>true</minimizeJar>
                        </configuration>
                    </execution>
                </executions>
            </plugin>

        </plugins>
    </build>

2.map阶段:把k1 v1 --> k2  v2
public class MyMapper extends Mapper<LongWritable,Text,Text,Text> {
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        //1.切割v1,获取v2
        String[] split01 = value.toString().split(":");
        String v2 = split01[0];
        //2.再切割
        String[] split02 = split01[1].split(",");
        Text text_k2 = new Text();
        Text text_v2 = new Text();
        //3.遍历数组获取k2,且把k2  v2写入context域中传递给shuffle阶段/reduce阶段
        for (String k2 : split02){
            text_k2.set(k2);
            text_v2.set(v2);
            context.write(text_k2,text_v2);
        }
    }
}

3.reduce阶段:把k2 v2 --> k3  v3
public class MyReducer extends Reducer<Text,Text,Text,Text> {
    @Override
    protected void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
        //把k2  v2 转化成 k3  v3
        //1.遍历集合,把v2转成k2
        StringBuffer buffer = new StringBuffer();
        for (Text text : values){
            buffer.append(text).append("-");
        }
        context.write(new Text(buffer.toString()),key);
    }
}

4.主方法,执行程序入口类
public class JonMain extends Configured implements Tool {
    @Override
    public int run(String[] args) throws Exception {
        //获取job任务对象
        Job job = Job.getInstance(super.getConf(),"friend");

        //第一步:设置读取方式和读取路径
        job.setInputFormatClass(TextInputFormat.class);
        TextInputFormat.addInputPath(job,new Path("hdfs://node01:8020/input"));

        //第二步:设置map阶段
        job.setMapperClass(MyMapper.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(Text.class);

        //第三步:分区
        //第四步:排序
        //第五步:规约
        //第六步:分组

        //第七步:设置reduce阶段
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        //第八步:设置输出方式和输出路径
        job.setOutputFormatClass(TextOutputFormat.class);
        Path path = new Path("hdfs://node01:8020/output01");
        TextOutputFormat.setOutputPath(job,path);

        //获取文件系统对象
        FileSystem fileSystem = FileSystem.get(new URI("hdfs://node01"),super.getConf());
        //判断输出目录是否存在,存在就删除,避免多次执行报错
        if (fileSystem.exists(path)){
            fileSystem.delete(path);
        }

        //等待任务结束
        boolean b = job.waitForCompletion(true);
        return b ? 0 : 1 ;
    }

    //主方法入口
    public static void main(String[] args) throws Exception {
        Configuration configuration = new Configuration();
        int run = ToolRunner.run(configuration, new JonMain(), args);
        System.exit(run);
    }
}

--------------------------------------------------------------第二阶段----------------------------------------------------------------------------

1.map阶段
public class MyMapper extends Mapper<LongWritable,Text,Text,Text> {
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        //1.切割v1,获取v2
        String[] split01 = value.toString().split("\t");
        String v2 = split01[1];
        //2.再切割
        String[] split02 = split01[0].split("-");
        Text text_k2 = new Text();
        Text text_v2 = new Text();
        text_v2.set(v2);
        //3.遍历数组获取k2
       for (int i =0;i < split02.length-1;i++){
           //4.排序
           Arrays.sort(split02);
           for (int j=i+1;j < split02.length ; j++){
               String k2 = split02[i]+"-"+split02[j];
               text_k2.set(k2);
               context.write(text_k2,text_v2);
           }
       }
    }
}

2.reduce阶段
public class MyReducer extends Reducer<Text,Text,Text,Text> {
    @Override
    protected void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
        //把k2  v2 转化成 k3  v3
        //1.遍历集合,拼接v2
        StringBuffer buffer = new StringBuffer();
        for (Text text : values){
            buffer.append(text).append("\t");
        }
        context.write(key,new Text(buffer.toString()));
    }
}

3.主方法
public class JonMain extends Configured implements Tool {
    @Override
    public int run(String[] args) throws Exception {
        //获取job任务对象
        Job job = Job.getInstance(super.getConf(),"friend");

        //第一步:设置读取方式和读取路径
        job.setInputFormatClass(TextInputFormat.class);
        TextInputFormat.addInputPath(job,new Path("hdfs://node01:8020/output01/part-r-00000"));

        //第二步:设置map阶段
        job.setMapperClass(MyMapper.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(Text.class);

        //第三步:分区
        //第四步:排序
        //第五步:规约
        //第六步:分组

        //第七步:设置reduce阶段
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        //第八步:设置输出方式和输出路径
        job.setOutputFormatClass(TextOutputFormat.class);
        Path path = new Path("hdfs://node01:8020/output02");
        TextOutputFormat.setOutputPath(job,path);

        //获取文件系统对象
        FileSystem fileSystem = FileSystem.get(new URI("hdfs://node01"),super.getConf());
        //判断输出目录是否存在,存在就删除,避免多次执行报错
        if (fileSystem.exists(path)){
            fileSystem.delete(path);
        }

        //等待任务结束
        boolean b = job.waitForCompletion(true);
        return b ? 0 : 1 ;
    }

    //主方法入口
    public static void main(String[] args) throws Exception {
        Configuration configuration = new Configuration();
        int run = ToolRunner.run(configuration, new JonMain(), args);
        System.exit(run);
    }
}

---------------------------------------------------------------结果对比示例---------------------------------------------------------------------------

1.第一次运行结果
I-K-B-G-F-H-O-C-D- A
A-F-C-J-E- B
E-A-H-B-F-G-K- C
E-C-L-A-F-H-G- D
K- D
F-M-L-H-G-D-C-B-A- E
D-A-M- F
G-L- F
M- G
O- H
O- I
C- I
O- J
B- K
D-E- L
E- M
F- M
F- O
J-I-H-A- O

2.第二次运行结果
A-B E C
A-C B E D
A-D F E
A-E C B D
A-F E B D C
A-G E D C
A-H C O D E
A-I O
A-J B O
A-K C
A-L E D
A-M F E
B-C A E
B-D E A
B-E C
B-F C E A
B-G C A E
B-H E C A
B-I A
B-K C A
B-L E
B-M E
B-O A
C-D E A
C-E B D
C-F E D B A
C-G D E A
C-H E D A
C-I A
C-J B
C-K A
C-L D E
C-M E
C-O A
D-E L
D-F E A
D-G A E
D-H A E
D-I A
D-K A
D-L E
D-M E F
D-O A
E-F D C B
E-G D C
E-H D C
E-J B
E-K C
E-L D
F-G D C A E
F-H A C D E
F-I A
F-J B
F-K C A
F-L D E
F-M E
F-O A
G-H A D E C
G-I A
G-K A C
G-L D E F
G-M E
G-O A
H-I A O
H-J O
H-K A C
H-L E D
H-M E
H-O A
I-J O
I-K A
I-O A
K-O A
L-M E