MR案例实现小练习

MR案例实现

题目：现有一张emp表，字段分别为

员工编号，员工姓名，工作，管理编号，生日，工资，备注，部门编号

数据：

7369,SMITH,CLERK,7902,1980/12/17,800,,20
7499,ALLEN,SALESMAN,7698,1981/2/20,1600,300,30
7521,WARD,SALESMAN,7698,1981/2/22,1250,500,30
7566,JONES,MANAGER,7839,1981/4/2,2975,,20
7654,MARTIN,SALESMAN,7698,1981/9/28,1250,1400,30
7698,BLAKE,MANAGER,7839,1981/5/1,2850,,30
7782,CLARK,MANAGER,7839,1981/6/9,2450,,10
7788,SCOTT,ANALYST,7566,1987/7/13,3000,,20
7839,KING,PRESIDENT,,1981/11/17,5000,,10
7844,TURNER,SALESMAN,7698,1981/9/8,1500,0,30
7876,ADAMS,CLERK,7788,1987/7/13,1100,,20
7783,BOB,ANALYST,7777,1983/7/13,3200,,10
7822,BING,PRESIDENT,,2001/12/17,3000,,20
1233,CINFG,PRESIDENT,,2001/12/17,4000,,30
1233,FFSFG,PRESIDENT,999999,2001/12/17,4000,999999,10
2312,SDA,CLERK,3422,1987/7/13,2222,,30
4353,DFDS,CLERK,4563,1987/7/13,3111,999999,20
4564,RTEW,CLERK,5645,1987/7/13,6753,,20
7783,WOOP,ANALYST,7777,1983/7/13,5500,,10
5675,COC,ANALYST,7777,1983/7/13,6750,,30
3222,DOD,ANALYST,3422,1983/7/13,8400,,20,12
3211,EOE,ANALYST,7777,1983/7/13,2500,,10,33

 

目标：

根据工作类型（job）进行分区，

分区之下对每个员工按照部门（deptno）进行分组，

分组内部保证工资(sal)是降序。

每个分区中拿到每个部门工资排名第二的人(no.2)的信息。

 

注意：

请注意字段个数（只获取分割后数组大小为8的）

数据中99999为无效数据，请去除。

 

最终效果：

三个文件：

以下为代码段 Mapper

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

public class Map_05 extends Mapper {

    bean_05 k = new bean_05();

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//读取文件内容并以“，”进行分割
        String[] strings = value.toString().split(",");
//根据题目要求，排除字段数量不为8且倒数第二字段为999999的数据，
        if (strings.length == 8 && !strings[strings.length - 2].equals("999999")) {
//根据要求字段类型存入K对应的值。
            k.set(strings[1],strings[7],strings[0],
                    strings[2],strings[3],strings[4],
                    Integer.parseInt(strings[5]),strings[6]);
//让MAP进行输出
            context.write(k, NullWritable.get());
        }
    }
}

Reducer 代码段

import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class Reducer_05 extends Reducer {
    bean_05 k = new bean_05();

    @Override
    protected void reduce(bean_05 key, Iterable values, Context context) throws IOException, InterruptedException {
//定义一个常量初始化数值为0
        int a = 0;
        for (NullWritable value : values) {
//执行如果a值为1则打印输出， 不为1的不打印进而选出二条数据
            if (a==1){
            context.write(key, NullWritable.get());
            }else a++;
        }
    }
}

分组代码段

import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.io.WritableComparator;

public class fenzu_05 extends WritableComparator {
    public fenzu_05(){
        super(bean_05.class,true);
    }

    @Override
    public int compare(WritableComparable a, WritableComparable b) {
        bean_05 a1= (bean_05) a ;
        bean_05 b1= (bean_05) b ;
//利用get方法，判断Deptno是否相等，相等返回0，不等返回1即可；
//这样可以把Deptno一样的分在一个组里。
        if (a1.getDeptno().equals(b1.getDeptno())){
            return 0;
        }else return 1;

    }
}

分区代码段

package MapReduce_05;

import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Partitioner;

public class fenqu_05 extends Partitioner {
    @Override
    public int getPartition(bean_05 bean_05, NullWritable nullWritable, int i) {
//利用Switch 判断字段是否相等，从而产生分区效果，让job字段相同的去同一个分区；
        switch (bean_05.getJob()) {
            case "ANALYST":
                return 0;
            case "CLERK":
                return 1;
            case "PRESIDENT":
                return 2;
            case "SALESMAN":
                return 3;
            case "MANAGER":
                return 4;
            default:
                return 5;
        }
    }
}

Bean 代码段

import org.apache.hadoop.io.WritableComparable;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

public class bean_05 implements WritableComparable {
//定义变量
    private String ename;
    private String deptno;
    private String empno;
    private String job;
    private String mgr;
    private String hiredate;
    private int sal;
    private String com;


    public bean_05(String ename, String deptno, String empno, String job, String mgr, String hiredate, int sal, String com) {
        this.ename = ename;
        this.deptno = deptno;
        this.empno = empno;
        this.job = job;
        this.mgr = mgr;
        this.hiredate = hiredate;
        this.sal = sal;
        this.com = com;
    }

    public void set(String ename, String deptno,
                    String empno, String job, String mgr,
                    String hiredate, int sal, String com) {
        this.ename = ename;
        this.deptno = deptno;
        this.empno = empno;
        this.job = job;
        this.mgr = mgr;
        this.hiredate = hiredate;
        this.sal = sal;
        this.com = com;
    }

    public bean_05() {
    }

    public String getEname() {
        return ename;
    }

    public void setEname(String ename) {
        this.ename = ename;
    }

    public String getDeptno() {
        return deptno;
    }

    public void setDeptno(String deptno) {
        this.deptno = deptno;
    }

    public String getEmpno() {
        return empno;
    }

    public void setEmpno(String empno) {
        this.empno = empno;
    }

    public String getJob() {
        return job;
    }

    public void setJob(String job) {
        this.job = job;
    }

    public String getMgr() {
        return mgr;
    }

    public void setMgr(String mgr) {
        this.mgr = mgr;
    }

    public String getHiredate() {
        return hiredate;
    }

    public void setHiredate(String hiredate) {
        this.hiredate = hiredate;
    }

    public int getSal() {
        return sal;
    }

    public void setSal(int sal) {
        this.sal = sal;
    }

    public String getCom() {
        return com;
    }

    public void setCom(String com) {
        this.com = com;
    }


//重新定义比较方法题设要求根据薪水降序排列，因此需要重写。
//本目的找出deptno相同组下的sal进行排序，不同组不排序。
//因此仅当 compareto 方法返回值为0时才进行下一步排序；
    @Override
    public int compareTo(bean_05 o) {
        int a;
        if (this.deptno.compareTo(o.getdeptno) == 0) {
            a = this.sal > o.getSal() ? -1 : (this.sal < o.getSal() ? 1 : 0);
        } else a = this.deptno.compareTo(o.deptno);
        return a;


    }

//序列化与反序列化
    @Override
    public void write(DataOutput dataOutput) throws IOException {
        dataOutput.writeUTF(empno);
        dataOutput.writeUTF(ename);
        dataOutput.writeUTF(job);
        dataOutput.writeUTF(mgr);
        dataOutput.writeUTF(hiredate);
        dataOutput.writeInt(sal);
        dataOutput.writeUTF(com);
        dataOutput.writeUTF(deptno);
    }

    @Override
    public void readFields(DataInput in) throws IOException {
        empno = in.readUTF();
        ename = in.readUTF();
        job = in.readUTF();
        mgr = in.readUTF();
        hiredate = in.readUTF();
        sal = in.readInt();
        com = in.readUTF();
        deptno = in.readUTF();
    }
//重写tostring方法 避免地址打印

    @Override
    public String toString() {
        return "bean_05{" +
                "ename='" + ename + '\'' +
                ", deptno='" + deptno + '\'' +
                ", empno='" + empno + '\'' +
                ", job='" + job + '\'' +
                ", mgr='" + mgr + '\'' +
                ", hiredate='" + hiredate + '\'' +
                ", sal=" + sal +
                ", com='" + com + '\'' +
                '}';
    }
}

 Runner 代码段

import Mapreducer.delete;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import java.io.File;

public class Runner_05 {
    public static void main(String[] args) throws Exception {
    //设定conf 读取配置文件
        Configuration conf = new Configuration();
    //设置本地运行
        conf.set("mapreduce.framework.name","local");
    //创建job对象
        Job job = Job.getInstance(conf);
    //设置job的jar包
        job.setJarByClass(Runner_05.class);
        job.setMapperClass(Map_05.class);
        job.setReducerClass(Reducer_05.class);
     //设置map输出对象
        job.setMapOutputKeyClass(bean_05.class);
        job.setMapOutputValueClass(NullWritable.class);
     //设置reduce输出对象
        job.setOutputKeyClass(bean_05.class);
        job.setOutputValueClass(NullWritable.class);
    //设置分区
        job.setPartitionerClass(fenqu_05.class);
    //设置task个数
        job.setNumReduceTasks(6);
    //设置分组
        job.setGroupingComparatorClass(fenzu_05.class);
    //配置输入输出路径
        String in = "D:\\in";
        String out = "D:\\out";
        FileInputFormat.setInputPaths(job, new Path(in));
    //检测文件夹是否存在如果存在即删除
        delete.deleteFile(new File(out));
        FileOutputFormat.setOutputPath(job, new Path(out));


     //向集群提交并等待结束
        boolean b = job.waitForCompletion(true);
        System.exit(b ? 0 : 1);
    }
}