hadoop编程之工资序列化排序

数据集展示

建立三个hadoop编程类EmployeeSortMain、Employee、EmployeeSortMapper这三个类

对应的java代码如下

实例

EmployeeSortMain

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;

public class EmployeeSortMain {
    public static void main(String[] args) throws Exception{
        //创建一个job
        Job job = Job.getInstance(new Configuration());
        job.setJarByClass(EmployeeSortMain.class);
        //指定job的mapper和输出的类型 k2  v2
        job.setMapperClass(EmployeeSortMapper.class);
        job.setOutputKeyClass(Employee.class);
        job.setMapOutputValueClass(NullWritable.class);
        //指定job的输入和输出的路径
        FileInputFormat.setInputPaths(job,new Path(args[0]));
        FileOutputFormat.setOutputPath(job,new Path(args[1]));
        //提交程序，并且监控打印程序执行的结果
        boolean b = job.waitForCompletion(true);
        System.exit(b?0:1);
    }
}

Employee

import org.apache.hadoop.io.WritableComparable;

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

//1.若要把Employee作为key2，则需要实现序列化
//2.员工对象为Employee类，可被排序
//数据：7654，MARTIN	，SALESMAN，7698，1981/9/28，1250，1400，30
public class Employee implements WritableComparable<Employee> {
    private int empno;
    private String ename;
    private String job;
    private int mgr;
    private String hiredate;
    private int sal;
    private int comm;
    private int deptno;
    
    @Override
    public String toString(){
        return "Employee[empno="+empno+",ename="+ename+",sal="+sal+",deptno="+deptno+"]";
    }
    @Override
    public int compareTo(Employee o) {
        //多个列的排序：select * from emp order by deptno,sal;
        //首先按照deptno排序
        if(this.deptno >o.getDeptno()){
            return 1;
        }else if(this.deptno < o.getDeptno()){
            return -1;
        }
        //如果deptno相等，按照sal排序
        if(this.sal >= o.getSal()){
            return 1;
        }else{
            return -1;
        }

    }

    @Override
    public void write(DataOutput output) throws IOException {
        //序列化
        output.writeInt(this.empno);
        output.writeUTF(this.ename);
        output.writeUTF(this.job);
        output.writeInt(this.mgr);
        output.writeUTF(this.hiredate);
        output.writeInt(this.sal);
        output.writeInt(this.comm);
        output.writeInt(this.deptno);
    }

    @Override
    public void readFields(DataInput input) throws IOException {
        //反序列化
        this.empno = input.readInt();
        this.ename = input.readUTF();
        this.job = input.readUTF();
        this.mgr = input.readInt();
        this.hiredate = input.readUTF();
        this.sal = input.readInt();
        this.comm = input.readInt();
        this.deptno = input.readInt();
    }

    public int getEmpno() {
        return empno;
    }

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

    public String getEname() {
        return ename;
    }

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

    public String getJob() {
        return job;
    }

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

    public int getMgr() {
        return mgr;
    }

    public void setMgr(int 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 int getComm() {
        return comm;
    }

    public void setComm(int comm) {
        this.comm = comm;
    }

    public int getDeptno() {
        return deptno;
    }

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

EmployeeSortMapper

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 EmployeeSortMapper extends Mapper<LongWritable,Text,Employee, NullWritable> {
    @Override
    protected void map(LongWritable key1, Text value1, Context context) throws IOException, InterruptedException {
        //数据：7654，MARTIN	，SALESMAN，7698，1981/9/28，1250，1400，30
        String data = value1.toString();
        //分词
        String[] words = data.split(",");
        //创建员工对象
        Employee e = new Employee();
        //设置员工的属性
        // 员工号
        e.setEmpno(Integer.parseInt(words[0]));
        //姓名
        e.setEname(words[1]);
        //职位
        e.setJob(words[2]);
        //老板号（注意：可能没有老板号）
        try{
            e.setMgr(Integer.parseInt(words[3]));
        }catch (Exception ex){
            //没有老板号
            e.setMgr(-1);
        }
        //入职日期
        e.setHiredate(words[4]);
        //月薪
        e.setSal(Integer.parseInt(words[5]));
        //奖金（注意：奖金也有可能没有）
        try{
            e.setComm(Integer.parseInt(words[6]));
        }catch (Exception ex){
            //没有奖金
            e.setComm(0);
        }
        //部门号
        e.setDeptno(Integer.parseInt(words[7]));
        //输出
        context.write(e,NullWritable.get());
    }
}

 代码命令

hadoop jar 3.jar  ch03.EmployeeSortMain  /user/data/input/emp.csv  /user/data/output/ch3
hadoop jar 包名   主类  输入路径  输出路径

结果展示：

 学习连接

hadoop编程之工资序列化排序-CSDN博客

hadoop编程之词频统计-CSDN博客

hadoop编程之工资序列化排序-CSDN博客

利用mapreduce统计部门的最高工资_使用mapreduce查询某个部门中薪资最高的员工姓名,如果输出结果的格式为“薪资 员-CSDN博客

在Ubuntu上用mapreduce进行词频统计（伪分布式）_mapreduce怎么统计txt文件词频终端-CSDN博客