MapReduce统计流量案例(自定义排序-全排序)基本实现

手机号  总上行流量  总下行流量  总流量

11136230513	500	500	1000
12959002129	1938	180	2118
19943685818	3659	3538	7197
22246544121	250	250	500
22256435636	250	250	500
33366251146	240	0	240
33371575951	1527	2106	3633
33388413456	4116	1432	5548

参考 MapReduce统计流量案例 的Maven配置  

参考 MapReduce统计流量案例 的log4j.properties配置  

package com.test.mapreduce.comparable;

import org.apache.hadoop.io.WritableComparable;

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

public class FlowBean implements WritableComparable {

    private Long upFlow;   // 上行流量
    private Long downFlow; // 下行流量
    private Long sumFlow;  // 总流量

    public Long getUpFlow() {
        return upFlow;
    }

    public void setUpFlow(Long upFlow) {
        this.upFlow = upFlow;
    }

    public Long getDownFlow() {
        return downFlow;
    }

    public void setDownFlow(Long downFlow) {
        this.downFlow = downFlow;
    }

    public Long getSumFlow() {
        return sumFlow;
    }

    public void setSumFlow() {
        this.sumFlow = this.upFlow + this.downFlow;
    }

    
    public FlowBean() {
    }

    
    @Override
    public void write(DataOutput dataOutput) throws IOException {
        // 序列化Value数据
        dataOutput.writeLong(upFlow);
        dataOutput.writeLong(downFlow);
        dataOutput.writeLong(sumFlow);

    }

    
    @Override
    public void readFields(DataInput dataInput) throws IOException {
        // 反序列化数据
        this.upFlow = dataInput.readLong();
        this.downFlow = dataInput.readLong();
        this.sumFlow = dataInput.readLong();
    }

    
    @Override
    public String toString() {
        return upFlow + "t" + downFlow + "t" + sumFlow;
    }

    
    @Override
    public int compareTo(FlowBean o) {
        // 按照总流量比较，倒序排序(倒序-1, 正序1)
        if (this.sumFlow > o.sumFlow){
            return -1;
        }else if(this.sumFlow < o.sumFlow){
            return 1;
        }else {
            return 0;
        }

    }
}

package com.test.mapreduce.comparable;

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

import java.io.IOException;

public class FlowMapper extends Mapper {

    // 定义一个FlowBean对象，用于封装key
    private FlowBean k = new FlowBean();
    // 定义一个Text对象，用于封装value
    private Text v = new Text();

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        // 1.获取每一行数据
        String line = value.toString();
        // 2.切割
        String[] dataList = line.split("t");
        // 3.封装数据
        k.setUpFlow(Long.parseLong(dataList[1]));
        k.setDownFlow(Long.parseLong(dataList[2]));
        k.setSumFlow();
        v.set(dataList[0]);
        // 4.输出
        context.write(k, v);
    }
}

package com.test.mapreduce.comparable;

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

import java.io.IOException;

public class FlowReducer extends Reducer {

    @Override
    protected void reduce(FlowBean key, Iterable values, Context context) throws IOException, InterruptedException {
        // 循环写出，避免总流量相同情况
        for (Text value : values) {
            context.write(value, key);
        }
    }
}

package com.test.mapreduce.comparable;

import org.apache.hadoop.conf.Configuration;
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.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import java.io.IOException;

public class FlowDriver {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        // 1.创建配置信息Configuration对象并获取Job单例对象
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf);

        // 2.设置关联本Driver程序的jar
        job.setJarByClass(FlowDriver.class);

        // 3.设置关联Mapper和Reducer的jar
        job.setMapperClass(FlowMapper.class);
        job.setReducerClass(FlowReducer.class);

        // 4.设置Mapper输出的kv类型
        job.setMapOutputKeyClass(FlowBean.class);
        job.setMapOutputValueClass(Text.class);

        // 5. 设置最终输出的kv类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(FlowBean.class);

        // 6.设置输入和输出路径
        FileInputFormat.setInputPaths(job, new Path("D:\input"));
        FileOutputFormat.setOutputPath(job, new Path("D:\output"));

        // 7.提交job
        boolean result = job.waitForCompletion(true);
        System.exit(result ? 0 : 1);
    }
}

19943685818	3659	3538	7197
33388413456	4116	1432	5548
33371575951	1527	2106	3633
12959002129	1938	180	2118
11136230513	500	500	1000
22256435636	250	250	500
22246544121	250	250	500
33366251146	240	0	240