Hadoop-26、分區

現在將txt文檔中的電話號碼進行拆分
phone_data.txt

1	13736230513	192.196.100.1	www.atguigu.com	2481	24681	200
2	13846544121	192.196.100.2			264	0	200
3 	13956435636	192.196.100.3			132	1512	200
4 	13966251146	192.168.100.1			240	0	404
5 	18271575951	192.168.100.2	www.atguigu.com	1527	2106	200
6 	84188413	192.168.100.3	www.atguigu.com	4116	1432	200
7 	13590439668	192.168.100.4			1116	954	200
8 	15910133277	192.168.100.5	www.hao123.com	3156	2936	200
9 	13729199489	192.168.100.6			240	0	200
10 	13630577991	192.168.100.7	www.shouhu.com	6960	690	200
11 	15043685818	192.168.100.8	www.baidu.com	3659	3538	200
12 	15959002129	192.168.100.9	www.atguigu.com	1938	180	500
13 	13560439638	192.168.100.10			918	4938	200
14 	13470253144	192.168.100.11			180	180	200
15 	13682846555	192.168.100.12	www.qq.com	1938	2910	200
16 	13992314666	192.168.100.13	www.gaga.com	3008	3720	200
17 	13509468723	192.168.100.14	www.qinghua.com	7335	110349	404
18 	18390173782	192.168.100.15	www.sogou.com	9531	2412	200
19 	13975057813	192.168.100.16	www.baidu.com	11058	48243	200
20 	13768778790	192.168.100.17			120	120	200
21 	13568436656	192.168.100.18	www.alibaba.com	2481	24681	200
22 	13568436656	192.168.100.19			1116	954	200

在前面的文件上繼承開發

MyPartitioner.java

package com.atguigu.partition;

import com.atguigu.flow.FlowBean;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Partitioner;

public class MyPartitioner extends Partitioner<Text, FlowBean> {
    @Override
    public int getPartition(Text text, FlowBean flowBean, int numPartitions) {
        String phone = text.toString();

        switch (phone.substring(0,3)){
            case "136":
                return 0;
            case "137":
                return 1;
            case "138":
                return 2;
            case "139":
                return 3;
            default:
                return 4;
        }
    }
}

PartitionerDriver.java

package com.atguigu.partition;

import com.atguigu.flow.FlowBean;
import com.atguigu.flow.FlowMapper;
import com.atguigu.flow.FlowReducer;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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 PartitionerDriver {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        //1.獲取Job實例
        Job job = Job.getInstance(new Configuration());

        //2. 設置類路徑
        job.setJarByClass(PartitionerDriver.class);

        //3. 設置Mapper和Reducer
        job.setMapperClass(FlowMapper.class);
        job.setReducerClass(FlowReducer.class);

        job.setNumReduceTasks(5);
        job.setPartitionerClass(MyPartitioner.class);

        //4. 設置輸入輸出類型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(FlowBean.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(FlowBean.class);

        //5. 設置輸入輸出路徑
        FileInputFormat.setInputPaths(job, new Path("d:\\input"));
        FileOutputFormat.setOutputPath(job, new Path("d:\\output"));

        //6 提交
        boolean b = job.waitForCompletion(true);
        System.exit(b ? 0:1);
    }
}

注意：要按照順序進行分區，從0開始，分多少區要和job.setNumReduceTasks(5);中的數字5進行一一對應。