本篇内容主要讲解“MapReduce怎么处理手机通信流量统计”，感兴趣的朋友不妨来看看。本文介绍的方法操作简单快捷，实用性强。下面就让小编来带大家学习“MapReduce怎么处理手机通信流量统计”吧!

创新互联是由多位在大型网络公司、广告设计公司的优秀设计人员和策划人员组成的一个具有丰富经验的团队，其中包括网站策划、网页美工、网站程序员、网页设计师、平面广告设计师、网络营销人员及形象策划。承接：成都网站设计、成都做网站、网站改版、网页设计制作、网站建设与维护、网络推广、数据库开发,以高性价比制作企业网站、行业门户平台等全方位的服务。

模拟元数据如下 HTTP_20130313143750.dat

1363157985066 13726230503 00-FD-07-A4-72-B8:CMCC 120.196.100.82 i02.c.aliimg.com 24 27 2481 24681 200

1363157995052 13826544101 5C-0E-8B-C7-F1-E0:CMCC 120.197.40.4 4 0 264 0 200

1363157991076 13926435656 20-10-7A-28-CC-0A:CMCC 120.196.100.99 2 4 132 1512 200

1363154400022 13926251106 5C-0E-8B-8B-B1-50:CMCC 120.197.40.4 4 0 240 0 200

1363157993044 18211575961 94-71-AC-CD-E6-18:CMCC-EASY 120.196.100.99 iface.qiyi.com 视频网站 15 12 1527 2106 200

1363157995074 84138413 5C-0E-8B-8C-E8-20:7DaysInn 120.197.40.4 122.72.52.12 20 16 4116 1432 200

1363157993055 13560439658 C4-17-FE-BA-DE-D9:CMCC 120.196.100.99 18 15 1116 954 200

1363157995033 15920133257 5C-0E-8B-C7-BA-20:CMCC 120.197.40.4 sug.so.360.cn 信息安全 20 20 3156 2936 200

1363157983019 13719199419 68-A1-B7-03-07-B1:CMCC-EASY 120.196.100.82 4 0 240 0 200

1363157984041 13660577991 5C-0E-8B-92-5C-20:CMCC-EASY 120.197.40.4 s19.cnzz.com 站点统计 24 9 6960 690 200

1363157973098 15013685858 5C-0E-8B-C7-F7-90:CMCC 120.197.40.4 rank.ie.sogou.com 搜索引擎 28 27 3659 3538 200

1363157986029 15989002119 E8-99-C4-4E-93-E0:CMCC-EASY 120.196.100.99 www.umeng.com 站点统计 3 3 1938 180 200

1363157992093 13560439658 C4-17-FE-BA-DE-D9:CMCC 120.196.100.99 15 9 918 4938 200

1363157986041 13480253104 5C-0E-8B-C7-FC-80:CMCC-EASY 120.197.40.4 3 3 180 180 200

1363157984040 13602846565 5C-0E-8B-8B-B6-00:CMCC 120.197.40.4 2052.flash3-http.qq.com 综合门户 15 12 1938 2910 200

1363157995093 13922314466 00-FD-07-A2-EC-BA:CMCC 120.196.100.82 img.qfc.cn 12 12 3008 3720 200

1363157982040 13502468823 5C-0A-5B-6A-0B-D4:CMCC-EASY 120.196.100.99 y0.ifengimg.com 综合门户 57 102 7335 110349 200

1363157986072 18320173382 84-25-DB-4F-10-1A:CMCC-EASY 120.196.100.99 input.shouji.sogou.com 搜索引擎 21 18 9531 2412 200

1363157990043 13925057413 00-1F-64-E1-E6-9A:CMCC 120.196.100.55 t3.baidu.com 搜索引擎 69 63 11058 48243 200

1363157988072 13760778710 00-FD-07-A4-7B-08:CMCC 120.196.100.82 2 2 120 120 200

1363157985079 13823070001 20-7C-8F-70-68-1F:CMCC 120.196.100.99 6 3 360 180 200

1363157985069 13600217502 00-1F-64-E2-E8-B1:CMCC 120.196.100.55 18 138 1080 186852 200

上面日志的格式如下

MapReduce代码如下

package MapReduce;

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

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner;

public class KpiApp {
    static final String INPUT_PATH = "hdfs://hadoop:9000/wlan";
    static final String OUT_PATH = "hdfs://hadoop:9000/outwlan";
    public static void main(String[] args) throws Exception{
        final Job job = new Job(new Configuration(), KpiApp.class.getSimpleName());
        //1.1 指定输入文件路径
        FileInputFormat.setInputPaths(job, INPUT_PATH);
        //指定哪个类用来格式化输入文件
        job.setInputFormatClass(TextInputFormat.class);
        
        //1.2指定自定义的Mapper类
        job.setMapperClass(MyMapper.class);
        //指定输出的类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(KpiWritable.class);
        
        //1.3 指定分区类
        job.setPartitionerClass(HashPartitioner.class);
        job.setNumReduceTasks(1);
        
        //1.4 TODO 排序、分区
        
        //1.5  TODO （可选）合并
        
        //2.2 指定自定义的reduce类
        job.setReducerClass(MyReducer.class);
        //指定输出的类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(KpiWritable.class);
        
        //2.3 指定输出到哪里
        FileOutputFormat.setOutputPath(job, new Path(OUT_PATH));
        //设定输出文件的格式化类
        job.setOutputFormatClass(TextOutputFormat.class);
        
        //把代码提交给JobTracker执行
        job.waitForCompletion(true);
    }

    static class MyMapper extends Mapper{
        protected void map(LongWritable key, Text value, org.apache.hadoop.mapreduce.Mapper.Context context) throws IOException ,InterruptedException {
            final String[] splited = value.toString().split("\t");
            final String msisdn = splited[1];
            final Text k2 = new Text(msisdn);
            final KpiWritable v2 = new KpiWritable(splited[6],splited[7],splited[8],splited[9]);
            context.write(k2, v2);
        };
    }
    
    static class MyReducer extends Reducer{
        /**
         * @param    k2    表示整个文件中不同的手机号码    
         * @param    v2s    表示该手机号在不同时段的流量的集合
         */
        protected void reduce(Text k2, java.lang.Iterable v2s, org.apache.hadoop.mapreduce.Reducer.Context context) throws IOException ,InterruptedException {
            long upPackNum = 0L;
            long downPackNum = 0L;
            long upPayLoad = 0L;
            long downPayLoad = 0L;
            
            for (KpiWritable kpiWritable : v2s) {
                upPackNum += kpiWritable.upPackNum;
                downPackNum += kpiWritable.downPackNum;
                upPayLoad += kpiWritable.upPayLoad;
                downPayLoad += kpiWritable.downPayLoad;
            }
            
            final KpiWritable v3 = new KpiWritable(upPackNum+"", downPackNum+"", upPayLoad+"", downPayLoad+"");
            context.write(k2, v3);
        };
    }
}

class KpiWritable implements Writable{
    long upPackNum;
    long downPackNum;
    long upPayLoad;
    long downPayLoad;
    
    public KpiWritable(){}
    
    public KpiWritable(String upPackNum, String downPackNum, String upPayLoad, String downPayLoad){
        this.upPackNum = Long.parseLong(upPackNum);
        this.downPackNum = Long.parseLong(downPackNum);
        this.upPayLoad = Long.parseLong(upPayLoad);
        this.downPayLoad = Long.parseLong(downPayLoad);
    }
    
    
    @Override
    public void readFields(DataInput in) throws IOException {
        this.upPackNum = in.readLong();
        this.downPackNum = in.readLong();
        this.upPayLoad = in.readLong();
        this.downPayLoad = in.readLong();
    }

    @Override
    public void write(DataOutput out) throws IOException {
        out.writeLong(upPackNum);
        out.writeLong(downPackNum);
        out.writeLong(upPayLoad);
        out.writeLong(downPayLoad);
    }
    
    @Override
    public String toString() {
        return upPackNum + "\t" + downPackNum + "\t" + upPayLoad + "\t" + downPayLoad;
    }
}

将HTTP_20130313143750.dat上传至hadoop HDFS文件系统中

运行MapReduce代码，查看输出的/outwlan/part-*文件下的内容

到此，相信大家对“MapReduce怎么处理手机通信流量统计”有了更深的了解，不妨来实际操作一番吧！这里是创新互联网站，更多相关内容可以进入相关频道进行查询，关注我们，继续学习！

新闻名称：MapReduce怎么处理手机通信流量统计
文章网址：http://scyanting.com/article/jejseh.html