1,代码

package mr;

import java.io.IOException;

import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.ArrayWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
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.output.FileOutputFormat; /**
* 使用ArrayWritable
*/
public class TrafficApp4 { public static void main(String[] args) throws Exception{
Configuration conf = new Configuration();
Job job = Job.getInstance(conf , TrafficApp4.class.getSimpleName());
job.setJarByClass(TrafficApp4.class); FileInputFormat.setInputPaths(job, args[]);
job.setMapperClass(TrafficMapper.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(LongArrayWritable.class); job.setReducerClass(TrafficReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(LongArrayWritable.class);
FileOutputFormat.setOutputPath(job, new Path(args[])); job.waitForCompletion(true);
} public static class TrafficMapper extends Mapper<LongWritable, Text, Text, LongArrayWritable>{
@Override
protected void map(LongWritable key, Text value,
Mapper<LongWritable, Text, Text, LongArrayWritable>.Context context)
throws IOException, InterruptedException {
String line = value.toString();
String[] splited = line.split("\t");
String phonenumber = splited[]; String upPackNum = splited[];
String downPackNum = splited[];
String upPayLoad = splited[];
String downPayLoad = splited[]; Text k2 = new Text(phonenumber);
LongArrayWritable v2 = new LongArrayWritable(upPackNum, downPackNum, upPayLoad, downPayLoad);
context.write(k2, v2);
}
} public static class TrafficReducer extends Reducer<Text, LongArrayWritable, Text, LongArrayWritable>{
@Override
protected void reduce(Text k2, Iterable<LongArrayWritable> v2s,
Reducer<Text, LongArrayWritable, Text, LongArrayWritable>.Context context)
throws IOException, InterruptedException { long upPackNum = 0L;
long downPackNum = 0L;
long upPayLoad = 0L;
long downPayLoad = 0L;
for (LongArrayWritable v2 : v2s) {
Writable[] values = v2.get();
upPackNum += ((LongWritable)values[]).get();
downPackNum += ((LongWritable)values[]).get();
upPayLoad += ((LongWritable)values[]).get();
downPayLoad += ((LongWritable)values[]).get();
} LongArrayWritable v3 = new LongArrayWritable(upPackNum, downPackNum, upPayLoad, downPayLoad);
context.write(k2, v3);
}
} public static class LongArrayWritable extends ArrayWritable{
/**
* 在调用的时候,首先调用该方法,然后调用set(Writable[])
*/
public LongArrayWritable() {
super(LongWritable.class);
}
/**
* 直接调用该方法即可
* @param values
*/
public LongArrayWritable(LongWritable[] values) {
super(LongWritable.class, values);
}
/**
* 直接调用该方法即可
* @param upPackNum
* @param downPackNum
* @param upPayLoad
* @param downPayLoad
*/
public LongArrayWritable(Long upPackNum, Long downPackNum, Long upPayLoad, Long downPayLoad) {
super(LongWritable.class);
LongWritable[] values = new LongWritable[];
values[] = new LongWritable(upPackNum);
values[] = new LongWritable(downPackNum);
values[] = new LongWritable(upPayLoad);
values[] = new LongWritable(downPayLoad);
super.set(values);
}
/**
* 直接调用该方法即可
* @param upPackNum
* @param downPackNum
* @param upPayLoad
* @param downPayLoad
*/
public LongArrayWritable(String upPackNum, String downPackNum, String upPayLoad, String downPayLoad) {
super(LongWritable.class);
LongWritable[] values = new LongWritable[];
values[] = new LongWritable(Long.parseLong(upPackNum));
values[] = new LongWritable(Long.parseLong(downPackNum));
values[] = new LongWritable(Long.parseLong(upPayLoad));
values[] = new LongWritable(Long.parseLong(downPayLoad));
super.set(values);
} @Override
public String toString() {
String[] array = super.toStrings();
return StringUtils.join(array, "\t");
}
} }

2,ArrayWritable的API

org.apache.hadoop.io
Class ArrayWritable

java.lang.Object
  

org.apache.hadoop.io.ArrayWritable
已实现的接口:
Writable

public class ArrayWritableextends Objectimplements Writable

A Writable for arrays containing instances of a class. The elements of this writable must all be instances of the same class. If this writable will be the input for a Reducer, you will need to create a subclass that sets the value to be of the proper type. For example: public class IntArrayWritable extends ArrayWritable { public IntArrayWritable() { super(IntWritable.class); } }


构造方法摘要
ArrayWritable(Class<? extends Writable> valueClass) 
           
ArrayWritable(Class<? extends Writable> valueClass, Writable[] values) 
           
ArrayWritable(String[] strings) 
           
方法摘要
 Writable[] get() 
           
 Class getValueClass() 
           
 void readFields(DataInput in) 
          Deserialize the fields of this object from in.
 void set(Writable[] values) 
           
 Object toArray() 
           
 String[] toStrings() 
           
 void write(DataOutput out) 
          Serialize the fields of this object to out.
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
构造方法详细信息

ArrayWritable

public ArrayWritable(Class<? extends Writable> valueClass)

ArrayWritable

public ArrayWritable(Class<? extends Writable> valueClass,
Writable[] values)

ArrayWritable

public ArrayWritable(String[] strings)
方法详细信息

getValueClass

public Class getValueClass()

toStrings

public String[] toStrings()

toArray

public Object toArray()

set

public void set(Writable[] values)

get

public Writable[] get()

readFields

public void readFields(DataInput in)
throws IOException
Description copied from interface: Writable
Deserialize the fields of this object from in.

For efficiency, implementations should attempt to re-use storage in the existing object where possible.

Specified by:
readFields in interface Writable
Parameters:
in - DataInput to deseriablize this object from.
Throws:
IOException

write

public void write(DataOutput out)
throws IOException
Description copied from interface: Writable
Serialize the fields of this object to out.

Specified by:
write in interface Writable
Parameters:
out - DataOuput to serialize this object into.
Throws:
IOException

 

 

基于MapReduce的手机流量统计分析的更多相关文章

  1. MapReduce的手机流量统计的案例

    程序:(另外一个关于单词计数的总结:http://www.cnblogs.com/DreamDrive/p/5492572.html) import java.io.IOException; impo ...

  2. 基于winpcap的以太网流量分析器(java)

    开发工具 IDE:eclipse -neon JDK:1.8 OS:Win10-64bit 主要功能 1.要求完成一个基于Winpcap的网络流量统计分析系统,具有易用.美观的界面. 2.完成局域网( ...

  3. 023_数量类型练习——Hadoop MapReduce手机流量统计

    1) 分析业务需求:用户使用手机上网,存在流量的消耗.流量包括两部分:其一是上行流量(发送消息流量),其二是下行流量(接收消息的流量).每种流量在网络传输过程中,有两种形式说明:包的大小,流量的大小. ...

  4. 第2节 mapreduce深入学习:8、手机流量汇总求和

    第2节 mapreduce深入学习:8.手机流量汇总求和 例子:MapReduce综合练习之上网流量统计. 数据格式参见资料夹 需求一:统计求和 统计每个手机号的上行流量总和,下行流量总和,上行总流量 ...

  5. MapReduce 经典案例手机流量排序的分析

    在进行流量排序之前,先要明白排序是发生在map阶段,排序之后(排序结束后map阶段才会显示100%完成)才会到reduce阶段(事实上reduce也会排序),.此外排序之前要已经完成了手机流量的统计工 ...

  6. 基于mapreduce的大规模连通图寻找算法

    基于mapreduce的大规模连通图寻找算法 当我们想要知道哪些账号是一个人的时候往往可以通过业务得到两个账号之间有联系,但是这种联系如何传播呢? 问题 已知每个账号之间的联系 如: A B B C ...

  7. 字节数转换为b,kb,mb,gb的方法 通用的手机流量计算方法

    //通用的手机流量计算方法 private String byteToMB(long size){ long kb = 1024; long mb = kb*1024; long gb = mb*10 ...

  8. MapReduce教程(一)基于MapReduce框架开发<转>

    1 MapReduce编程 1.1 MapReduce简介 MapReduce是一种编程模型,用于大规模数据集(大于1TB)的并行运算,用于解决海量数据的计算问题. MapReduce分成了两个部分: ...

  9. 基于MapReduce的贝叶斯网络算法研究参考文献

    原文链接(系列):http://blog.csdn.net/XuanZuoNuo/article/details/10472219 论文: 加速贝叶斯网络:Accelerating Bayesian ...

随机推荐

  1. MFC随笔记录——1

    这段时间用MFC做完了项目里的一个对图像处理(字迹匹配)的软件,通过项目的具体要求的一步一步的实现,我也学习到了很多以前困惑很久的问题,算是对自己的一个提高吧,把一些有技巧性的操作记在这里,给以后的自 ...

  2. CentOS7安装Oracle 11gR2 图文详解

    注:Oracle11gR2 X64安装 一.环境准备 安装包: 1.VMware-workstation-full-11.1.0-2496824.exe 2.CentOS-7-x86_64-DVD-1 ...

  3. Linux上jdk的安装(CentOS6.5)

    centos openjdk 安装 http://www.cnblogs.com/ilahsa/archive/2012/12/11/2813059.html 知CentOS6.5桌面版默认安装的是J ...

  4. C#3DES加密了解一下

    最近一个项目中,因为服务端是用的java开发的,客户端是用的C#,由于通信部分采用到了3DES加密,所以做个记录,以备以后需要的时候直接用. 这是对方(java)的加密算法,和网上流传的代码也差不多( ...

  5. JavaScript调试中Console命令

    JS调试中,用console.log 感觉比 alert 好用,不用弹出窗口,还要关闭.除了console.log()其他命令没怎么用过,先在这里记一下,用到时在看看 一.显示信息的命令 consol ...

  6. python 基础篇 16 递归和二分数查找与编码补充回顾

    编码回顾补充: 回顾编码问题:        编码相当于密码本,关系到二进制与看懂的文字的的对应关系.    最早期的密码本:        ascii码:只包含英文字母,数字,特殊字符.       ...

  7. 第16讲——C++中的代码重用

    C++的一个主要目标是促进代码重用.除了我们之前学的公有继承,我们在这一讲将介绍另一种代码重用的方法——类模板.

  8. Python调用MYSQL,将文件名和路径批量入库用法小结

    最近项目需要将大量的压缩文件导入到数据库中,所以开始总结用Python批量处理的办法,本次是首先将这些压缩文件的文件名提取出来,然后导入到数据库中. 由于涉及到路径的读取处理,所以方法有os模块和co ...

  9. 多线程 定时器 Timer TimerTask

    定时器是一种特殊的多线程,使用Timer来安排一次或者重复执行某个任务 package org.zln.thread; import java.util.Date; import java.util. ...

  10. 关于全球唯一标识符GUID

    在C#中的语法: Console.WriteLine(System.Guid.NewGuid()); Console.ReadKey(); System.Guid.NewGuid().ToString ...