irms模拟数据生成及数据分析

一、数据准备

1、每天生成随机一个文本，每小时向文本中追加2次数据，每次10万条

随机数据生成：

2,32  * * * *  bash /mnt/jediael/irms/signalGenerator/signalGenerator.sh >> /home/jediael/sg.log 2>&1

类：SignalGenerator

2、每天将前一天生成的数据文本导入HDFS

32 0 * * * bash /mnt/jediael/irms/signalGenerator/copySignalToHdfs.sh >>/home/jediael/sg.log 2>&1

二、数据分析

1、每天执行一次数据分析，将结果输出到hdfs文本中。

42 0 * * * bash /mnt/jediael/irms/signalparser/signalParser.sh >>/home/jediael/sg.log 2>&1

类：SignalParser

程序文件：

/mnt/jediael/irms/signalGenerator/signalGenerator.sh

#!/bin/bash
export JAVA_HOME=/usr/java/jdk1.7.0_51
export PATH=$JAVA_HOME/bin:$PATH
export CLASSPATH=$CLASSPATH:/mnt/jediael/irms/signalGenerator/
java SignalGenerator 

/mnt/jediael/irms/signalGenerator/copySignalToHdfs.sh

#!/bin/bash
export JAVA_HOME=/usr/java/jdk1.7.0_51
PATH=/mnt/jediael/hadoop-1.2.1/bin/:/mnt/jediael/hbase-0.94.26/bin:/mnt/jediael/tomcat-7.0.54/bin:$JAVA_HOME/bin:$PATH
hadoop fs -copyFromLocal /mnt/jediael/irms/signalGenerator/`date -d "-1 day" +%Y%m%d`.txt /irms/signal >> sg.log

/mnt/jediael/irms/signalparser/signalParser.sh

#!/bin/bash

export JAVA_HOME=/usr/java/jdk1.7.0_51
PATH=/mnt/jediael/hadoop-1.2.1/bin/:/mnt/jediael/hbase-0.94.26/bin:/mnt/jediael/tomcat-7.0.54/bin:$JAVA_HOME/bin:$PATH
hadoop jar signalgenerator.jar  /irms/signal/`date -d "-1 day" +%Y%m%d`.txt  /irms/result/`date -d "-1 day" +%Y%m%d`

SignalGenerator.java

package com.gmcc.irms.util;

import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStream;
import java.text.SimpleDateFormat;
import java.util.Random;

//此类用于模拟生成信令数据,每次生成100000条

public class SignalGenerator {
	// 业务类型，如呼入、呼出、发短信、收短信、上网、WLAN等
	private int activeType = 0;

	private String getNextSign() {
		String sign = "";
		Random rand = new Random();
		activeType = rand.nextInt(6);
		// 主叫号码
		String callNum = "1390222" + rand.nextInt(9) + rand.nextInt(9)
				+ rand.nextInt(9) + rand.nextInt(9);
		// 被叫号码
		String beCallNum = "1390222" + rand.nextInt(9) + rand.nextInt(9)
				+ rand.nextInt(9) + rand.nextInt(9);
		// 时长、或者是流量
		String callDuration = "";
		for (int i = 0; i < 16; i++) {
			callDuration += rand.nextInt(9);
		}
		sign = activeType + callNum + beCallNum + callDuration;
		for (int i = 0; i < 800; i++) {
			sign += rand.nextInt(9);
		}
		return sign;

	}

	public static void main(String[] args) throws IOException {

		SimpleDateFormat sdf = new SimpleDateFormat("yyyyMMdd");
		long time = System.currentTimeMillis();
		String fileName = sdf.format(time) + ".txt";
		OutputStream os = new FileOutputStream(fileName, true);
		SignalGenerator sg = new SignalGenerator();
		String newline = System.getProperty("line.separator");

		for (int i = 0; i < 100000; i++) {
			os.write((sg.getNextSign() + newline).getBytes());

		}
		os.flush();
		os.close();

	}

}

SignalParser.java

package com.gmcc.irms.signal;

import java.io.IOException;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
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;

public class SignalParser {
	public static void main(String[] args) throws Exception {

		Job job = new Job();
		job.setJarByClass(SignalParser.class);
		job.setJobName("signal parser");
		FileInputFormat.addInputPath(job, new Path(args[0]));
		FileOutputFormat.setOutputPath(job, new Path(args[1]));
		job.setMapperClass(SignalParserMapper.class);
		job.setReducerClass(SignalParserReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(Text.class);
		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}
}

class SignalParserMapper extends Mapper<LongWritable, Text, Text, Text> {

	@Override
	public void map(LongWritable key, Text value, Context context)
			throws IOException, InterruptedException {
		String line = value.toString();
		// 业务类型
		String activeType = line.substring(0, 1);
		// 主叫电话号码
		String customer = line.substring(1, 12);
		// 通话时长、web时长、wlan时长
		int duration = Integer.parseInt(line.substring(23, 30));

		context.write(new Text(customer),new Text(activeType + "," + duration));

	}
}

class SignalParserReducer extends Reducer<Text, Text, Text, Text> {
	@Override
	public void reduce(Text key, Iterable<Text> values, Context context)
			throws IOException, InterruptedException {
		//总通话时长
		int sumCallDuration = 0;
		//通话次数
		int callTimes = 0;
		//发送短信次数
		int smsTimes = 0;
		//上网总时长
		int sumWebDuration = 0;
		//上网次数
		int webTimes = 0;
		//WLAN总时长
		int sumWlanDuration = 0;
		//WLAN次数
		int wlanTimes = 0;

		String[] valueArray = null;
		int activeType = -1;
		int duration = -1;
		for (Text value:values){

			valueArray = value.toString().split(",");
			System.out.println(valueArray[0]+" a "+valueArray[1]);
			activeType = Integer.parseInt(valueArray[0]);
			duration = Integer.parseInt(valueArray[1]);
			if(activeType == 0){
				//呼出
				sumCallDuration += duration;
				callTimes++;
			}else if(activeType == 2){
				//发sms
				smsTimes++;
			}else if(activeType == 4){
				//上网
				sumWebDuration += duration;
				webTimes ++;
			}else if(activeType == 5){
				//WLAN
				sumWlanDuration += duration;
				wlanTimes ++;
			}else{

			}
		}

		context.write(key, new Text(sumCallDuration + "\t" + callTimes + "\t" +smsTimes+"\t" + sumWebDuration+"\t" + webTimes+"\t" + sumWebDuration+"\t" + webTimes));
	}
}