irms模拟数据生成及数据分析

时间：2023-03-09 00:29:21
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));

	}

}

相关文章