这篇文章主要讲解了“hadoop网站日志举例分析”,文中的讲解内容简单清晰,易于学习与理解,下面请大家跟着小编的思路慢慢深入,一起来研究和学习“hadoop网站日志举例分析”吧!
一、项目要求
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日志处理方法中的日志,仅指Web日志。其实并没有精确的定义,可能包括但不限于各种前端Web服务器——apache、lighttpd、nginx、tomcat等产生的用户访问日志,以及各种Web应用程序自己输出的日志。
二、需求分析: KPI指标设计
PV(PageView): 页面访问量统计
IP: 页面独立IP的访问量统计
Time: 用户每小时PV的统计
Source: 用户来源域名的统计
Browser: 用户的访问设备统计
下面我着重分析浏览器统计
三、分析过程
1、 日志的一条nginx记录内容
222.68.172.190 – – [18/Sep/2013:06:49:57 +0000] "GET /images/my.jpg HTTP/1.1" 200 19939
"http://www.angularjs.cn/A00n"
"Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/29.0.1547.66 Safari/537.36"
2、对上面的日志记录进行分析
remote_addr : 记录客户端的ip地址, 222.68.172.190
remote_user : 记录客户端用户名称, –
time_local: 记录访问时间与时区, [18/Sep/2013:06:49:57 +0000]
request: 记录请求的url与http协议, “GET /images/my.jpg HTTP/1.1″
status: 记录请求状态,成功是200, 200
body_bytes_sent: 记录发送给客户端文件主体内容大小, 19939
http_referer: 用来记录从那个页面链接访问过来的, “http://www.angularjs.cn/A00n”
http_user_agent: 记录客户浏览器的相关信息, “Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/29.0.1547.66 Safari/537.36″
3、java语言分析上面一条日志记录(使用空格切分)
String line = "222.68.172.190 - - [18/Sep/2013:06:49:57 +0000] /"GET /images/my.jpg HTTP/1.1/" 200 19939 /"http://www.angularjs.cn/A00n/" /"Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/29.0.1547.66 Safari/537.36/""; String[] elementList = line.split(" "); for(int i=0;i<elementList.length;i++){ System.out.println(i+" : "+elementList[i]); }
测试结果:
0 : 222.68.172.190 1 : - 2 : - 3 : [18/Sep/2013:06:49:57 4 : +0000] 5 : "GET 6 : /images/my.jpg 7 : HTTP/1.1" 8 : 200 9 : 19939 10 : "http://www.angularjs.cn/A00n" 11 : "Mozilla/5.0 12 : (Windows 13 : NT 14 : 6.1) 15 : AppleWebKit/537.36 16 : (KHTML, 17 : like 18 : Gecko) 19 : Chrome/29.0.1547.66 20 : Safari/537.36"
4、实体Kpi类的代码:
public class Kpi { private String remote_addr;// 记录客户端的ip地址 private String remote_user;// 记录客户端用户名称,忽略属性"-" private String time_local;// 记录访问时间与时区 private String request;// 记录请求的url与http协议 private String status;// 记录请求状态;成功是200 private String body_bytes_sent;// 记录发送给客户端文件主体内容大小 private String http_referer;// 用来记录从那个页面链接访问过来的 private String http_user_agent;// 记录客户浏览器的相关信息 private String method;//请求方法 get post private String http_version; //http版本 public String getMethod() { return method; } public void setMethod(String method) { this.method = method; } public String getHttp_version() { return http_version; } public void setHttp_version(String http_version) { this.http_version = http_version; } public String getRemote_addr() { return remote_addr; } public void setRemote_addr(String remote_addr) { this.remote_addr = remote_addr; } public String getRemote_user() { return remote_user; } public void setRemote_user(String remote_user) { this.remote_user = remote_user; } public String getTime_local() { return time_local; } public void setTime_local(String time_local) { this.time_local = time_local; } public String getRequest() { return request; } public void setRequest(String request) { this.request = request; } public String getStatus() { return status; } public void setStatus(String status) { this.status = status; } public String getBody_bytes_sent() { return body_bytes_sent; } public void setBody_bytes_sent(String body_bytes_sent) { this.body_bytes_sent = body_bytes_sent; } public String getHttp_referer() { return http_referer; } public void setHttp_referer(String http_referer) { this.http_referer = http_referer; } public String getHttp_user_agent() { return http_user_agent; } public void setHttp_user_agent(String http_user_agent) { this.http_user_agent = http_user_agent; } @Override public String toString() { return "Kpi [remote_addr=" + remote_addr + ", remote_user=" + remote_user + ", time_local=" + time_local + ", request=" + request + ", status=" + status + ", body_bytes_sent=" + body_bytes_sent + ", http_referer=" + http_referer + ", http_user_agent=" + http_user_agent + ", method=" + method + ", http_version=" + http_version + "]"; } }
5、kpi的工具类
package org.aaa.kpi; public class KpiUtil { /*** * line记录转化成kpi对象 * @param line 日志的一条记录 * @author tianbx * */ public static Kpi transformLineKpi(String line){ String[] elementList = line.split(" "); Kpi kpi = new Kpi(); kpi.setRemote_addr(elementList[0]); kpi.setRemote_user(elementList[1]); kpi.setTime_local(elementList[3].substring(1)); kpi.setMethod(elementList[5].substring(1)); kpi.setRequest(elementList[6]); kpi.setHttp_version(elementList[7]); kpi.setStatus(elementList[8]); kpi.setBody_bytes_sent(elementList[9]); kpi.setHttp_referer(elementList[10]); kpi.setHttp_user_agent(elementList[11] + " " + elementList[12]); return kpi; } }
6、算法模型: 并行算法
Browser: 用户的访问设备统计
– Map: {key:$http_user_agent,value:1}
– Reduce: {key:$http_user_agent,value:求和(sum)}
7、map-reduce分析代码
import java.io.IOException; import java.util.Iterator; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.FileInputFormat; import org.apache.hadoop.mapred.FileOutputFormat; import org.apache.hadoop.mapred.JobClient; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.MapReduceBase; import org.apache.hadoop.mapred.Mapper; import org.apache.hadoop.mapred.OutputCollector; import org.apache.hadoop.mapred.Reducer; import org.apache.hadoop.mapred.Reporter; import org.apache.hadoop.mapred.TextInputFormat; import org.apache.hadoop.mapred.TextOutputFormat; import org.hmahout.kpi.entity.Kpi; import org.hmahout.kpi.util.KpiUtil; import cz.mallat.uasparser.UASparser; import cz.mallat.uasparser.UserAgentInfo; public class KpiBrowserSimpleV { public static class KpiBrowserSimpleMapper extends MapReduceBase implements Mapper<Object, Text, Text, IntWritable> { UASparser parser = null; @Override public void map(Object key, Text value, OutputCollector<Text, IntWritable> out, Reporter reporter) throws IOException { Kpi kpi = KpiUtil.transformLineKpi(value.toString()); if(kpi!=null && kpi.getHttP_user_agent_info()!=null){ if(parser==null){ parser = new UASparser(); } UserAgentInfo info = parser.parseBrowserOnly(kpi.getHttP_user_agent_info()); if("unknown".equals(info.getUaName())){ out.collect(new Text(info.getUaName()), new IntWritable(1)); }else{ out.collect(new Text(info.getUaFamily()), new IntWritable(1)); } } } } public static class KpiBrowserSimpleReducer extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable>{ @Override public void reduce(Text key, Iterator<IntWritable> value, OutputCollector<Text, IntWritable> out, Reporter reporter) throws IOException { IntWritable sum = new IntWritable(0); while(value.hasNext()){ sum.set(sum.get()+value.next().get()); } out.collect(key, sum); } } public static void main(String[] args) throws IOException { String input = "hdfs://127.0.0.1:9000/user/tianbx/log_kpi/input"; String output ="hdfs://127.0.0.1:9000/user/tianbx/log_kpi/browerSimpleV"; JobConf conf = new JobConf(KpiBrowserSimpleV.class); conf.setJobName("KpiBrowserSimpleV"); String url = "classpath:"; conf.addResource(url+"/hadoop/core-site.xml"); conf.addResource(url+"/hadoop/hdfs-site.xml"); conf.addResource(url+"/hadoop/mapred-site.xml"); conf.setMapOutputKeyClass(Text.class); conf.setMapOutputValueClass(IntWritable.class); conf.setOutputKeyClass(Text.class); conf.setOutputValueClass(IntWritable.class); conf.setMapperClass(KpiBrowserSimpleMapper.class); conf.setCombinerClass(KpiBrowserSimpleReducer.class); conf.setReducerClass(KpiBrowserSimpleReducer.class); conf.setInputFormat(TextInputFormat.class); conf.setOutputFormat(TextOutputFormat.class); FileInputFormat.setInputPaths(conf, new Path(input)); FileOutputFormat.setOutputPath(conf, new Path(output)); JobClient.runJob(conf); System.exit(0); } }
8、输出文件log_kpi/browerSimpleV内容
AOL Explorer 1
Android Webkit 123
Chrome 4867
CoolNovo 23
Firefox 1700
Google App Engine 5
IE 1521
Jakarta Commons-HttpClient 3
Maxthon 27
Mobile Safari 273
Mozilla 130
Openwave Mobile Browser 2
Opera 2
Pale Moon 1
Python-urllib 4
Safari 246
Sogou Explorer 157
unknown 4685
8 R制作图片
data<-read.table(file="borwer.txt",header=FALSE,sep=",")
names(data)<-c("borwer","num")
qplot(borwer,num,data=data,geom="bar")
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