這篇文章主要講解了“hadoop網(wǎng)站日志舉例分析”，文中的講解內(nèi)容簡單清晰，易于學(xué)習(xí)與理解，下面請大家跟著小編的思路慢慢深入，一起來研究和學(xué)習(xí)“hadoop網(wǎng)站日志舉例分析”吧！
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一、項目要求
日志處理方法中的日志，僅指Web日志。其實并沒有精確的定義，可能包括但不限于各種前端Web服務(wù)器——apache、lighttpd、nginx、tomcat等產(chǎn)生的用戶訪問日志，以及各種Web應(yīng)用程序自己輸出的日志。
二、需求分析： KPI指標(biāo)設(shè)計
PV(PageView): 頁面訪問量統(tǒng)計
IP: 頁面獨立IP的訪問量統(tǒng)計
Time: 用戶每小時PV的統(tǒng)計
Source: 用戶來源域名的統(tǒng)計
Browser: 用戶的訪問設(shè)備統(tǒng)計
下面我著重分析瀏覽器統(tǒng)計
三、分析過程
1、 日志的一條nginx記錄內(nèi)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、對上面的日志記錄進行分析
remote_addr : 記錄客戶端的ip地址, 222.68.172.190
remote_user : 記錄客戶端用戶名稱, –
time_local: 記錄訪問時間與時區(qū), [18/Sep/2013:06:49:57 +0000]
request: 記錄請求的url與http協(xié)議, “GET /images/my.jpg HTTP/1.1″
status: 記錄請求狀態(tài),成功是200, 200
body_bytes_sent: 記錄發(fā)送給客戶端文件主體內(nèi)容大小, 19939
http_referer: 用來記錄從那個頁面鏈接訪問過來的, “http://www.angularjs.cn/A00n”
http_user_agent: 記錄客戶瀏覽器的相關(guān)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語言分析上面一條日志記錄（使用空格切分）
重慶分公司
重慶分公司
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測試結(jié)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、實體Kpi類的代碼：
public class Kpi {
private String remote_addr;// 記錄客戶端的ip地址
private String remote_user;// 記錄客戶端用戶名稱,忽略屬性"-"
private String time_local;// 記錄訪問時間與時區(qū)
private String request;// 記錄請求的url與http協(xié)議
private String status;// 記錄請求狀態(tài)；成功是200
private String body_bytes_sent;// 記錄發(fā)送給客戶端文件主體內(nèi)容大小
private String http_referer;// 用來記錄從那個頁面鏈接訪問過來的
private String http_user_agent;// 記錄客戶瀏覽器的相關(guān)信息
private String method;//請求方法 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的工具類
package org.aaa.kpi;
public class KpiUtil {
/***
* line記錄轉(zhuǎn)化成kpi對象
* @param line 日志的一條記錄
* @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: 用戶的訪問設(shè)備統(tǒng)計
– Map: {key:$http_user_agent,value:1}
– Reduce: {key:$http_user_agent,value:求和(sum)}
7、map-reduce分析代碼
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 {
UASparser parser = null;
@Override
public void map(Object key, Text value,
OutputCollector 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{
@Override
public void reduce(Text key, Iterator value,
OutputCollector 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、輸出文件log_kpi/browerSimpleV內(nèi)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制作圖片
data<-read.table(file="borwer.txt",header=FALSE,sep=",")
names(data)<-c("borwer","num")
qplot(borwer,num,data=data,geom="bar")
感謝各位的閱讀，以上就是“hadoop網(wǎng)站日志舉例分析”的內(nèi)容了，經(jīng)過本文的學(xué)習(xí)后，相信大家對hadoop網(wǎng)站日志舉例分析這一問題有了更深刻的體會，具體使用情況還需要大家實踐驗證。這里是創(chuàng)新互聯(lián)，小編將為大家推送更多相關(guān)知識點的文章，歡迎關(guān)注！
名稱欄目：hadoop網(wǎng)站日志舉例分析
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