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使用外部表分析eygle.com的网站访问日志

作者:eygle 来源:eygle (2007-02-06 16:41:10)

  经过使用Oracle的外部表对Oracle的警告日志文件、跟踪文件进行获取和分析之后,我发现外部表实在是非常易用,甚至到了随心所欲的境地(当然外部表尚不能修改外部文件)。

  使用外部表可以很容易的实现网站的访问日志分析。

  虽然使用Awstats等工具也可以实现,可是使用Oracle来分析我们更应该得心应手。

  而且这一切还是有那么一点点Cool的。

  好了,闲言少叙,让我们来看一下我分析的过程。

  首先创建路径指向日志存放目录:

  [oracle@jumper elog]$ pwd

  /opt/oracle/elog

  [oracle@jumper elog]$ ls

  eygle_access_log.20061016

  [oracle@jumper elog]$ sqlplus "/ as sysdba"

  SQL*Plus: Release 9.2.0.4.0 - Production on Wed Oct 18 08:59:35 2006

  Copyright (c) 1982, 2002, Oracle Corporation. All rights reserved.

  Connected to:

  Oracle9i Enterprise Edition Release 9.2.0.4.0 - Production

  With the Partitioning option

  JServer Release 9.2.0.4.0 - Production

  SQL> create or replace directory elog

  2 as '/opt/oracle/elog';

  Directory created.

  然后我将这个路径的访问权限授予eygle用户来进行具体操作:

  SQL> grant read,write on directory elog to eygle;

  Grant succeeded.

  选择合适的分隔符创建外部表:

  SQL> connect eygle/eygle

  Connected.

  SQL> create table eygle_access_log_20061016

  2 ( ip_address_date varchar2(100),

  3 acc_file varchar2(400),

  4 acc_cdsz varchar2(20),

  5 acc_url varchar2(400),

  6 left_blank varchar2(10),

  7 acc_agent varchar2(400))

  8 organization external (

  9 type oracle_loader

  10 default directory ELOG

  11 access parameters (

  12 records delimited by newline

  13 nobadfile

  14 nodiscardfile

  15 nologfile

  16 fields terminated by '"'

  17 missing field values are null

  18 )

  19 location('eygle_access_log.20061016')

  20 ) reject limit unlimited

  21 /

  Table created.

  此时我们就可以对eygle.com的2006年10月16日的访问日志进行分析了。

  我们可以先看一下各个字段的分界结果,示例如下:

  SQL> select ip_address_date from eygle_access_log_20061016

  2 where rownum <11;

  IP_ADDRESS_DATE

  -------------------------------------------------------------

  38.102.128.140 - - [16/Oct/2006:00:00:17 +0800]

  66.249.65.113 - - [16/Oct/2006:00:00:19 +0800]

  202.160.178.221 - - [16/Oct/2006:00:00:35 +0800]

  59.36.78.100 - - [16/Oct/2006:00:00:37 +0800]

  59.36.78.100 - - [16/Oct/2006:00:00:38 +0800]

  72.30.61.8 - - [16/Oct/2006:00:00:38 +0800]

  221.217.84.230 - - [16/Oct/2006:00:00:42 +0800]

  221.217.84.230 - - [16/Oct/2006:00:00:42 +0800]

  74.6.65.236 - - [16/Oct/2006:00:01:07 +0800]

  74.6.73.36 - - [16/Oct/2006:00:01:09 +0800]

  10 rows selected.

  通过SQL析取出访问的ip地址:

  SQL> select substr(ip_address_date,1,instr(ip_address_date,' ')) ip_address

  2 from eygle_access_log_20061016 where rownum <11;

  IP_ADDRESS

  ---------------------------------------------------------------------------

  38.102.128.140

  66.249.65.113

  202.160.178.221

  59.36.78.100

  59.36.78.100

  72.30.61.8

  221.217.84.230

  221.217.84.230

  74.6.65.236

  74.6.73.36

  10 rows selected.

  接下来我们就可以很容易的获得当日访问我站点的独立IP数量了:

  SQL> set timing on

  SQL> select count(distinct(substr(ip_address_date,1,instr(ip_address_date,' ')))) uip

  2 from eygle_access_log_20061016;

  UIP

  ----------

  7534

  Elapsed: 00:00:06.86

  因为外部表的处理性能上要差一些,我们记录了一下时间,以上查询大约用了7秒的时间。

  我们可以对比一下数据库表的性能。

  首先将日志加载到数据库表中:

  SQL> create table ealog as

  2 select * from eygle_access_log_20061016;

  Table created.

  SQL> desc ealog;

  Name Null? Type

  ----------------------------------------------------------------- -------- --------------------------------------------

  IP_ADDRESS_DATE VARCHAR2(100)

  ACC_FILE VARCHAR2(400)

  ACC_CDSZ VARCHAR2(20)

  ACC_URL VARCHAR2(400)

  LEFT_BLANK VARCHAR2(10)

  ACC_AGENT VARCHAR2(400)

  SQL> select count(*) from ealog;

  COUNT(*)

  ----------

  165443

  然后我们强制刷新Buffer Cache,消除Cache的影响,再次执行查询:

  SQL> alter session set events = 'immediate trace name flush_cache';

  Session altered.

  Elapsed: 00:00:00.03

  SQL> select count(distinct(substr(ip_address_date,1,instr(ip_address_date,' ')))) uip

  2 from ealog;

  UIP

  ----------

  7528

  Elapsed: 00:00:02.15

  此时用了大约2秒的时间,也就是说,外部表的性能较数据库表大约慢了3倍左右。

  继续,我们可以查询当日网站中,哪些网页是被最频繁访问的:

  SQL> select replace((replace(acc_file,'GET ','www.eygle.com')),'HTTP/1.1') accfile,ct from (

  2 select ACC_FILE,count(*) ct from eygle_access_log_20061016

  3 where acc_file like '%htm%'

  4 group by acc_file order by ct desc)

  5 where rownum <21;

  ACCFILE CT

  -------------------------------------------------------------------------------- ----------

  www.eygle.com/index-tech.htm 110

  www.eygle.com/archives/2006/10/wish_home.html 103

  www.eygle.com/index-ha.htm 79

  www.eygle.com/me/fairy_tale_leaf.htm 77

  www.eygle.com/archives/2006/11/use_oracle_external_table.html 73

  www.eygle.com/index-sql.htm 69

  www.eygle.com/archives/2006/10/tom_oracle_9i10g.html 68

  www.eygle.com/archives/2008/08/my_book_services.html 63

  www.eygle.com/archives/2006/11/welcome_friend.html 62

  www.eygle.com/archives/2006/10/veritas_vcs_simulator.html 61

  www.eygle.com/index-case.htm 60

  www.eygle.com/archives/2004/08/aoaouiiciona.html 59

  www.eygle.com/archives/2006/08/oracle_fundbook_recommand.html 52

  www.eygle.com/archives/2006/08/5460_8174.html 49

  www.eygle.com/archives/2004/12/gmailaeaeoa.html 48

  www.eygle.com/archives/2005/06/howlsmovingcast.html 48

  www.eygle.com/gbook/index.html 48

  www.eygle.com/index-hist.htm 44

  www.eygle.com/index-special.htm 41

  www.eygle.com/index-f&l.htm 37

  20 rows selected.

  Elapsed: 00:00:06.31

  SQL>

  通过外部表及SQL查询,只要日志文件中存在的信息,都可以很容易的被获取和分析.

  -The End-


(http://www.fanqiang.com)

原文链接:http://www.eygle.com/archives/2006/10/use_external_talbe_analyze_eyglecom_log.html

 
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