DBA_Oracle性能优化的基本方法概述(方法论)

2014-12-18 Created By BaoXinjian

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Oracle 性能优化的基本方法概述

  • 1)设立合理的性能优化目标。
  • 2)测量并记录当前性能。
  • 3)确定当前Oracle性能瓶颈(Oracle等待什么、哪些SQL语句是该等待事件的成分)。
  • 4)把等待事件记入跟踪文件。
  • 5)确定当前的OS瓶颈。
  • 6)优化所需的成分(应用程序、数据库、I/O、争用、OS等)。
  • 7)跟踪并实施更改控制过程。
  • 8)测量并记录当前性能
  • 9)重复步骤3到7,直到满足优化目标

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Step1.设立合理的性能优化目标

重点:关于设立目标的最重要的一点是它们必须是可量化和可达到的。

方法:目标必须是当前性能和所需性能的的陈述形式的语句。只需填写下列语句中的空格即可。

花费了(时/分/秒),但要求它在 (时/分/秒)内执行。

使用了(资源量),  但它不能使用超过。

Step2. 测量并记录当前性能

重点:

(1).需要在峰值活动时间获得当前系统性能快照

(2).关键是要在出现性能问题的时间段内采集信息

(3).必须在合理的时间段上采集,一般在峰值期间照几个为期15分钟的快照

方法:执行STATSPACK

(1). 建立性能快照表空间

sqlplus sys as sysdba

create tablespace perfstat datafile '/u02/oradata/dbnms/perfstat.dbf' size 500M extent management local;

(2). 安装STATSPACK

 @$ORACLE_HOME/rdbms/admin/spcreate.sql;

(3). 获取性能数据,可以生成多个快照

 sqlplus perfstat

 execute statspack.snap;

(4). 生成性能快照的报表

 sqlplus perfstat

 select min(snap_id) snapid_min, max(snap_id) snapid_max from stats$snapshot;

 @$ORACLE_HOME/rdbms/admin/spreport;

(5). 该报告中有关于性能的重要信息,如前5位的等待事件、cache大小、各种内存结构的命中率、每秒及每事务逻辑、物理读写数据块数、性能最差的sql语句等

Step3.确定当前Oracle性能瓶颈

重点:

从Oracle 等待接口v$system_event、v$session_event和v$session_wait中获得等待事件,进而找出影响性能的对象和sql语句

方法:

(1). 利用v$system_event视图执行下面的查询查看数据库中某些常见的等待事件:

select * from v$system_event
where event in ('buffer busy waits',
'db file sequential read',
'db file scattered read',
'enqueue',
'free buffer waits',
'latch free',
'log file parallel write',
'log file sync');

(2). 接着,利用下面对v$session_event和v$session视图进行的查询,研究具有对上面显示的内容有贡献的等待事件的会话:

select se.sid,s.username,se.event,se.total_waits,se.time_waited,se.average_wait
from v$session s,v$session_event se
where s.sid = se.sid
and se.event not like 'SQL*Net%'
and s.status = 'ACTIVE'
and s.username is not null;

(3). 使用下面查询找到与所连接的会话有关的当前等待事件。这些信息是动态的,为了查看一个会话的等待最多的事件是什么,需要多次执行此查询。

select sw.sid,s.username,sw.event,sw.wait_time,sw.state,sw.seconds_in_wait SEC_IN_WAIT
from v$session s,v$session_wait sw
where s.sid = sw.sid
and sw.event not like 'SQL*Net%'
and s.username is not null
order by sw.wait_time desc;

(4). 查询会话等待事件的详细信息

select sid,event,p1text,p1,p2text,p2,p3text,p3
from v$session_wait
where sid between &1 and &2
and event not like '%SQL%'
and event not like '%rdbms%';

(5). 利用P1、P2的信息,找出等待事件的相关的段

select owner,segment_name,segment_type,tablespace_name
from dba_extents
where file_id = &fileid_in
and &blockid_in between block_id and block_id + blocks - 1;

(6). 获得操作该段的sql语句:

select sid, getsqltxt(sql_hash_value,sql_address)
from v$session
where sid = &sid_in;

(7). getsqltxt函数

create or replace
function GetSQLtxt (hashaddr_in in v$sqltext.hash_value%type,
addr_in in v$sqltext.address%type)
return varchar2
is
temp_sqltxt varchar2(32767);
cursor sqlpiece_cur
is
select piece,sql_text
from v$sqltext
where hash_value = hashaddr_in
and address = addr_in
order by piece;
begin
for sqlpiece_rec in sqlpiece_cur
loop
temp_sqltxt := temp_sqltxt || sqlpiece_rec.sql_text;
end loop;
return temp_sqltxt;
end GetSQLtxt;

(8). 至此已经找到影响性能的对象和sql语句,可以有针对性地优化

Step4. 把等待事件记入跟踪文件

重点:

如果在跟踪系统上的等待事件时,由于某种原因遇到了麻烦,则可以将这些等待事件记入一个跟踪文件。

方法:

(1). 对于当前会话:

alter session set timed_statistics=true;

alter session set max_dump_file_size=unlimited;

alter session set events '10046 trace name context forever, level 12';

执行应用程序,然后在USER_DUMP_DEST指出的目录中找到跟踪文件。

查看文件中以词WAIT开始的所有行。

(2). 对于其它的会话, 确定会话的进程ID(SPID),下面的查询识别出名称以A开始的所有用户的会话进程ID:

select S.Username, P.Spid from V$SESSION S, V$PROCESS P
where S.PADDR = P.ADDR and S.Username like 'A%';

(3). 以 sysdba 进入sqlplus执行

alter session set timed_statistics=true;

alter session set max_dump_file_size=unlimited;

oradebug setospid <SPID>

oradebug unlimit

oradebug event 10046 trace name context forever, level X /* Where X = (1,4,8,12) */

跟踪某个时间间隔得会话应用程序。

在USER_DUMP_DEST 的值指出的目录中利用SPID查看跟踪文件

查看文件中以词WAIT开始的所有行。

Step5. 确定当前OS瓶颈

(1). Windows NT上的监控

使用控制面板-〉管理工具-〉性能即可

(2). UNIX上的监控

使用通用性的工具,包括sar、iostat、cpustat、mpstat、netstat、top、osview等。

I. CPU使用情况

sar -u 5 1000

%sys和%wio的数值应该小于百分之10到15

II. 设备使用情况

sar -d 5 1000

在%busy超过60%时,最佳设备利用率开始降低;在具有足够磁盘高速缓存的系统上,认为avserv为100毫秒的值非常高。

III. 虚拟内存使用情况

vmstat -S 5 1000

执行队列(r)应该明确的平均小于(2*CPU数目)

Step6.优化所需的成分(应用程序、数据库、I/O、争用、OS等)

Step7.跟踪并实施更改控制过程

Step8.测量并记录当前性能

Step9.重复步骤3到7,直到满足优化目标

Thanks and Regards

转载 一江水-http://www.cnblogs.com/rootq/archive/2008/09/03/1282690.html

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" 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