Oracle SQL调优系列之体系结构学习笔记

柔光的暖阳◎ 2021-09-19 06:34 310阅读 0赞

Oracle体系结构由实例和一组数据文件组成，实例由SGA内存区，SGA意思是共享内存区，由share pool(共享池)、data buffer(数据缓冲区)、log buffer(日志缓冲区)组成  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9zbWlsZW5pY2t5LmJsb2cuY3Nkbi5uZXQ_size_16_color_FFFFFF_t_70]

SGA内存区的share pool是解析SQL并保存执行计划的，然后SQL根据执行计划获取数据时先看data buffer里是否有数据，没数据才从磁盘读，然后还是读到data buffer里，下次就直接读data buffer的，当SQL更新时，data buffer的数据就必须写入磁盘备份，为了保护这些数据，才有log buffer，这就是大概的原理简介  
系统结构关系图如图，图来自《收获，不止SQL优化》一书：![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9zbWlsZW5pY2t5LmJsb2cuY3Nkbi5uZXQ_size_16_color_FFFFFF_t_70 1]

下面介绍共享池、数据缓冲、日志缓冲方面调优的例子

**共享池相关例子**

未使用使用绑定变量的情况，进行一下批量写数据，在登录系统，经常用的sql是`select * from sys_users where username='admin'`或者什么什么的，假如有很多用户登录，就需要执行很多次这样类似的sql，能不能用一条SQL代表？意思是不需要Oracle优化器每次都解析sql获取执行计划，对于这种类似的sql是没必要的，Oracle提供了绑定变量的方法，可以用于调优sql，然后一堆sql就可以用

select * from sys_users where username=:x

这里用一个变量x表示，具体例子如下，

新建一张表来测试

create table t (x int);

不使用绑定遍历，批量写数据

begin 
    	for i in 1 .. 1000
    	loop
    		execute immediate
    		'insert into t values('|| i ||')';
    		commit;
    	end loop;
    end;
    /

输出

> 已用时间: 00: 00: 00.80

加上绑定遍历，绑定变量是用:x的形式

begin 
    	for i in 1 .. 100
    	loop
    		execute immediate
    		'insert into t values( :x )' using i;
    	commit;
    	end loop;
    end;
    /

> 已用时间: 00: 00: 00.05

**数据缓冲相关例子**  
这里介绍和数据缓存相关例子

(1) 清解析缓存

//创建一个表来测试
    SQL> create table t as select * from dba_objects;
    表已创建。
    //设置打印行数
    SQL> set linesize 1000
    //设置执行计划开启
    SQL> set autotrace on
    //打印出时间
    SQL> set timing on
    //查询一下数据
    SQL> select count(1) from t;
    
      COUNT(1)
    ----------
         72043
    
    已用时间:  00: 00: 00.10
    
    //清一下缓冲区缓存(ps:这个sql不能随便在生产环境执行)
    SQL> alter system flush buffer_cache;
    系统已更改。
    已用时间:  00: 00: 00.08
    
    //清一下共享池缓存(ps:这个sql不能随便在生产环境执行)
    SQL> alter system flush shared_pool;
    
    //再次查询，发现查询快了
    SQL> select count(1) from t;
    
      COUNT(1)
    ----------
         72043
    
    已用时间:  00: 00: 00.12
    
    SQL>

**日志缓冲相关例子**

这里说明一下，日志关闭是可以提供性能的，不过在生生产环境还是不能随便用，只能说是一些特定创建，SQL如：

alter table [表名] nologging;

**调优拓展知识**  
这些是看《收获，不止SQL优化》一书的小记

(1) 批量写数据事务问题  
对于循环批量事务提交的问题，commit放在循环内和放在循环外的区别，

放在循环内，每次执行就提交一次事务，这种时间相对比较少的

begin 
    	for i in 1 .. 1000
    	loop
    		execute immediate
    		'insert into t values('|| i ||')';
    		commit;
    	end loop;
    end;

放在循环外，sql循环成功，再提交一次事务，这种时间相对比较多一点

begin 
    	for i in 1 .. 1000
    	loop
    		execute immediate
    		'insert into t values('|| i ||')';
    	end loop;
    	commit;
    end;

《收获，不止SQL优化》一书提供的脚本，用于查看逻辑读、解析、事务数等等情况：

select s.snap_date,
           decode(s.redosize, null, '--shutdown or end--', s.currtime) "TIME",
           to_char(round(s.seconds / 60, 2)) "elapse(min)",
           round(t.db_time / 1000000 / 60, 2) "DB time(min)",
           s.redosize redo,
           round(s.redosize / s.seconds, 2) "redo/s",
           s.logicalreads logical,
           round(s.logicalreads / s.seconds, 2) "logical/s",
           physicalreads physical,
           round(s.physicalreads / s.seconds, 2) "phy/s",
           s.executes execs,
           round(s.executes / s.seconds, 2) "execs/s",
           s.parse,
           round(s.parse / s.seconds, 2) "parse/s",
           s.hardparse,
           round(s.hardparse / s.seconds, 2) "hardparse/s",
           s.transactions trans,
           round(s.transactions / s.seconds, 2) "trans/s"
      from (select curr_redo - last_redo redosize,
                   curr_logicalreads - last_logicalreads logicalreads,
                   curr_physicalreads - last_physicalreads physicalreads,
                   curr_executes - last_executes executes,
                   curr_parse - last_parse parse,
                   curr_hardparse - last_hardparse hardparse,
                   curr_transactions - last_transactions transactions,
                   round(((currtime + 0) - (lasttime + 0)) * 3600 * 24, 0) seconds,
                   to_char(currtime, 'yy/mm/dd') snap_date,
                   to_char(currtime, 'hh24:mi') currtime,
                   currsnap_id endsnap_id,
                   to_char(startup_time, 'yyyy-mm-dd hh24:mi:ss') startup_time
              from (select a.redo last_redo,
                           a.logicalreads last_logicalreads,
                           a.physicalreads last_physicalreads,
                           a.executes last_executes,
                           a.parse last_parse,
                           a.hardparse last_hardparse,
                           a.transactions last_transactions,
                           lead(a.redo, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_redo,
                           lead(a.logicalreads, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_logicalreads,
                           lead(a.physicalreads, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_physicalreads,
                           lead(a.executes, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_executes,
                           lead(a.parse, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_parse,
                           lead(a.hardparse, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_hardparse,
                           lead(a.transactions, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_transactions,
                           b.end_interval_time lasttime,
                           lead(b.end_interval_time, 1, null) over(partition by b.startup_time order by b.end_interval_time) currtime,
                           lead(b.snap_id, 1, null) over(partition by b.startup_time order by b.end_interval_time) currsnap_id,
                           b.startup_time
                      from (select snap_id,
                                   dbid,
                                   instance_number,
                                   sum(decode(stat_name, 'redo size', value, 0)) redo,
                                   sum(decode(stat_name,
                                              'session logical reads',
                                              value,
                                              0)) logicalreads,
                                   sum(decode(stat_name,
                                              'physical reads',
                                              value,
                                              0)) physicalreads,
                                   sum(decode(stat_name, 'execute count', value, 0)) executes,
                                   sum(decode(stat_name,
                                              'parse count (total)',
                                              value,
                                              0)) parse,
                                   sum(decode(stat_name,
                                              'parse count (hard)',
                                              value,
                                              0)) hardparse,
                                   sum(decode(stat_name,
                                              'user rollbacks',
                                              value,
                                              'user commits',
                                              value,
                                              0)) transactions
                              from dba_hist_sysstat
                             where stat_name in
                                   ('redo size',
                                    'session logical reads',
                                    'physical reads',
                                    'execute count',
                                    'user rollbacks',
                                    'user commits',
                                    'parse count (hard)',
                                    'parse count (total)')
                             group by snap_id, dbid, instance_number) a,
                           dba_hist_snapshot b
                     where a.snap_id = b.snap_id
                       and a.dbid = b.dbid
                       and a.instance_number = b.instance_number
                     order by end_interval_time)) s,
           (select lead(a.value, 1, null) over(partition by b.startup_time order by b.end_interval_time) - a.value db_time,
                   lead(b.snap_id, 1, null) over(partition by b.startup_time order by b.end_interval_time) endsnap_id
              from dba_hist_sys_time_model a, dba_hist_snapshot b
             where a.snap_id = b.snap_id
               and a.dbid = b.dbid
               and a.instance_number = b.instance_number
               and a.stat_name = 'DB time') t
     where s.endsnap_id = t.endsnap_id
     order by s.snap_date, time desc;

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