PLSQL_性能优化系列20_Oracle Result Cash结果缓存

20150528 Created By BaoXinjian

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SQL 查询结果高速缓存可在数据库内存中对查询结果集和查询碎片启用显式高速缓存。

存储在共享池（Share Pool）中的专用内存缓冲区可用于存储和检索高速缓存的结果。

对查询访问的数据库对象中的数据进行修改后，存储在该高速缓存中的查询结果将失效。

虽然SQL 查询高速缓存可用于任何查询，但最适用于需要访问大量行却仅返回其中一少部分的语句。 数据仓库应用程序大多属于这种情况。

1. 注意点：

(1). RAC 配置中的每个节点都有一个专用的结果高速缓存。

一个实例的高速缓存结果不能供另一个实例使用。

但是，失效会对多个实例产生影响。

要处理RAC 实例之间与SQL 查询结果高速缓存相关的所有同步操作，需对每个实例使用专门的RCBG 进程。

(2). 通过并行查询，可对整个结果进行高速缓存（在RAC 中，是在查询协调程序实例上执行高速缓存的），但单个并行查询进程无法使用高速缓存。

2.  简言之：

高速缓存查询或查询块的结果以供将来重用。

可跨语句和会话使用高速缓存，除非该高速缓存已过时。

3. 优点：

可扩展性

降低内存使用量

4. 适用的语句：

访问多行

返回少数行

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查询优化程序根据初始化参数文件中RESULT_CACHE_MODE 参数的设置管理结果高速缓存机制。

可以使用此参数确定优化程序是否将查询结果自动发送到结果高速缓存中。

可以在系统和会话级别设置RESULT_CACHE_MODE 参数。

参数值可以是AUTO、MANUAL 和FORCE：

(1) 设置为AUTO 时，优化程序将根据重复的执行操作确定将哪些结果存储在高速缓存中。

(2) 设置为MANUAL（默认值）时，必须使用RESULT_CACHE 提示指定在高速缓存中存储特定结果。

(3) 设置为FORCE 时，所有结果都将存储在高速缓存中。

注：对于AUTO 和FORCE 设置，如果语句中包含[NO_]RESULT_CACHE 提示，则该提示优先于参数设置。

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可以改变初始化参数文件中的多种参数设置，以管理数据库的SQL 查询结果高速缓存。

默认情况下，数据库会为SGA 中共享池(Share Pool)内的结果高速缓存分配内存。

分配给结果高速缓存的内存大小取决于SGA的内存大小以及内存管理系统。

可以通过设置RESULT_CACHE_MAX_SIZE参数来更改分配给结果高速缓存的内存。

如果将结果高速缓存的值设为0，则会禁用此结果高速缓存。

此参数的值将四舍五入到不超过指定值的32 KB的最大倍数。如果四舍五入得到的值是0，则会禁用该功能。

使用RESULT_CACHE_MAX_RESULT参数可以指定任一结果可使用的最大高速缓存量。

默认值为5%，但可指定1 到100 之间的任一百分比值。可在系统和会话级别上实施此参数。

使用RESULT_CACHE_REMOTE_EXPIRATION参数可以指定依赖于远程数据库对象的结果保持有效的时间（以分钟为单位）。

默认值为0，表示不会高速缓存使用远程对象的结果。

将此参数设置为非零值可能会生成过时的信息：例如，当结果使用的远程表在远程数据库上发生了更改时。

使用以下初始化参数进行管理：

1. RESULT_CACHE_MAX_SIZE

– 此参数设置分配给结果高速缓存的内存。

– 如果将其值设为0，则会禁用结果高速缓存。

– 默认值取决于其它内存设置（memory_target的0.25% 或sga_target 的0.5% 或shared_pool_size 的1%）

– 不能大于共享池的75%

2. RESULT_CACHE_MAX_RESULE

– 设置单个结果的最大高速缓存

– 默认值为5%

3. RESULT_CACHE_REMOTE_EXPIRATION

– 根据远程数据库对象设置高速缓存结果的过期时间

– 默认值为0

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAATCAIAAAAf7rriAAABHklEQVQ4jc3Tv0sCcRjH8Wc4/wL9H4T0P3CpXYQcHQpuFIQayjvXQrnulhosHDpQsBZB8Q9wuWu1QVBcbMtNyaAm3y0e/fC4Lmvo4bO++D6fB74CLJdPm0X+MRaRn2HuowziDFNMVBFhajDvsHB4GYXBMQZxRikeVBHh0WDeDo+jKzz5gJ8dXjfAU4NZm4UbEse+4uC1qVYplSgU2Ntf4aHXeXrGLBjX65TLaEXyeTIZdrYjCskEIpLdRdMwTWybOxc/3GpxfsHpCUfH5HKk0xGF5JaHi1gm9jWuP3Ycbm+o1bAsDg9Q1U9YC8b9Pt0uzSZXl/LdrOHxmF6PTodGg0oFXY8oJLzOuveyf+f1vB8si17EDFj7zz5GyPwKvwECQrZ4yvBSdAAAAABJRU5ErkJggg==" alt="" />四、通过Hint测试Result Cashe

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Step1. 创建测试数据表gavin.test_resultcache

create table gavin.test_resultcache as select * from dba_objects;

Step2.1 第一次运行select count(*) from gavin.test_resultcache;

我们第一次执行该SQL可以看到consistent gets和physical reads大致相同

SQL> set autotrace on;
SQL> select count(*) from gavin.test_resultcache;

  COUNT(*)
----------
     73258

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=ALL_ROWS (Cost=293 Card=1)
   1    0   SORT (AGGREGATE)
   2    1     TABLE ACCESS (FULL) OF 'TEST_RESULTCACHE' (TABLE) (Cost=293 Card=72217)

Statistics
----------------------------------------------------------
         28  recursive calls
          0  db block gets
       1118  consistent gets
       1044  physical reads
          0  redo size
        352  bytes sent via SQL*Net to client
        503  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          1  rows processed

Step2.2  第二次运行select count(*) from gavin.test_resultcache;

再次执行同样查询时，由于数据Cache在内存中，physical reads会减少到0,但是consistent gets仍然不变

SQL> select count(*) from gavin.test_resultcache;

  COUNT(*)
----------
     73258

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=ALL_ROWS (Cost=293 Card=1)
   1    0   SORT (AGGREGATE)
   2    1     TABLE ACCESS (FULL) OF 'TEST_RESULTCACHE' (TABLE) (Cost=293 Card=72217)
Statistics
----------------------------------------------------------
          0  recursive calls
          0  db block gets
       1049  consistent gets
          0  physical reads
          0  redo size
        352  bytes sent via SQL*Net to client
        503  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          1  rows processed

Step2.3  第三次运行select count(*) from gavin.test_resultcache;

加入/*+ result_cache*/将查询结果放入高速缓存中

SQL> select  /*+ result_cache */ count(*) from gavin.test_resultcache;

  COUNT(*)
----------
     73258

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=ALL_ROWS (Cost=293 Card=1)
   1    0   RESULT CACHE OF '8asjtwtjdzshb8jmtfy6s1rzv9'
   2    1     SORT (AGGREGATE)
   3    2       TABLE ACCESS (FULL) OF 'TEST_RESULTCACHE' (TABLE) (Cost=293 Card=72217)

Statistics
----------------------------------------------------------
          4  recursive calls
          0  db block gets
       1116  consistent gets
          0  physical reads
          0  redo size
        352  bytes sent via SQL*Net to client
        503  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          1  rows processed

Step2.4  第四次运行select count(*) from gavin.test_resultcache;

在这个利用到Result Cache的查询中，consistent gets减少到0，直接访问结果集，不再需要执行SQL查询。

这就是Result
Cache的强大之处。

SQL> select  /*+ result_cache */ count(*) from gavin.test_resultcache;

  COUNT(*)
----------
     73258

Execution Plan
----------------------------------------------------------
   0      SELECT STATEMENT Optimizer=ALL_ROWS (Cost=293 Card=1)
   1    0   RESULT CACHE OF '8asjtwtjdzshb8jmtfy6s1rzv9'
   2    1     SORT (AGGREGATE)
   3    2       TABLE ACCESS (FULL) OF 'TEST_RESULTCACHE' (TABLE) (Cost=293 Card=72217)

Statistics
----------------------------------------------------------
          0  recursive calls
          0  db block gets
          0  consistent gets
          0  physical reads
          0  redo size
        352  bytes sent via SQL*Net to client
        503  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          1  rows processed

Step3. 通过视图查看result cashe的使用和管理情况

1. 通过查询v$result_cache_memory视图来看Cache的使用情况

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" 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2. 通过查询v$result_cache_statistics视图来看Result Cache的统计信息

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" alt="" />

3. 通过查询v$result_cache_objects视图来记录了Cache的对象

aaarticlea/png;base64,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" alt="" />

Step4. 通过dbms包查看result cashe的使用情况

SQL> set serveroutput on;
SQL> exec dbms_result_cache.memory_report;
R e s u l t   C a c h e   M e m o r y   R e p o r t
[Parameters]
Block Size          = 1K bytes
Maximum Cache Size  = 1M bytes (1K blocks)
Maximum Result Size = 51K bytes (51 blocks)
[Memory]
Total Memory = 107836 bytes [0.068% of the Shared Pool]
... Fixed Memory = 9440 bytes [0.006% of the Shared Pool]
... Dynamic Memory = 98396 bytes [0.062% of the Shared Pool]
....... Overhead = 65628 bytes
....... Cache Memory = 32K bytes (32 blocks)
........... Unused Memory = 30 blocks
........... Used Memory = 2 blocks
............... Dependencies = 1 blocks (1 count)
............... Results = 1 blocks
................... SQL     = 1 blocks (1 count)

PL/SQL procedure successfully completed.

Thanks and Regards

参考：Eygle - http://www.eygle.com/archives/2007/09/11g_server_result_cache.html

参考：Linux - http://www.linuxidc.com/Linux/2012-12/76119.htm

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" 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