Oracle Database Tips by Donald Burleson

RAM Access Speed with Oracle Databases

Now that inexpensive Solid-state disk is available, Oracle professionals are struggling to understand how to leverage this hardware for Oracle databases. Understanding the nature of Oracle RAM caching can help demonstrate the importance of this issue.  The following sections will cover these topics:

• The history of Oracle RAM data buffering

• The problem of duplicate RAM caches

• The issue of expensive logical I/O

A review of the existing research will provide insight into the best placement for SSD in an Oracle environment.

The History of Oracle RAM data buffering

When Oracle was first introduced in the early 1990's RAM was very expensive and very few databases could afford to run large data buffer regions.  Because RAM was such a limited resource, Oracle utilized a least-frequently-used algorithm within the data buffer to ensure that only the most-frequently referenced data remained in the data buffer cache. 

As of Oracle10g there are seven RAM data buffers to hold incoming data blocks.  These RAM areas define RAM space for incoming data blocks and are governed by the following Oracle10g parameters.  The sum of all of these parameter values determines the total space reserved for Oracle data blocks.

• db_cache_size

• db_keep_cache_size

• db_recycle_cache_size

• db_2k_cache_size

• db_4k_cache_size

• db_8k_cache_size

• db_16k_cache_size

• db_32k_cache_size

The following graphic plots the relationship between the size of the RAM data buffers and physical disk reads showing the non-linear nature of RAM scalability for Oracle (Figure 1.2).

This relationship can be expressed mathematically as:

RAM Buffer Size =             n          .      
                                Physical reads

Where n = an observed constant

This relationship is the basis of the Automatic Memory Management(AMM) features of Oracle10g.  Because the Automatic Workload Repository (AWR) is polling the efficiency of the data buffer, the AMM component can compute the point of diminishing marginal returns and re-assign SGA RAM resources to ensure optimal sizing for all seven Oracle10g data buffers.

Oracle uses this data to dynamically adjust each of the seven data buffers to keep them at their optimal size.  AMM in Oracle 10g uses the AWR to collect historical buffer utilization information. The dba_hist_db_cache_adviceview can be used to access this information for Oracle RAM management (Figure 1.3). 

Additional RAM is very valuable when there is not enough RAM to cache the frequently-used data blocks. The diagram below demonstrates how a small increase in RAM results in a large decrease in disk I/O (Figure 1.4).

Traditionally, the optimal size of the Oracle RAM data buffer cache has been the point where the marginal benefit begins to decline, as measured by the acceleration of the curve denoted in Figure 1.2.

However, this marginal benefit does not last forever.  As full-caching of the Oracle database is approached, a relatively large amount of RAM is required to reduce physical disk I/O (Figure 1.5). This occurs because rarely read data blocks are now being pulled into the SGA data buffers.

This optimal point is calculated using the Oracle10g Automatic Memory Management(AMM) utility.  To begin, take a look at the script to display the output from the Oracle v$db_cache_adviceutility:

-- *************************************************
-- Copyright © 2003 by Rampant TechPress
-- This script is free for non-commercial purposes
-- with no warranties.  Use at your own risk.
--
-- To license this script for a commercial purpose,
-- contact info@rampant.cc
-- *************************************************

column c1   heading 'Cache Size (m)'              format 999,999,999,999
column c2   heading 'Buffers'                          format 999,999,999
column c3   heading 'Estd Phys|Read Factor'  format 999.90
column c4   heading 'Estd Phys| Reads'          format 999,999,999

select
   size_for_estimate                 c1,
   buffers_for_estimate            c2,
   estd_physical_read_factor   c3,
   estd_physical_reads            c4
from
   v$db_cache_advice
where
   name = 'DEFAULT'
and
   block_size  = (SELECT value FROM V$PARAMETER
                   WHERE name = 'db_block_size')
And
   advice_status = 'ON';

When this utility is executed, the relationship between the RAM buffer size and physical reads is demonstrated.  Note that the values range from 10 percent of the current size to double the current size of the db_cache_size.

                                Estd Phys    Estd Phys
 Cache Size (MB)      Buffers Read Factor        Reads
---------------- ------------ ----------- ------------
              30        3,802       18.70  192,317,943  10% size
              60        7,604       12.83  131,949,536
              91       11,406        7.38   75,865,861
             121       15,208        4.97   51,111,658
             152       19,010        3.64   37,460,786
             182       22,812        2.50   25,668,196
             212       26,614        1.74   17,850,847
             243       30,416        1.33   13,720,149
             273       34,218        1.13   11,583,180
             304       38,020        1.00   10,282,475  Current Size
             334       41,822         .93    9,515,878
             364       45,624         .87    8,909,026
             395       49,426         .83    8,495,039
             424       53,228         .79    8,116,496
             456       57,030         .76    7,824,764
             486       60,832         .74    7,563,180
             517       64,634         .71    7,311,729
             547       68,436         .69    7,104,280
             577       72,238         .67    6,895,122
             608       76,040         .66    6,739,731  2x size

This predictive model is the basis for Oracle10g AMM.  Figure 1.6 shows the tradeoff that occurs when data is taken from Oracle's predictive mode and plotted.

The main point of the relationship between RAM buffering and physical reads is that all Oracle databases have data that is accessed at different frequencies.  In sum, the larger the number of frequently referenced data blocks, the greater the benefit from speeding-up block access.

The next step is to apply this knowledge to the use of SSD for Oracle.

This is an excerpt from the book Oracle Solid State Disk Tuning.  You can get it for more than 30% by buying it directly from the publisher and get immediate access to working code examples.

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