Oracle multiple block sizes Don Burleson

Important 2015 Update: For the latest consensus on using multiple blocksizes in Oracle, see The latest consensus on multiple blocksizes.

I've been using multiple blocksizes on mainframes since the 1980's, and Oracle since 9i, and it's a well proven tool, used by many of the hardware vendors themselves.

These Oracle TPC benchmarks thoroughly tested multiple blocksizes vs. one-size fits all, and they chose multiple blocksizes because it provided the fastest performance. HP spent a small fortune doing their testing because they wanted their benchmark to have truly stunning speed, and multiple blocksizes (and the segregated pools) worked for them.  Also, this UNISYS Oracle benchmark used multiple blocksizes to achieve optimal performance:

db_cache_size = 4000M
db_recycle_cache_size = 500M
db_8k_cache_size = 200M
db_16k_cache_size = 4056M
db_2k_cache_size = 35430M
 

Benefits from multiple blocksizes have been seen in my experience with many Fortune 500 companies that utilize multiple blocksizes, benefits to both performance and manageability:

- Far better management of buffering with multiple buffers
- Less RAM wastage in the SGA

For my clients, the best part is segregating objects that get multi-block scans (e.g. index FFS, range scans) into 32k blocksizes.

• The benefits of Oracle multiple block sizes are very well documented, but specific rules for multiple block sizes must be followed.
   
• Here, Oracle expert Robin Schumacher proves that Oracle b-tree indexes are best in a 32k block size.
      
• One issue with Oracle multiple block sizes is the setting for db_file_multiblock_read_count because this value influences the SQL optimizer about the costs of a full-table scan.  Objects that experience full-table scans should be placed in a larger block size, with db_file_multiblock_read_count set to the block size of that tablespace.
   

The benefits of a large blocksize

The benefits of large blocksizes are demonstrated on this OTN thread where we see a demo showing 3x faster performance using a larger block size:

SQL> r
1 select count(MYFIELD) from table_8K where ttime >to_date('27/09/2006','dd/mm/y
2* and ttime <to_date('06/10/2006','dd/mm/yyyy')

COUNT(MYFIELD)
-------------------
164864

Elapsed: 00:00:01.40
...

(This command is executed several times - the execution time was approximately the same ~
00:00:01.40)

And now the test with the same table, but created together with the index in 16k tablespace:

SQL> r
1 select count(MYFIELD) from table_16K where ttime >to_date('27/09/2006','dd/mm/
2* and ttime <to_date('06/10/2006','dd/mm/yyyy')

COUNT(MYFIELD)
-------------------
164864

Elapsed: 00:00:00.36

(Again, the command is executed several times, the new execution time is approximately the same ~
 

See my other notes on multiple blocksizes here: