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Now, these two simulations ran in about the same amount of time by the CPU clock. The material difference to note, however, is the large reduction in cache buffers chains latches. The first implementation (hashed) used significantly fewer, meaning the hashed implementation should scale better in a read-intensive environment, since it needs fewer resources that require some level of serialization. This was due entirely to the fact that the I/O needed by the hashed implementation was significantly reduced over the HEAP table you can see the statistic consistent gets in that report bears this out. The TKPROF shows it even more clearly: SELECT * FROM T_HASHED WHERE OBJECT_ID = :B1 call count ------- -----Parse 1 Execute 72081 Fetch 72081 ------- -----total 144163 cpu elapsed disk query current -------- ---------- ---------- ---------- ---------0.00 0.00 0 0 0 10.20 10.36 0 2 0 1.73 1.69 0 72081 0 -------- ---------- ---------- ---------- ---------11.94 12.06 0 72083 0 rows ---------0 0 72081 ---------72081

4.3.2 Per-object association Oftentimes, reusable base aspects need to keep some per-object state consisting of the data that is associated with each object, without having sufficient information about the type of objects that will participate in the static crosscutting mechanism of member introduction. Consider a cache-management aspect that needs to track the last access time for each object in the cache so that it can remove from the cache objects that are not accessed for a long duration. Since such cache management is a reusable concept, we want to create a reusable base aspect. By associating a separate aspect instance with each object under cache management and by keeping the field definition for the last accessed time inside the base aspect, we can track the required information for each cache-managed object. The per-object association feature lets us associate a new aspect instance with an execution or target object by using a pointcut. In the following snippet, a new aspect instance is associated with each new execution object using perthis(), which matches the abstract access() pointcut:

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USER, 'T', 500, 7, 100 );

Rows Row Source Operation ------- --------------------------------------------------1 TABLE ACCESS HASH T_HASHED (cr=1 pr=0 pw=0 time=0 us) ******************************************************************************** SELECT * FROM T_HEAP WHERE OBJECT_ID = :B1 call count ------- -----Parse 1 Execute 72080 Fetch 72080 ------- -----total 144161 Rows ------1 1 cpu elapsed disk query current -------- ---------- ---------- ---------- ---------0.00 0.00 0 0 0 10.55 10.84 0 0 0 1.80 1.85 0 216240 0 -------- ---------- ---------- ---------- ---------12.36 12.70 0 216240 0 rows ---------0 0 72080 ---------72080

8 / PL/SQL procedure successfully completed. ops$tkyte@ORA10G> select table_name, num_rows, blocks, avg_row_len 2 from user_tables 3 where table_name = 'T'; TABLE_NAME NUM_ROWS BLOCKS AVG_ROW_LEN ------------------------------ ---------- ---------- ----------T 500 7 100 Now, the optimizer won t use its best guess it will use our best guess for this information.

public abstract aspect CacheManagementAspect perthis(access()) { ... aspect's state instance members such as the last accessed time abstract pointcut access(); ... advice to access() pointcut to update the last accessed time ... advice using the aspect s state }

Row Source Operation --------------------------------------------------TABLE ACCESS BY INDEX ROWID T_HEAP (cr=3 pr=0 pw=0 time=0 us cost=2 si ) INDEX UNIQUE SCAN T_HEAP_PK (cr=2 pr=0 pw=0 time=0 us cost=1 size=0 )

Temporary tables can be useful in an application where you need to temporarily store a set of rows to be processed against other tables, for either a session or a transaction. They are not meant to be used as a means to take a single larger query and break it up into smaller result sets that would be combined back together (which seems to be the most popular use of temporary tables in other databases). In fact, you will find in almost all cases that a single query broken up into smaller temporary table queries performs more slowly in Oracle than the single query would have. I ve seen this behavior time and time again, when given the opportunity to rewrite the series of INSERTs into temporary tables as SELECTs in the form of one large query, the resulting single query executes much faster than the original multistep process. Temporary tables generate a minimum amount of redo, but they still generate some redo, and there is no way to disable that. The redo is generated for the rollback data, and in most typical uses it will be negligible. If you only INSERT and SELECT from temporary tables, the amount of redo generated will not be noticeable. Only if you DELETE or UPDATE a temporary table heavily will you see large amounts of redo generated. Statistics used by the CBO can be generated on a temporary table with care; however, a better guess set of statistics may be set on a temporary table using the DBMS_STATS package or dynamically collected by the optimizer at hard parse time using dynamic sampling.

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