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Figure 8-28. Creating an event handler thread on the event target side Although both techniques achieve the same goal, it sometimes makes more sense to use the first technique. Why Because other objects might call the target event handler method, and those objects may not require an asynchronous behavior. By putting the threading burden on the event source, the event target doesn t have to undergo modifications just because you happen to be using it with an event source desiring asynchronous execution. If the target were already designed to use background threads, then obviously you would want to leverage that fact and avoid adding additional threading logic to the event source. If you don t have access to the event source s source code, but you don t want to have the event target manage the threading logic, you can use an adapter between the event source and the target, as shown in Figure 8-29.

query ranks the transactions by the total number of elapsed seconds. You can also rank the statements according to CPU seconds used. SQL> 2 3 4 5 SELECT hash_value, executions, ROUND (elapsed_time/1000000, 2) total_time, ROUND (cpu_time/1000000, 2) cpu_seconds FROM (SELECT * FROM V$SQL ORDER BY elapsed_time desc); TOTAL_TIME CPU_SECONDS ---------- -----------9.51 9.27 4.98 5.01

Note Starting in Oracle9i, you have the ability to resize various SGA components while the database is up and running. If you want the ability to grow the size of the SGA beyond its initial allocation, you must have set the SGA_MAX_SIZE parameter to some value larger than the allocated SGA. For example, if after startup your SGA size was 128MB and you wanted to add an additional 64MB to the buffer cache, you would have had to set the SGA_MAX_SIZE to 192MB or larger to allow for the growth.

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Once you have the value for the HASH_VALUE column from the query you just ran, it s a simple matter to find out the execution plan for this statement, which is in your library cache. The following query uses the V$SQL_PLAN view to get you the execution plan for your longest-running SQL statements: SQL> SELECT * FROM V$SQL_PLAN WHERE hash_value = 238087931;

Event Source FireEvent()

Just because your database users are complaining, you shouldn t be in a hurry to conclude that the problem lies within the database. After all, the database doesn t work in a vacuum it runs on the server and is subject to the resource constraints and bottlenecks of that server. If the non-Oracle users on the server are using up critical resources such as CPU processing and disk I/O, your database may be the victim of circumstances, and you need to look for answers outside the database. That s why it s critical that DBAs understand how to measure general system performance, including memory, the disk storage subsystem, the network, and the processors. In the following sections you ll take a look at the system resources you should focus on.

In this example, I will shrink my DB_CACHE_SIZE since I currently have it set rather large:

Oracle uses locks to control access to two broad types of objects: user objects, which include tables, and system objects, which may include shared memory structures and data dictionary objects. Oracle follows a pessimistic locking approach, which anticipates potential conflicts and will block some transactions from interfering with others in order to avoid conflicts between concurrent transactions.

Granularity, in the context of locking, is the size of the data unit locked by the locking mechanism. Oracle uses row-level granularity to lock objects, which is finest level of granularity (exclusive table locking is the most coarse level). Several databases, including Microsoft SQL Server, provide only page-level, not row-level, locking. A page is somewhat similar to an Oracle data block, and it can have a bunch of rows, so page-level locking means that during an update, several rows in addition to the rows of interest are locked; if other users need the locked rows that are not part of the update, they have to wait for the lock on the page to be released. For example, if your page size is 8KB, and the average row length in a table is 100 bytes, about 80 rows can fit in that one page. If one of the rows is being updated, a block-level lock limits access to the other 79 rows in the block. Locking at a level larger than the row level would reduce data concurrency.

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