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You can then use tools to organize and visualize the event firing statistics, creating a toplevel profile of the system and identifying which events are most often fired, which event handlers are called, and other details Profiling may identify not only high-frequency events, but also common event sequences that you might need to coalesce into shorter sequences You may need to build different profiles if a system has different modes of operation Once the profile of the system is known, you can apply static optimization techniques Handlers called with the highest frequency can be recoded carefully to improve their speed You can also apply compiler optimizations to inline code or store variables in CPU registers Using a more dynamic technique, you can instrument the system with code that monitors the event firing patterns.

Improving SQL statements is something that can t happen right away, so you need to do other things to help matters in this case. This means you need to increase the I/O bandwidth by doing either or both of the following: Make sure that the key database objects that are used heavily are spread evenly on the disks. Increase the number of disks. Storage disks are getting larger and larger, but the I/O rates aren t quite keeping up with the increased disk sizes. Thus, servers are frequently I/O bound in environments with large databases. Innovative techniques such as file caching might be one solution to a serious I/O bottleneck. On average, about 50 percent of I/O activity involves less than 5 percent of the total data files in your database, so caching this limited number of hot files should be a win. Caching gives you the benefit of read/write operations at memory speeds, which could be 200 times faster than disk speed. You can include your temp, redo log, and undo tablespace files, as well as the most frequently used table and index data files on file cache accelerators. It s possible for large segments to waste a lot of disk space due to fragmentation caused by update and delete operations over time. This space fragmentation could cause severe performance degradation. You can use the Segment Advisor to find out which objects are candidates for a space reclamation exercise due to excessive fragmentation within the segment.

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If you don t use it for an extended period of time, it will be aged out if the Shared pool fills up and space is needed for other objects The easiest way to break Oracle s Shared pool is to not use bind variables As you saw in 1, not using bind variables can bring a system to its knees for two reasons: The system spends an exorbitant amount of CPU time parsing queries The system uses large amounts of resources managing the objects in the Shared pool as a result of never reusing queries If every query submitted to Oracle is a unique query with the values hard-coded, the concept of the Shared pool is substantially defeated The Shared pool was designed so that query plans would be used over and over again If every query is a brand-new, never-before-seen query, then caching only adds overhead.

If you have baseline numbers for the database load, you can see if the current load on the database is relatively too high. Pay attention to the following data, which you can obtain from the V$SYSSTAT view: physical reads and writes, redo size, hard and soft parse counts, and user calls. You can also check the Load Profile section of the AWR report for load data that s normalized over transactions and over time.

As you saw earlier in this chapter, high buffer cache and shared pool hit ratios aren t guarantees of efficient instance performance. Sometimes, an excessive preoccupation with hit ratios can lead you to allocate too much memory to Oracle, which opens the door to serious problems such as paging and swapping at the operating-system level. Make sure that the paging and swapping indicators don t show anything abnormal. High amounts of paging and swapping slow down everything, including the databases on the server. Due to the virtual memory system used by most operating systems, a certain amount of paging is normal and to be expected. If physical memory isn t enough to process the demand for memory, the operating system will go to the disk to use its virtual memory, and this results in a page fault. Processes that result in high page faults are going to run slowly. When it comes to Oracle memory allocation, don t forget to pay proper attention to PGA memory allocation, especially if you re dealing with a DSS-type environment. Databases that perform a large number of heavy sorting and hashing activities need a high amount of PGA memory allocation. The database self-tunes the PGA, but you still have to ensure that the pga_aggregate_target value is high enough for Oracle to perform its magic.

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