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That is, each parallel process would be able to use about 03 * PGA_AGGREGATE_TARGET / (number of parallel processes) OK, so how can we observe the different work area sizes being allocated to our session By applying the same technique we used earlier in the manual memory management section, to observe the memory used by our session and the amount of I/O to temp we performed The following test was performed on a Red Hat Advanced Server 30 Linux machine using Oracle 10103 and dedicated server connections This was a two-CPU Dell PowerEdge with hyperthreading enabled, so it was as if there were four CPUs available Using reset_statsql and a slightly modified version of watch_statsql from earlier, I captured the session statistics for a session as well as the total statistics for the instance The slightly modified watch_stat.

// update file number fileNumber++; if (fileNumber > 999) fileNumber = 0; FireNotificationReceived(payload); } public delegate void NoticationReceivedHandler(string thePayload); public event NoticationReceivedHandler OnNotificationReceived; void FireNotificationReceived(string thePayload) { if (OnNotificationReceived != null) OnNotificationReceived(thePayload); } } public class SharedFileSystem { System.Threading.Thread receiverThread; string sharedDirectory = @"c:\MyDirectory"; Sender sender; Receiver receiver; public SharedFileSystem() { sender = new Sender(sharedDirectory); receiver = new Receiver(sharedDirectory); receiverThread = new System.Threading.Thread( new System.Threading.ThreadStart(receiver.Run) ); receiverThread.Start(); } public void Stop() { // stop the subscriber thread receiver.terminationRequested = true; } public void FireEvent() { // send a notification from Sender to Receiver sender.FireEvent(DateTime.Now.ToString() ); } }

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Database hit ratios are the most commonly used measures of performance. These include the buffer cache hit ratio, the library cache and dictionary cache hit ratios, the latch hit ratio, and the disk sort ratios. These hit ratios don t indicate how well your system is performing. They re broad indicators of proper SGA allocation, and they may be high even when the system as a whole is performing poorly. The thing to remember is that the hit ratios only measure such things as how physical reads compare with logical reads, and how much of the time a parsed version of a statement is found in memory. As to whether the statements themselves are efficient or not, the hit ratios can t tell you anything. When your system is slow due to bottlenecks, the hit ratios are of little help, and you should turn to a careful study of wait statistics instead.

Caution Even if you have a 99.99 percent buffer cache hit ratio, you may still have major inefficiencies in your application. What if you have an extremely high number of unnecessary logical reads This makes your buffer cache hit ratio look good, as that hit ratio is defined as physical reads over the sum of logical reads. Although you may think your application should run faster because you re doing most of your reads from memory instead of disk, this may well not happen. The reason is that even if you re doing logical reads, you re still burning up the CPU units to do the unnecessary logical reads. In essence, by focusing zealously on the buffer cache hit ratio to relieve the I/O subsystem, you could be an unwitting party to a CPU usage problem. Please read Cary Millsap s interesting article, Why You Should Focus on LIOs instead of PIOs (http://www.hotsos.com/e-library/abstract. php id=7), which explains why a high logical I/O level could be a major problem.

sql script captured this information via the MERGE statement: merge into sess_stats using ( select aname, bvalue from v$statname a, v$sesstat b where astatistic# = bstatistic# and bsid = &1 and (aname like '%ga %' or aname like '%direct temp%') union all select 'total: ' || aname, sum(bvalue) from v$statname a, v$sesstat b, v$session c where astatistic# = bstatistic# and (aname like '%ga %'.

When faced with a slow-performing database or a demand for shorter response times, Oracle DBAs have traditionally looked to increase their database hit ratios and tune the database by adjusting a host of initialization parameters (such as SGA allocations). More recently, there s been awareness that the key area to focus on is clearing up database bottlenecks that contribute to a higher response time. The total response time for a query is the time Oracle takes to execute it, plus the time the process spends waiting for resources such as latches, data buffers, and so on. For a database instance to perform well, ideally your application should spend little time waiting for access to critical resources. Let s now turn to examining the critical wait events in your database, which can be real showstoppers on a busy day in a production instance.

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