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When your users complain that the database is crawling and they can t get their queries returned fast enough, there s no use in your protesting that your database is showing high hit ratios for the shared pool and the buffer cache (and the large pool and redo log buffer as well). If the users are waiting for long periods of time to complete their tasks, then the response time will be slow, and you can t say that the database is performing well, the high hit ratios notwithstanding.

For an interesting review of the Oracle wait analysis (the wait interface), please read one of the early papers in this area, titled Yet Another Performance Profiling Method (or YAPP-Method), by Anjo Kolk, Shari Yamaguchi, and Jim Viscusi. It s available at the OraPerf web site at http://www.oraperf.com (a free registration is required).

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The receiver would also have to be modified: If it doesn t find the file using the expected number, it would have to check for a restarted file number (ie, SharedFile000) Using the single shared file approach, the sender would need to acquire a lock on the file, append the notification payload to it, and then close the file The receiver might detect new notifications by monitoring the size of the file When the file size changed, the reader would acquire a lock on the file, remove notifications from it, and then close the file The receiver could read any number of notifications at once, including all of those found If there are no receivers, files will continue to accumulate indefinitely in the notification directory, so there must be a mechanism for deleting files at an opportune time.

exit when l_status = 0; for x in ( select * from big_table order by 1, 2, 3, 4 ) loop null; end loop; end loop; end; / exit The script to stop these processes from running is as follows: begin dbms_alert.signal( 'WAITING', '' ); commit; end; To observe the differing amounts of RAM allocated to the session I was measuring, I initially ran the SELECT in isolation as the only session. I captured the same six statistics and saved them into another table, along with the count of active sessions. Then I added 25 sessions to the system (i.e., I ran the preceding benchmark script with the loop in 25 new sessions). I waited a short period of time one minute for the system to adjust to this new load and then I created a new session, captured the statistics for it with reset_stat.sql, ran the query that would sort, and then ran watch_stat.sql to capture the differences. I did this repeatedly, for up to 500 concurrent users. It should be noted that I asked the database instance to do an impossible thing here. As noted previously, based on the first time we ran watch_stat.sql, each connection to Oracle, before even doing a single sort, consumed almost .5MB of RAM. At 500 users, we would be very close to the PGA_AGGREGATE_TARGET setting just by having them all logged in, let alone actually doing any work! This drives home the point that the PGA_AGGREGATE_TARGET is just that: a target, not a directive. We can and will exceed this value for various reasons. Table 4-1 summarizes my findings using approximately 25 user increments. Table 4-1. PGA Memory Allocation Behavior with Increasing Numbers of Active Sessions, with PGA_AGGREGATE_TARGET Set to 256MB

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