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A synchronization object for signaling the control of threads. A two-state (on/off) WaitHandle that resets itself to off automatically after the signal is read. Similar to a two-state traffic light. A two-state (on/off) WaitHandle that requires a call to ManualResetEvent.Reset() to set it off. A lock-like object that can be shared between operating system processes. Used to limit the number of threads simultaneously accessing a resource. However, use a mutex or lock if at most one thread can access a resource at a time. Atomic operations on memory locations. Especially useful for atomic operations on F# reference cells.

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The hope is that the holder of the latch is busy processing on the other CPU (and since latches are designed to be held for very short periods of time, this is likely) and will give it up soon If after spinning and constantly trying to get the latch, we still fail to obtain it, only then will our process sleep, or take itself off of the CPU, and let some other work take place This sleep action is usually the result of many sessions concurrently requesting the same latch; it is not that a single session is holding it for a long time, but rather that so many sessions want it at the same time and each hold it for a short duration If you do something short (fast) often enough, it adds up! The pseudo-code for a latch get might look like this: Loop for i in 1 ..

2000 loop try to get latch if got latch, return if i = 1 then misses=misses+1 end loop INCREMENT WAIT COUNT sleep Add WAIT TIME End loop;.

Summary

The logic is to try to get the latch and, failing that, to increment the miss count, a statistic we can see in a statspack report or by querying the V$LATCH view directly. Once the process misses, it will loop some number of times (an undocumented parameter controls the number of times and is typically set to 2,000), attempting to get the latch over and over. If one of these get attempts succeeds, then it returns and we continue processing. If they all fail, the process will go to sleep for a short duration of time, after incrementing the sleep count for that latch. Upon waking up, the process begins all over again. This implies that the cost of getting a latch is not just the test and set -type operation that takes place, but also a considerable amount of CPU while we try to get the latch. Our system will appear to be very busy (with much CPU being consumed), but not much work is getting done.

processing at night, you might discover that the daytime SGA is much larger than the PGA and the nighttime SGA is much smaller than the PGA. This would reflect the different memory needs of these two application types. Just as with automatic SGA memory management, the DBA can set up lower bounds for the size of each memory area by setting the SGA_TARGET and PGA_AGGREGATE_TARGET, or the lower bound of each of the pools in the SGA by setting their values to that lower bound. The database will remember the optimal settings for the pools and the SGA and PGA in the stored parameter file if you are using one. For example, on one of my test systems I ve set: memory_target = 756m sga_target = 256m pga_aggregate_target = 256m

In this chapter, we covered concurrent, reactive, and asynchronous programming, which is a set of topics of growing importance in modern programming because of the widespread adoption of multicore microprocessors, network-aware applications, and asynchronous I/O channels. We ve covered in depth background processing and a powerful F# construct called asynchronous workflows. Finally, we covered applications of asynchronous workflows to messageprocessing agents and web crawling, and we covered some of the shared-memory primitives for concurrent programming on the .NET platform. In the next chapter, we ll look at web programming, from serving web pages to delivering applications via web browsers.

The stored parameter file for that database currently has: sys%ORA11GR2> create pfile='/tmp/pfile' from spfile; File created. sys%ORA11GR2> !cat /tmp/pfile; ora11gr2.__db_cache_size=88080384 ora11gr2.__java_pool_size=4194304 ora11gr2.__large_pool_size=4194304 ora11gr2.__pga_aggregate_target=524288000 ora11gr2.__sga_target=268435456 ora11gr2.__shared_io_pool_size=0 ora11gr2.__shared_pool_size=146800640 ora11gr2.__streams_pool_size=0 *.compatible='11.2.0.0.0' *.control_files='/home/ora11gr2/app/ora11gr2/oradata/orcl/control01.ctl','/home/ora11gr2/ app/ora11gr2/flash_recovery_area/orcl/control02.ctl' *.db_16k_cache_size=16777216 *.db_block_size=8192 *.db_name='orcl' *.db_recovery_file_dest='/home/ora11gr2/app/ora11gr2/flash_recovery_area' *.db_recovery_file_dest_size=4039114752 *.diagnostic_dest='/home/ora11gr2/app/ora11gr2' *.log_buffer=1 *.memory_target=792723456 *.open_cursors=300 *.pga_aggregate_target=256m *.processes=600 *.remote_login_passwordfile='EXCLUSIVE' *.resource_limit=TRUE *.sga_target=268435456 *.undo_tablespace='UNDOTBS1' As you can see, the double-underscore parameters in bold now include the __sga_target and __pga_aggregate_target settings as well as the various pools. These values are derived based on the last three memory parameters shown in bold, as well as the observed server workload. In this fashion, Oracle will remember your last optimal SGA/PGA settings and use them upon the next restart.