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Other latches may be requested in an immediate mode, which is similar in concept to a SELECT FOR UPDATE NOWAIT, meaning that the process will go do something else, such as try to grab an equivalent sibling latch that may be free, rather than sit and wait for this latch to become available Since many requestors may be waiting for a latch at the same time, you may see some processes waiting longer than others Latches are assigned rather randomly, based on the luck of the draw, if you will Whichever session asks for a latch right after it was released will get it There is no line of latch waiters just a mob of waiters constantly retrying Oracle uses atomic instructions like test and set and compare and swap for operating on latches.

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just the concurrency properties you have documented. Don t lock just for the sake of it, and don t hold locks longer than necessary. In particular, beware of making indirect calls to externally supplied function values, interfaces, or abstract members while a lock is held. The code providing the implementation may not be expecting to be called when a lock is held and may attempt to acquire further locks in an inconsistent fashion.

Since the instructions to set and free latches are atomic, the operating system itself guarantees that only one process gets to test and set the latch even though many processes may be going for it simultaneously Since the instruction is only one instruction, it can be quite fast (but the overall latching algorithm itself is many CPU instructions!) Latches are held for short periods of time and provide a mechanism for cleanup in case a latch holder dies abnormally while holding it This cleanup process would be performed by PMON Enqueues, which we discussed earlier, are another, more sophisticated serialization device used when updating rows in a database table, for example They differ from latches in that they allow the.

requestor to queue up and wait for the resource. With a latch request, the requestor session is told right away whether or not it got the latch. With an enqueue lock, the requestor session will be blocked until it can actually attain it.

It is common that mutable data structures get read more than they are written. Indeed, mutation is often used only to initialize a mutable data structure. In this case, you can use a .NET ReaderWriterLock to protect access to a resource. The following two functions are provided in the F# library module Microsoft.FSharp.Control.SharedMemory.Helpers: open System.Threading let readLock (rwlock : ReaderWriterLock) f = rwlock.AcquireReaderLock(Timeout.Infinite) try f() finally rwlock.ReleaseReaderLock() let writeLock (rwlock : ReaderWriterLock) f = rwlock.AcquireWriterLock(Timeout.Infinite) try f(); Thread.MemoryBarrier() finally rwlock.ReleaseWriterLock() Listing 13-15 shows how to use these functions to protect the MutablePair class. Listing 13-15. Shared-Memory Code with a Race Condition type MutablePair<'a,'b>(x:'a,y:'b) = let mutable currentX = x let mutable currentY = y let rwlock = new ReaderWriterLock() member p.Value = readLock rwlock (fun () -> (currentX,currentY)) member p.Update(x,y) = writeLock rwlock (fun () -> currentX <- x; currentY <- y)

Note Using SELECT FOR UPDATE NOWAIT or WAIT [n], you can optionally decide not to wait for an enqueue lock

As such, an enqueue is not as fast as a latch can be, but it does provide functionality over and above what a latch can offer. Enqueues may be obtained at various levels, so you can have many share locks and locks with various degrees of shareability.

Table 13-7 shows some of the other shared-memory concurrency primitives available in the .NET Framework.

One thing I d like to drive home with regard to latches is this: latches are a type of lock, locks are serialization devices, and serialization devices inhibit scalability If your goal is to construct an application that scales well in an Oracle environment, you must look for approaches and solutions that minimize the amount of latching you need to perform Even seemingly simple activities, such as parsing a SQL statement, acquire and release hundreds or thousands of latches on the library cache and related structures in the shared pool If we have a latch, then someone else might be waiting for it When we go to get a latch, we may well have to wait for it ourselves Waiting for a latch can be an expensive operation.

If the latch is not available immediately and we are willing to wait for it, as we likely are most of the time, then on a multi-CPU machine our session will spin, trying over and over, in a loop, to get the latch The reasoning behind this is that context switching (ie, getting kicked off the CPU and having to get back on the CPU) is expensive So, if the process cannot get a latch immediately, we ll stay on the CPU and try again immediately rather than just going to sleep, giving up the CPU, and trying later when we ll have to get scheduled back on the CPU.