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By - Al Ries -Read Online. Buffett -Full Books. Series By - -Full Books. Marino -Full Books. K Sheindlin -Full Pages. Wong -Read Online. Davis -Read Online. Norris -Read Online. Once all foreground threads finish, the application ends, and any background threads still running abruptly terminate.
Get the whole book. If this program is called with no arguments, the worker thread assumes foreground status and will wait on the ReadLine statement for the user to press Enter. Meanwhile, the main thread exits, but the application keeps running because a foreground thread is still alive.
On the other hand, if an argument is passed to Main , the worker is assigned background status, and the program exits almost immediately as the main thread ends terminating the ReadLine. When a process terminates in this manner, any finally blocks in the execution stack of background threads are circumvented.
This is a problem if your program employs finally or using blocks to perform cleanup work such as releasing resources or deleting temporary files. To avoid this, you can explicitly wait out such background threads upon exiting an application.
There are two ways to accomplish this:. In either case, you should specify a timeout, so you can abandon a renegade thread should it refuse to finish for some reason.
This is your backup exit strategy: in the end, you want your application to close — without the user having to enlist help from the Task Manager! If a user uses the Task Manager to forcibly end a.
This is observed rather than documented behavior, and it could vary depending on the CLR and operating system version. A common cause for applications failing to exit properly is the presence of active foreground threads. To perform real-time work, you must also elevate the process priority using the Process class in System.
High is actually one notch short of the highest priority: Realtime. Setting a process priority to Realtime instructs the OS that you never want the process to yield CPU time to another process. If your program enters an accidental infinite loop, you might find even the operating system locked out, with nothing short of the power button left to rescue you!
For this reason, High is usually the best choice for real-time applications. If your real-time application has a user interface, elevating the process priority gives screen updates excessive CPU time, slowing down the entire computer particularly if the UI is complex.
An ideal solution is to have the real-time worker and user interface run as separate applications with different process priorities, communicating via Remoting or memory-mapped files. Memory-mapped files are ideally suited to this task; we explain how they work in Chapters 14 and 25 of C 4. In addition to the issues of latency introduced by automatic garbage collection, the operating system may present additional challenges — even for unmanaged applications — that are best solved with dedicated hardware or a specialized real-time platform.
Consider the following program:. This behavior makes sense when you consider that each thread has an independent execution path. You need an exception handler on all thread entry methods in production applications — just as you do usually at a higher level, in the execution stack on your main thread.
An unhandled exception causes the whole application to shut down. With an ugly dialog! However, the cost of doing so is that the user will lose his recent work — open documents, for instance. DispatcherUnhandledException and Application.
ThreadException fire only for exceptions thrown on the main UI thread. You still must handle exceptions on worker threads manually. UnhandledException fires on any unhandled exception, but provides no means of preventing the application from shutting down afterward.
NET Framework does it for you. These are covered in upcoming sections, and are:. Whenever you start a thread, a few hundred microseconds are spent organizing such things as a fresh private local variable stack.
Each thread also consumes by default around 1 MB of memory. The thread pool cuts these overheads by sharing and recycling threads, allowing multithreading to be applied at a very granular level without a performance penalty.
The thread pool also keeps a lid on the total number of worker threads it will run simultaneously. Too many active threads throttle the operating system with administrative burden and render CPU caches ineffective.
Once a limit is reached, jobs queue up and start only when another finishes. This makes arbitrarily concurrent applications possible, such as a web server. The asynchronous method pattern is an advanced technique that takes this further by making highly efficient use of the pooled threads; we describe this in Chapter 23 of C 4.
We discuss these in detail in Part 5 ; right now, we'll look briefly at how you can use the Task class as a simple means of running a delegate on a pooled thread. You are free to change the priority of a pooled thread — it will be restored to normal when released back to the pool. You can enter the thread pool easily using the Task classes in the Task Parallel Library.
The Task classes were introduced in Framework 4. The newer constructs are faster, more convenient, and more flexible than the old. To use the nongeneric Task class, call Task. StartNew , passing in a delegate of the target method:. StartNew returns a Task object, which you can then use to monitor the task — for instance, you can wait for it to complete by calling its Wait method. Any unhandled exceptions are conveniently rethrown onto the host thread when you call a task's Wait method.
It lets you get a return value back from the task after it finishes executing. Any unhandled exceptions are automatically rethrown when you query the task's Result property, wrapped in an AggregateException. The Task Parallel Library has many more features, and is particularly well suited to leveraging multicore processors. You can't use the Task Parallel Library if you're targeting an earlier version of the.
NET Framework prior to 4. Instead, you must use one of the older constructs for entering the thread pool: ThreadPool. QueueUserWorkItem and asynchronous delegates.
The difference between the two is that asynchronous delegates let you return data from the thread. Asynchronous delegates also marshal any exception back to the caller. To use QueueUserWorkItem , simply call this method with a delegate that you want to run on a pooled thread:.
Our target method, Go , must accept a single object argument to satisfy the WaitCallback delegate. This provides a convenient way of passing data to the method, just like with ParameterizedThreadStart.
Unlike with Task , QueueUserWorkItem doesn't return an object to help you subsequently manage execution. Also, you must explicitly deal with exceptions in the target code — unhandled exceptions will take down the program.
Asynchronous delegate invocations asynchronous delegates for short solve this, allowing any number of typed arguments to be passed in both directions. Asynchronous methods follow a similar protocol outwardly, but they exist to solve a much harder problem, which we describe in Chapter 23 of C 4. EndInvoke does three things.
Second, it receives the return value as well as any ref or out parameters. Third, it throws any unhandled worker exception back to the calling thread. In practice, this is open to debate; there are no EndInvoke police to administer punishment to noncompliers! The thread pool starts out with one thread in its pool. You can set the upper limit of threads that the pool will create by calling ThreadPool.
SetMaxThreads ; the defaults are:. These figures may vary according to the hardware and operating system. The reason there are that many is to ensure progress should some threads be blocked idling while awaiting some condition, such as a response from a remote computer.
You can also set a lower limit by calling ThreadPool. Raising the minimum thread count improves concurrency when there are blocked threads see sidebar. The default lower limit is one thread per processor core — the minimum that allows full CPU utilization. On server environments, though such ASP. Rather, it instructs the pool manager to create up to x threads the instant they are required. To illustrate, consider a quad-core computer running a client application that enqueues 40 tasks at once.
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