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cancelTokThrowIfCancellationRequested(); } ThreadSleep(500); ConsoleWriteLine("In MyTask(), count is " + count ); } ConsoleWriteLine("MyTask terminating"); } static void Main() { ConsoleWriteLine("Main thread starting"); // Create a cancellation token source CancellationTokenSource cancelTokSrc = new CancellationTokenSource(); // Start a task, passing the cancellation token to both // the delegate and the task Task tsk = TaskFactoryStartNew(MyTask, cancelTokSrcToken, cancelTokSrcToken); // Let tsk run until cancelled ThreadSleep(2000); try { // Cancel the task cancelTokSrcCancel(); // Suspend Main() until tsk terminates tskWait(); } catch (AggregateException exc) { if(tskIsCanceled) ConsoleWriteLine("\ntsk Cancelled\n"); // To see the exception, un-comment this line: // ConsoleWriteLine(exc); } finally { tskDispose(); cancelTokSrcDispose(); } ConsoleWriteLine("Main thread ending"); } }

Main thread starting MyTask() starting In MyTask(), count is 0 In MyTask(), count is 1 In MyTask(), count is 2 In MyTask(), count is 3 Cancellation request received

24:

The job description must be rewritten, we must advertise the position, and interviews must commence by the end of the week

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M u l t i t h r e a d i n g , P a r t Tw o : E x p l o r i n g t h e Ta s k P a r a l l e l L i b r a r y a n d P L I N Q

As the output shows, MyTask( ) was cancelled by Main( ) after a delay of 2 seconds Thus, MyTask( ) executes four loop iterations When an AggregateException is caught, the status of the task is checked If it is cancelled (which it will be in this example), the cancellation of tsk is reported It is important to understand that when AggregateException is thrown in response to a cancellation, it does not indicate an error It simply means that the task was cancelled Although the preceding discussion introduces the fundamental concepts behind task cancellation and AggregateException, there is much more to these topics These are areas that you will need to study in-depth if you want to create high-performance, scalable code

The preceding sections have described several of the concepts and fundamental techniques involved with tasks However, there are other features that you may find useful For example, you can create nested tasks, which are tasks created by a task, and child tasks, which are nested tasks that are closely tied to the creating task Although the AggregateException was briefly discussed in the preceding section, it has some other features that you may find useful One is the Flatten( ) method It is used to convert any inner exceptions of type AggregateException into a single AggregateException Another is the Handle( ) method, which is used to handle an exception contained within an AggregateException When you create a task, it is possible to specify various options that affect the task s execution characteristics This is done by specifying an instance of TaskCreationOptions in either the Task constructor or the StartNew( ) factory method Also, TaskFactory supports the FromAsync( ) family of methods that support the Asynchronous Programming Model As mentioned early on in this chapter, tasks are scheduled by an instance of TaskScheduler Normally, the default scheduler provided by the NET Framework is used, but it is possible to tailor aspects of the scheduler to best fit your needs Custom schedulers are also possible

= 1

So far, the preceding examples have show situations in which the TPL has been used in much the same way in which Thread would be used, but this is just its most basic application Significantly more sophisticated features are available One of the most important is the Parallel class It facilitates the execution of concurrent code and provides methods that streamline both task and data parallelism Parallel is a static class that defines the For( ), ForEach( ), and Invoke( ) methods Each has various forms The For( ) method executes a parallelized for loop, and the ForEach( ) method executes a parallelized foreach loop Both of these support data parallelism Invoke( ) supports the concurrent execution of two or more methods Thus, it supports task parallelism As you will see, these methods offer the advantage of providing easy ways to utilize common parallel programming techniques without the need to manage tasks or threads explicitly The following sections examine each of these methods

Part II:

Parallelizing Tasks via Invoke( )