Parallelism in .NET – Part 13, Introducing the Task class

Once we’ve used a task-based decomposition to decompose a problem, we need a clean abstraction usable to implement the resulting decomposition.  Given that task decomposition is founded upon defining discrete tasks, .NET 4 has introduced a new API for dealing with task related issues, the aptly named Task class.

The Task class is a wrapper for a delegate representing a single, discrete task within your decomposition.  We will go into various methods of construction for tasks later, but, when reduced to its fundamentals, an instance of a Task is nothing more than a wrapper around a delegate with some utility functionality added. 

In order to fully understand the Task class within the new Task Parallel Library, it is important to realize that a task really is just a delegate – nothing more.  In particular, note that I never mentioned threading or parallelism in my description of a Task.  Although the Task class exists in the new System.Threading.Tasks namespace:

Tasks are not directly related to threads or multithreading.

Of course, Task instances will typically be used in our implementation of concurrency within an application, but the Task class itself does not provide the concurrency used.  The Task API supports using Tasks in an entirely single threaded, synchronous manner.

Tasks are very much like standard delegates.  You can execute a task synchronously via Task.RunSynchronously(), or you can use Task.Start() to schedule a task to run, typically asynchronously.  This is very similar to using delegate.Invoke to execute a delegate synchronously, or using delegate.BeginInvoke to execute it asynchronously.

The Task class adds some nice functionality on top of a standard delegate which improves usability in both synchronous and multithreaded environments.

The first addition provided by Task is a means of handling cancellation via the new unified cancellation mechanism of .NET 4.  If the wrapped delegate within a Task raises an OperationCanceledException during it’s operation, which is typically generated via calling ThrowIfCancellationRequested on a CancellationToken, or if the CancellationToken used to construct a Task instance is flagged as canceled, the Task’s IsCanceled property will be set to true automatically.  This provides a clean way to determine whether a Task has been canceled, often without requiring specific exception handling.

Tasks also provide a clean API which can be used for waiting on a task.  Although the Task class explicitly implements IAsyncResult, Tasks provide a nicer usage model than the traditional .NET Asynchronous Programming Model.  Instead of needing to track an IAsyncResult handle, you can just directly call Task.Wait() to block until a Task has completed.  Overloads exist for providing a timeout, a CancellationToken, or both to prevent waiting indefinitely.  In addition, the Task class provides static methods for waiting on multiple tasks – Task.WaitAll and Task.WaitAny, again with overloads providing time out options.  This provides a very simple, clean API for waiting on single or multiple tasks.

Finally, Tasks provide a much nicer model for Exception handling.  If the delegate wrapped within a Task raises an exception, the exception will automatically get wrapped into an AggregateException and exposed via the Task.Exception property.  This exception is stored with the Task directly, and does not tear down the application.  Later, when Task.Wait() (or Task.WaitAll or Task.WaitAny) is called on this task, an AggregateException will be raised at that point if any of the tasks raised an exception. 

For example, suppose we have the following code:

Task taskOne = new Task(
                       () =>
                       {
                           throw new ApplicationException("Random Exception!");
                       });
Task taskTwo = new Task(
                       () =>
                       {
                           throw new ArgumentException("Different exception here");
                       });

// Start the tasks
taskOne.Start();
taskTwo.Start();

try
{
    Task.WaitAll(new[] { taskOne, taskTwo });
}
catch (AggregateException e)
{
    Console.WriteLine(e.InnerExceptions.Count);
    foreach (var inner in e.InnerExceptions)
        Console.WriteLine(inner.Message);
}

Here, our routine will print:

2
Different exception here
Random Exception!

Note that we had two separate tasks, each of which raised two distinctly different types of exceptions.  We can handle this cleanly, with very little code, in a much nicer manner than the Asynchronous Programming API.  We no longer need to handle TargetInvocationException or worry about implementing the Event-based Asynchronous Pattern properly by setting the AsyncCompletedEventArgs.Error property.  Instead, we just raise our exception as normal, and handle AggregateException in a single location in our calling code.