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Under the Hood: Implementing Async.Parallel
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Async.Parallel can appear magical. Computation tasks are created, executed, and resynchronized almost without effort. However, Listing 13-9 shows that a basic implementation of this operator is simple and again helps you see how Async<'a> values work under the hood. Listing 13-9. A Basic Implementation of Async.Parallel let Parallel(taskSeq) = Async.Primitive (fun (cont,econt) -> let tasks = Seq.to_array taskSeq let count = ref tasks.Length let results = Array.zero_create tasks.Length tasks |> Array.iteri (fun i p -> Async.Spawn (async { let! res = p do results.[i] <- res; let n = System.Threading.Interlocked.Decrement(count) do if n=0 then cont results })))
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CH A PT ER 1 3 RE ACT I VE, A SYN CH RO NO US, A ND C ONC URREN T PRO GRA MMI NG
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This basic implementation Parallel first converts the input task sequence to an array and then creates mutable state count and results to record the progress of the parallel computations. It then iterates through the tasks and queues each for execution in the .NET thread pool. Upon completion, each writes its result and decrements the counter using an atomic Interlocked. Decrement operator, discussed further in the section Understanding Shared-Memory Concurrency at the end of this chapter. The last process to finish calls the continuation with the collected results. In practice, Parallel is implemented slightly differently to take into account exceptions and cancellation; once again, see the F# library code for full details.
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Understanding Exceptions and Cancellation
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Two recurring topics in asynchronous programming are exceptions and cancellation. Let s first explore some of the behavior of asynchronous programs with regard to exceptions. > let failingTask = async { do failwith "fail" };; val failingTask: Async<unit> > Async.Run failingTask;; Microsoft.FSharp.Core.FailureException: fail stopped due to error > let failingTasks = [ async { do failwith "fail A" }; async { do failwith "fail B" }; ];; val failingTasks: Async<unit> > Async.Run (Async.Parallel failingTasks);; Microsoft.FSharp.Core.FailureException: fail A stopped due to error > Async.Run (Async.Parallel failingTasks);; Microsoft.FSharp.Core.FailureException: fail B stopped due to error From this you can see the following: Tasks fail only when they are actually executed. The construction of a task using the async { ... } syntax will never fail. Tasks run using Async.Run report any failure back to the controlling thread as an exception. It is nondeterministic which task will fail first. Tasks composed using Async.Parallel report the first failure from amongst the collected set of tasks. An attempt is made to cancel other tasks by setting the cancellation flag for the group of tasks, and any further failures are ignored. You can wrap a task using the Async.Catch combinator. This has the following type:
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CHAPTER 13 REA CTIV E, A SYN CHRON OUS , A ND CONC URRENT PROGRAM MIN G
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static member Catch : Async<'a> -> Async<Choice<'a,exn>>
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For example: > Async.Run (Async.Catch failingTask);; val it : Choice<unit,exn> = Choice2_2 (FailureException ()) You can also handle errors by using try/finally in an async { ... } workflow.
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Note You can find further information and examples of asynchronous workflows at http://www.
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expert-fsharp.net/topics/AsyncWorkflows.
Passing and Processing Messages
A distinction is often made between shared-memory concurrency and message passing concurrency. The former is often more efficient on local machines and is covered in the section Using Shared-Memory Concurrency later in this chapter. The latter scales to systems where there is no shared memory, for example, distributed systems, and can also be used to avoid performance problems associated with shared memory. Asynchronous message passing and processing is a common foundation for concurrent programming, and in this section we look at some simple examples of message-passing programs.
Introducing Message Processing
In a sense you have already seen a good deal of message passing in this chapter. For example: In the BackgroundWorker design pattern, the CancelAsync method is a simple kind of message. Whenever you raise events on a GUI thread from a background thread, you are, under the hood, posting a message to the GUI s event queue. On Windows this event queue is managed by the operating system, and the processing of the events on the GUI thread is called the Windows Event Loop. In this section we cover a simple kind of message processing called mailbox processing. This is popular in languages such as Erlang. A mailbox is a message queue that you can scan for a message particularly relevant to the message-processing agent you are defining. Listing 13-10 shows a concurrent agent that implements a simple counter by processing a mailbox as messages arrive. The type MailboxProcessor is defined in the F# library module Microsoft.FSharp. Control.Mailboxes.
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