I want to know when some parallel tasks are completed.
I'm using this code to make between 1500 and 2000 small WebClient.DownloadString with a 10 seconds HttpRequest Timeout on a website:
Task.Factory.StartNew(() =>
Parallel.ForEach<string>(myKeywords, new ParallelOptions
{ MaxDegreeOfParallelism = 5 }, getKey));
Sometimes, a query fails, so that there are exceptions and the function never finish, and the UI refresh inside each getKey function sometimes seems to be called twice, so I cannot get an accurate idea about how many tasks are completed. I'm calculating: Number of UI refresh calls / total number of keywords, and get a result between 100% and 250%, and I never know when task are completed. I search in a lot of SO discussion but none was a direct method or a method that suits my needs. So I guess Framework 4.0 doesn't provides any Tasks.AllCompleted Event Handler or similar workaround?
Should I run my Parallel.Foreach in one other thread instead of my UI thread then add it?
myTasks.WaitAll
[EDIT]
A temporary solution was to copy my list of string in a ArrayList, then removing one by one each item from the list at the beginning of each query. Whenever the function worked well or not, I know when all items have been processed.
Parallel.ForEach is no different than other loops when it comes to handling exceptions. If an exception is thrown, then it is going to stop processing of the loop. This is probably why you're seeing variances in the percentages (I assume you might be processing the count as you're processing the loop).
Also, you don't really need Parallel.ForEach becuase the asynchronous calls that you're making on the WebClient class are going to block waiting on IO completion (the network responses), they are not computationally bound (Parallel.ForEach is much better when you are computationally bound).
That said, you should first translate your calls to WebClient to use Task<TResult>. Translating the event-based asynchronous pattern to the task-based asynchronous pattern is simple with the use of the TaskCompletionSource<TResult> class.
Assuming that you have a sequence of Uri instances that are produced as a result of your calls to getKey, you can create a function to do this:
static Task<String> DownloadStringAsync(Uri uri)
{
// Create a WebClient
var wc = new WebClient();
// Set up your web client.
// Create the TaskCompletionSource.
var tcs = new TaskCompletionSource<string>();
// Set the event handler on the web client.
wc.DownloadStringCompleted += (s, e) => {
// Dispose of the WebClient when done.
using (wc)
{
// Set the task completion source based on the
// event.
if (e.Cancelled)
{
// Set cancellation.
tcs.SetCancelled();
return;
}
// Exception?
if (e.Error != null)
{
// Set exception.
tcs.SetException(e.Error);
return;
}
// Set result.
tcs.SetResult(e.Result);
};
// Return the task.
return tcs.Task;
};
Note, the above can be optimized to use one WebClient, that is left as an exercise for you (assuming your tests show you need it).
From there, you can get a sequence of Task<string>:
// Gotten from myKeywords
IEnumerable<Uri> uris = ...;
// The tasks.
Task<string>[] tasks = uris.Select(DownloadStringAsync).ToArray();
Note that you must call the ToArray extension method in order for the tasks to start running. This is to get around deferred execution. You don't have to call ToArray, but you must call something which will enumerate through the entire list and cause the tasks to start running.
Once you have these Task<string> instances, you can wait on them all to complete by calling the ContinueWhenAll<TAntecedentResult> method on the TaskFactory class, like so:
Task.Factory.ContinueWhenAll(tasks, a => { }).Wait();
When this is done, you can cycle through the tasks array and look at the Exception and/or Result properties to check to see what the exception or result was.
If you are updating a user interface, then you should look at intercepting the call to Enumerable.Select, namely, you should call the ContinueWith<TNewResult> method on the Task<TResult> to perform an operation when that download is complete, like so:
// The tasks.
Task<string>[] tasks = uris.
Select(DownloadStringAsync).
// Select receives a Task<T> here, continue that.
Select(t => t.ContinueWith(t2 => {
// Do something here:
// - increment a count
// - fire an event
// - update the UI
// Note that you have to take care of synchronization here, so
// make sure to synchronize access to a count, or serialize calls
// to the UI thread appropriately with a SynchronizationContext.
...
// Return the result, this ensures that you'll have a Task<string>
// waiting.
return t2;
})).
ToArray();
This will allow you to update things as they happen. Note that in the above case, if you call Select again, you might want to check the state of t2 and fire some other events, depending on what you want your error handling mechanism to be.
Related
I have the following method which is returning me a list of stock prices.
var tickers = Ticker.text.splice(',',' ');
var service = new StockService();
var tickerLoadingTasks = new List<Task<IEnumerable<StockePrice>>>();
foreach(var ticker in tickers)
{
var loadTask = service.GetStockPriceFor(ticker,cancellationTokenSource.Token)
tickerLoadingTasks.Add(loadTask);
}
await Task.WhenAll(tickerLoadingTasks);
// code for updating UI
I have above method which returns me list of stock price data. My confusion is that for each value in tickers, is new thread created or what?
GetStockPrice returns me Task of List of the stock prices for each stock.
Assuming that StockService is an Http client, GetStockPriceFor will do an HTTP request. If the code is implemented correctly, the returned Task can be awaited to get the result of the HTTP call. While awaiting the Task, no thread is used.
The idea of async/await and I/O calls is that you can continue using the thread for something else while the operating system waits for the I/O call to finish. Once it's finished, a thread will be used to process the result of the I/O call.
Now remember, this is based upon the assumption you're doing an HTTP call.
This is a huge if since you don't show the actual implementation of the code. It could be that the code fetches the results synchronously and uses Task.FromResult to give you a Task that will immediately complete and not even switch threads.
Can someone tell me what the best practice/proper way of doing this is?
I'm also using WPF, not a console or ASP.NET.
Using Listener to accept clients and spin off a new "thread" for each client that handles all the I/O and Exception catching for that client.
Method 1: Fire and forget, and just throw it into a variable to get rid of the warning.
public static async Task Start(CancellationToken token)
{
m_server = TcpListener.Create(33777);
m_server.Start();
running = true;
clientCount = 0;
// TODO: Add try... catch
while (!token.IsCancellationRequested)
{
var client = await m_server.AcceptTcpClientAsync().ConfigureAwait(false);
Client c = new Client(client);
var _ = HandleClientAsync(c);
}
}
Here's the Client Handler code:
public static async Task HandleClientAsync(Client c)
{
// TODO: add try...catch
while (c.connected)
{
string data = await c.reader.ReadLineAsync();
// Now we will parse the data and update variables accordingly
// Just Regex and some parsing that updates variables
ParseAndUpdate(data);
}
}
Method 2: The same thing... but with Task.Run()
var _ = Task.Run(() => HandleClientAsync());
Method 3: an intermediate non async function (doubt this is good. Should be Async all the way)
But this at least gets rid of the squiggly line without using the variable trick which kinda feels dirty.
while (!token.IsCancellationRequested)
{
var client = await m_server.AcceptTcpClientAsync().ConfigureAwait(false);
Client c = new Client(client);
NonAsync(c);
}
public static void NonAsync(VClient vc)
{
Task.Run(() => HandleClientAsync(vc));
}
Method 4: Make HandleClientAsync an Async void instead of Async Task (really bad)
public static async Task HandleClientAsync(Client c)
// Would change to
public static async Void HandleClientAsync(Client c)
Questions:
Is it any better to use Task.Run() When doing a fire and forget task?
Is it just accepted that you need to use the var _ = FireAndForget() trick to do fire and forget? I could just ignore the warning but something feels wrong about it.
If I wanted to update my UI from a Client, how would I do that? Would I just use a dispatcher?
Thanks guys
I've never been a fan of background workers which you expect to run for a long time, being run in a task. Tasks get scheduled to run on threads drawn from a pool. As you schedule these long running tasks, the thread pool gets smaller and smaller. Eventually all of the threads from the pool are busy running your tasks, and things get really slow and unmanageable.
My recommendation here? Use the Thread class and manage them yourselves. In this way, you keep your thread pool and the overhead for for tasks out of the picture.
Addendum - Producer Consumer Model
Another interesting question to consider: Do you really need a thread for every client? Threads are reasonably costly to create and maintain in terms of memory overhead, and if your client interaction is such that the client threads spend the vast majority of their time waiting around on something to do, then perhaps a producer consumer model is more suited to your use case.
Example:
Client connects on listening thread, gets put in a client queue
Worker thread responsible for checking to see if the clients need anything comes along through that queue every so often and checks - does the client have a new message to service? If so, it services all messages the client has, then moves on
In this way, you limit the number of threads working to just the number needed to manage the message queue. You can even get fancy and add worker threads dynamically based on how long its been since all the clients have been serviced.
If you insist
If you really like what you have going, I suggest refactoring what youre doing a bit so that rather than HandleClientAsync you do something more akin to CreateServiceForClient(c);
This could be a synchronous method that returns something like a ClientService. ClientService could then create the task that does what your HandleClientAsync does now, and store that task as a member. It could also provide methods like
ClientService.WaitUntilEnd()
and
ClientService.Disconnect() (which could set a cancellation token, also stored as a member variable)
I want to queue dependant tasks across several flows that need to be processed in order (in each flow). The flows can be processed in parallel.
To be specific, let's say I need two queues and I want the tasks in each queue to be processed in order. Here is sample pseudocode to illustrate the desired behavior:
Queue1_WorkItem wi1a=...;
enqueue wi1a;
... time passes ...
Queue1_WorkItem wi1b=...;
enqueue wi1b; // This must be processed after processing of item wi1a is complete
... time passes ...
Queue2_WorkItem wi2a=...;
enqueue wi2a; // This can be processed concurrently with the wi1a/wi1b
... time passes ...
Queue1_WorkItem wi1c=...;
enqueue wi1c; // This must be processed after processing of item wi1b is complete
Here is a diagram with arrows illustrating dependencies between work items:
The question is how do I do this using C# 4.0/.NET 4.0? Right now I have two worker threads, one per queue and I use a BlockingCollection<> for each queue. I would like to instead leverage the .NET thread pool and have worker threads process items concurrently (across flows), but serially within a flow. In other words I would like to be able to indicate that for example wi1b depends on completion of wi1a, without having to track completion and remember wi1a, when wi1b arrives. In other words, I just want to say, "I want to submit a work item for queue1, which is to be processed serially with other items I have already submitted for queue1, but possibly in parallel with work items submitted to other queues".
I hope this description made sense. If not please feel free to ask questions in the comments and I will update this question accordingly.
Thanks for reading.
Update:
To summarize "flawed" solutions so far, here are the solutions from the answers section that I cannot use and the reason(s) why I cannot use them:
TPL tasks require specifying the antecedent task for a ContinueWith(). I do not want to maintain knowledge of each queue's antecedent task when submitting a new task.
TDF ActionBlocks looked promising, but it would appear that items posted to an ActionBlock are processed in parallel. I need for the items for a particular queue to be processed serially.
Update 2:
RE: ActionBlocks
It would appear that setting the MaxDegreeOfParallelism option to one prevents parallel processing of work items submitted to a single ActionBlock. Therefore it seems that having an ActionBlock per queue solves my problem with the only disadvantage being that this requires the installation and deployment of the TDF library from Microsoft and I was hoping for a pure .NET 4.0 solution. So far, this is the candidate accepted answer, unless someone can figure out a way to do this with a pure .NET 4.0 solution that doesn't degenerate to a worker thread per queue (which I am already using).
I understand you have many queues and don't want to tie up threads. You could have an ActionBlock per queue. The ActionBlock automates most of what you need: It processes work items serially, and only starts a Task when work is pending. When no work is pending, no Task/Thread is blocked.
The best way is to use the Task Parallel Library (TPL) and Continuations. A continuation not only allows you to create a flow of tasks but also handles your exceptions. This is a great introduction to the TPL. But to give you some idea...
You can start a TPL task using
Task task = Task.Factory.StartNew(() =>
{
// Do some work here...
});
Now to start a second task when an antecedent task finishes (in error or successfully) you can use the ContinueWith method
Task task1 = Task.Factory.StartNew(() => Console.WriteLine("Antecedant Task"));
Task task2 = task1.ContinueWith(antTask => Console.WriteLine("Continuation..."));
So as soon as task1 completes, fails or is cancelled task2 'fires-up' and starts running. Note that if task1 had completed before reaching the second line of code task2 would be scheduled to execute immediately. The antTask argument passed to the second lambda is a reference to the antecedent task. See this link for more detailed examples...
You can also pass continuations results from the antecedent task
Task.Factory.StartNew<int>(() => 1)
.ContinueWith(antTask => antTask.Result * 4)
.ContinueWith(antTask => antTask.Result * 4)
.ContinueWith(antTask =>Console.WriteLine(antTask.Result * 4)); // Prints 64.
Note. Be sure to read up on exception handling in the first link provided as this can lead a newcomer to TPL astray.
One last thing to look at in particular for what you want is child tasks. Child tasks are those which are created as AttachedToParent. In this case the continuation will not run until all child tasks have completed
TaskCreationOptions atp = TaskCreationOptions.AttachedToParent;
Task.Factory.StartNew(() =>
{
Task.Factory.StartNew(() => { SomeMethod() }, atp);
Task.Factory.StartNew(() => { SomeOtherMethod() }, atp);
}).ContinueWith( cont => { Console.WriteLine("Finished!") });
I hope this helps.
Edit: Have you had a look at ConcurrentCollections in particular the BlockngCollection<T>. So in your case you might use something like
public class TaskQueue : IDisposable
{
BlockingCollection<Action> taskX = new BlockingCollection<Action>();
public TaskQueue(int taskCount)
{
// Create and start new Task for each consumer.
for (int i = 0; i < taskCount; i++)
Task.Factory.StartNew(Consumer);
}
public void Dispose() { taskX.CompleteAdding(); }
public void EnqueueTask (Action action) { taskX.Add(Action); }
void Consumer()
{
// This seq. that we are enumerating will BLOCK when no elements
// are avalible and will end when CompleteAdding is called.
foreach (Action action in taskX.GetConsumingEnumerable())
action(); // Perform your task.
}
}
A .NET 4.0 solution based on TPL is possible, while hiding away the fact that it needs to store the parent task somewhere. For example:
class QueuePool
{
private readonly Task[] _queues;
public QueuePool(int queueCount)
{ _queues = new Task[queueCount]; }
public void Enqueue(int queueIndex, Action action)
{
lock (_queues)
{
var parent = _queue[queueIndex];
if (parent == null)
_queues[queueIndex] = Task.Factory.StartNew(action);
else
_queues[queueIndex] = parent.ContinueWith(_ => action());
}
}
}
This is using a single lock for all queues, to illustrate the idea. In production code, however, I would use a lock per queue to reduce contention.
It looks like the design you already have is good and working. Your worker threads (one per queue) are long-running so if you want to use Task's instead, specify TaskCreationOptions.LongRunning so you get a dedicated worker thread.
But there isn't really a need to use the ThreadPool here. It doesn't offer many benefits for long-running work.
[This appears to be a loooong question but I have tried to make it as clear as possible. Please have patience and help me...]
I have written a test class which supports an Async operation. That operation does nothing but reports 4 numbers:
class AsyncDemoUsingAsyncOperations
{
AsyncOperation asyncOp;
bool isBusy;
void NotifyStarted () {
isBusy = true;
Started (this, new EventArgs ());
}
void NotifyStopped () {
isBusy = false;
Stopped (this, new EventArgs ());
}
public void Start () {
if (isBusy)
throw new InvalidOperationException ("Already working you moron...");
asyncOp = AsyncOperationManager.CreateOperation (null);
ThreadPool.QueueUserWorkItem (new WaitCallback (StartOperation));
}
public event EventHandler Started = delegate { };
public event EventHandler Stopped = delegate { };
public event EventHandler<NewNumberEventArgs> NewNumber = delegate { };
private void StartOperation (object state) {
asyncOp.Post (args => NotifyStarted (), null);
for (int i = 1; i < 5; i++)
asyncOp.Post (args => NewNumber (this, args as NewNumberEventArgs), new NewNumberEventArgs (i));
asyncOp.Post (args => NotifyStopped (), null);
}
}
class NewNumberEventArgs: EventArgs
{
public int Num { get; private set; }
public NewNumberEventArgs (int num) {
Num = num;
}
}
Then I wrote 2 test programs; one as console app and another as windows form app. Windows form app works as expected when I call Start repeatedly:
But console app has hard time ensuring the order:
Since I am working on class library, I have to ensure that my library works correctly in all app models (Haven't tested in ASP.NET app yet). So I have following questions:
I have tested enough times and it appears to be working but is it OK to assume above code will always work in windows form app?
Whats the reason it (order) doesn't work correctly in console app? How can I fix it?
Not much experienced with ASP.NET. Will the order work in ASP.NET app?
[EDIT: Test stubs can be seen here if that helps.]
Unless I am missing something then given the code above I believe there is no way of guaranteeing the order of execution. I have never used the AsyncOperation and AsyncOperationManager class but I looked in reflector and as could be assumed AsyncOperation.Post uses the thread pool to execute the given code asynchronously.
This means that in the example you have provided 4 tasks will be queued to the thread pool synchronously in very quick succession. The thread pool will then dequeue the tasks in FIFO order (first in first out) but it's entirely possible for one of later threads to be scheduled before an earlier one or one of the later threads to complete before an earlier thread has completed its work.
Therefore given what you have there is no way to control the order in the way you desire. There are ways to do this, a good place to look is this article on MSDN.
http://msdn.microsoft.com/en-us/magazine/dd419664.aspx
I use a Queue you can then Enqueue stuff and Dequeue stuff in the correct order. This solved this problem for me.
The documentation for AsyncOperation.Post states:
Console applications do not synchronize the execution of Post calls. This can cause ProgressChanged events to be raised out of order. If you wish to have serialized execution of Post calls, implement and install a System.Threading.SynchronizationContext class.
I think this is the exact behavior you’re seeing. Basically, if the code that wants to subscribe to notifications from your asynchronous event wants to receive the updates in order, it must ensure that there is a synchronization context installed and that your AsyncOperationManager.CreateOperation() call is run inside of that context. If the code consuming the asynchronous events doesn’t care about receiving them in the correct order, it simply needs to avoid installing a synchronization context which will result in the “default” context being used (which just queues calls directly to the threadpool which may execute them in any order it wants to).
In the GUI version of your application, if you call your API from a UI thread, you will automatically have a synchronization context. This context is wired up to use the UI’s message queueing system which guarantees that posted messages are processed in order and serially (i.e., not concurrently).
In a Console application, unless if you manually install your own synchronization context, you will be using the default, non-synchronizing threadpool version. I am not exactly sure, but I don’t think that .net makes installing a serializing synchronization context very easy to do. I just use Nito.AsyncEx.AsyncContext from the Nito.AsyncEx nuget package to do that for me. Basically, if you call Nito.AsyncEx.AsyncContext.Run(MyMethod), it will capture the current thread and run an event loop with MyMethod as the first “handler” in that event loop. If MyMethod calls something that creates an AsyncOperation, that operation increments an “ongoing operations” counter and that loop will continue until the operation is completed via AsyncOperation.PostOperationCompleted or AsyncOperation.OperationCompleted. Just like the synchronization context provided by a UI thread, AsyncContext will queue posts from AsyncOperation.Post() in the order it receives them and run them serially in its event loop.
Here is an example of how to use AsyncContext with your demo asynchronous operation:
class Program
{
static void Main(string[] args)
{
Console.WriteLine("Starting SynchronizationContext");
Nito.AsyncEx.AsyncContext.Run(Run);
Console.WriteLine("SynchronizationContext finished");
}
// This method is run like it is a UI callback. I.e., it has a
// single-threaded event-loop-based synchronization context which
// processes asynchronous callbacks.
static Task Run()
{
var remainingTasks = new Queue<Action>();
Action startNextTask = () =>
{
if (remainingTasks.Any())
remainingTasks.Dequeue()();
};
foreach (var i in Enumerable.Range(0, 4))
{
remainingTasks.Enqueue(
() =>
{
var demoOperation = new AsyncDemoUsingAsyncOperations();
demoOperation.Started += (sender, e) => Console.WriteLine("Started");
demoOperation.NewNumber += (sender, e) => Console.WriteLine($"Received number {e.Num}");
demoOperation.Stopped += (sender, e) =>
{
// The AsyncDemoUsingAsyncOperation has a bug where it fails to call
// AsyncOperation.OperationCompleted(). Do that for it. If we don’t,
// the AsyncContext will never exit because there are outstanding unfinished
// asynchronous operations.
((AsyncOperation)typeof(AsyncDemoUsingAsyncOperations).GetField("asyncOp", BindingFlags.NonPublic|BindingFlags.Instance).GetValue(demoOperation)).OperationCompleted();
Console.WriteLine("Stopped");
// Start the next task.
startNextTask();
};
demoOperation.Start();
});
}
// Start the first one.
startNextTask();
// AsyncContext requires us to return a Task because that is its
// normal use case.
return Nito.AsyncEx.TaskConstants.Completed;
}
}
With output:
Starting SynchronizationContext
Started
Received number 1
Received number 2
Received number 3
Received number 4
Stopped
Started
Received number 1
Received number 2
Received number 3
Received number 4
Stopped
Started
Received number 1
Received number 2
Received number 3
Received number 4
Stopped
Started
Received number 1
Received number 2
Received number 3
Received number 4
Stopped
SynchronizationContext finished
Note that in my example code I work around a bug in AsyncDemoUsingAsyncOperations which you should probably fix: when your operation stops, you never call AsyncOperation.OperationCompleted or AsyncOperation.PostOperationCompleted. This causes AsyncContext.Run() to hang forever because it is waiting for the outstanding operations to complete. You should make sure that your asynchronous operations complete—even in error cases. Otherwise you might run into similar issues elsewhere.
Also, my demo code, to imitate the output you showed in the winforms and console example, waits for each operation to finish before starting the next one. That kind of defeats the point of asynchronous coding. You can probably tell that my code could be greatly simplified by starting all four tasks at once. Each individual task would receive its callbacks in the correct order, but they would all make progress concurrently.
Recommendation
Because of how AsyncOperation seems to work and how it is intended to be used, it is the responsibility of the caller of an asynchronous API that uses this pattern to decide if it wants to receive events in order or not. If you are going to use AsyncOperation, you should document that the asynchronous events will only be received in order by the caller if the caller has a synchronization context that enforces serialization and suggest that the caller call your API on either a UI thread or in something like AsyncContext.Run(). If you try to use synchronization primitives and whatnot inside of the delegate you call with AsyncOperation.Post(), you could end up putting threadpool threads in a sleeping state which is a bad thing when considering performance and is completely redundant/wasteful when the caller of your API has properly set up a synchronization context already. This also enables the caller to decide that, if it is fine with receiving things out of order, that it is willing to process events concurrently and out of order. That may even enable speedup depending on what you’re doing. Or you might even decide to put something like a sequence number in your NewNumberEventArgs in case the caller wants both concurrency and still needs to be able to assemble the events into order at some point.
how do set a timeout for a busy method +C#.
Ok, here's the real answer.
...
void LongRunningMethod(object monitorSync)
{
//do stuff
lock (monitorSync) {
Monitor.Pulse(monitorSync);
}
}
void ImpatientMethod() {
Action<object> longMethod = LongRunningMethod;
object monitorSync = new object();
bool timedOut;
lock (monitorSync) {
longMethod.BeginInvoke(monitorSync, null, null);
timedOut = !Monitor.Wait(monitorSync, TimeSpan.FromSeconds(30)); // waiting 30 secs
}
if (timedOut) {
// it timed out.
}
}
...
This combines two of the most fun parts of using C#. First off, to call the method asynchronously, use a delegate which has the fancy-pants BeginInvoke magic.
Then, use a monitor to send a message from the LongRunningMethod back to the ImpatientMethod to let it know when it's done, or if it hasn't heard from it in a certain amount of time, just give up on it.
(p.s.- Just kidding about this being the real answer. I know there are 2^9303 ways to skin a cat. Especially in .Net)
You can not do that, unless you change the method.
There are two ways:
The method is built in such a way that it itself measures how long it has been running, and then returns prematurely if it exceeds some threshold.
The method is built in such a way that it monitors a variable/event that says "when this variable is set, please exit", and then you have another thread measure the time spent in the first method, and then set that variable when the time elapsed has exceeded some threshold.
The most obvious, but unfortunately wrong, answer you can get here is "Just run the method in a thread and use Thread.Abort when it has ran for too long".
The only correct way is for the method to cooperate in such a way that it will do a clean exit when it has been running too long.
There's also a third way, where you execute the method on a separate thread, but after waiting for it to finish, and it takes too long to do that, you simply say "I am not going to wait for it to finish, but just discard it". In this case, the method will still run, and eventually finish, but that other thread that was waiting for it will simply give up.
Think of the third way as calling someone and asking them to search their house for that book you lent them, and after you waiting on your end of the phone for 5 minutes you simply say "aw, chuck it", and hang up. Eventually that other person will find the book and get back to the phone, only to notice that you no longer care for the result.
This is an old question but it has a simpler solution now that was not available then: Tasks!
Here is a sample code:
var task = Task.Run(() => LongRunningMethod());//you can pass parameters to the method as well
if (task.Wait(TimeSpan.FromSeconds(30)))
return task.Result; //the method returns elegantly
else
throw new TimeoutException();//the method timed-out
While MojoFilter's answer is nice it can lead to leaks if the "LongMethod" freezes. You should ABORT the operation if you're not interested in the result anymore.
public void LongMethod()
{
//do stuff
}
public void ImpatientMethod()
{
Action longMethod = LongMethod; //use Func if you need a return value
ManualResetEvent mre = new ManualResetEvent(false);
Thread actionThread = new Thread(new ThreadStart(() =>
{
var iar = longMethod.BeginInvoke(null, null);
longMethod.EndInvoke(iar); //always call endinvoke
mre.Set();
}));
actionThread.Start();
mre.WaitOne(30000); // waiting 30 secs (or less)
if (actionThread.IsAlive) actionThread.Abort();
}
You can run the method in a separate thread, and monitor it and force it to exit if it works too long. A good way, if you can call it as such, would be to develop an attribute for the method in Post Sharp so the watching code isn't littering your application.
I've written the following as sample code(note the sample code part, it works, but could suffer issues from multithreading, or if the method in question captures the ThreadAbortException would break it):
static void ActualMethodWrapper(Action method, Action callBackMethod)
{
try
{
method.Invoke();
} catch (ThreadAbortException)
{
Console.WriteLine("Method aborted early");
} finally
{
callBackMethod.Invoke();
}
}
static void CallTimedOutMethod(Action method, Action callBackMethod, int milliseconds)
{
new Thread(new ThreadStart(() =>
{
Thread actionThread = new Thread(new ThreadStart(() =>
{
ActualMethodWrapper(method, callBackMethod);
}));
actionThread.Start();
Thread.Sleep(milliseconds);
if (actionThread.IsAlive) actionThread.Abort();
})).Start();
}
With the following invocation:
CallTimedOutMethod(() =>
{
Console.WriteLine("In method");
Thread.Sleep(2000);
Console.WriteLine("Method done");
}, () =>
{
Console.WriteLine("In CallBackMethod");
}, 1000);
I need to work on my code readability.
Methods don't have timeouts in C#, unless your in the debugger or the OS believes your app has 'hung'. Even then processing still continues and as long as you don't kill the application a response is returned and the app continues to work.
Calls to databases can have timeouts.
Could you create an Asynchronous Method so that you can continue doing other stuff whilst the "busy" method completes?
I regularly write apps where I have to synchronize time critical tasks across platforms. If you can avoid thread.abort you should. See http://blogs.msdn.com/b/ericlippert/archive/2010/02/22/should-i-specify-a-timeout.aspx and http://www.interact-sw.co.uk/iangblog/2004/11/12/cancellation for guidelines on when thread.abort is appropriate. Here are the concept I implement:
Selective execution: Only run if a reasonable chance of success exists (based on ability to meet timeout or likelihood of success result relative to other queued items). If you break code into segments and know roughly the expected time between task chunks, you can predict if you should skip any further processing. Total time can be measured by wrapping an object bin tasks with a recursive function for time calculation or by having a controller class that watches workers to know expected wait times.
Selective orphaning: Only wait for return if reasonable chance of success exists. Indexed tasks are run in a managed queue. Tasks that exceed their timeout or risk causing other timeouts are orphaned and a null record is returned in their stead. Longer running tasks can be wrapped in async calls. See example async call wrapper: http://www.vbusers.com/codecsharp/codeget.asp?ThreadID=67&PostID=1
Conditional selection: Similar to selective execution but based on group instead of individual task. If many of your tasks are interconnected such that one success or fail renders additional processing irrelevant, create a flag that is checked before execution begins and again before long running sub-tasks begin. This is especially useful when you are using parallel.for or other such queued concurrency tasks.