Develop Reference

Is there a better LinkedList threadsafe implementation

I'm using a LinkedList and switching between storing data that i'm getting through updates, performing computations on it and removing old updates.
To perform this, I have to lock the reading and sampling section but this comes with a perfomance hit.
Since I'm constantly adding and removing nodes I thought LinkedList is the best datastructure for this task (to my understanding, using a list for this would incur mulitple actions of copying the list)
As far as I'm aware there's no thread-safe implemation of LinkedList.
I'm running this code on a large volume of data, and it take hours to complete.
Is there a way I could speed it up?
edit: I'm adding nodes to the end of the list and removing from the start of it
private readonly ConcurrentQueue<Update> _UpdatesQueue = new ConcurrentQueue<Update>();
private volatile bool _AddingUpdates = false;
public void InsertUpdate(Update update)
{
_UpdatesQueue.Enqueue(update);
if (_AddingUpdates)
{
return;
}
lock (_updateQueueLock)
{
if (_AddingUpdates)
{
return;
}
_AddingUpdates = true;
}
Task.Factory.StartNew(() =>
{
lock (_updateQueueLock)
{
Update lastupdate = null;
while (_UpdatesQueue.TryDequeue(out update))
{
updateWindow.AddLast(update);
}
}
}).ContinueWith(x =>
{
_AddingUpdates = false;
});
}
private volatile bool _Sampling = false;
private readonly ConcurrentQueue<Tuple<Timestamp, Action<float>>> _RequestsQueue = new ConcurrentQueue<Tuple<Timestamp, Action<float>>>();
public void GetFeatureAtTime(Timestamp time, Action<float> valueCallback)
{
_RequestsQueue.Enqueue(new Tuple<Timestamp, Action<float>>(time, valueCallback));
if (_Sampling)
{
return;
}
lock (_updateQueueLock)
{
if (_Sampling)
{
return;
}
_Sampling = true;
}
Task.Factory.StartNew(() =>
{
lock (_updateQueueLock)
{
Timestamp lastTime = null;
while (_RequestsQueue.TryPeek(out var request))
{
GetFeatureAtTimeInternal(request.Item1, request.Item2, out var haveEnoughData);
if (haveEnoughData)
{
_RequestsQueue.TryDequeue(out _);
}
else
{
break;
}
}
}
}).ContinueWith(x => _Sampling = false);
}
From what i'm seeing in the Concurrency Visualizer tool in VS, 76% of the cpu is spent on synchornization.
Also, sampling can sometimes be a leangthy action as compared to insertion.

Looking for a way to do less locking while caching

I am using the code below to cache items. It's pretty basic.
The issue I have is that every time it caches an item, section of the code locks. So with roughly a million items arriving every hour or so, this is a problem.
I've tried creating a dictionary of static lock objects per cacheKey, so that locking is granular, but that in itself becomes an issue with managing expiration of them, etc...
Is there a better way to implement minimal locking?
private static readonly object cacheLock = new object();
public static T GetFromCache<T>(string cacheKey, Func<T> GetData) where T : class {
// Returns null if the string does not exist, prevents a race condition
// where the cache invalidates between the contains check and the retrieval.
T cachedData = MemoryCache.Default.Get(cacheKey) as T;
if (cachedData != null) {
return cachedData;
}
lock (cacheLock) {
// Check to see if anyone wrote to the cache while we where
// waiting our turn to write the new value.
cachedData = MemoryCache.Default.Get(cacheKey) as T;
if (cachedData != null) {
return cachedData;
}
// The value still did not exist so we now write it in to the cache.
cachedData = GetData();
MemoryCache.Default.Set(cacheKey, cachedData, new CacheItemPolicy(...));
return cachedData;
}
}

You may want to consider using ReaderWriterLockSlim, which you can obtain write lock only when needed.
Using cacheLock.EnterReadLock(); and cacheLock.EnterWriteLock(); should greatly improve the performance.
That link I gave even have an example of a cache, exactly what you need, I copy here:
public class SynchronizedCache
{
private ReaderWriterLockSlim cacheLock = new ReaderWriterLockSlim();
private Dictionary<int, string> innerCache = new Dictionary<int, string>();
public int Count
{ get { return innerCache.Count; } }
public string Read(int key)
{
cacheLock.EnterReadLock();
try
{
return innerCache[key];
}
finally
{
cacheLock.ExitReadLock();
}
}
public void Add(int key, string value)
{
cacheLock.EnterWriteLock();
try
{
innerCache.Add(key, value);
}
finally
{
cacheLock.ExitWriteLock();
}
}
public bool AddWithTimeout(int key, string value, int timeout)
{
if (cacheLock.TryEnterWriteLock(timeout))
{
try
{
innerCache.Add(key, value);
}
finally
{
cacheLock.ExitWriteLock();
}
return true;
}
else
{
return false;
}
}
public AddOrUpdateStatus AddOrUpdate(int key, string value)
{
cacheLock.EnterUpgradeableReadLock();
try
{
string result = null;
if (innerCache.TryGetValue(key, out result))
{
if (result == value)
{
return AddOrUpdateStatus.Unchanged;
}
else
{
cacheLock.EnterWriteLock();
try
{
innerCache[key] = value;
}
finally
{
cacheLock.ExitWriteLock();
}
return AddOrUpdateStatus.Updated;
}
}
else
{
cacheLock.EnterWriteLock();
try
{
innerCache.Add(key, value);
}
finally
{
cacheLock.ExitWriteLock();
}
return AddOrUpdateStatus.Added;
}
}
finally
{
cacheLock.ExitUpgradeableReadLock();
}
}
public void Delete(int key)
{
cacheLock.EnterWriteLock();
try
{
innerCache.Remove(key);
}
finally
{
cacheLock.ExitWriteLock();
}
}
public enum AddOrUpdateStatus
{
Added,
Updated,
Unchanged
};
~SynchronizedCache()
{
if (cacheLock != null) cacheLock.Dispose();
}
}

I don't know how MemoryCache.Default is implemented, or whether or not you have control over it.
But in general, prefer using ConcurrentDictionary over Dictionary with lock in a multi threaded environment.
GetFromCache would just become
ConcurrentDictionary<string, T> cache = new ConcurrentDictionary<string, T>();
...
cache.GetOrAdd("someKey", (key) =>
{
var data = PullDataFromDatabase(key);
return data;
});
There are two more things to take care about.
Expiry
Instead of saving T as the value of the dictionary, you can define a type
struct CacheItem<T>
{
public T Item { get; set; }
public DateTime Expiry { get; set; }
}
And store the cache as a CacheItem with a defined expiry.
cache.GetOrAdd("someKey", (key) =>
{
var data = PullDataFromDatabase(key);
return new CacheItem<T>() { Item = data, Expiry = DateTime.UtcNow.Add(TimeSpan.FromHours(1)) };
});
Now you can implement expiration in an asynchronous thread.
Timer expirationTimer = new Timer(ExpireCache, null, 60000, 60000);
...
void ExpireCache(object state)
{
var needToExpire = cache.Where(c => DateTime.UtcNow >= c.Value.Expiry).Select(c => c.Key);
foreach (var key in needToExpire)
{
cache.TryRemove(key, out CacheItem<T> _);
}
}
Once a minute, you search for all cache entries that need to be expired, and remove them.
"Locking"
Using ConcurrentDictionary guarantees that simultaneous read/writes won't corrupt the dictionary or throw an exception.
But, you can still end up with a situation where two simultaneous reads cause you to fetch the data from the database twice.
One neat trick to solve this is to wrap the value of the dictionary with Lazy
ConcurrentDictionary<string, Lazy<CacheItem<T>>> cache = new ConcurrentDictionary<string, Lazy<CacheItem<T>>>();
...
var data = cache.GetOrData("someKey", key => new Lazy<CacheItem<T>>(() =>
{
var data = PullDataFromDatabase(key);
return new CacheItem<T>() { Item = data, Expiry = DateTime.UtcNow.Add(TimeSpan.FromHours(1)) };
})).Value;
Explanation
with GetOrAdd you might end up invoking the "get from database if not in cache" delegate multiple times in the case of simultaneous requests.
However, GetOrAdd will end up using only one of the values that the delegate returned, and by returning a Lazy, you guaranty that only one Lazy will get invoked.

Parallel.ForEach stalled when integrated with BlockingCollection

I adopted my implementation of parallel/consumer based on the code in this question
class ParallelConsumer<T> : IDisposable
{
private readonly int _maxParallel;
private readonly Action<T> _action;
private readonly TaskFactory _factory = new TaskFactory();
private CancellationTokenSource _tokenSource;
private readonly BlockingCollection<T> _entries = new BlockingCollection<T>();
private Task _task;
public ParallelConsumer(int maxParallel, Action<T> action)
{
_maxParallel = maxParallel;
_action = action;
}
public void Start()
{
try
{
_tokenSource = new CancellationTokenSource();
_task = _factory.StartNew(
() =>
{
Parallel.ForEach(
_entries.GetConsumingEnumerable(),
new ParallelOptions { MaxDegreeOfParallelism = _maxParallel, CancellationToken = _tokenSource.Token },
(item, loopState) =>
{
Log("Taking" + item);
if (!_tokenSource.IsCancellationRequested)
{
_action(item);
Log("Finished" + item);
}
else
{
Log("Not Taking" + item);
_entries.CompleteAdding();
loopState.Stop();
}
});
},
_tokenSource.Token);
}
catch (OperationCanceledException oce)
{
System.Diagnostics.Debug.WriteLine(oce);
}
}
private void Log(string message)
{
Console.WriteLine(message);
}
public void Stop()
{
Dispose();
}
public void Enqueue(T entry)
{
Log("Enqueuing" + entry);
_entries.Add(entry);
}
public void Dispose()
{
if (_task == null)
{
return;
}
_tokenSource.Cancel();
while (!_task.IsCanceled)
{
}
_task.Dispose();
_tokenSource.Dispose();
_task = null;
}
}
And here is a test code
class Program
{
static void Main(string[] args)
{
TestRepeatedEnqueue(100, 1);
}
private static void TestRepeatedEnqueue(int itemCount, int parallelCount)
{
bool[] flags = new bool[itemCount];
var consumer = new ParallelConsumer<int>(parallelCount,
(i) =>
{
flags[i] = true;
}
);
consumer.Start();
for (int i = 0; i < itemCount; i++)
{
consumer.Enqueue(i);
}
Thread.Sleep(1000);
Debug.Assert(flags.All(b => b == true));
}
}
The test always fails - it always stuck at around 93th-item from the 100 tested. Any idea which part of my code caused this issue, and how to fix it?

You cannot use Parallel.Foreach() with BlockingCollection.GetConsumingEnumerable(), as you have discovered.
For an explanation, see this blog post:
https://devblogs.microsoft.com/pfxteam/parallelextensionsextras-tour-4-blockingcollectionextensions/
Excerpt from the blog:
BlockingCollection’s GetConsumingEnumerable implementation is using BlockingCollection’s internal synchronization which already supports multiple consumers concurrently, but ForEach doesn’t know that, and its enumerable-partitioning logic also needs to take a lock while accessing the enumerable.
As such, there’s more synchronization here than is actually necessary, resulting in a potentially non-negligable performance hit.
[Also] the partitioning algorithm employed by default by both Parallel.ForEach and PLINQ use chunking in order to minimize synchronization costs: rather than taking the lock once per element, it'll take the lock, grab a group of elements (a chunk), and then release the lock.
While this design can help with overall throughput, for scenarios that are focused more on low latency, that chunking can be prohibitive.
That blog also provides the source code for a method called GetConsumingPartitioner() which you can use to solve the problem.
public static class BlockingCollectionExtensions
{
public static Partitioner<T> GetConsumingPartitioner<T>(this BlockingCollection<T> collection)
{
return new BlockingCollectionPartitioner<T>(collection);
}
public class BlockingCollectionPartitioner<T> : Partitioner<T>
{
private BlockingCollection<T> _collection;
internal BlockingCollectionPartitioner(BlockingCollection<T> collection)
{
if (collection == null)
throw new ArgumentNullException("collection");
_collection = collection;
}
public override bool SupportsDynamicPartitions
{
get { return true; }
}
public override IList<IEnumerator<T>> GetPartitions(int partitionCount)
{
if (partitionCount < 1)
throw new ArgumentOutOfRangeException("partitionCount");
var dynamicPartitioner = GetDynamicPartitions();
return Enumerable.Range(0, partitionCount).Select(_ => dynamicPartitioner.GetEnumerator()).ToArray();
}
public override IEnumerable<T> GetDynamicPartitions()
{
return _collection.GetConsumingEnumerable();
}
}
}

The reason for failure is because of the following reason as explained here
The partitioning algorithm employed by default by both
Parallel.ForEach and PLINQ use chunking in order to minimize
synchronization costs: rather than taking the lock once per element,
it'll take the lock, grab a group of elements (a chunk), and then
release the lock.
To get it to work, you can add a method on your ParallelConsumer<T> class to indicate that the adding is completed, as below
public void StopAdding()
{
_entries.CompleteAdding();
}
And now call this method after your for loop , as below
consumer.Start();
for (int i = 0; i < itemCount; i++)
{
consumer.Enqueue(i);
}
consumer.StopAdding();
Otherwise, Parallel.ForEach() would wait for the threshold to be reached so as to grab the chunk and start processing.

Threading and List<> collection

I have List<string> collection called List<string> list.
I have two threads.
One thread is enumerating through all list elements and adding to collection.
Second thread is enumerating through all list elements and removing from it.
How can make it thread safe?
I tried creating global Object "MyLock" and using lock(MyLock) block in each thread function but it didn't work.
Can you help me?

If you have access to .NET 4.0 you can use the class ConcurrentQueue or a BlockingCollection with a ConcurrentQueue backing it. It does exactly what you are trying to do and does not require any locking. The BlockingCollection will make your thread wait if there is no items available in the list.
A example of removing from the ConcurrentQueue you do something like
ConcurrentQueue<MyClass> cq = new ConcurrentQueue<MyClass>();
void GetStuff()
{
MyClass item;
if(cq.TryDeqeue(out item))
{
//Work with item
}
}
This will try to remove a item, but if there are none available it does nothing.
BlockingCollection<MyClass> bc = BlockingCollection<MyClass>(new ConcurrentQueue<MyClass>());
void GetStuff()
{
if(!bc.IsCompleated) //check to see if CompleatedAdding() was called and the list is empty.
{
try
{
MyClass item = bc.Take();
//Work with item
}
catch (InvalidOpperationExecption)
{
//Take is marked as completed and is empty so there will be nothing to take
}
}
}
This will block and wait on the Take till there is something available to take from the list. Once you are done you can call CompleteAdding() and Take will throw a execption when the list becomes empty instead of blocking.

Without knowing more about your program and requirements, I'm going say that this is a "Bad Idea". Altering a List<> while iterating through it's contents will most likely throw an exception.
You're better off using a Queue<> instead of a List<>, as a Queue<> was designed with synchronization in mind.

You should be able to lock directly on your list:
lock(list) {
//work with list here
}
However adding/removing from the list while enumerating it will likely cause an exception...

Lock on the SyncRoot of your List<T>:
lock(list.SyncRoot)
{
}
More information on how to use it properly can be found here

You could implement your own version of IList<T> that wraps the underlying List<T> to provide locking on every method call.
public class LockingList<T> : IList<T>
{
public LockingList(IList<T> inner)
{
this.Inner = inner;
}
private readonly object gate = new object();
public IList<T> Inner { get; private set; }
public int IndexOf(T item)
{
lock (gate)
{
return this.Inner.IndexOf(item);
}
}
public void Insert(int index, T item)
{
lock (gate)
{
this.Inner.Insert(index, item);
}
}
public void RemoveAt(int index)
{
lock (gate)
{
this.Inner.RemoveAt(index);
}
}
public T this[int index]
{
get
{
lock (gate)
{
return this.Inner[index];
}
}
set
{
lock (gate)
{
this.Inner[index] = value;
}
}
}
public void Add(T item)
{
lock (gate)
{
this.Inner.Add(item);
}
}
public void Clear()
{
lock (gate)
{
this.Inner.Clear();
}
}
public bool Contains(T item)
{
lock (gate)
{
return this.Inner.Contains(item);
}
}
public void CopyTo(T[] array, int arrayIndex)
{
lock (gate)
{
this.Inner.CopyTo(array, arrayIndex);
}
}
public int Count
{
get
{
lock (gate)
{
return this.Inner.Count;
}
}
}
public bool IsReadOnly
{
get
{
lock (gate)
{
return this.Inner.IsReadOnly;
}
}
}
public bool Remove(T item)
{
lock (gate)
{
return this.Inner.Remove(item);
}
}
public IEnumerator<T> GetEnumerator()
{
lock (gate)
{
return this.Inner.ToArray().AsEnumerable().GetEnumerator();
}
}
IEnumerator IEnumerable.GetEnumerator()
{
lock (gate)
{
return this.Inner.ToArray().GetEnumerator();
}
}
}
You would use this code like this:
var list = new LockingList<int>(new List<int>());
If you're using large lists and/or performance is an issue then this kind of locking may not be terribly performant, but in most cases it should be fine.
It is very important to notice that the two GetEnumerator methods call .ToArray(). This forces the evaluation of the enumerator before the lock is released thus ensuring that any modifications to the list don't affect the actual enumeration.
Using code like lock (list) { ... } or lock (list.SyncRoot) { ... } do not cover you against list changes occurring during enumerations. These solutions only cover against concurrent modifications to the list - and that's only if all callers do so within a lock. Also these solutions can cause your code to die if some nasty bit of code takes a lock and doesn't release it.
In my solution you'll notice I have a object gate that is a private variable internal to the class that I lock on. Nothing outside the class can lock on this so it is safe.
I hope this helps.

As others already said, you can use concurrent collections from the System.Collections.Concurrent namespace. If you can use one of those, this is preferred.
But if you really want a list which is just synchronized, you could look at the SynchronizedCollection<T>-Class in System.Collections.Generic.
Note that you had to include the System.ServiceModel assembly, which is also the reason why I don't like it so much. But sometimes I use it.

Async result handle to return to callers

I have a method that queues some work to be executed asynchronously. I'd like to return some sort of handle to the caller that can be polled, waited on, or used to fetch the return value from the operation, but I can't find a class or interface that's suitable for the task.
BackgroundWorker comes close, but it's geared to the case where the worker has its own dedicated thread, which isn't true in my case. IAsyncResult looks promising, but the provided AsyncResult implementation is also unusable for me. Should I implement IAsyncResult myself?
Clarification:
I have a class that conceptually looks like this:
class AsyncScheduler
{
private List<object> _workList = new List<object>();
private bool _finished = false;
public SomeHandle QueueAsyncWork(object workObject)
{
// simplified for the sake of example
_workList.Add(workObject);
return SomeHandle;
}
private void WorkThread()
{
// simplified for the sake of example
while (!_finished)
{
foreach (object workObject in _workList)
{
if (!workObject.IsFinished)
{
workObject.DoSomeWork();
}
}
Thread.Sleep(1000);
}
}
}
The QueueAsyncWork function pushes a work item onto the polling list for a dedicated work thread, of which there will only over be one. My problem is not with writing the QueueAsyncWork function--that's fine. My question is, what do I return to the caller? What should SomeHandle be?
The existing .Net classes for this are geared towards the situation where the asynchronous operation can be encapsulated in a single method call that returns. That's not the case here--all of the work objects do their work on the same thread, and a complete work operation might span multiple calls to workObject.DoSomeWork(). In this case, what's a reasonable approach for offering the caller some handle for progress notification, completion, and getting the final outcome of the operation?

Yes, implement IAsyncResult (or rather, an extended version of it, to provide for progress reporting).
public class WorkObjectHandle : IAsyncResult, IDisposable
{
private int _percentComplete;
private ManualResetEvent _waitHandle;
public int PercentComplete {
get {return _percentComplete;}
set
{
if (value < 0 || value > 100) throw new InvalidArgumentException("Percent complete should be between 0 and 100");
if (_percentComplete = 100) throw new InvalidOperationException("Already complete");
if (value == 100 && Complete != null) Complete(this, new CompleteArgs(WorkObject));
_percentComplete = value;
}
public IWorkObject WorkObject {get; private set;}
public object AsyncState {get {return WorkObject;}}
public bool IsCompleted {get {return _percentComplete == 100;}}
public event EventHandler<CompleteArgs> Complete; // CompleteArgs in a usual pattern
// you may also want to have Progress event
public bool CompletedSynchronously {get {return false;}}
public WaitHandle
{
get
{
// initialize it lazily
if (_waitHandle == null)
{
ManualResetEvent newWaitHandle = new ManualResetEvent(false);
if (Interlocked.CompareExchange(ref _waitHandle, newWaitHandle, null) != null)
newWaitHandle.Dispose();
}
return _waitHandle;
}
}
public void Dispose()
{
if (_waitHandle != null)
_waitHandle.Dispose();
// dispose _workObject too, if needed
}
public WorkObjectHandle(IWorkObject workObject)
{
WorkObject = workObject;
_percentComplete = 0;
}
}
public class AsyncScheduler
{
private Queue<WorkObjectHandle> _workQueue = new Queue<WorkObjectHandle>();
private bool _finished = false;
public WorkObjectHandle QueueAsyncWork(IWorkObject workObject)
{
var handle = new WorkObjectHandle(workObject);
lock(_workQueue)
{
_workQueue.Enqueue(handle);
}
return handle;
}
private void WorkThread()
{
// simplified for the sake of example
while (!_finished)
{
WorkObjectHandle handle;
lock(_workQueue)
{
if (_workQueue.Count == 0) break;
handle = _workQueue.Dequeue();
}
try
{
var workObject = handle.WorkObject;
// do whatever you want with workObject, set handle.PercentCompleted, etc.
}
finally
{
handle.Dispose();
}
}
}
}

If I understand correctly you have a collection of work objects (IWorkObject) that each complete a task via multiple calls to a DoSomeWork method. When an IWorkObject object has finished its work you'd like to respond to that somehow and during the process you'd like to respond to any reported progress?
In that case I'd suggest you take a slightly different approach. You could take a look at the Parallel Extension framework (blog). Using the framework, you could write something like this:
public void QueueWork(IWorkObject workObject)
{
Task.TaskFactory.StartNew(() =>
{
while (!workObject.Finished)
{
int progress = workObject.DoSomeWork();
DoSomethingWithReportedProgress(workObject, progress);
}
WorkObjectIsFinished(workObject);
});
}
Some things to note:
QueueWork now returns void. The reason for this is that the actions that occur when progress is reported or when the task completes have become part of the thread that executes the work. You could of course return the Task that the factory creates and return that from the method (to enable polling for example).
The progress-reporting and finish-handling are now part of the thread because you should always avoid polling when possible. Polling is more expensive because usually you either poll too frequently (too early) or not often enough (too late). There is no reason you can't report on the progress and finishing of the task from within the thread that is running the task.
The above could also be implemented using the (lower level) ThreadPool.QueueUserWorkItem method.
Using QueueUserWorkItem:
public void QueueWork(IWorkObject workObject)
{
ThreadPool.QueueUserWorkItem(() =>
{
while (!workObject.Finished)
{
int progress = workObject.DoSomeWork();
DoSomethingWithReportedProgress(workObject, progress);
}
WorkObjectIsFinished(workObject);
});
}

The WorkObject class can contain the properties that need to be tracked.
public class WorkObject
{
public PercentComplete { get; private set; }
public IsFinished { get; private set; }
public void DoSomeWork()
{
// work done here
this.PercentComplete = 50;
// some more work done here
this.PercentComplete = 100;
this.IsFinished = true;
}
}
Then in your example:
Change the collection from a List to a Dictionary that can hold Guid values (or any other means of uniquely identifying the value).
Expose the correct WorkObject's properties by having the caller pass the Guid that it received from QueueAsyncWork.
I'm assuming that you'll start WorkThread asynchronously (albeit, the only asynchronous thread); plus, you'll have to make retrieving the dictionary values and WorkObject properties thread-safe.
private Dictionary<Guid, WorkObject> _workList =
new Dictionary<Guid, WorkObject>();
private bool _finished = false;
public Guid QueueAsyncWork(WorkObject workObject)
{
Guid guid = Guid.NewGuid();
// simplified for the sake of example
_workList.Add(guid, workObject);
return guid;
}
private void WorkThread()
{
// simplified for the sake of example
while (!_finished)
{
foreach (WorkObject workObject in _workList)
{
if (!workObject.IsFinished)
{
workObject.DoSomeWork();
}
}
Thread.Sleep(1000);
}
}
// an example of getting the WorkObject's property
public int GetPercentComplete(Guid guid)
{
WorkObject workObject = null;
if (!_workList.TryGetValue(guid, out workObject)
throw new Exception("Unable to find Guid");
return workObject.PercentComplete;
}

The simplest way to do this is described here. Suppose you have a method string DoSomeWork(int). You then create a delegate of the correct type, for example:
Func<int, string> myDelegate = DoSomeWork;
Then you call the BeginInvoke method on the delegate:
int parameter = 10;
myDelegate.BeginInvoke(parameter, Callback, null);
The Callback delegate will be called once your asynchronous call has completed. You can define this method as follows:
void Callback(IAsyncResult result)
{
var asyncResult = (AsyncResult) result;
var #delegate = (Func<int, string>) asyncResult.AsyncDelegate;
string methodReturnValue = #delegate.EndInvoke(result);
}
Using the described scenario, you can also poll for results or wait on them. Take a look at the url I provided for more info.
Regards,
Ronald

If you don't want to use async callbacks, you can use an explicit WaitHandle, such as a ManualResetEvent:
public abstract class WorkObject : IDispose
{
ManualResetEvent _waitHandle = new ManualResetEvent(false);
public void DoSomeWork()
{
try
{
this.DoSomeWorkOverride();
}
finally
{
_waitHandle.Set();
}
}
protected abstract DoSomeWorkOverride();
public void WaitForCompletion()
{
_waitHandle.WaitOne();
}
public void Dispose()
{
_waitHandle.Dispose();
}
}
And in your code you could say
using (var workObject = new SomeConcreteWorkObject())
{
asyncScheduler.QueueAsyncWork(workObject);
workObject.WaitForCompletion();
}
Don't forget to call Dispose on your workObject though.
You can always use alternate implementations which create a wrapper like this for every work object, and who call _waitHandle.Dispose() in WaitForCompletion(), you can lazily instantiate the wait handle (careful: race conditions ahead), etc. (That's pretty much what BeginInvoke does for delegates.)