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;
}
}
这是一个测试代码
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));
}
}
解决方法
http://blogs.msdn.com/b/pfxteam/archive/2010/04/06/9990420.aspx
该博客还提供了一个名为GetConsumingPartitioner()的方法的源代码,您可以使用它来解决问题.
摘自博客：
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.
