如何限制每秒对Web服务器的HttpWebRequest数量

我遇到了同样的问题，找不到现成的解决方案，所以我做了一个，就在这里。这个想法是使用BlockingCollection<T>添加需要处理的项目，并使用反应式扩展订阅速率受限的处理器。

节流类是此速率限制器的重命名版本

public static class BlockingCollectionExtensions
{
    // TODO: devise a way to avoid problems if collection gets too big (produced faster than consumed)
    public static IObservable<T> AsRateLimitedObservable<T>(this BlockingCollection<T> sequence, int items, TimeSpan timePeriod, CancellationToken producerToken)
    {
        Subject<T> subject = new Subject<T>();
        // this is a dummyToken just so we can recreate the TokenSource
        // which we will pass the proxy class so it can cancel the task
        // on disposal
        CancellationToken dummyToken = new CancellationToken();
        CancellationTokenSource tokenSource = CancellationTokenSource.CreateLinkedTokenSource(producerToken, dummyToken);
        var consumingTask = new Task(() =>
        {
            using (var throttle = new Throttle(items, timePeriod))
            {
                while (!sequence.IsCompleted)
                {
                    try
                    {
                        T item = sequence.Take(producerToken);
                        throttle.WaitToProceed();
                        try
                        {
                            subject.OnNext(item);
                        }
                        catch (Exception ex)
                        {
                            subject.OnError(ex);
                        }
                    }
                    catch (OperationCanceledException)
                    {
                        break;
                    }
                }
                subject.OnCompleted();
            }
        }, TaskCreationOptions.LongRunning);
        return new TaskAwareObservable<T>(subject, consumingTask, tokenSource);
    }
    private class TaskAwareObservable<T> : IObservable<T>, IDisposable
    {
        private readonly Task task;
        private readonly Subject<T> subject;
        private readonly CancellationTokenSource taskCancellationTokenSource;
        public TaskAwareObservable(Subject<T> subject, Task task, CancellationTokenSource tokenSource)
        {
            this.task = task;
            this.subject = subject;
            this.taskCancellationTokenSource = tokenSource;
        }
        public IDisposable Subscribe(IObserver<T> observer)
        {
            var disposable = subject.Subscribe(observer);
            if (task.Status == TaskStatus.Created)
                task.Start();
            return disposable;
        }
        public void Dispose()
        {
            // cancel consumption and wait task to finish
            taskCancellationTokenSource.Cancel();
            task.Wait();
            // dispose tokenSource and task
            taskCancellationTokenSource.Dispose();
            task.Dispose();
            // dispose subject
            subject.Dispose();
        }
    }
}

单元测试：

class BlockCollectionExtensionsTest
{
    [Fact]
    public void AsRateLimitedObservable()
    {
        const int maxItems = 1; // fix this to 1 to ease testing
        TimeSpan during = TimeSpan.FromSeconds(1);
        // populate collection
        int[] items = new[] { 1, 2, 3, 4 };
        BlockingCollection<int> collection = new BlockingCollection<int>();
        foreach (var i in items) collection.Add(i);
        collection.CompleteAdding();
        IObservable<int> observable = collection.AsRateLimitedObservable(maxItems, during, CancellationToken.None);
        BlockingCollection<int> processedItems = new BlockingCollection<int>();
        ManualResetEvent completed = new ManualResetEvent(false);
        DateTime last = DateTime.UtcNow;
        observable
            // this is so we'll receive exceptions
            .ObserveOn(new SynchronizationContext()) 
            .Subscribe(item =>
                {
                    if (item == 1)
                        last = DateTime.UtcNow;
                    else
                    {
                        TimeSpan diff = (DateTime.UtcNow - last);
                        last = DateTime.UtcNow;
                        Assert.InRange(diff.TotalMilliseconds,
                            during.TotalMilliseconds - 30,
                            during.TotalMilliseconds + 30);
                    }
                    processedItems.Add(item);
                },
                () => completed.Set()
            );
        completed.WaitOne();
        Assert.Equal(items, processedItems, new CollectionEqualityComparer<int>());
    }
}

Throttle（） 和 Sample（） 扩展方法（On Observable）允许您将快速的事件序列调节为"较慢"序列。

这是一篇博客文章，其中包含确保最大速率的Sample(Timespan)示例。

我最初的帖子讨论了如何通过客户端行为扩展向 WCF 添加限制机制，但随后指出我误读了这个问题（doh！

总体而言，方法是检查确定我们是否违反了速率限制的类。关于如何检查费率违规，已经有很多讨论。

限制

方法 在 N 秒内调用 M 个请求

如果您违反了速率限制，请睡眠一段时间，然后再次检查。如果没有，请继续进行 HttpWebRequest 调用。