限制任務並行庫中的線程數

Question

我有幾百個文件需要上傳到Azure Blob存儲。
我想使用並行任務庫。
但是，如何在foreach文件列表中運行所有100個線程上傳，我如何限制它可以使用的最大線程數並並行完成作業。 還是自動平衡事物？

Answer 1

你根本不應該使用線程。 有一個基於Task的API，它自然是異步的： CloudBlockBlob.UploadFromFileAsync 。 與async/await和SemaphoreSlim一起使用它可以限制並行上傳的次數。

示例（未經測試）：

const MAX_PARALLEL_UPLOADS = 5;

async Task UploadFiles()
{
    var files = new List<string>();
    // ... add files to the list

    // init the blob block and
    // upload files asynchronously
    using (var blobBlock = new CloudBlockBlob(url, credentials))
    using (var semaphore = new SemaphoreSlim(MAX_PARALLEL_UPLOADS))
    {
        var tasks = files.Select(async(filename) => 
        {
            await semaphore.WaitAsync();
            try
            {
                await blobBlock.UploadFromFileAsync(filename, FileMode.Create);
            }
            finally
            {
                semaphore.Release();
            }
        }).ToArray();

        await Task.WhenAll(tasks);
    }
}

Answer 2

你嘗試過使用MaxDegreeOfParallelism嗎？ 像這樣：

System.Threading.Tasks.Parallel.Invoke(
new Tasks.ParallelOptions {MaxDegreeOfParallelism =  5 }, actionsArray)

Answer 3

基本上，您將要為要上載的每個文件創建一個Action或Task，將它們放入List中，然后處理該列表，從而限制可以並行處理的數量。

我的博客文章展示了如何使用“任務”和“操作”執行此操作，並提供了一個示例項目，您可以下載並運行以查看兩者的實際操作。

有了動作

如果使用Actions，則可以使用內置的.Net Parallel.Invoke函數。 在這里，我們將其限制為最多並行運行5個線程。

var listOfActions = new List<Action>();
foreach (var file in files)
{
    var localFile = file;
    // Note that we create the Task here, but do not start it.
    listOfTasks.Add(new Task(() => blobBlock.UploadFromFileAsync(localFile, FileMode.Create)));
}

var options = new ParallelOptions {MaxDegreeOfParallelism = 5};
Parallel.Invoke(options, listOfActions.ToArray());

但是，此選項不使用UploadFromFileAsync的異步特性，因此您可能希望使用下面的Task示例。

隨着任務

使用任務，沒有內置功能。 但是，您可以使用我在博客上提供的那個。

    /// <summary>
    /// Starts the given tasks and waits for them to complete. This will run, at most, the specified number of tasks in parallel.
    /// <para>NOTE: If one of the given tasks has already been started, an exception will be thrown.</para>
    /// </summary>
    /// <param name="tasksToRun">The tasks to run.</param>
    /// <param name="maxTasksToRunInParallel">The maximum number of tasks to run in parallel.</param>
    /// <param name="cancellationToken">The cancellation token.</param>
    public static async Task StartAndWaitAllThrottledAsync(IEnumerable<Task> tasksToRun, int maxTasksToRunInParallel, CancellationToken cancellationToken = new CancellationToken())
    {
        await StartAndWaitAllThrottledAsync(tasksToRun, maxTasksToRunInParallel, -1, cancellationToken);
    }

    /// <summary>
    /// Starts the given tasks and waits for them to complete. This will run the specified number of tasks in parallel.
    /// <para>NOTE: If a timeout is reached before the Task completes, another Task may be started, potentially running more than the specified maximum allowed.</para>
    /// <para>NOTE: If one of the given tasks has already been started, an exception will be thrown.</para>
    /// </summary>
    /// <param name="tasksToRun">The tasks to run.</param>
    /// <param name="maxTasksToRunInParallel">The maximum number of tasks to run in parallel.</param>
    /// <param name="timeoutInMilliseconds">The maximum milliseconds we should allow the max tasks to run in parallel before allowing another task to start. Specify -1 to wait indefinitely.</param>
    /// <param name="cancellationToken">The cancellation token.</param>
    public static async Task StartAndWaitAllThrottledAsync(IEnumerable<Task> tasksToRun, int maxTasksToRunInParallel, int timeoutInMilliseconds, CancellationToken cancellationToken = new CancellationToken())
    {
        // Convert to a list of tasks so that we don't enumerate over it multiple times needlessly.
        var tasks = tasksToRun.ToList();

        using (var throttler = new SemaphoreSlim(maxTasksToRunInParallel))
        {
            var postTaskTasks = new List<Task>();

            // Have each task notify the throttler when it completes so that it decrements the number of tasks currently running.
            tasks.ForEach(t => postTaskTasks.Add(t.ContinueWith(tsk => throttler.Release())));

            // Start running each task.
            foreach (var task in tasks)
            {
                // Increment the number of tasks currently running and wait if too many are running.
                await throttler.WaitAsync(timeoutInMilliseconds, cancellationToken);

                cancellationToken.ThrowIfCancellationRequested();
                task.Start();
            }

            // Wait for all of the provided tasks to complete.
            // We wait on the list of "post" tasks instead of the original tasks, otherwise there is a potential race condition where the throttler's using block is exited before some Tasks have had their "post" action completed, which references the throttler, resulting in an exception due to accessing a disposed object.
            await Task.WhenAll(postTaskTasks.ToArray());
        }
    }

然后創建任務列表並調用函數讓它們運行，一次最多同時執行5個，你可以這樣做：

var listOfTasks = new List<Task>();
foreach (var file in files)
{
    var localFile = file;
    // Note that we create the Task here, but do not start it.
    listOfTasks.Add(new Task(async () => await blobBlock.UploadFromFileAsync(localFile, FileMode.Create)));
}
await Tasks.StartAndWaitAllThrottledAsync(listOfTasks, 5);

Answer 4

你可以通過運行這個來找到：

class Program
{
    static void Main(string[] args)
    {
        var list = new List<int>();

        for (int i = 0; i < 100; i++)
        {
            list.Add(i);
        }

        var runningIndex = 0;

        Task.Factory.StartNew(() => Action(ref runningIndex));

        Parallel.ForEach(list, i =>
        {
            runningIndex ++;
            Console.WriteLine(i);
            Thread.Sleep(3000);
        });

        Console.ReadKey();
    }

    private static void Action(ref int number)
    {
        while (true)
        {
            Console.WriteLine("worked through {0}", number);
            Thread.Sleep(2900);
        }
    }
}

正如您所看到的，並行性的數量在開始時較小，變得更大，並且在結束時變小。 所以肯定會有某種自動優化。