在Parallel.ForEach中嵌套等待

在Metro应用程序中，我需要执行许多WCF调用。需要进行大量调用，因此我需要在并行循环中进行调用。问题在于并行循环在WCF调用全部完成之前退出。

您将如何重构它以使其按预期工作？

var ids = new List<string>() { "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" };
var customers = new  System.Collections.Concurrent.BlockingCollection<Customer>();

Parallel.ForEach(ids, async i =>
{
    ICustomerRepo repo = new CustomerRepo();
    var cust = await repo.GetCustomer(i);
    customers.Add(cust);
});

foreach ( var customer in customers )
{
    Console.WriteLine(customer.ID);
}

Console.ReadKey();

背后的整个想法Parallel.ForEach()是，您有一组线程，每个线程处理集合的一部分。正如您所注意到的，这不适用于async- await，您要在异步调用期间释放线程。

您可以通过阻塞ForEach()线程来“修复”该问题，但这使async- 的全部观点无效await。

您可以做的是使用TPL Dataflow代替Parallel.ForEach()，它Task很好地支持异步。

具体来说，您的代码可以使用编写TransformBlock，该代码Customer使用asynclambda 将每个id转换为。可以将该块配置为并行执行。您可以将该块链接到ActionBlock写入每个Customer控制台。设置区块网络后，您可以将Post()每个ID分配到TransformBlock。

在代码中：

var ids = new List<string> { "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" };

var getCustomerBlock = new TransformBlock<string, Customer>(
    async i =>
    {
        ICustomerRepo repo = new CustomerRepo();
        return await repo.GetCustomer(i);
    }, new ExecutionDataflowBlockOptions
    {
        MaxDegreeOfParallelism = DataflowBlockOptions.Unbounded
    });
var writeCustomerBlock = new ActionBlock<Customer>(c => Console.WriteLine(c.ID));
getCustomerBlock.LinkTo(
    writeCustomerBlock, new DataflowLinkOptions
    {
        PropagateCompletion = true
    });

foreach (var id in ids)
    getCustomerBlock.Post(id);

getCustomerBlock.Complete();
writeCustomerBlock.Completion.Wait();

尽管您可能希望将的并行性限制TransformBlock为一些小常数。另外，您可以限制TransformBlock并使用异步添加项目SendAsync()，例如，如果集合太大。

与您的代码（如果可行）相比，另一个好处是，写入将在单个项目完成后立即开始，而不必等到所有处理都完成了。

svick的答案（与往常一样）非常好。

但是，当您实际上有大量数据要传输时，我发现Dataflow更加有用。或者，当您需要async兼容的队列时。

在您的情况下，一个更简单的解决方案是仅使用async-style并行性：

var ids = new List<string>() { "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" };

var customerTasks = ids.Select(i =>
  {
    ICustomerRepo repo = new CustomerRepo();
    return repo.GetCustomer(i);
  });
var customers = await Task.WhenAll(customerTasks);

foreach (var customer in customers)
{
  Console.WriteLine(customer.ID);
}

Console.ReadKey();

如建议的那样使用DataFlow可能会过大，并且Stephen的答案没有提供控制操作并发的方法。但是，可以很简单地实现：

public static async Task RunWithMaxDegreeOfConcurrency<T>(
     int maxDegreeOfConcurrency, IEnumerable<T> collection, Func<T, Task> taskFactory)
{
    var activeTasks = new List<Task>(maxDegreeOfConcurrency);
    foreach (var task in collection.Select(taskFactory))
    {
        activeTasks.Add(task);
        if (activeTasks.Count == maxDegreeOfConcurrency)
        {
            await Task.WhenAny(activeTasks.ToArray());
            //observe exceptions here
            activeTasks.RemoveAll(t => t.IsCompleted); 
        }
    }
    await Task.WhenAll(activeTasks.ToArray()).ContinueWith(t => 
    {
        //observe exceptions in a manner consistent with the above   
    });
}

该ToArray()呼叫可以通过使用数组，而不是一个列表，并更换完成的任务进行优化，但我怀疑这会挣很多在大多数情况下的差别。根据OP的问题使用示例：

RunWithMaxDegreeOfConcurrency(10, ids, async i =>
{
    ICustomerRepo repo = new CustomerRepo();
    var cust = await repo.GetCustomer(i);
    customers.Add(cust);
});

编辑研究员SO用户和TPL wiz Eli Arbel向我介绍了Stephen Toub的相关文章。和往常一样，他的实现既优雅又高效：

public static Task ForEachAsync<T>(
      this IEnumerable<T> source, int dop, Func<T, Task> body) 
{ 
    return Task.WhenAll( 
        from partition in Partitioner.Create(source).GetPartitions(dop) 
        select Task.Run(async delegate { 
            using (partition) 
                while (partition.MoveNext()) 
                    await body(partition.Current).ContinueWith(t => 
                          {
                              //observe exceptions
                          });

        })); 
}

您可以使用新的AsyncEnumerator NuGet包节省精力，该包在4年前最初发布该问题时还不存在。它允许您控制并行度：

using System.Collections.Async;
...

await ids.ParallelForEachAsync(async i =>
{
    ICustomerRepo repo = new CustomerRepo();
    var cust = await repo.GetCustomer(i);
    customers.Add(cust);
},
maxDegreeOfParallelism: 10);

免责声明：我是AsyncEnumerator库的作者，该库是MIT许可的开放源代码，并且我发布此消息只是为了帮助社区。

将Parallel.Foreach换成a Task.Run()，而不是await关键字use[yourasyncmethod].Result

（您需要执行Task.Run之类的操作才能不阻塞UI线程）

像这样：

var yourForeachTask = Task.Run(() =>
        {
            Parallel.ForEach(ids, i =>
            {
                ICustomerRepo repo = new CustomerRepo();
                var cust = repo.GetCustomer(i).Result;
                customers.Add(cust);
            });
        });
await yourForeachTask;

与使整个TPL Dataflow正常工作相比，这应该是非常有效的，并且更容易：

var customers = await ids.SelectAsync(async i =>
{
    ICustomerRepo repo = new CustomerRepo();
    return await repo.GetCustomer(i);
});

...

public static async Task<IList<TResult>> SelectAsync<TSource, TResult>(this IEnumerable<TSource> source, Func<TSource, Task<TResult>> selector, int maxDegreesOfParallelism = 4)
{
    var results = new List<TResult>();

    var activeTasks = new HashSet<Task<TResult>>();
    foreach (var item in source)
    {
        activeTasks.Add(selector(item));
        if (activeTasks.Count >= maxDegreesOfParallelism)
        {
            var completed = await Task.WhenAny(activeTasks);
            activeTasks.Remove(completed);
            results.Add(completed.Result);
        }
    }

    results.AddRange(await Task.WhenAll(activeTasks));
    return results;
}

我来晚了一点，但是您可能要考虑使用GetAwaiter.GetResult（）在同步上下文中运行异步代码，但如下所示；

 Parallel.ForEach(ids, i =>
{
    ICustomerRepo repo = new CustomerRepo();
    // Run this in thread which Parallel library occupied.
    var cust = repo.GetCustomer(i).GetAwaiter().GetResult();
    customers.Add(cust);
});

一个扩展方法，它使用SemaphoreSlim并允许设置最大并行度

    /// <summary>
    /// Concurrently Executes async actions for each item of <see cref="IEnumerable<typeparamref name="T"/>
    /// </summary>
    /// <typeparam name="T">Type of IEnumerable</typeparam>
    /// <param name="enumerable">instance of <see cref="IEnumerable<typeparamref name="T"/>"/></param>
    /// <param name="action">an async <see cref="Action" /> to execute</param>
    /// <param name="maxDegreeOfParallelism">Optional, An integer that represents the maximum degree of parallelism,
    /// Must be grater than 0</param>
    /// <returns>A Task representing an async operation</returns>
    /// <exception cref="ArgumentOutOfRangeException">If the maxActionsToRunInParallel is less than 1</exception>
    public static async Task ForEachAsyncConcurrent<T>(
        this IEnumerable<T> enumerable,
        Func<T, Task> action,
        int? maxDegreeOfParallelism = null)
    {
        if (maxDegreeOfParallelism.HasValue)
        {
            using (var semaphoreSlim = new SemaphoreSlim(
                maxDegreeOfParallelism.Value, maxDegreeOfParallelism.Value))
            {
                var tasksWithThrottler = new List<Task>();

                foreach (var item in enumerable)
                {
                    // Increment the number of currently running tasks and wait if they are more than limit.
                    await semaphoreSlim.WaitAsync();

                    tasksWithThrottler.Add(Task.Run(async () =>
                    {
                        await action(item).ContinueWith(res =>
                        {
                            // action is completed, so decrement the number of currently running tasks
                            semaphoreSlim.Release();
                        });
                    }));
                }

                // Wait for all tasks to complete.
                await Task.WhenAll(tasksWithThrottler.ToArray());
            }
        }
        else
        {
            await Task.WhenAll(enumerable.Select(item => action(item)));
        }
    }

用法示例：

await enumerable.ForEachAsyncConcurrent(
    async item =>
    {
        await SomeAsyncMethod(item);
    },
    5);

引入了许多辅助方法之后，您将可以使用以下简单语法运行并行查询：

const int DegreeOfParallelism = 10;
IEnumerable<double> result = await Enumerable.Range(0, 1000000)
    .Split(DegreeOfParallelism)
    .SelectManyAsync(async i => await CalculateAsync(i).ConfigureAwait(false))
    .ConfigureAwait(false);

这里发生的是：我们将源集合分为10个块（.Split(DegreeOfParallelism)），然后运行10个任务，每个任务一个接一个地处理其项目），然后.SelectManyAsync(...)将这些项目合并回到一个列表中。

值得一提的是有一个更简单的方法：

double[] result2 = await Enumerable.Range(0, 1000000)
    .Select(async i => await CalculateAsync(i).ConfigureAwait(false))
    .WhenAll()
    .ConfigureAwait(false);

但是需要注意：如果您的源集合太大，则会立即Task为每个项目安排一个源集合，这可能会严重影响性能。

上面的示例中使用的扩展方法如下所示：

public static class CollectionExtensions
{
    /// <summary>
    /// Splits collection into number of collections of nearly equal size.
    /// </summary>
    public static IEnumerable<List<T>> Split<T>(this IEnumerable<T> src, int slicesCount)
    {
        if (slicesCount <= 0) throw new ArgumentOutOfRangeException(nameof(slicesCount));

        List<T> source = src.ToList();
        var sourceIndex = 0;
        for (var targetIndex = 0; targetIndex < slicesCount; targetIndex++)
        {
            var list = new List<T>();
            int itemsLeft = source.Count - targetIndex;
            while (slicesCount * list.Count < itemsLeft)
            {
                list.Add(source[sourceIndex++]);
            }

            yield return list;
        }
    }

    /// <summary>
    /// Takes collection of collections, projects those in parallel and merges results.
    /// </summary>
    public static async Task<IEnumerable<TResult>> SelectManyAsync<T, TResult>(
        this IEnumerable<IEnumerable<T>> source,
        Func<T, Task<TResult>> func)
    {
        List<TResult>[] slices = await source
            .Select(async slice => await slice.SelectListAsync(func).ConfigureAwait(false))
            .WhenAll()
            .ConfigureAwait(false);
        return slices.SelectMany(s => s);
    }

    /// <summary>Runs selector and awaits results.</summary>
    public static async Task<List<TResult>> SelectListAsync<TSource, TResult>(this IEnumerable<TSource> source, Func<TSource, Task<TResult>> selector)
    {
        List<TResult> result = new List<TResult>();
        foreach (TSource source1 in source)
        {
            TResult result1 = await selector(source1).ConfigureAwait(false);
            result.Add(result1);
        }
        return result;
    }

    /// <summary>Wraps tasks with Task.WhenAll.</summary>
    public static Task<TResult[]> WhenAll<TResult>(this IEnumerable<Task<TResult>> source)
    {
        return Task.WhenAll<TResult>(source);
    }
}