Nesting await in Parallel.ForEach

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In a metro app, I need to execute a number of WCF calls. There are a significant number of calls to be made, so I need to do them in a parallel loop. The problem is that the parallel loop exits before the WCF calls are all complete.

How would you refactor this to work as expected?

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();
11 Answers

An extension method for this which makes use of SemaphoreSlim and also allows to set maximum degree of parallelism

    /// <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)));
        }
    }

Sample Usage:

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

After introducing a bunch of helper methods, you will be able run parallel queries with this simple syntax:

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

What happens here is: we split source collection into 10 chunks (.Split(DegreeOfParallelism)), then run 10 tasks each processing its items one by one (.SelectManyAsync(...)) and merge those back into a single list.

Worth mentioning there is a simpler approach:

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

But it needs a precaution: if you have a source collection that is too big, it will schedule a Task for every item right away, which may cause significant performance hits.

Extension methods used in examples above look as follows:

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);
    }
}

.NET 6 update: The implementations below are no longer relevant after the introduction of the Parallel.ForEachAsync API. They can be useful only for projects that are targeting versions of the .NET platform older than the .NET 6.


Here is a simple generic implementation of a ForEachAsync method, based on an ActionBlock from the TPL Dataflow library, now embedded in the .NET 5 platform:

public static Task ForEachAsync<T>(this IEnumerable<T> source,
    Func<T, Task> action, int dop)
{
    // Arguments validation omitted
    var block = new ActionBlock<T>(action,
        new ExecutionDataflowBlockOptions() { MaxDegreeOfParallelism = dop });
    try
    {
        foreach (var item in source) block.Post(item);
        block.Complete();
    }
    catch (Exception ex) { ((IDataflowBlock)block).Fault(ex); }
    return block.Completion;
}

This solution enumerates eagerly the supplied IEnumerable, and sends immediately all its elements to the ActionBlock. So it is not very suitable for enumerables with huge number of elements. Below is a more sophisticated approach, that enumerates the source lazily, and sends its elements to the ActionBlock one by one:

public static async Task ForEachAsync<T>(this IEnumerable<T> source,
    Func<T, Task> action, int dop)
{
    // Arguments validation omitted
    var block = new ActionBlock<T>(action, new ExecutionDataflowBlockOptions()
    { MaxDegreeOfParallelism = dop, BoundedCapacity = dop });
    try
    {
        foreach (var item in source)
            if (!await block.SendAsync(item).ConfigureAwait(false)) break;
        block.Complete();
    }
    catch (Exception ex) { ((IDataflowBlock)block).Fault(ex); }
    try { await block.Completion.ConfigureAwait(false); }
    catch { block.Completion.Wait(); } // Propagate AggregateException
}

These two methods have different behavior in case of exceptions. The first¹ propagates an AggregateException containing the exceptions directly in its InnerExceptions property. The second propagates an AggregateException that contains another AggregateException with the exceptions. Personally I find the behavior of the second method more convenient in practice, because awaiting it eliminates automatically a level of nesting, and so I can simply catch (AggregateException aex) and handle the aex.InnerExceptions inside the catch block. The first method requires to store the Task before awaiting it, so that I can gain access the task.Exception.InnerExceptions inside the catch block. For more info about propagating exceptions from async methods, look here or here.

Both implementations handle gracefully any errors that may occur during the enumeration of the source. The ForEachAsync method does not complete before all pending operations are completed. No tasks are left behind unobserved (in fire-and-forget fashion).

¹ The first implementation elides async and await.

Easy native way without TPL:

int totalThreads = 0; int maxThreads = 3;

foreach (var item in YouList)
{
    while (totalThreads >= maxThreads) await Task.Delay(500);
    Interlocked.Increment(ref totalThreads);

    MyAsyncTask(item).ContinueWith((res) => Interlocked.Decrement(ref totalThreads));
}

you can check this solution with next task:

async static Task MyAsyncTask(string item)
{
    await Task.Delay(2500);
    Console.WriteLine(item);
}
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