I am trying to update my toolset with the new tools offered by C# 8, and one method that seems particularly useful is a version of Task.WhenAll
that returns an IAsyncEnumerable
. This method should stream the task results as soon as they become available, so naming it WhenAll
doesn't make much sense. WhenEach
sounds more appropriate. The signature of the method is:
public static IAsyncEnumerable<TResult> WhenEach<TResult>(Task<TResult>[] tasks);
This method could be used like this:
var tasks = new Task<int>[]
{
ProcessAsync(1, 300),
ProcessAsync(2, 500),
ProcessAsync(3, 400),
ProcessAsync(4, 200),
ProcessAsync(5, 100),
};
await foreach (int result in WhenEach(tasks))
{
Console.WriteLine($"Processed: {result}");
}
static async Task<int> ProcessAsync(int result, int delay)
{
await Task.Delay(delay);
return result;
}
Expected output:
Processed: 5
Processed: 4
Processed: 1
Processed: 3
Processed: 2
I managed to write a basic implementation using the method Task.WhenAny
in a loop, but there is a problem with this approach:
public static async IAsyncEnumerable<TResult> WhenEach<TResult>(
Task<TResult>[] tasks)
{
var hashSet = new HashSet<Task<TResult>>(tasks);
while (hashSet.Count > 0)
{
var task = await Task.WhenAny(hashSet).ConfigureAwait(false);
yield return await task.ConfigureAwait(false);
hashSet.Remove(task);
}
}
The problem is the performance. The implementation of the Task.WhenAny
creates a defensive copy of the supplied list of tasks, so calling it repeatedly in a loop results in O(n²) computational complexity. My naive implementation struggles to process 10,000 tasks. The overhead is nearly 10 sec in my machine. I would like the method to be nearly as performant as the build-in Task.WhenAll
, that can handle hundreds of thousands of tasks with ease. How could I improve the WhenEach
method to make it performs decently?
By using code from this article, you can implement the following:
Then change your
WhenEach
to call theInterleaved
codeThen you can call your
WhenEach
as per usualI did some rudimentary benchmarking with 10k tasks and performed 5 times better in terms of speed.
You can use a Channel as an async queue. Each task can write to the channel when it completes. Items in the channel will be returned as an IAsyncEnumerable through ChannelReader.ReadAllAsync.
When all tasks complete
writer.Complete()
is called to close the channel.To test this, this code produces tasks with decreasing delays. This should return the indexes in reverse order :
Produces :
Just for the fun of it, using
System.Reactive
andSystem.Interactive.Async
: