What if you need to run multiple asynchronous I/O tasks in parallel but need to make sure that no more than X I/O processes are running at the same time; and pre and post I/O processing tasks shouldn't have such limitation.
Here is a scenario - let's say there are 1000 tasks; each of them accepts a text string as an input parameter; transforms that text (pre I/O processing) then writes that transformed text into a file. The goal is to make pre-processing logic utilize 100% of CPU/Cores and I/O portion of the tasks run with max 10 degree of parallelism (max 10 simultaneously opened for writing files at a time).
Can you provide a sample code how to do it with C# / .NET 4.5?
http://blogs.msdn.com/b/csharpfaq/archive/2012/01/23/using-async-for-file-access-alan-berman.aspx
I think using TPL Dataflow for this would be a good idea: you create pre- and post-process blocks with unbounded parallelism, a file-writing block with limited parallelism and link them together. Something like:
var unboundedParallelismOptions =
new ExecutionDataflowBlockOptions
{
MaxDegreeOfParallelism = DataflowBlockOptions.Unbounded
};
var preProcessBlock = new TransformBlock<string, string>(
s => PreProcess(s), unboundedParallelismOptions);
var writeToFileBlock = new TransformBlock<string, string>(
async s =>
{
await WriteToFile(s);
return s;
},
new ExecutionDataflowBlockOptions { MaxDegreeOfParallelism = 10 });
var postProcessBlock = new ActionBlock<string>(
s => PostProcess(s), unboundedParallelismOptions);
var propagateCompletionOptions =
new DataflowLinkOptions { PropagateCompletion = true };
preProcessBlock.LinkTo(writeToFileBlock, propagateCompletionOptions);
writeToFileBlock.LinkTo(postProcessBlock, propagateCompletionOptions);
// use something like await preProcessBlock.SendAsync("text") here
preProcessBlock.Complete();
await postProcessBlock.Completion;
Where WriteToFile()
could look like this:
private static async Task WriteToFile(string s)
{
using (var writer = new StreamWriter(GetFileName()))
await writer.WriteAsync(s);
}
It sounds like you'd want to consider a Djikstra Semaphore to control access to the starting of tasks.
However, this sounds like a typical queue/fixed number of consumers kind of problem, which may be a more appropriate way to structure it.
I would create an extension method in which one can set maximum degree of parallelism. SemaphoreSlim will be the savior here.
/// <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);
来源:https://stackoverflow.com/questions/10801328/how-to-properly-run-multiple-async-tasks-in-parallel