[英]Clarification on running multiple async tasks in parallel with throttling
编辑:由于 Bulkhead 策略需要使用 WaitAndRetry 策略进行包装,无论如何...我倾向于将示例 3 作为保持并行性、节流和 polly 策略重试的最佳解决方案。 看起来很奇怪,因为我认为 Parallel.ForEach 用于同步操作,而 Bulkhead 更适合异步
我正在尝试使用 polly AsyncBulkheadPolicy 与节流并行运行多个异步任务。 到目前为止,我的理解是策略方法 ExecuteAsync 本身不会调用线程,而是将其留给默认的 TaskScheduler 或之前的某个人。 因此,如果我的任务以某种方式受 CPU 限制,那么我需要在执行任务时使用 Parallel.ForEach 或 Task.Run() 与 ExecuteAsync 方法一起使用,以便将任务安排到后台线程。
有人可以查看下面的示例并阐明它们在并行性和线程池方面的工作方式吗?
https://github.com/App-vNext/Polly/wiki/Bulkhead - 操作:Bulkhead 策略不会创建它自己的线程,它假设我们已经这样做了。
async Task DoSomething(IEnumerable<object> objects);
//Example 1:
//Simple use, but then I don't have access to retry policies from polly
Parallel.ForEach(groupedObjects, (set) =>
{
var task = DoSomething(set);
task.Wait();
});
//Example 2:
//Uses default TaskScheduler which may or may not run the tasks in parallel
var parallelTasks = new List<Task>();
foreach (var set in groupedObjects)
{
var task = bulkheadPolicy.ExecuteAsync(async () => DoSomething(set));
parallelTasks.Add(task);
};
await Task.WhenAll(parallelTasks);
//Example 3:
//seems to defeat the purpose of the bulkhead since Parallel.ForEach and
//PolicyBulkheadAsync can both do throttling...just use basic RetryPolicy
//here?
Parallel.ForEach(groupedObjects, (set) =>
{
var task = bulkheadPolicy.ExecuteAsync(async () => DoSomething(set));
task.Wait();
});
//Example 4:
//Task.Run still uses the default Task scheduler and isn't any different than
//Example 2; just makes more tasks...this is my understanding.
var parallelTasks = new List<Task>();
foreach (var set in groupedObjects)
{
var task = Task.Run(async () => await bulkheadPolicy.ExecuteAsync(async () => DoSomething(set)));
parallelTasks.Add(task);
};
await Task.WhenAll(parallelTasks);
DoSomething 是一种对一组对象进行操作的异步方法。 我希望这发生在并行线程中,同时尊重 polly 的重试策略并允许限制。
然而,当涉及到如何处理任务/线程时,我似乎一直对 Parallel.ForEach 和使用 Bulkhead.ExecuteAsync 的功能行为究竟是什么感到困惑。
您可能是对的,使用Parallel.ForEach
违背了隔板的目的。 我认为一个带有延迟的简单循环将完成为舱壁提供任务的工作。 尽管我猜想在现实生活中的示例中会有连续的数据流,而不是预定义的列表或数组。
using Polly;
using Polly.Bulkhead;
static async Task Main(string[] args)
{
var groupedObjects = Enumerable.Range(0, 10)
.Select(n => new object[] { n }); // Create 10 sets to work with
var bulkheadPolicy = Policy
.BulkheadAsync(3, 3); // maxParallelization, maxQueuingActions
var parallelTasks = new List<Task>();
foreach (var set in groupedObjects)
{
Console.WriteLine(@$"Scheduling, Available: {bulkheadPolicy
.BulkheadAvailableCount}, QueueAvailable: {bulkheadPolicy
.QueueAvailableCount}");
// Start the task
var task = bulkheadPolicy.ExecuteAsync(async () =>
{
// Await the task without capturing the context
await DoSomethingAsync(set).ConfigureAwait(false);
});
parallelTasks.Add(task);
await Task.Delay(50); // Interval between scheduling more tasks
}
var whenAllTasks = Task.WhenAll(parallelTasks);
try
{
// Await all the tasks (await throws only one of the exceptions)
await whenAllTasks;
}
catch when (whenAllTasks.IsFaulted) // It might also be canceled
{
// Ignore rejections, rethrow other exceptions
whenAllTasks.Exception.Handle(ex => ex is BulkheadRejectedException);
}
Console.WriteLine(@$"Processed: {parallelTasks
.Where(t => t.Status == TaskStatus.RanToCompletion).Count()}");
Console.WriteLine($"Faulted: {parallelTasks.Where(t => t.IsFaulted).Count()}");
}
static async Task DoSomethingAsync(IEnumerable<object> set)
{
// Pretend we are doing something with the set
await Task.Delay(500).ConfigureAwait(false);
}
输出:
Scheduling, Available: 3, QueueAvailable: 3
Scheduling, Available: 2, QueueAvailable: 3
Scheduling, Available: 1, QueueAvailable: 3
Scheduling, Available: 0, QueueAvailable: 3
Scheduling, Available: 0, QueueAvailable: 2
Scheduling, Available: 0, QueueAvailable: 1
Scheduling, Available: 0, QueueAvailable: 0
Scheduling, Available: 0, QueueAvailable: 0
Scheduling, Available: 0, QueueAvailable: 0
Scheduling, Available: 0, QueueAvailable: 1
Processed: 7
Faulted: 3
更新:稍微更真实的DoSomethingAsync
版本,它实际上强制 CPU 做一些实际工作(在我的四核机器中 CPU 利用率接近 100%)。
private static async Task DoSomethingAsync(IEnumerable<object> objects)
{
await Task.Run(() =>
{
long sum = 0; for (int i = 0; i < 500000000; i++) sum += i;
}).ConfigureAwait(false);
}
此方法并未针对所有数据集运行。 它仅针对不被隔板拒绝的集合运行。
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