答案取决于要调度的任务是受 CPU 限制还是 I/O 限制。
对于 CPU 密集型工作,我将使用 Parallel.For() API 通过 ParallelOptions 的 MaxDegreeOfParallelism 属性设置线程/任务数
对于 I/O 绑定的工作,并发执行任务的数量可能会明显大于可用 CPU 的数量,因此策略是尽可能依赖异步方法,从而减少等待完成的线程总数.
如何在新任务完成之前停止 for 循环并启动
新的?
可以使用 await 来限制循环:
static void Main(string[] args)
{
var task = DoWorkAsync();
task.Wait();
// handle results
// task.Result;
Console.WriteLine("Done.");
}
async static Task<bool> DoWorkAsync()
{
const int NUMBER_OF_SLOTS = 10;
string param1="test";
string param2="test";
var results = new bool[NUMBER_OF_SLOTS];
AsyncWorkScheduler ws = new AsyncWorkScheduler(NUMBER_OF_SLOTS);
for (int i = 0; i < 1000; ++i)
{
await ws.ScheduleAsync((slotNumber) => DoWorkAsync(i, slotNumber, param1, param2, results));
}
ws.Complete();
await ws.Completion;
}
async static Task DoWorkAsync(int index, int slotNumber, string param1, string param2, bool[] results)
{
results[slotNumber] = results[slotNumber} && await Task.Factory.StartNew<bool>(() =>
{
MyClass cls = new MyClass();
bool bRet = cls.Method1(param1, param2, i); // takes up to 2 minutes to finish
return bRet;
}));
}
帮助类 AsyncWorkScheduler 使用 TPL.DataFlow 组件以及 Task.WhenAll():
class AsyncWorkScheduler
{
public AsyncWorkScheduler(int numberOfSlots)
{
m_slots = new Task[numberOfSlots];
m_availableSlots = new BufferBlock<int>();
m_errors = new List<Exception>();
m_tcs = new TaskCompletionSource<bool>();
m_completionPending = 0;
// Initial state: all slots are available
for(int i = 0; i < m_slots.Length; ++i)
{
m_slots[i] = Task.FromResult(false);
m_availableSlots.Post(i);
}
}
public async Task ScheduleAsync(Func<int, Task> action)
{
if (Volatile.Read(ref m_completionPending) != 0)
{
throw new InvalidOperationException("Unable to schedule new items.");
}
// Acquire a slot
int slotNumber = await m_availableSlots.ReceiveAsync().ConfigureAwait(false);
// Schedule a new task for a given slot
var task = action(slotNumber);
// Store a continuation on the task to handle completion events
m_slots[slotNumber] = task.ContinueWith(t => HandleCompletedTask(t, slotNumber), TaskContinuationOptions.ExecuteSynchronously);
}
public async void Complete()
{
if (Interlocked.CompareExchange(ref m_completionPending, 1, 0) != 0)
{
return;
}
// Signal the queue's completion
m_availableSlots.Complete();
await Task.WhenAll(m_slots).ConfigureAwait(false);
// Set completion
if (m_errors.Count != 0)
{
m_tcs.TrySetException(m_errors);
}
else
{
m_tcs.TrySetResult(true);
}
}
public Task Completion
{
get
{
return m_tcs.Task;
}
}
void SetFailed(Exception error)
{
lock(m_errors)
{
m_errors.Add(error);
}
}
void HandleCompletedTask(Task task, int slotNumber)
{
if (task.IsFaulted || task.IsCanceled)
{
SetFailed(task.Exception);
return;
}
if (Volatile.Read(ref m_completionPending) == 1)
{
return;
}
// Release a slot
m_availableSlots.Post(slotNumber);
}
int m_completionPending;
List<Exception> m_errors;
BufferBlock<int> m_availableSlots;
TaskCompletionSource<bool> m_tcs;
Task[] m_slots;
}