[英]blocking collection process n items at a time - continuing as soon as 1 is done
[英]Creating a file pickup process with a Blocking Collection
我現在得到的是一個每5000毫秒觸發一次的計時器:
static Timer _aTimer = new System.Timers.Timer();
static void Main(string[] args)
{
_aTimer.Elapsed += new ElapsedEventHandler(OnTimedEvent);
_aTimer.Interval = 5000;
_aTimer.Enabled = true;
Console.WriteLine("Press \'q\' to quit the sample.");
while (Console.Read() != 'q') ;
}
着火后,它將設置用於處理文件的隊列:
private static void OnTimedEvent(object source, ElapsedEventArgs e)
{
// stop the timer so we dont reprocess files we already have in the queue
StopTimer();
// setup a list of queues
var lists = new List<IncomingOrderQueue>();
//get the accounts in which the files we are looking in
var accounts = new List<string>() { "Account1", "Account2" };
//loop through the accounts and set up the queue
foreach (var acc in accounts)
{
// create the queue
var tmp = new IncomingOrderQueue();
// for each file in the folders add it to be processed in the queue
foreach (var orderFile in OrderFiles(acc))
{
tmp.EnqueueSweep(new QueueVariables() { Account = acc, File = orderFile });
}
// add the queue to the list of queues
lists.Add(tmp);
}
// for each of the queues consume all the contents of them
Parallel.ForEach(lists, l => l.Consume());
//start the timer back up again because we have finished all the files we have in the current queue
StartTimer();
}
public static void StopTimer()
{
Console.WriteLine("Stop Timer");
_aTimer.Stop();
_aTimer.Enabled = false;
}
public static void StartTimer()
{
Console.WriteLine("Start Timer");
_aTimer.Enabled = true;
_aTimer.Start();
}
阻塞隊列自身:
public class IncomingOrderQueue
{
BlockingCollection<QueueVariables> _orderQ = new BlockingCollection<QueueVariables>();
public void EnqueueSweep(QueueVariables incoming)
{
// add items to the queue
_orderQ.Add(incoming);
}
public void Consume()
{
// stop anything been adding to the queue
_orderQ.CompleteAdding();
// consume all the objects in the blocking collection
Parallel.ForEach(_orderQ.GetConsumingEnumerable(), Processor.Order.Object);
}
public int QueueCount
{
get
{
return _orderQ.Count;
}
}
}
我的工作原理是,啟動計時器->停止計時器->觸發收集文件夾中所有文件的過程->處理所有文件->重新啟動計時器。
我不禁想到,有一種更好的方法可以做即時消息,特別是當要為帳戶創建的隊列數為200-400時。
謝謝
我認為您不需要停止和啟動生產者和消費者。 如果BlockingCollection
達到最大容量,則可以阻止生產者,如果為空,則可以阻止使用者。
我可能還從一個BlockingCollection
,直到剖析表明我需要另一個。 根據生產者和消費者的相對速度,可能需要調整他們的數量。 如果它們是受IO約束的,則它們應該是異步的,並且可以有很多;如果它們是受CPU約束的,則可能不需要的處理器數量也就更多。
我重做了您的示例,假設IO約束了生產者和消費者,希望它能給您一些想法。 它以10秒的間隔觸發生產者,並且可以繼續進行,直到您通過CanellationToken
取消生產CanellationToken
。 只有取消並完成生產后,您才可以CompleteAdding
以釋放被阻止的消費者。
public class QueueVariables
{
public string Account {get;set;}
public string File {get;set;}
}
public static ConcurrentQueue<string> GetACcounts()
{
return new ConcurrentQueue<string>(new []
{
"Account1",
"Account2",
"Account3",
"Account4",
"Account5",
"Account6",
"Account7",
"Account8",
"Account9",
"Account10",
"Account11",
"Account12",
});
}
public static List<string> GetFiles(string acct)
{
return new List<string>
{
"File1",
"File2",
"File3",
"File4",
"File5",
"File6",
"File7",
"File8",
"File9",
"File10",
"File11",
"File12",
};
}
public static async Task StartPeriodicProducers(int numProducers, TimeSpan period, CancellationToken ct)
{
while(!ct.IsCancellationRequested)
{
var producers = StartProducers(numProducers, ct);
// wait for production to finish
await Task.WhenAll(producers.ToArray());
// wait before running again
Console.WriteLine("***Waiting " + period);
await Task.Delay(period, ct);
}
}
public static List<Task> StartProducers(int numProducers, CancellationToken ct)
{
List<Task> producingTasks = new List<Task>();
var accounts = GetACcounts();
for (int i = 0; i < numProducers; i++)
{
producingTasks.Add(Task.Run(async () =>
{
string acct;
while(accounts.TryDequeue(out acct) && !ct.IsCancellationRequested)
{
foreach (var file in GetFiles(acct))
{
_orderQ.Add(new UserQuery.QueueVariables{ Account = acct, File = file });
Console.WriteLine("Produced Account:{0} File:{1}", acct, file);
await Task.Delay(50, ct); // simulate production delay
}
}
Console.WriteLine("Finished producing");
}));
}
return producingTasks;
}
public static List<Task> StartConsumers(int numConsumers)
{
List<Task> consumingTasks = new List<Task>();
for (int j = 0; j < numConsumers; j++)
{
consumingTasks.Add(Task.Run(async () =>
{
try
{
while(true)
{
var queueVar = _orderQ.Take();
Console.WriteLine("Consumed Account:{0} File:{1}", queueVar.Account, queueVar.File);
await Task.Delay(200); // simulate consumption delay
}
}
catch(InvalidOperationException)
{
Console.WriteLine("Finished Consuming");
}
}));
}
return consumingTasks;
}
private static async Task MainAsync()
{
CancellationTokenSource cts = new CancellationTokenSource();
var periodicProducers = StartPeriodicProducers(2, TimeSpan.FromSeconds(10), cts.Token);
var consumingTasks = StartConsumers(4);
await Task.Delay(TimeSpan.FromSeconds(120));
// stop production
cts.Cancel();
try
{
// wait for producers to finish producing
await periodicProducers;
}
catch(OperationCanceledException)
{
// operation was cancelled
}
// complete adding to release blocked consumers
_orderQ.CompleteAdding();
// wait for consumers to finish consuming
await Task.WhenAll(consumingTasks.ToArray());
}
// maximum size 10, after that capaicity is reached the producers block
private static BlockingCollection<QueueVariables> _orderQ = new BlockingCollection<QueueVariables>(10);
void Main()
{
MainAsync().Wait();
Console.ReadLine();
}
// Define other methods and classes here
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.