blocking collection process n items at a time - co

2019-05-18 05:06发布

I have the following Scenario.

  1. I take 50 jobs from the database into a blocking collection.

  2. Each job is a long running one. (potentially could be). So I want to run them in a separate thread. (I know - it may be better to run them as Task.WhenAll and let the TPL figure it out - but I want to control how many runs simultaneously)

  3. Say I want to run 5 of them simultaneously (configurable)

  4. I create 5 tasks (TPL), one for each job and run them in parallel.

What I want to do is to pick up the next Job in the blocking collection as soon as one of the jobs from step 4 is complete and keep going until all 50 are done.

I am thinking of creating a Static blockingCollection and a TaskCompletionSource which will be invoked when a job is complete and then it can call the consumer again to pick one job at a time from the queue. I would also like to call async/await on each job - but that's on top of this - not sure if that has an impact on the approach.

Is this the right way to accomplish what I'm trying to do?

Similar to this link, but catch is that I want to process the next Job as soon as one of the first N items are done. Not after all N are done.

Update :

Ok, I have this code snippet doing exactly what I want, if someone wants to use it later. As you can see below, 5 threads are created and each thread starts the next job when it is done with current. Only 5 threads are active at any given time. I understand this may not work 100% like this always, and will have performance issues of context switching if used with one cpu/core.

var block = new ActionBlock<Job>(
                job => Handler.HandleJob(job), 
                    new ExecutionDataflowBlockOptions { MaxDegreeOfParallelism = 5 });

              foreach (Job j in GetJobs())
                  block.SendAsync(j);

Job 2 started on thread :13. wait time:3600000ms. Time:8/29/2014 3:14:43 PM

Job 4 started on thread :14. wait time:15000ms. Time:8/29/2014 3:14:43 PM

Job 0 started on thread :7. wait time:600000ms. Time:8/29/2014 3:14:43 PM

Job 1 started on thread :12. wait time:900000ms. Time:8/29/2014 3:14:43 PM

Job 3 started on thread :11. wait time:120000ms. Time:8/29/2014 3:14:43 PM

job 4 finished on thread :14. 8/29/2014 3:14:58 PM

Job 5 started on thread :14. wait time:1800000ms. Time:8/29/2014 3:14:58 PM

job 3 finished on thread :11. 8/29/2014 3:16:43 PM

Job 6 started on thread :11. wait time:1200000ms. Time:8/29/2014 3:16:43 PM

job 0 finished on thread :7. 8/29/2014 3:24:43 PM

Job 7 started on thread :7. wait time:30000ms. Time:8/29/2014 3:24:43 PM

job 7 finished on thread :7. 8/29/2014 3:25:13 PM

Job 8 started on thread :7. wait time:100000ms. Time:8/29/2014 3:25:13 PM

job 8 finished on thread :7. 8/29/2014 3:26:53 PM

Job 9 started on thread :7. wait time:900000ms. Time:8/29/2014 3:26:53 PM

job 1 finished on thread :12. 8/29/2014 3:29:43 PM

Job 10 started on thread :12. wait time:300000ms. Time:8/29/2014 3:29:43 PM

job 10 finished on thread :12. 8/29/2014 3:34:43 PM

Job 11 started on thread :12. wait time:600000ms. Time:8/29/2014 3:34:43 PM

job 6 finished on thread :11. 8/29/2014 3:36:43 PM

Job 12 started on thread :11. wait time:300000ms. Time:8/29/2014 3:36:43 PM

job 12 finished on thread :11. 8/29/2014 3:41:43 PM

Job 13 started on thread :11. wait time:100000ms. Time:8/29/2014 3:41:43 PM

job 9 finished on thread :7. 8/29/2014 3:41:53 PM

Job 14 started on thread :7. wait time:300000ms. Time:8/29/2014 3:41:53 PM

job 13 finished on thread :11. 8/29/2014 3:43:23 PM

job 11 finished on thread :12. 8/29/2014 3:44:43 PM

job 5 finished on thread :14. 8/29/2014 3:44:58 PM

job 14 finished on thread :7. 8/29/2014 3:46:53 PM

job 2 finished on thread :13. 8/29/2014 4:14:43 PM

3条回答
放我归山
2楼-- · 2019-05-18 05:58

You can use BlockingCollection and it will work just fine, but it was built before async-await so it blocks synchronously which could be less scalable in most cases.

You're better off using async ready TPL Dataflow as Yuval Itzchakov suggested. All you need is an ActionBlock that processes each item concurrently with a MaxDegreeOfParallelism of 5 and you post your work to it synchronously (block.Post(item)) or asynchronously (await block.SendAsync(item)):

private static void Main()
{
    var block = new ActionBlock<Job>(
        async job => await job.ProcessAsync(),
        new ExecutionDataflowBlockOptions {MaxDegreeOfParallelism = 5});

    for (var i = 0; i < 50; i++)
    {
        block.Post(new Job());
    }

    Console.ReadKey();
}
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smile是对你的礼貌
3楼-- · 2019-05-18 06:05

You could do this with a SemaphoreSlim like in this answer, or using ForEachAsync like in this answer.

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等我变得足够好
4楼-- · 2019-05-18 06:08

You can easily achieve what you need using TPL Dataflow.

What you can do is use BufferBlock<T>, which is a buffer for storing you data, and link it together with an ActionBlock<T> which will consume those requests as they're coming in from the BufferBlock<T>.

Now, the beauty here is that you can specify how many requests you want the ActionBlock<T> to handle concurrently using the ExecutionDataflowBlockOptions class.

Here's a simplified console version, which processes a bunch of numbers as they're coming in, prints their name and Thread.ManagedThreadID:

private static void Main(string[] args)
{
    var bufferBlock = new BufferBlock<int>();

    var actionBlock =
        new ActionBlock<int>(i => Console.WriteLine("Reading number {0} in thread {1}",
                                  i, Thread.CurrentThread.ManagedThreadId),
                             new ExecutionDataflowBlockOptions 
                                 {MaxDegreeOfParallelism = 5});

    bufferBlock.LinkTo(actionBlock);
    Produce(bufferBlock);

    Console.ReadKey();
}

private static void Produce(BufferBlock<int> bufferBlock)
{
    foreach (var num in Enumerable.Range(0, 500))
    {
        bufferBlock.Post(num);
    }
}

You can also post them asynchronously if needed, using the awaitable BufferBlock.SendAsync

That way, you let the TPL handle all the throttling for you without needing to do it manually.

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