工人池，其中某些任务只能由某些工人完成

Question

I have a lot of tasks that I'd like to execute a few at a time. The normal solution for this is a thread pool. However, my tasks need resources that only certain threads have. So I can't just farm a task out to any old thread; the thread has to have the resource the task needs.

It seems like there should be a concurrency pattern for this, but I can't seem to find it. I'm implementing this in Python 2 with multiprocessing, so answers in those terms would be great, but a generic solution is fine. In my case the "threads" are actually separate OS processes and the resources are network connections (and no, it's not a server, so (e)poll/select is not going to help). In general, a thread/process can hold several resources.

Here is a naive solution: put the tasks in a work queue and turn my thread pool loose on it. Have each thread check, "Can I do this task?" If yes, do it; if no, put it back in the queue. However, if each task can only be done by one of N threads, then I'm doing ~2N expensive, wasted accesses to a shared queue just to get one unit of work.

Here is my current thought: have a shared work queue for each resource. Farm out tasks to the matching queue. Each thread checks the queue(s) it can handle.

Ideas?

Answer 1

A common approach to this is to not allocate resources to threads and queue the appropriate resource in with the data, though I appreciate that this is not always possible if a resource is bound to a particular thread.

The idea of using a queue per resource with threads only popping objects from the queues containing objects it can handle may work.

It may be possible to use a semaphore+concurrentQueue array, indexed by resource, for signaling such threads and also providing a priority system, so eliminating most of the polling and wasteful requeueing. I will have to think a bit more about that - it kinda depends on how the resources map to the threads.