Actually the LinkedHashMap does exactly what you want. You need to override the removeEldestEntry method. Example for a queue with max 10 elements: queue = new LinkedHashMap<Integer, String>() { @Override protected boolean removeEldestEntry(Map.Entry<Integer, String> eldest) { return this.size() > 10; } }; If the “removeEldestEntry” returns true, the eldest entry is removed from the map.
var stack = []; stack.push(2); // stack is now [2] stack.push(5); // stack is now [2, 5] var i = stack.pop(); // stack is now [2] alert(i); // displays 5 var queue = []; queue.push(2); // queue is now [2] queue.push(5); // queue is now [2, 5] var i = queue.shift(); // queue is now … Read more
Well, let’s take a closer look at the scenario you are describing above. I think it’s important to paste the documentation immediately prior to the snippet in your question to provide context: Section 4.7 of the AMQP 0-9-1 core specification explains the conditions under which ordering is guaranteed: messages published in one channel, passing through … Read more
You problem here is, that .ajax() fires an asyncronous running Ajax request. That means, .ajax() returns immediately, non-blocking. So your queue the functions but they will fire almost at the same time like you described. I don’t think the .queue() is a good place to have ajax requests in, it’s more intended for the use … Read more
You can implement a stack with O(1) pop(), push() and get_min(): just store the current minimum together with each element. So, for example, the stack [4,2,5,1] (1 on top) becomes [(4,4), (2,2), (5,2), (1,1)]. Then you can use two stacks to implement the queue. Push to one stack, pop from another one; if the second … Read more
I would write a wrapper class that on Enqueue would check the Count and then Dequeue when the count exceeds the limit. public class FixedSizedQueue<T> { ConcurrentQueue<T> q = new ConcurrentQueue<T>(); private object lockObject = new object(); public int Limit { get; set; } public void Enqueue(T obj) { q.Enqueue(obj); lock (lockObject) { T overflow; … Read more
Try using multiprocessing.Manager to manage your queue and to also make it accessible to different workers. import multiprocessing def worker(name, que): que.put(“%d is done” % name) if __name__ == ‘__main__’: pool = multiprocessing.Pool(processes=3) m = multiprocessing.Manager() q = m.Queue() workers = pool.apply_async(worker, (33, q))
jQuery 1.5+ I developed an $.ajaxQueue() plugin that uses the $.Deferred, .queue(), and $.ajax() to also pass back a promise that is resolved when the request completes. /* * jQuery.ajaxQueue – A queue for ajax requests * * (c) 2011 Corey Frang * Dual licensed under the MIT and GPL licenses. * * Requires jQuery … Read more
Java 5+ has all the tools you need for this kind of thing. You will want to: Put all your Producers in one ExecutorService; Put all your Consumers in another ExecutorService; If necessary, communicate between the two using a BlockingQueue. I say “if necessary” for (3) because from my experience it’s an unnecessary step. All … Read more
I’ve used the queuing approach, and it works well as you can defer that processing until your server load is idle, letting you manage your load quite effectively if you can partition off “tasks which aren’t urgent” easily. Rolling your own isn’t too tricky, here’s a few other options to check out: GearMan – this … Read more