FastPriorityQueue.js : a fast heap-based priority queue in JavaScript
In a priority queue, you can...
- query or remove (poll) the smallest element quickly
- insert elements quickly
In practice, "quickly" often means in logarithmic time (O(log n)).
A heap can be used to implement a priority queue.
FastPriorityQueue is an attempt to implement a performance-oriented priority queue in JavaScript. It can be several times faster than other similar libraries. It is ideal when performance matters.
License: Apache License 2.0
Usage
var x = new FastPriorityQueue();
x.add(1);
x.add(0);
x.add(5);
x.add(4);
x.add(3);
x.peek(); // should return 0, leaves x unchanged
x.size; // should return 5, leaves x unchanged
while(!x.isEmpty()) {
console.log(x.poll());
} // will print 0 1 3 4 5
x.trim(); // (optional) optimizes memory usageYou can also provide the constructor with a comparator function.
var x = new FastPriorityQueue(function(a,b) {return a > b});
x.add(1);
x.add(0);
x.add(5);
x.add(4);
x.add(3);
while(!x.isEmpty()) {
console.log(x.poll());
} // will print 5 4 3 1 0 If you are using node.js, you need to import the module:
var FastPriorityQueue = require("fastpriorityqueue");
var b = new FastPriorityQueue();// initially empty
b.add(1);// add the value "1"The replaceTop function allows you to add and poll in one integrated operation, which is useful fast top-k queries. See Top speed for top-k queries.
npm install
$ npm install fastpriorityqueue
Computational complexity
The function calls "add" and "poll" have logarithmic complexity with respect to the size of the data structure (attribute size). Looking at the top value is a constant time operation.
Testing
Using node.js (npm), you can test the code as follows...
$ npm install mocha
$ npm test
Is it faster?
It tends to fare well against the competition. In some tests, it can be five times faster than any other JavaScript implementation we could find.
$ node test.js
Platform: linux 4.4.0-38-generic x64
Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz
Node version 4.5.0, v8 version 4.5.103.37
Comparing against:
js-priority-queue: https://github.com/adamhooper/js-priority-queue 0.1.5
heap.js: https://github.com/qiao/heap.js 0.2.6
binaryheapx: https://github.com/xudafeng/BinaryHeap 0.1.1
priority_queue: https://github.com/agnat/js_priority_queue 0.1.3
js-heap: https://github.com/thauburger/js-heap 0.3.1
queue-priority: https://github.com/augustohp/Priority-Queue-NodeJS 1.0.0
priorityqueuejs: https://github.com/janogonzalez/priorityqueuejs 1.0.0
qheap: https://github.com/andrasq/node-qheap 1.3.0
yabh: https://github.com/jmdobry/yabh 1.2.0
starting dynamic queue/enqueue benchmark
FastPriorityQueue x 36,813 ops/sec ±0.15% (98 runs sampled)
js-priority-queue x 5,374 ops/sec ±0.29% (97 runs sampled)
heap.js x 7,525 ops/sec ±0.21% (94 runs sampled)
binaryheapx x 4,741 ops/sec ±0.19% (98 runs sampled)
priority_queue x 3,657 ops/sec ±2.37% (92 runs sampled)
js-heap x 271 ops/sec ±0.35% (90 runs sampled)
queue-priority x 455 ops/sec ±0.44% (90 runs sampled)
priorityqueuejs x 7,012 ops/sec ±0.14% (75 runs sampled)
qheap x 36,289 ops/sec ±0.33% (97 runs sampled)
yabh x 3,975 ops/sec ±3.57% (76 runs sampled)
Fastest is FastPriorityQueue
Note that qheap has been updated following the introduction of FastPriorityQueue, with a reference to FastPriorityQueue which might explains the fact that its performance is comparable to FastPriorityQueue.
Insertion order
A binary heap does not keep track of the insertion order.
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