Efficient way to implement Priority Queue in Javascript?

问题

Priority Queues have a priority value and data, for every entry.

Thus, when adding a new element to the queue, it bubbles up to the surface if it has a higher priority value than elements already in the collection.

When one calls pop, we get the data for the element with highest priority.

What is an efficient implementation of such a priority queue in Javascript?

Does it make sense to have a new object called PriorityQueue, create two methods (push and pop) that take two params (data, priority)? That much makes sense to me as a coder, but I'm uncertain of which data structure to use in the underbelly that will allow manipulation of the ordering of elements. Or can we just store it all in an array and walk through the array every time to grab the element with max priority?

What's a good way to do this?

回答1:

Below is what I believe to be a truly efficient version of a PriorityQueue which uses an array-based binary heap (where the root is at index 0, and the children of a node at index i are at indices 2i + 1 and 2i + 2, respectively).

This implementation includes the classical priority queue methods like push, peek, pop, and size, as well as convenience methods isEmpty and replace (the latter being a more efficient substitute for a pop followed immediately by a push). Values are stored not as [value, priority] pairs, but simply as values; this allows for automatic prioritization of types that can be natively compared using the > operator. A custom comparator function passed to the PriorityQueue constructor can be used to emulate the behavior of pairwise semantics, however, as shown in the example below.

Heap-based Implementation:

const top = 0;
const parent = i => ((i + 1) >>> 1) - 1;
const left = i => (i << 1) + 1;
const right = i => (i + 1) << 1;

class PriorityQueue {
  constructor(comparator = (a, b) => a > b) {
    this._heap = [];
    this._comparator = comparator;
  }
  size() {
    return this._heap.length;
  }
  isEmpty() {
    return this.size() == 0;
  }
  peek() {
    return this._heap[top];
  }
  push(...values) {
    values.forEach(value => {
      this._heap.push(value);
      this._siftUp();
    });
    return this.size();
  }
  pop() {
    const poppedValue = this.peek();
    const bottom = this.size() - 1;
    if (bottom > top) {
      this._swap(top, bottom);
    }
    this._heap.pop();
    this._siftDown();
    return poppedValue;
  }
  replace(value) {
    const replacedValue = this.peek();
    this._heap[top] = value;
    this._siftDown();
    return replacedValue;
  }
  _greater(i, j) {
    return this._comparator(this._heap[i], this._heap[j]);
  }
  _swap(i, j) {
    [this._heap[i], this._heap[j]] = [this._heap[j], this._heap[i]];
  }
  _siftUp() {
    let node = this.size() - 1;
    while (node > top && this._greater(node, parent(node))) {
      this._swap(node, parent(node));
      node = parent(node);
    }
  }
  _siftDown() {
    let node = top;
    while (
      (left(node) < this.size() && this._greater(left(node), node)) ||
      (right(node) < this.size() && this._greater(right(node), node))
    ) {
      let maxChild = (right(node) < this.size() && this._greater(right(node), left(node))) ? right(node) : left(node);
      this._swap(node, maxChild);
      node = maxChild;
    }
  }
}

---

Example:

{const top=0,parent=c=>(c+1>>>1)-1,left=c=>(c<<1)+1,right=c=>c+1<<1;class PriorityQueue{constructor(c=(d,e)=>d>e){this._heap=[],this._comparator=c}size(){return this._heap.length}isEmpty(){return 0==this.size()}peek(){return this._heap[top]}push(...c){return c.forEach(d=>{this._heap.push(d),this._siftUp()}),this.size()}pop(){const c=this.peek(),d=this.size()-1;return d>top&&this._swap(top,d),this._heap.pop(),this._siftDown(),c}replace(c){const d=this.peek();return this._heap[top]=c,this._siftDown(),d}_greater(c,d){return this._comparator(this._heap[c],this._heap[d])}_swap(c,d){[this._heap[c],this._heap[d]]=[this._heap[d],this._heap[c]]}_siftUp(){for(let c=this.size()-1;c>top&&this._greater(c,parent(c));)this._swap(c,parent(c)),c=parent(c)}_siftDown(){for(let d,c=top;left(c)<this.size()&&this._greater(left(c),c)||right(c)<this.size()&&this._greater(right(c),c);)d=right(c)<this.size()&&this._greater(right(c),left(c))?right(c):left(c),this._swap(c,d),c=d}}window.PriorityQueue=PriorityQueue}

// Default comparison semantics
const queue = new PriorityQueue();
queue.push(10, 20, 30, 40, 50);
console.log('Top:', queue.peek()); //=> 50
console.log('Size:', queue.size()); //=> 5
console.log('Contents:');
while (!queue.isEmpty()) {
  console.log(queue.pop()); //=> 40, 30, 20, 10
}

// Pairwise comparison semantics
const pairwiseQueue = new PriorityQueue((a, b) => a[1] > b[1]);
pairwiseQueue.push(['low', 0], ['medium', 5], ['high', 10]);
console.log('\nContents:');
while (!pairwiseQueue.isEmpty()) {
  console.log(pairwiseQueue.pop()[0]); //=> 'high', 'medium', 'low'
}

.as-console-wrapper{min-height:100%}

回答2:

You should use standard libraries like e.g. the Closure Library (goog.structs.PriorityQueue):

https://google.github.io/closure-library/api/goog.structs.PriorityQueue.html

By clicking at the source code, you will know it is actually linking to goog.structs.Heap which you can follow:

https://github.com/google/closure-library/blob/master/closure/goog/structs/heap.js

来源：https://stackoverflow.com/questions/42919469/efficient-way-to-implement-priority-queue-in-javascript