Javascript中的常规数组结构是一个堆栈(先入后出)，也可以用作队列(先入先出)，这取决于你所做的调用。

检查这个链接，看看如何让一个数组像一个队列:

队列

数组是Javascript中的堆栈。只需使用arr.push(x)和y = arr.pop()。

下面是用Javascript实现队列的最简单方法，对于enqueue(x)和y = dequeue()，它的平摊时间都是O(1)。它使用从插入索引到元素的映射。

function newQueue() {
    return {
        headIdx: 0,
        tailIdx: 0,
        elts: {},
        enqueue: (elt) => queue.elts[queue.tailIdx++] = elt,
        dequeue: () => {
            if (queue.headIdx == queue.tailIdx) {
                throw new Error("Queue is empty");
            }
            return queue.elts[queue.headIdx++];
        },
        size: () => queue.tailIdx - queue.headIdx,
        isEmpty: () => queue.tailIdx == queue.headIdx
    };
}

使用链表实现的队列比这种基于映射的方法更有效，使用循环缓冲区实现的队列比这种基于映射的方法更有效，但这两种数据结构的实现更复杂(特别是循环缓冲区数据结构)。

你可以基于这个概念使用你自己的自定义类，这里是你可以用来做这些事情的代码片段

/*
*   Stack implementation in JavaScript
*/



function Stack() {
  this.top = null;
  this.count = 0;

  this.getCount = function() {
    return this.count;
  }

  this.getTop = function() {
    return this.top;
  }

  this.push = function(data) {
    var node = {
      data: data,
      next: null
    }

    node.next = this.top;
    this.top = node;

    this.count++;
  }

  this.peek = function() {
    if (this.top === null) {
      return null;
    } else {
      return this.top.data;
    }
  }

  this.pop = function() {
    if (this.top === null) {
      return null;
    } else {
      var out = this.top;
      this.top = this.top.next;
      if (this.count > 0) {
        this.count--;
      }

      return out.data;
    }
  }

  this.displayAll = function() {
    if (this.top === null) {
      return null;
    } else {
      var arr = new Array();

      var current = this.top;
      //console.log(current);
      for (var i = 0; i < this.count; i++) {
        arr[i] = current.data;
        current = current.next;
      }

      return arr;
    }
  }
}

要检查这一点，请使用控制台，并逐一尝试这些行。

>> var st = new Stack();

>> st.push("BP");

>> st.push("NK");

>> st.getTop();

>> st.getCount();

>> st.displayAll();

>> st.pop();

>> st.displayAll();

>> st.getTop();

>> st.peek();

  var x = 10; 
  var y = 11; 
  var Queue = new Array();
  Queue.unshift(x);
  Queue.unshift(y);

  console.log(Queue)
  // Output [11, 10]

  Queue.pop()
  console.log(Queue)
  // Output [11]

Create a pair of classes that provide the various methods that each of these data structures has (push, pop, peek, etc). Now implement the methods. If you're familiar with the concepts behind stack/queue, this should be pretty straightforward. You can implement the stack with an array, and a queue with a linked list, although there are certainly other ways to go about it. Javascript will make this easy, because it is weakly typed, so you don't even have to worry about generic types, which you'd have to do if you were implementing it in Java or C#.

Javascript数组shift()很慢，特别是当包含很多元素时。我知道两种方法来实现平摊O(1)复杂度的队列。

首先是使用循环缓冲区和表加倍。我以前实现过这个。你可以在这里看到我的源代码 https://github.com/kevyuu/rapid-queue

第二种方法是使用两个堆栈。这是带有两个堆栈的队列的代码

function createDoubleStackQueue() {
var that = {};
var pushContainer = [];
var popContainer = [];

function moveElementToPopContainer() {
    while (pushContainer.length !==0 ) {
        var element = pushContainer.pop();
        popContainer.push(element);
    }
}

that.push = function(element) {
    pushContainer.push(element);
};

that.shift = function() {
    if (popContainer.length === 0) {
        moveElementToPopContainer();
    }
    if (popContainer.length === 0) {
        return null;
    } else {
        return popContainer.pop();
    }
};

that.front = function() {
    if (popContainer.length === 0) {
        moveElementToPopContainer();
    }
    if (popContainer.length === 0) {
        return null;
    }
    return popContainer[popContainer.length - 1];
};

that.length = function() {
    return pushContainer.length + popContainer.length;
};

that.isEmpty = function() {
    return (pushContainer.length + popContainer.length) === 0;
};

return that;}

这是使用jsPerf进行的性能比较

CircularQueue.shift() vs Array.shift()

http://jsperf.com/rapidqueue-shift-vs-array-shift

正如你所看到的，大数据集的速度要快得多