lite-fifo

Lightweight and efficient Queue implementations

This package aims to provide zero-dependencies implementations of a queue, focusing on:

• memory footprint (RAM)
• efficiency (ops/sec)

The production code is dependency free. The only dependencies are for testing.

Installation

npm install lite-fifo

Usage

const { DynamicArrayQueue } = require('lite-fifo');

const queue = new DynamicArrayQueue();
queue.enqueue(123);
queue.enqueue(45);
queue.enqueue(67);

console.log(queue.toJSON());
// => [123, 45, 67]

const temp = queue.dequeue(); // holds 123
console.log(queue.toJSON());
// => [45, 67]

Common implementations and mistakes

Array + push + shift

A very common implementation of a queue looks like this:

class DynamicArrayQueue { /* DON'T USE THIS CODE, IT DOESN'T SCALE */
    constructor() {
        this._arr = [];
    }
    enqueue(item) {
        this._arr.push(item);
    }
    dequeue() {
        return this._arr.shift();
    }
}

The time complexity of the dequeue operation is O(n). At small scale - we wouldn't notice.
On a high scale, say 300000 items, this implementation would have only 5 (five!) ops per second. Complexity matters..
At the bottom line, this implementation is a mistake.

Linked List

A linked list implementation for a queue behaves very well in terms of time complexity: O(1).
On the memory side, the provided implementation, LinkedQueue, introduces an optimization: instead of relying on a doubly-linked-list, it relies on a singly-linked-list.
However, even with this optimization, the memory footprint of LinkedQueue is the highest (see the benchmark table below).

Better implementations

Linked List of Ring Buffers

A ring buffer, or a cyclic queue, is a bounded data structure that relies on an array. It's very fast, but bounded.
We can, however, introduce a new data structure named ChunkedQueue, in which we create a LinkedQueue with each item in it to be a cyclic queue.
It's not a generic queue, as it has a weakness, which is out of the scope of this page, so use with caution.

DynamicCyclicQueue

Same as a cyclic queue, but can exceed the initial length of the underlying array.
How? when it's full, the next enqueue operation would trigger a re-order of the underlying array, and then would expand it with push operations. This process is O(1) amortized, and therefore this is a generic queue, and can be used in any scenario.

The Benchmark

Methodology

The scenario being checked is the following:
set P = 100000
enqueue 30P items
dequeue 5P
do 6 times:
  enqueue 1P
  dequeue 5P

Apply this scenario T times (set T=20) for every relevant class (see table below), measure RAM used and ops/sec.
Remove best and worst results (in terms of ops/sec), and take the average (mean) from the rest of the results.

Note: we took a very large value for P, otherwise complexity related issues won't come up.

Results

Class Name	Ops/Sec	RAM used (MB)
DynamicArrayQueue	5	8
ChunkedQueue	28307	28
DynamicCyclicQueue	44864	102
LinkedQueue	25815	143

Analysis

1. The naive implementation, DynamicArrayQueue, is so slow that it can't be considered as an option
2. The fastest implementation is DynamicCyclicQueue, and has an average RAM usage
3. The default implementation of ChunkedQueue has the lowest RAM usage, with the second-fastest measure of ops/sec
4. The common LinkedQueue implementation is not the fastest one, even with O(1) time complexity, and it's the most wasteful in terms of RAM usage

Suggestions

• Use the provided DynamicCyclicQueue for a generic solution
• For some cases, e.g. telemetry shipping, ChunkedQueue is better - very low memory footprint

License

MIT © Ron Klein