bee-queue-dynamic v0.1.0

bee-queue-dynamic

This project helps distribute jobs evenly across multiple queues.

It uses object-hash to compute hash of the job's payload and then transforms it into a number. Then this number is transformed into a token by applying module operation (token = hashVal % maxToken). Tokens then used to decide on which queue to post the job (queueIndex = token % amountOfQueues).

Why?

Bee Queue is amazing module. As for august 2018 it doesn't support redis cluster. So scaling queues on multiple servers requires synchronised redis instance. This is not as fast as using redis locally. You can set up multiple instances of your app to use different redis servers (available locally) and use this module to distribute jobs between them.

Usage

new Dynamic(options)

Create an instance of dynamic bee-queue wrapper

• options.algorithm: algorithm to use for hashing. Defaults to sha512
• options.strategy: strategy to use for job distribution. Can be token or random. Defaults to token

dynamic.registerQueue(queue)

Register queue to use with wrapper

• queue: instance of bee-queue

dynamic.unregisterQueue(queue)

Unregister previously registered queue. This is useful in case if redis connection dies. The wrapper will continue to work with queues that have left

• queue: instance of bee-queue. should be the same object that was used in registerQueue

dynamic.createJob(data)

Create new job on one of registered queues. This will throw an error if no queues are present.

Example

import Queue from 'bee-queue'
import Dynamic from 'bee-queue-dynamic'

const redisServers = [
  {
    host: '0.0.0.1',
    port: 6379,
    db: 0,
    options: {},
  },
  {
    host: '0.0.0.2',
    port: 6379,
    db: 0,
    options: {},
  },
  // ...
]

const dynamic = new Dynamic()

for (const redis of redisServers) {
  const queue = new Queue('test', { redis })

  dynamic.registerQueue(queue)
}

void (async function main() {
  // job will be created on one of the queues
  const job = await dynamic.createJob({ test: 'data' }).save()

  console.log(job.queue.settings.redis.host) // outputs one of: '0.0.0.1', '0.0.0.2'
})()

FAQ

Q: How much exactly even the distribution is?

A: It depends on how different your job payloads are. This project has not been tested in any production environment yet. I will update this QA once I do some actual tests.

Here is test results for distributing 100 000 fully random jobs across 17 queues:

jobsPerQueue { 'queue-0': 5944,
  'queue-1': 5892,
  'queue-2': 5826,
  'queue-3': 5878,
  'queue-4': 5785,
  'queue-5': 5895,
  'queue-6': 5870,
  'queue-7': 5861,
  'queue-8': 5881,
  'queue-9': 5914,
  'queue-10': 5788,
  'queue-11': 5997,
  'queue-12': 5867,
  'queue-13': 5858,
  'queue-14': 6003,
  'queue-15': 5827,
  'queue-16': 5914 }