Modern applications grow to require expensive processing, asynchronous operations, necessary tasks delays before completions, logging, and triggering processes from initiated application/user events.
Why queue system?
A queue system would thus, efficiently cater to the increasing asynchronous operations from an increase of actions/events. thus reducing errors, improving user experience, and processing actions in the background, and executing functions or triggering an application service when it's ready.
Some tasks that can be handled by a job queue:
- Sending system-authored push notifications
- Sending system-authored emails
- communication with third applications and webhooks
- event-driven programming
- logging events, e.t.c
Necessary terminology in the context of queues;
Job - This is a task that can get pushed into a queue system, to be processed at a later stage in the application flow. the job is the Object that contains the required data for the consumer to process.
Consumer -
This is the task to be carried out in the queue process. such as sending emails, push notifications e.t.c
Producer - The producer would represent the instantiated queue constructor. Many Jobs can be added to the specified named queue object; for processing to be carried out. such as push notifications, notifications, emails.
The options argument will have options such as delay (when to execute the job from the time of creation), attempts (number of retries when a job fails), rate-limiting of jobs e.t.c.
Let's get started with a simple queue system implementation with Bull
Bull sells its queue system implementation as
The fastest, most reliable, Redis-based queue for Node.
Carefully written for rock-solid stability and atomicity.
Bull is fully is compatible with typescript, well tested, queue system UI, and built on top of Redis cache with a lot of helpful abstraction methods and functionalities.
Of course, the community could use more abstracted systems to simplify solutions when using the plethora of tools with their surging complexities 😅.
Implementation
- Install Redis locally or set up a Redis docker container as below; let's add a
Dockerfile and a docker-compose.yml:
services:
simple_queue_redis:
image: redis:6.2-alpine
container_name: simple_queue_redis
environment:
- ALLOW_EMPTY_PASSWORD=yes
ports:
- 6379:6379
volumes:
- ./redis:/db
FROM node:14-alpine
WORKDIR /app
RUN yarn install
RUN yarn
COPY . .
CMD ["yarn", "start:dev"]
- Install the Bull package from NPM using the following command.
npm install bull --save
- Create queues and processes.
We assume that we're working in a type-safe environment, hence the use of typescript.
Create a new file named
notificationQueue.ts and paste the following code.
Here we assume we're working on a notification job.
The NotificationQueue instance, in this case, would represent the producer and the notification job gets added to the consumer, the notificationProcess.
import Queue from 'bull';
import { notificationProcess } from '../processes';
const NotificationQueue = new Queue('Notification', process.env.REDIS_URL);
NotificationQueue.process(notificationProcess);
export const addNewNotification = (data: {
title: string,
body: string,
url: string,
}
) => {
NotificationQueue.add(data);
};
export default NotificationQueue;
The following code block defines the implementation of the push notification job from the server.
We're working with pusher beams for sending push messages from the server. it's easy to use, has good documentation, and helps abstract the complexities of socketing a server to allow messaging between the server and client 😀.
Install the pusher Nodejs SDK from NPM using the following command.
npm i @pusher/push-notifications-server
We won't be focusing on how pusher works in this tutorial, the official docs is a good resource.
import { Job } from 'bull';
import PushNotifications from '@pusher/push-notifications-server';
const beamsClient = new PushNotifications({
instanceId: process.env.PUSHER_BEAMS_INSTANCE,
secretKey: process.env.PUSHER_BEAMS_SECRET,
});
const NotificationProcess = async (job: Job) => {
const {
title,
body,
url,
} = job.data as {
title: string,
body: string,
url: string,
};
await beamsClient.publishToInterests([userId], {
web: {
notification: {
title,
body,
deep_link: `${process.env.BASE_URL}${url}`,
},
},
});
return true;
}
export default NotificationProcess;
Save the file and run it using node ./index.ts. A notification will be sent to the subscribed client. (not covered in this tutorial).
import { NotificationQueueHelpers, } from '.../queues';
...
NotificationQueueHelpers.addNewNotification({
title: "simple queue system",
body: "push notification sent...",
url: `/notification/${user.id}`,
});
Wrap-up
This is a simple example of a queue system using Bull to create queues and schedule Jobs. As mentioned above bull offers a lot more options to manage the Redis caching system behind the scenes such as Event listeners, Rate limiters, Job types, delayed jobs, number of retries, using Cron expressions, and etc.
The official documentation is still a great resource worth exploring, do check it out.
Thanks for the audience and I hope you found this article helpful 🤗. Feel free to reach out to me on Github, Twitter and LinkedIn.
Do drop a like, comment, and share 😌.
Happy coding 💙!
