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A Distributed Background Task Processing System. Enqueue your background jobs using WorkQueue and elevate user experience with the power of Go and Redis.

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WorkQueue

A Distributed Background Task Processing System written in Go, using Redis for job queuing.

High level overview overview

What's the need for this?

This system is designed to handle the processing and execution of background tasks concurrently to improve user experience.

Example: When a user signs in to your website and clicks the login button, you might want to send them a welcome email. If that email task is part of the API call, the user would have to wait until the email is sent. Instead, you can add the "send_email" task to WorkQueue and let it handle the execution in the background.

Note: This is built to be modular — any type of job can be added to it, not just sending emails. You just need to add the logic for that job as described below.

Services

This repo provides two independent services:

1. Producer

Provides a /enqueue route to add your jobs/tasks.

How to add a job?

  • Send an HTTP POST request to the exposed /enqueue route on this URL: workqueue-producer
  • It accepts a task in this format (JSON):

Example: An inbuilt task the system supports is sending an email. Its JSON request would look like this:

{
    "type": "send_email",
    "Retries": 3,
    "payload": {
        "to": "worldisweird2020@gmail.com",
        "subject": "testing producer"
    }
}
  • type - REQUIRED. Tells the producer the type of job being added to the queue.
  • Retries - Number of times the system should try to enqueue the job if it fails.
  • Payload - Contains details about the task in key-value pairs (Note: you can add any type/number of key-value pairs inside the payload, as the backend is built to flexibly accept all types).

This is the Go struct type it accepts:

type Task struct {
    Type    string                 `json:"type"`
    Payload map[string]interface{} `json:"payload"`
    Retries int                    `json:"retries"`
}

The response will look like this:

Producer response

2. Worker

  • Takes the jobs from the queue in a reliable manner and executes them
  • Provides a /metrics endpoint to view statistics

How to view the status of your job?

Send an HTTP GET request to worker-url

This will give a response like this:

Worker metrics

  • total_jobs_in_queue - Number of jobs inside the Redis queue at that moment
  • jobs_done - Total number of jobs executed so far
  • jobs_failed - Number of jobs that failed to execute, if any

How are jobs executed?

Inside the internal/worker/worker.go, you will find this function. The switch case makes it modular enough so you can add your job type just by adding another case.

To add a new type of task: Just add its function inside a new switch case, and that's it!

func Process_Task(task_to_execute task.Task) error {
    if task_to_execute.Payload == nil {
        return fmt.Errorf("payload is empty")
    }

    // Add your task type here, and perform the task under your switch case
    switch task_to_execute.Type {
    case "send_email":
        time.Sleep(2 * time.Second)
        fmt.Println("Sending email to ", task_to_execute.Payload["to"], " with subject ", task_to_execute.Payload["subject"])
        return nil
    case "resize_image":
        fmt.Println("Resizing image to x coordinate: ", task_to_execute.Payload["new_x"], " y coordinate: ", task_to_execute.Payload["new_y"])
        return nil
    case "generate_pdf":
        fmt.Println("Generating pdf...")
        return nil
    case "":
        return fmt.Errorf("task type is empty")
    default:
        return fmt.Errorf("unsupported task")
    }
}

Additional features

  • Concurrency is provided to enable fast execution using goroutines and the sync package.

  • Logging of each event is provided and stored inside the logs.txt file. This helps to trace back the success or failure of a job.

Example: Logging example

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