Task Queue System

Overview

This project implements a distributed task queue system using Go. It consists of multiple components working together to schedule, manage, and execute tasks efficiently.

Dataflow diagram for the Distributed Task Queue System

Data flow diagram of Distributed Task Queue System

Components

1. Coordinator: The central component that manages task distribution and tracks execution status.
2. Worker: Executes tasks assigned by the Coordinator.
3. Scheduler: Handles task scheduling and insertion into the database.
4. PostgreSQL Database: Stores task information and status.

Features

• Task scheduling with specified execution times.
• Distributed task execution across multiple workers.
• Real-time task status updates.
• REST API for task submission, scheduling, and status checking.
• gRPC communication between components for efficient data transfer.
• Persistent storage of tasks and their statuses in PostgreSQL.
• Heartbeat mechanism to manage worker availability.

Architecture

The system follows a distributed architecture:

• Clients interact with the Scheduler to schedule tasks and the Coordinator to submit immediate tasks or check status.
• The Coordinator manages a pool of Workers, distributing tasks and collecting status updates.
• Workers execute tasks and report back to the Coordinator.
• All task information is persisted in the PostgreSQL database.

Getting Started

Prerequisites

• Go 1.21 or higher
• Docker and Docker Compose
• PostgreSQL

Installation

1. Clone the repository:

   git clone https://github.com/sagoresarker/task-queue.git

2. Navigate to the project directory:

   cd task-queue

3. Build the project:

   docker-compose build

Usage

1. Start the system:

   docker-compose up

2. The system exposes the following services:

   • Scheduler API: http://localhost:8081
   • Coordinator API: http://localhost:8080

3. To schedule a task:

   curl -X POST http://localhost:8081/schedule -d '{"command":"your_task_command", "scheduled_at":"2023-04-01T15:04:05Z"}'

4. To check task status:

   curl http://localhost:8081/status?task_id=your_task_id

Development

• The project uses Protocol Buffers for defining the gRPC service interfaces.
• To modify the gRPC definitions, edit the pkg/grpcapi/api.proto file and regenerate the Go code using the pkg/grpcapi/build.sh script.