FilmFlix - Movie Recommendation System

Project Overview FilmFlix is ​​a personalized movie recommendation system that leverages the Alternating Least Squares (ALS) algorithm. Users can rate movies, and based on their ratings, the system provides customized movie recommendations.

Architecture

React - used to build a responsive and interactive UI for users to browse movies, submit ratings, and view recommendations. Back end:

Flask - serves as the API layer, handling client requests, user authentication, and communication with the recommendation system. Message Queue:

Kafka - used as the messaging queue for sending user rating data from the front end to the recommendation engine. Streaming & Recommendation Engine:

Spark Streaming - processes the data

Spark MLlib - generates movie recommendations using the ALS algorithm. Database: MongoDB stores user data, movie information, and ratings.

Technologies Used

• Frontend: React, JavaScript, Material-UI
• Backend: Flask, Python, Flask-CORS, Flask-JWT
• Queue: Kafka
• Data Processing: Apache Spark, Spark Streaming
• Database: MongoDB
• Containerization: Docker

Installation

Set up Frontend without docker:

cd frontend
npm install
npm start

Set up Backend without docker:

cd backend
python -m venv venv
source venv/bin/activate  # For Linux/macOS
venv\Scripts\activate     # For Windows
pip install -r requirements.txt
python app.py

Run all in docker:

docker-compose up

Images