Movie Recommendation System in Spark for Big Data
Published:
Systems for Data Science, 100/100, 2021
Developed and deployed a movie recommendation system in Scala with Spark. The movie recommender is modeled with an approximate k-NN system that can predict efficiently over several machines the best movie for a user. The personalized recommender is implemented using modern libraries, such as Spark and written in Scala. The efficiency and economics are evaluated, and the model has been tested on multiple scale data sets and benchmarks, such as MovieLens 10M.