Movie Recommendation System using Apache Spark

Recommendations have become a very important part of everyone’s life as today we have a huge number of options for a particular product and choosing the one which meets our need is monotonous. Also, movies have become a very popular form of entertainment in the modern world. However manually searching for movies of our interest from such a mammoth set of present movies can be a tedious task. Movie recommendation System plays an important role in this scenario therefore the proposed system helps the user in selecting movies of their choice by collecting the user data and then analysing their preferences and collecting various related data to use in our algorithm to then recommend the best possible movies to the user. Weights are assigned to the various preferences in order to get the best possible results. To implement the proposed system the Apache Spark framework is used. The language used to implement the system is Scala which is the native language in which Spark has been implemented. We will also use the capabilities of MLLib which is the Machine Learning Library of Spark to implement the system. Many algorithms from MLLib will be used. The expected model would be able to propose movies to the user from a predefined dataset according to his preferences in a very short span of time i.e. - the model will give really good performance as compared to already existing systems.