Building a recommendation engine with AWS Data Pipeline, Elastic MapReduce and Spark

From Google's advertisements to Amazon's product suggestions, recommendation engines are everywhere. As users of smart internet services, we've become so accustomed to seeing things we like. This blog post is an overview of how we built a product recommendation engine for Hubba. I'll start with an explanation of different types of recommenders and how we went about the selection process. Then I'll cover our AWS solution before diving into some implementation details. Content-based recommenders use discrete properties of an item, such as its tags.