Teaching Big Data with a Virtual Cluster
Joshua Eckroth · 2016
Both industry and academia are confronting the challenge of big data, i.e., data processing that involves data so voluminous or arriving at such high velocity that no single commodity machine is capable of storing or processing them all. A common approach to handling big data is to divide and distribute the processing job to a cluster of machines. Ideally, a course that teaches students how to work with big data would provide students access to a cluster for hands-on practice. However, a cluster of physical, on-premise machines may be prohibitively expensive, particularly at smaller institutions with smaller budgets.