Cloud-agnostic architectures for machine learning based on Apache Spark

Reference architectures for Big Data, machine learning and stream processing include not only recommended practices and interconnected building blocks but considerations for scalability, availability, manageability, and security as well. However, the automated deployment of multi-VM platforms on various clouds leveraging on such reference architectures may raise several issues. The paper focuses particularly on the widespread Apache Spark Big...