When examining big data processing systems, we think it is important to look at not just the system itself, but also how it can be extended and how it integrates with external systems so that greater levels of functionality can be offered. In a book of this size, we cannot cover every option, but by introducing a topic, we can hopefully stimulate the reader's interest so that they can investigate further.
We have used the H2O machine learning library, SystemML and Deeplearning4j, to extend Apache Spark's MLlib machine learning module. We have shown that Deeplearning and highly performant cost-based optimized machine learning can be introduced to Apache Spark. However, we have just scratched the surface of all the frameworks' functionality.