We started this chapter on a simple note by going over the very basic yet very power simple analytics on simple datasets. While doing so, we also learned a very powerful module of Apache Spark called Spark SQL. Using this module, Java developers can use their regular SQL skills and analyze their big data datasets.
After exploring the simple analytics piece using spark-sql, we went over two complex analytic algorithms: Apriori and FP-Growth. We learned how we can use these algorithms to build association rules from a transaction dataset.
In the next chapter, we will learn the basics of machine learning and get an introduction to the machine learning approach for dealing with a predictive analytics problem.
