Book Image

Big Data Analytics with Java

Book Image

Big Data Analytics with Java


Overview of this book

This book covers case studies such as sentiment analysis on a tweet dataset, recommendations on a movielens dataset, customer segmentation on an ecommerce dataset, and graph analysis on actual flights dataset. This book is an end-to-end guide to implement analytics on big data with Java. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into two sections. The first part is an introduction that will help the readers get acquainted with big data environments, whereas the second part will contain a hardcore discussion on all the concepts in analytics on big data. It will take you from data analysis and data visualization to the core concepts and advantages of machine learning, real-life usage of regression and classification using Naïve Bayes, a deep discussion on the concepts of clustering,and a review of simple neural networks on big data using deepLearning4j or plain Java Spark code. This book is a must-have book for Java developers who want to start learning big data analytics and want to use it in the real world.
Table of Contents (21 chapters)
Big Data Analytics with Java
About the Author
About the Reviewers
Customer Feedback
Free Chapter
Big Data Analytics with Java
Ensembling on Big Data
Real-Time Analytics on Big Data


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.