Book Image

Apache Spark 2.x for Java Developers

By : Sourav Gulati, Sumit Kumar
Book Image

Apache Spark 2.x for Java Developers

By: Sourav Gulati, Sumit Kumar

Overview of this book

Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone. The book starts with an introduction to the Apache Spark 2.x ecosystem, followed by explaining how to install and configure Spark, and refreshes the Java concepts that will be useful to you when consuming Apache Spark's APIs. You will explore RDD and its associated common Action and Transformation Java APIs, set up a production-like clustered environment, and work with Spark SQL. Moving on, you will perform near-real-time processing with Spark streaming, Machine Learning analytics with Spark MLlib, and graph processing with GraphX, all using various Java packages. By the end of the book, you will have a solid foundation in implementing components in the Spark framework in Java to build fast, real-time applications.
Table of Contents (19 chapters)
Title Page
About the Authors
About the Reviewer
Customer Feedback


In this chapter, we started with a Hello World program and setting up an IDE (Eclipse) for executing Spark Jobs. Then we discussed various RDD Transformation and various common transformations such as map, flatMap, mapToPair, and so on. We also explored commonly used RDD actions and some of the use cases associated with it. We also gained some understanding in improving Spark Job performance by using Apache Spark's inbuilt cache and persist mechanism.

The next chapter will focus on the interactional aspect of Apache Spark as far as the Data and Storage layer is concerned. We will learn about Spark integration with external storage systems such as HDFS, S3 etc and its ability to process various data formats such as xml, json etc.