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

Intermediate operations

Intermediate operations always return another stream and get lazily evaluated only when terminal operations are called. The feature of lazy evaluation optimizes intermediate operations when multiple operations are chained together as evaluation only takes place after terminal operation. Another scenario where lazy evaluation tends to be useful is in use cases of infinite or large streams as iteration over an entire stream may not be required or even possible, such as anyMatch, findFirst(), and so on. In these scenarios, short circuiting (discussed in the next section) takes place and the terminal operation exits the flow just after meeting the criteria rather than iterating over entire elements.

Intermediate operations can further be sub-divided into stateful and stateless operations. Stateful operations preserve the last seen value, as in methods such as sorted(), limit(), sequential(), and so on since they need them while processing the current record. For example...