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

Introduction to Property Graph

It is the basic abstraction of the Graphx API. Property is a directed multi-graph where every vertex and edge is associated with a property. Each vertex in the Property Graph is also associated with a unique 64-bit long identifier (VertexId). A directed multi-graph is defined as a directed graph where there can be multiple edges (relationships) between the same vertices, such as A can be a friend and team mate of B.

The following is a logical representation of a Property Graph:

Logical representation of Property Graph

Here, we have a Property Graph consisting of five vertices. Each vertex in the graph consists of a VertexId and a property, which is a string object in this case, and every edge is also associated with a property, which is a string object as well, which describes the relation between the vertices.

Spark stores vertices and edges in different RDDs as follows:

Storage representation of Property Graph

Every element of the RDD of vertices contains a VertexId...