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

Interaction with external storage systems

As we know, Spark is a processing engine that can help to process a humongous amount of data; however, to process the data it should be read from external systems. In this section, we will learn how to store/read data in Spark from/to different storage systems.

We will start with the local filesystem and then will implement Spark with some popular storage systems used in the big data world.

Interaction with local filesystem

It is very straightforward and easy to read data from a local filesystem in Spark. Let's discuss this with examples, as follows:

Let's put first things first. First, create (or reuse) the Maven project described in the previous chapter and create a Java class (with main method) for our application. We will start by creating a JavaSparkContext:

SparkConf conf =new SparkConf().setMaster("local").setAppName("Local File system Example"); 
JavaSparkContext jsc=new JavaSparkContext(conf); 

To read a text file in Spark, the textFile method...