Key Features

Perform big data processing with Spark―without having to learn Scala!

Use the Spark Java API to implement efficient enterprise-grade applications for data processing and analytics

Go beyond mainstream data processing by adding querying capability, Machine Learning, and graph processing using Spark

Book Description

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.

What you will learn

Process data using different file formats such as XML, JSON, CSV, and plain and delimited text, using the Spark core Library.

Perform analytics on data from various data sources such as Kafka, and Flume

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