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
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Concepts of machine learning


A reductionist approach to defining machine learning in general would be, a programming paradigm where existing data helps in either generalizing the results as in classification algorithms or make some predictions. One of the pioneers of machine learning, Andrew Ng, defines machine learning as the Science of how computers learn without being explicitly programmed. Whichever assertion resonates with you, one thing which is clear that machine learning encompasses areas and solves problems from health diagnostics to space exploration and the way you connect with your friends online to the way your food is getting delivered to your doorstep.

Every day, system intelligence is being added to the services that make machines more intelligent while showing us ways to optimize and improve. Machine learning very broadly can be categorized into four categories:

  • Supervised learning: Algorithms that learn from existing datasets output (label) and then utilize them to predict...