Book Image

Mastering Spark for Data Science

By : Andrew Morgan, Antoine Amend, Matthew Hallett, David George
Book Image

Mastering Spark for Data Science

By: Andrew Morgan, Antoine Amend, Matthew Hallett, David George

Overview of this book

Data science seeks to transform the world using data, and this is typically achieved through disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance –solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs. This book deep dives into using Spark to deliver production-grade data science solutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more. You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly.
Table of Contents (22 chapters)
Mastering Spark for Data Science
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Summary


This chapter was really complex and the story mutation problem could not be easily solved in the time frame allowed for delivering this chapter. However, what we discovered is truly amazing as it opens up a lot of questions. We did not want to draw any conclusion though, so we stopped our process right after the observation of the Paris attack disturbance and left that discussion open for our readers. Feel free to download our code base and study any breaking news and their potential impacts in what we define as an Equilibrium state. We are very much looking forward to hearing back from you and learning about your findings and different interpretations.

Surprisingly, we did not know anything about the Galaxy Note 7 fiasco before writing this chapter, and without the API created in the first section, the related articles would surely have been indistinguishable from the mass. De-duplicating content using  Simhash really helped us get a better overview of the world news events.

In the...