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

Building a song analyzer


However, before deep diving into the recommender itself, the reader may have noticed an important property that we were able to extract out of the signal data. Since we generated audio signatures at regular time intervals, we can compare signatures and find potential duplicates. For example, given a random song, we should be able to guess the title, based on previously indexed signatures. In fact, this is the exact approach taken by many companies when providing music recognition services. To take it one step further, we could potentially provide insight into a band's musical influences, or further, perhaps even identify song plagiarism, once and for all settling the Stairway to Heaven dispute between Led Zeppelin and the American rock band Spirit http://consequenceofsound.net/2014/05/did-led-zeppelin-steal-stairway-to-heaven-legendary-rock-band-facing-lawsuit-from-former-tourmates/.

With this in mind, we will take a detour from our recommendation use case by continuing...