Book Image

Mastering Spark for Data Science

By : Bifet, Morgan, Amend, Hallett, George
Book Image

Mastering Spark for Data Science

By: Bifet, Morgan, Amend, Hallett, 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 (15 chapters)

Summary

While our recommendation system may not have taken the typical textbook approach, nor may it be the most accurate recommender possible, it does represent a fully demonstrable and incredibly interesting approach to one of the most commonplace techniques in data science today. Further, with persistent data storage, a REST API interface, distributed shared memory caching, and a modern web 2.0-based user interface, it provides a reasonably complete and rounded candidate solution.

Of course, building a production-grade product out of this prototype would still require much effort and expertise. There are still improvements to be sought in the area of signal processing. For example, one could improve the sound pressure and reduce the signal noise by using a loudness filter, http://languagelog.ldc.upenn.edu/myl/StevensJASA1955.pdf, by extracting pitches and melodies, or most importantly, by converting stereo to a mono signal.

Note

All these processes are actually part of an active...