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


In this chapter, we have explored the topic of data security and explained some of the surrounding issues. We have discovered that not only is there technical knowledge to master, but also that a data security mindset is just as important. Data security is often overlooked and, therefore, taking a systematic approach, and educating others, is a key responsibility for mastering data science.

We have explained the data security life cycle and outlined the most important areas of responsibility, including authorization, authentication and access, along with related examples and use cases. We have also explored the Hadoop security ecosystem and described the important open source solutions currently available.

A significant part of this chapter was dedicated to building a Hadoop InputFormat compressor that operates as a data encryption utility that can be used with Spark. Appropriate configuration allows the codec to be used in a variety of key areas, crucially when spilling shuffled records...