Book Image

Spark for Data Science

By : Srinivas Duvvuri, Bikramaditya Singhal
Book Image

Spark for Data Science

By: Srinivas Duvvuri, Bikramaditya Singhal

Overview of this book

This is the era of Big Data. The words ‘Big Data’ implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages. Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R. With ample case studies and real-world examples, Spark for Data Science will help you ensure the successful execution of your data science projects.
Table of Contents (18 chapters)
Spark for Data Science
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Preface

The Scala advantage


Apache Spark allows you to write applications in Python, R, Java, or Scala. With this flexibility comes the responsibility of choosing the right language for your requirements. But regardless of your usual language of choice, you may want to consider Scala for your Spark-powered application. In this section, we will explain why.

Let's digress to gain a high-level understanding of imperative and functional programming paradigms first. Languages such as C, Python, and Java belong to the imperative programming paradigm. In the imperative programming paradigm, a program is a sequence of instructions and it has a program state. The program state is usually represented as a set of variables and their values at any given point in time. Assignments and reassignments are fairly common. Variable values are expected to change over the period of execution by one or more functions. Variable value modification in a function is not limited to local variables. Global variables and public...