Mastering Spark for Data Science

Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products

Key Features

• Develop and apply advanced analytical techniques with Spark
• Learn how to tell a compelling story with data science using Spark’s ecosystem
• Explore data at scale and work with cutting edge data science methods

Book Description

What you will learn

• Learn the design patterns that integrate Spark into industrialized data science pipelines
• See how commercial data scientists design scalable code and reusable code for data science services
• Explore cutting edge data science methods so that you can study trends
• and causality
• Discover advanced programming techniques using RDD and the DataFrame and Dataset APIs
• Find out how Spark can be used as a universal ingestion engine tool and as a web scraper
• Practice the implementation of advanced topics in graph processing, such as community detection and contact chaining
• Get to know the best practices when performing Extended Exploratory Data Analysis, commonly used in commercial data science teams
• Study advanced Spark concepts, solution design patterns, and integration architectures
• Demonstrate powerful data science pipelines

Who this book is for

This book is for those who have beginner-level familiarity with the Spark architecture and data science applications, especially those who are looking for a challenge and want to learn cutting edge techniques. This book assumes working knowledge of data science, common machine learning methods, and popular data science tools, and assumes you have previously run proof of concept studies and built prototypes.