Time Series Analysis with Spark: A practical guide to processing, modeling, and forecasting time series with Apache Spark - Softcover

Yoni Ramaswami

Softcover

ISBN 10: 1803232250 ISBN 13: 9781803232256

Publisher: Packt Publishing, 2025

Synopsis

Master the fundamentals of time series analysis with Apache Spark and Databricks and uncover actionable insights at scale

Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*

Key Features

• Quickly get started with your first models and explore the potential of Generative AI
• Learn how to use Apache Spark and Databricks for scalable time series solutions
• Establish best practices to ensure success from development to production and beyond
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Written by Databricks Senior Solutions Architect Yoni Ramaswami, whose expertise in Data and AI has shaped innovative digital transformations across industries, this comprehensive guide bridges foundational concepts of time series analysis with the Spark framework and Databricks, preparing you to tackle real-world challenges with confidence.

From preparing and processing large-scale time series datasets to building reliable models, this book offers practical techniques that scale effortlessly for big data environments. You’ll explore advanced topics such as scaling your analyses, deploying time series models into production, Generative AI, and leveraging Spark's latest features for cutting-edge applications across industries. Packed with hands-on examples and industry-relevant use cases, this guide is perfect for data engineers, ML engineers, data scientists, and analysts looking to enhance their expertise in handling large-scale time series data.

By the end of this book, you’ll have mastered the skills to design and deploy robust, scalable time series models tailored to your unique project needs—qualifying you to excel in the rapidly evolving world of big data analytics.

*Email sign-up and proof of purchase required

What you will learn

• Understand the core concepts and architectures of Apache Spark
• Clean and organize time series data
• Choose the most suitable modeling approach for your use case
• Gain expertise in building and training a variety of time series models
• Explore ways to leverage Apache Spark and Databricks to scale your models
• Deploy time series models in production
• Integrate your time series solutions with big data tools for enhanced analytics
• Leverage GenAI to enhance predictions and uncover patterns

Who this book is for

If you are a data engineer, ML engineer, data scientist, or analyst looking to enhance your skills in time series analysis with Apache Spark and Databricks, this book is for you. Whether you’re new to time series or an experienced practitioner, this guide provides valuable insights and techniques to improve your data processing capabilities. A basic understanding of Apache Spark is helpful, but no prior experience with time series analysis is required.

Table of Contents

1. What Are Time Series
2. Why Time Series Analysis?
3. Introduction to Apache Spark
4. End-to-End View of a Time Series Analysis Project
5. Data Preparation
6. Exploratory Data Analysis
7. Building and Testing Models
8. Going at Scale
9. Going to Production
10. Going Further with Apache Spark
11. Recent Developments in Time Series Analysis

About this title

About the Author

Yoni Ramaswami is a Senior Solutions Architect at Databricks with two decades of experience in IT, data, and AI. Recognized for his contributions to projects spanning digitally innovative technologies across industries, Yoni combines thought leadership, architecture, and implementation expertise. Originally from Mauritius, Yoni earned his Diplôme d'Ingénieur from UTC in France and Chalmers in Sweden, grounding his global perspective in both technical rigour and cultural insight. When not devising practical, high-impact solutions, he can be found exploring the lush landscapes of Mauritius with his son.

Edition details

• Publisher: Packt Publishing
• Publication date: 2025
• Language: English
• ISBN 10: 1803232250
• ISBN 13: 9781803232256
• Binding: Paperback
• Number of pages: 298