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Time Series Analysis with Spark

Time Series Analysis with Spark

By : Yoni Ramaswami
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Time Series Analysis with Spark

Time Series Analysis with Spark

3 (1)
By: Yoni Ramaswami

Overview of this book

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
Table of Contents (18 chapters)
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Part 1: Introduction to Time Series and Apache Spark
5
Part 2: From Data to Models
10
Part 3: Scaling to Production and Beyond

Introduction to Apache Spark

This chapter provides an overview of Apache Spark, explaining its distributed computing capabilities and suitability for processing large-scale time series data. It explains how Spark addresses the challenges of parallel processing, scalability, and fault tolerance. This foundational knowledge is essential as it sets the stage for leveraging Spark’s strengths in handling vast temporal datasets, facilitating efficient time series analysis. Practical knowledge of Spark’s role enhances practitioners’ ability to harness its power for complex computations, making it a valuable resource for scalable, high-performance time series applications.

We’re going to cover the following main topics:

  • Apache Spark and its architecture
  • How Apache Spark works
  • Installation of Apache Spark
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Time Series Analysis with Spark
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