Nonfiction
Book
Availability
Details
PUBLISHED
©2026
EDITION
DESCRIPTION
xx, 387 pages : illustrations ; 24 cm
ISBN/ISSN
LANGUAGE
NOTES
Includes index
Preface -- 1. Introduction to high perfromance Spark -- 2. How Spark works -- 3. Upgrading Spark -- 4. What's new in Spark 4.2 since 2.4 -- 5. DataFrames, datasets, and Spark SQL -- 6. Joins (SQL and core) -- 7. Effective transformations -- 8. Working with key/value data -- 9. Going beyond Scala -- 10. Spark: a thoughtful step into generative AI -- 11. Testing, validation, and side-by-side runs -- 12. Spark components and packages -- A Just enough Iceberg and friends -- b. Spark connect -- C. When not tu use Spark -- D. Advanced task scheduling: gangs and resource profiles -- E. Spark streaming -- F. The Spark web UI: debugging and optimizing your jobs -- Index
Apache Spark is amazing when everything clicks. But if you haven't seen the performance improvements you expected or still don't feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau, Adi Polak, and Rachel Warren walk you through the secrets of the Spark code base and demonstrate performance optimizations that will help your data pipelines run faster, scale to larger datasets, and avoid costly antipatterns. With this book, you will learn how to accelerate your ML workflows with integrations including PyTorch, handle key skew and take advantage of Spark's new dynamic partitioning, make your code reliable with scalable testing and validation techniques, make Spark high performance, deploy Spark on Kubernetes and similar environments, take advantage of GPU acceleration with RAPIDS and resource profiles, get your Spark jobs to run faster, use Spark to productionize exploratory data science projects, handle even larger datasets with Spark, and gain faster insights by reducing pipeline running times