| Book Description | This book is an in-depth guide to understanding and mastering Apache Spark — one of the most powerful open-source frameworks for large-scale data processing. It covers everything from the fundamentals of Spark architecture to advanced techniques in data engineering, stream processing, and machine learning integration. The author provides clear explanations, practical examples, and real-world case studies that help readers gain both theoretical knowledge and hands-on experience in big data analytics.
Readers will learn how to build efficient data pipelines, optimize Spark performance, and handle massive datasets with ease. The book explores Spark’s core components, including RDDs, DataFrames, Spark SQL, Structured Streaming, and the MLlib machine learning library. Whether you are a student, data engineer, or data scientist, this book equips you with the skills needed to process, analyze, and store big data effectively using Spark’s distributed computing capabilities. |
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