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Spark Big Data Processing: Principles, Algorithms and Examples is a September 2016 Tsinghua University Publishing Co. Book, authored by Liu Jun, Lin Wenhui, and Fang Cheng. Taking the flaws of the most popular Hadoop as a starting point, this book provides an in-depth introduction to the advantages and necessity of Spark, the core technology of next-generation big data processing, and shows how to set up a Spark big data processing environment in 10 minutes with the most concise guideline steps. On this basis, the book systematically reveals Spark's operation principles, operator usage, algorithm design and optimization means in the form of illustrations and rich sample code explanations, providing readers with a reference book for quickly mastering Spark's basic capabilities and advanced skills from shallow to deep. This book *** Six chapters, covering topics mainly include the inevitability of the development of big data processing technology from Hadoop to Spark, guidelines for a quick experience of Spark, Spark architecture and principles, RDD operator usage and examples, Spark algorithm design examples, and Spark program optimization methods. This book is suitable for programmers, architects, and product managers who need to use Spark for big data processing as a technical reference and training material, and can also be used as a textbook for graduate and undergraduate students in universities.