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This book is for the advanced Spark user, who is looking to deploy Spark in Docker containers, and wants to learn not only how to work with the basic Spark features, but also how to extend it to fit custom requirements (such as leveraging GPU processing nodes) aided by a series of real-world implementation examples where possible using real data.
Spark is an exciting new analytical platform by the Apache Foundation. It combines fault tolerant distributed computing with very low latency by keeping data in memory and keeping processing as local to the compute nodes as possible. This way Spark can achieve magnitudes of performance improvements over conventional Hadoop cluster processing.
