O’Reilly Media, 2019. — 633 p. — ISBN13: 978-1-491-96927-4. There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern...
O’Reilly, 2015. — 858 p. — ISBN: 978-1-491-90618-7. If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem,...
Packt Publishing, 2015. — 164 p. — ISBN: 978-1-78588-808-3. Explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies A Data Lake is a highly scalable platform for storing huge volumes of multistructured data from disparate sources with centralized data management services. This book...
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