Large Scale and Big Data: Processing and Management
"Large Scale and Big Data: Processing and Management" provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments.
The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book’s second section examines the usage of advanced Big Data processing techniques in different domains, including semantic Web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security.
Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and Web scale data processing.
In this excerpt from chapter 9, readers are provided on overview of the NoSQL world, exploring the recent advancements and the new approaches of Web-scale data management, the advantages and disadvantages of several recently introduced approaches and their suitability to support certain class of applications and end users.
Excerpted with permission from the publisher, Auerbach Publications, from "Large Scale and Big Data: Processing and Management," edited by Sherif Sakr and Mohamed Gaber. © 2014.
The attached zip file includes:
- Intro Page.pdf
- Terms and Conditions.pdf
- Large Scale and Big Data.pdf