ABSTRACT

From the Foreword:

"Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies."

---Sartaj Sahni, University of Florida, USA

"Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields.

--Hai Jin, Huazhong University of Science and Technology, China

Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems.

The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions.

The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.

chapter 1|16 pages

Big Data *

Legal Compliance and Quality Management

chapter 7|24 pages

Tyche

An Efficient Ethernet-Based Protocol for Converged Networked Storage

chapter 9|18 pages

SQL-on-Hadoop Systems

State-of-the-Art Exploration, Models, Performances, Issues, and Recommendations

chapter 10|24 pages

One Platform Rules All

From Hadoop 1.0 to Hadoop 2.0 and Spark

chapter 11|24 pages

Security, Privacy, and Trust for User-Generated Content

The Challenges and Solutions

chapter 15|36 pages

Complex Mining from Uncertain Big Data in Distributed Environments

Problems, Definitions, and Two Effective and Efficient Algorithms

chapter 16|14 pages

Clustering in Big Data

chapter 18|22 pages

Big Data in Genomics

chapter 19|18 pages

Maximizing the Return on Investment in Big Data Projects

An Approach Based upon the Incremental Funding of Project Development