ABSTRACT
Big Data Systems encompass massive challenges related to data diversity, storage mechanisms, and requirements of massive computational power. Further, capabilities of big data systems also vary with respect to type of problems. For instance, distributed memory systems are not recommended for iterative algorithms. Similarly, variations in big data systems also exist related to consistency and fault tolerance. The purpose of this book is to provide a detailed explanation of big data systems. The book covers various topics including Networking, Security, Privacy, Storage, Computation, Cloud Computing, NoSQL and NewSQL systems, High Performance Computing, and Deep Learning. An illustrative and practical approach has been adopted in which theoretical topics have been aided by well-explained programming and illustrative examples.
Key Features:
- Introduces concepts and evolution of Big Data technology.
- Illustrates examples for thorough understanding.
- Contains programming examples for hands on development.
- Explains a variety of topics including NoSQL Systems, NewSQL systems, Security, Privacy, Networking, Cloud, High Performance Computing, and Deep Learning.
- Exemplifies widely used big data technologies such as Hadoop and Spark.
- Includes discussion on case studies and open issues.
- Provides end of chapter questions for enhanced learning.
TABLE OF CONTENTS
section I|62 pages
Introduction
section II|118 pages
Storage and Processing for Big Data
section III|50 pages
Networking, Security, and Privacy for Big Data
section IV|40 pages
Computation for Big Data
section V|12 pages
Networking, Security, and Privacy for Big Data
