© 2017

Distributed Computing in Big Data Analytics

Concepts, Technologies and Applications

  • Sourav Mazumder
  • Robin Singh Bhadoria
  • Ganesh Chandra Deka

Part of the Scalable Computing and Communications book series (SCC)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Julio César Santos dos Anjos, Cláudio Fernando Resin Geyer, Jorge Luis Victória Barbosa
    Pages 35-55
  3. Subarna Bhattacharyya, Detelina Ivanova
    Pages 95-106
  4. Vishwanath Kamat
    Pages 107-120
  5. Khalifeh AlJadda, Mohammed Korayem, Trey Grainger
    Pages 137-160

About this book


Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use.

This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations.

Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.


Distributed computing Cognitive analytics Internet of things Social media analytics Scientific data analytics Machine learning Streaming Analytics Spark Hadoop Cloud Computing Graph Computing

Editors and affiliations

  • Sourav Mazumder
    • 1
  • Robin Singh Bhadoria
    • 2
  • Ganesh Chandra Deka
    • 3
  1. 1.IBM AnalyticsSan RamonUSA
  2. 2.Discipline of Computer Science and EngineeringIndian Institute of Technology IndoreIndoreIndia
  3. 3.Directorate General of TrainingMinistry of Skill Development and EntrepreneurshipNew DelhiIndia

Bibliographic information

Industry Sectors
IT & Software
Consumer Packaged Goods
Materials & Steel
Finance, Business & Banking
Energy, Utilities & Environment
Oil, Gas & Geosciences