High-Performance Big-Data Analytics

Computing Systems and Approaches

  • Pethuru Raj
  • Anupama Raman
  • Dhivya Nagaraj
  • Siddhartha Duggirala

Part of the Computer Communications and Networks book series (CCN)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 1-23
  3. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 25-66
  4. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 67-99
  5. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 101-126
  6. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 127-159
  7. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 161-185
  8. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 187-206
  9. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 207-231
  10. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 233-274
  11. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 275-315
  12. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 317-337
  13. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 339-365
  14. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 367-390
  15. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, Siddhartha Duggirala
    Pages 391-424
  16. Back Matter
    Pages 425-428

About this book

Introduction

This important and timely text/reference presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. 

Comprehensively covering a diverse range of computer systems and proven techniques for high-performance big-data analytics, the book also presents case studies, practical guidelines, and best practices for enabling decision-making toward implementing the appropriate computer systems and approaches.

Topics and features:

  • Includes case studies and learning activities throughout the book, and self-study exercises at the end of every chapter
  • Presents detailed case studies on social media analytics for intelligent businesses, and on big data analytics in the healthcare sector
  • Describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data
  • Examines real-time analytics solutions, such as machine data analytics and operational analytics
  • Introduces in-database processing and in-memory analytics techniques for data mining
  • Discusses the use of mainframes for handling real-time big data, and the latest types of data management systems for big and fast data analytics
  • Provides information on the use of cluster, grid and cloud computing systems for big data analytics and data-intensive processing
  • Reviews the peer-to-peer techniques and tools, and the common information visualization techniques, used in big data analytics

Software engineers, cloud professionals and big data scientists will find this book to be an informative and inspiring read, highlighting the indispensable role data analytics will play in shaping a smart future.

Keywords

Big Data Analytics Hadoop Distributed File System (HDFS) Hadoop Software Framework Internet of Things (IoT) Machine-to-Machine (M2M) Integration NoSQL Databases Peer-to-Peer, Grid and Cloud Computer Systems

Authors and affiliations

  • Pethuru Raj
    • 1
  • Anupama Raman
    • 2
  • Dhivya Nagaraj
    • 3
  • Siddhartha Duggirala
    • 4
  1. 1.IBM IndiaBangaloreIndia
  2. 2.IBM IndiaBangaloreIndia
  3. 3.IBM IndiaBangaloreIndia
  4. 4.Indian Institute of TechnologyIndoreIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-20744-5
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-20743-8
  • Online ISBN 978-3-319-20744-5
  • Series Print ISSN 1617-7975
  • Series Online ISSN 2197-8433
  • About this book
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