Skip to main content
SpringerLink
Log in

Fundamental Concepts of Distributed Computing Used in Big Data Analytics

  • Chapter
  • First Online:
Distributed Computing in Big Data Analytics

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

Abstract

The study of distributed computing started in late 70s and many fundamental concepts has been proposed and successfully used in this area since then. Those concepts are used in various Big Data Technologies of present time, which are in turn the key building blocks of the Big Data Analytics used today in various businesses and industries. So it is essential for practitioners of Big Data Analytics to understand these fundamental concepts related to Distributed Computing. In this chapter we cover these fundamental concepts of Distributed Computing along with the Quality of Service aspects associated with them with examples wherever applicable.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. https://www.britannica.com/technology/multiprocessing

  2. https://en.wikipedia.org/wiki/Multithreading_%28computer_architecture%29

  3. http://www.w3ii.com/en-US/operating_system/os_multi_threading.html

  4. https://en.wikipedia.org/wiki/MIMD

  5. http://essaymonster.net/science/69515-study-on-mimd-and-shared-memory-architectures.html

  6. https://www.techopedia.com/7/31151/technology-trends/what-is-the-difference-between-scale-out-versus-scale-up-architecture-applicat

  7. MEN170: SYSTEMS MODELLING AND SIMULATION. QUT, SCHOOL OF MECHANICAL, MANUFACTURING & MEDICAL ENGINEERING

    Google Scholar 

  8. Queueing systems and networks. Models and applications. B. FILIPOWICZ and J. KWIECIEŃ

    Google Scholar 

  9. https://www.researchgate.net/publication/273575710_Adaptive_Scheduling_in_the_Cloud_-_SLA_for_Hadoop_Job_Scheduling

  10. http://robertgreiner.com/2014/08/cap-theorem-revisited/

  11. https://mytechnetknowhows.wordpress.com/2016/05/31/cap-theorem-consistency-availability-and-partition-tolerance/

  12. https://en.wikipedia.org/wiki/CAP_theorem

  13. https://codahale.com/you-cant-sacrifice-partition-tolerance/

  14. https://www.techopedia.com/definition/6581/computer-cluster

  15. https://en.wikipedia.org/wiki/Computer_cluster

  16. https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.3.4/bk_hadoop-ha/content/ch_HA-NameNode.html

  17. https://www.techopedia.com/definition/631/interoperability

  18. https://www.qubole.com/blog/big-data/hadoop-security-issues/

  19. http://blingtechs.blogspot.com/2016/02/cap-theorem.html

  20. http://mesos.apache.org

  21. https://hadoop.apache.org/docs/r2.7.2/hadoop-yarn/hadoop-yarn-site/YARN.html

  22. https://zeppelin.apache.org/

  23. https://www.cloudamqp.com/blog/2016-09-13-asynchronous-communication-with-rabbitmq.html

Download references

Author information

Authors and Affiliations

  1. Big Data Architect, Lab Service, IBM Analytics, Seattle, Washington, DC, USA

    Qi Jun Wang

Authors
  1. Qi Jun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qi Jun Wang .

Editor information

Editors and Affiliations

  1. IBM Analytics, San Ramon, California, USA

    Sourav Mazumder

  2. Discipline of Computer Science and Engineering, Indian Institute of Technology Indore, Indore, Madhya Pradesh, India

    Robin Singh Bhadoria

  3. Directorate General of Training, Ministry of Skill Development and Entrepreneurship, New Delhi, Delhi, India

    Ganesh Chandra Deka

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Wang, Q.J. (2017). Fundamental Concepts of Distributed Computing Used in Big Data Analytics. In: Mazumder, S., Singh Bhadoria, R., Deka, G. (eds) Distributed Computing in Big Data Analytics. Scalable Computing and Communications. Springer, Cham. https://doi.org/10.1007/978-3-319-59834-5_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59834-5_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59833-8

  • Online ISBN: 978-3-319-59834-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation