Open Access   Article Go Back

Big Data: Challenges and Solutions

M.A. Srinuvasu1 , A. Koushik2 , E.B. Santhosh3

  1. Dept. of Computer Science and Engineering, Raghu Institute of Technology, Visakhapatnam, INDIA.
  2. Dept. of Computer Science and Engineering, Raghu Institute of Technology, Visakhapatnam, INDIA.
  3. Dept. of Computer Science and Engineering, Raghu Institute of Technology, Visakhapatnam, INDIA.
  4. Dept. of Computer Science and Engineering, Raghu Institute of Technology, Visakhapatnam, INDIA.

Correspondence should be addressed to: srinuvasu.mutti@gmailmail.com.

Section:Review Paper, Product Type: Journal Paper
Volume-5 , Issue-10 , Page no. 250-255, Oct-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i10.250255

Online published on Oct 30, 2017

Copyright © M.A. Srinuvasu, A. Koushik, E.B. Santhosh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

IEEE Style Citation: M.A. Srinuvasu, A. Koushik, E.B. Santhosh, “Big Data: Challenges and Solutions,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.250-255, 2017.

MLA Style Citation: M.A. Srinuvasu, A. Koushik, E.B. Santhosh "Big Data: Challenges and Solutions." International Journal of Computer Sciences and Engineering 5.10 (2017): 250-255.

APA Style Citation: M.A. Srinuvasu, A. Koushik, E.B. Santhosh, (2017). Big Data: Challenges and Solutions. International Journal of Computer Sciences and Engineering, 5(10), 250-255.

BibTex Style Citation:
@article{Srinuvasu_2017,
author = {M.A. Srinuvasu, A. Koushik, E.B. Santhosh},
title = {Big Data: Challenges and Solutions},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2017},
volume = {5},
Issue = {10},
month = {10},
year = {2017},
issn = {2347-2693},
pages = {250-255},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1508},
doi = {https://doi.org/10.26438/ijcse/v5i10.250255}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i10.250255}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1508
TI - Big Data: Challenges and Solutions
T2 - International Journal of Computer Sciences and Engineering
AU - M.A. Srinuvasu, A. Koushik, E.B. Santhosh
PY - 2017
DA - 2017/10/30
PB - IJCSE, Indore, INDIA
SP - 250-255
IS - 10
VL - 5
SN - 2347-2693
ER -

VIEWS PDF XML
1046 451 downloads 425 downloads
  
  
           

Abstract

Big data is huge amount of data which is beyond the processing capacity of conventional data base systems to manage and analyze the data in a specific time interval. The data is too big to store and processed by a single machine. New innovative methods are necessary to process and store large volumes of data. This paper endows with overview of big data, its size, nature, 12Vs of Big data and some technologies to handle it.

Key-Words / Index Term

Big Data, Hadoop, Map Reduce, YARN

References

[1] R. Gupta,S. Gupta, A singhal," Big Data : Overview", International Journal of Computer Trends and Technology, Vol 9, Issue 5, pp. 266-268, 2014.
[2] S. Sagiroglu, D. Sinanc, "Big data: A review", In the Proceedings of the 2013 International Conference on Collaboration Technologies and Systems (CTS), San Diego, CA, pp. 42-47, 2013.
[3] S. Sathyamoorthy, "Data Mining and Information Security in Big Data", International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.86-91, 2017.
[4] Cuzzocrea, I. Song, K.C. Davis "Analytics over Large-Scale Multidimensional Data: The Big Data Revolution", In the Proceedings of the ACM International Workshop on Data Warehousing and OLAP, pp. 101-104, 2011.
[5] Palaghat Yaswanth Sai, Pabolu Harika, "Illustration of IOT with Big Data Analytics", International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.221-223, 2017.
[6] Raju Din, Prabadevi B. , "Data Analyzing using Big Data (Hadoop) in Billing System", International Journal of Computer Sciences and Engineering, Vol.5, Issue.5, pp.84-88, 2017.
[7] V.K. Vavilapalli, A.C. Murthy, Ch. Douglas, S. Agarwal, M. Konar, R. Evans, T. Graves, J. Lowe, H. Shah, S. Seth, B. Saha, C. Curino, Owen O`Malley, S.Radia, B. Reed, and E. Baldeschwieler, "Apache Hadoop YARN: yet another resource negotiator", In Proceedings of the 4th annual Symposium on Cloud Computing (SOCC `13). ACM, New York, NY, USA, , Article 5 , pp.16, 2013.
[8] P. Sharma, V. Garg, R, Kaur, S, Sonare, " Big Data in Cloude Environment" International Journal of Computer Sciences and Engineering, Vol 1, Issue 3, pp.15-17, 2013.
[9] Prakash Singh , "Efficient Deep Learning for Big Data: A Review", International Journal of Scientific Research in Computer Science and Engineering, Vol.4, Issue.6, pp.36-41, 2016.
[10] M. Bhanu Sridhar, A. Koushik, “A Study of Big Data Analytics in Clouds with a Security Perspective”, International Journal of Engineering Research and Technology, Vol 6, Issue 1, pp.5-9, January 2017.