Comparative Study of Apache Hadoop vs Spark

Authors(1) :-Varsha KR

The paper focuses on analyzing the differences and comparative study of two most talked about frameworks Hadoop and Spark - both of which have increasing potential for the big data management. The analysis is carried out regarding components, design, data storage, recovery from failure among other features. Comparative analysis is made by executing certain algorithms on two platforms and comparing the execution time. Similarly, suitability of frameworks for different scenarios is discussed.

Authors and Affiliations

Varsha KR
Department of Computer Science and Engineering, RV College of Engineering Bangalore, Karnataka, India

Hadoop, Spark, Map-Reduce, HDFS

  1. Verma Ankush, Mansuri Ashik Hussain, Jain Neelesh, "Big Data Management Processing with Hadoop MapReduce and Spark Technology: A Comparison", 2016 Symposium on Colossal Data Analysis and Networking (CDAN).
  2. S Humbetov, "Data-intensive computing with map-reduce and hadoop", International Conference on Applcation of Information and Communication Technologies, pp. 1-5, 17-190ct. 2012.
  3. Polato Ivanilton, R Reginaldo, Goldman Alfredo, Kon Fabio, "A comprehensive view of Hadoop research-A systematic literature review", Journal of Network and Computer Applications, vol. 46, pp. 1-25, November 2014.
  4. online] Available: http://spark.apache.hadoop.org/.
  5. online] Available: http://spark.apache.org/docs/latest/mllib-Iinear-methods.html.

Publication Details

Published in : Volume 3 | Issue 7 | September-October 2018
Date of Publication : 2018-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 390-394
Manuscript Number : CSEIT183782
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Varsha KR, "Comparative Study of Apache Hadoop vs Spark", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 7, pp.390-394, September-October-2018.
Journal URL : http://ijsrcseit.com/CSEIT183782

Follow Us

Contact Us