Loading...
Loading...

Go to the content (press return)

Mapreduce performance model for Hadoop 2.x

Author
Glushkova, D.; Jovanovic, P.; Abello, A.
Type of activity
Journal article
Journal
Information systems
Date of publication
2019-01
Volume
79
First page
32
Last page
43
DOI
https://doi.org/10.1016/j.is.2017.11.006 Open in new window
Project funding
(GENESIS) Generation and Evolution of Smart APIs
Repository
http://hdl.handle.net/2117/124328 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0306437917304659 Open in new window
Abstract
MapReduce is a popular programming model for distributed processing of large data sets. Apache Hadoop is one of the most common open-source implementations of such paradigm. Performance analysis of concurrent job executions has been recognized as a challenging problem, at the same time, that may provide reasonably accurate job response time estimation at significantly lower cost than experimental evaluation of real setups. In this paper, we tackle the challenge of defining MapReduce performance ...
Citation
Glushkova, D., Jovanovic, P., Abelló, A. Mapreduce performance model for Hadoop 2.x. "Information systems", Gener 2019, vol. 79, p. 32-43.
Keywords
Hadoop 2.x, MapReduce performance model
Group of research
inLab FIB
inSSIDE - integrated Software, Service, Information and Data Engineering

Participants