Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering

Analysis of the Big Data based on MapReduce

Authors
Zi-de Tian
Corresponding Author
Zi-de Tian
Available Online April 2015.
DOI
10.2991/amcce-15.2015.41How to use a DOI?
Keywords
Big Data; MapReduce;SQL server
Abstract

Big Data are becoming a popular technology focus both in science and in industry and motivate technology shift to data centric architecture and operational models. Big Data is bringing a positive change in the decision making process of various business organizations.In this paper, MapReduce big data analysis methods, and with SQL server performance comparison, the experimental results show that, compared to SQL server, MapReduce method loads a small time, as the data set increases, the performance MapReduce approach is better. So MapReduce method has better scalability and speedup for large data processing applications.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
Series
Advances in Intelligent Systems Research
Publication Date
April 2015
ISBN
10.2991/amcce-15.2015.41
ISSN
1951-6851
DOI
10.2991/amcce-15.2015.41How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zi-de Tian
PY  - 2015/04
DA  - 2015/04
TI  - Analysis of the Big Data based on MapReduce
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 226
EP  - 230
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.41
DO  - 10.2991/amcce-15.2015.41
ID  - Tian2015/04
ER  -