Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science

Memory Database Application in the Processing of Huge Amounts of Data

Authors
Daqiang Xiao, Qi Qian, Jianhua Yang, Guang Chen
Corresponding Author
Daqiang Xiao
Available Online June 2016.
DOI
10.2991/icamcs-16.2016.110How to use a DOI?
Keywords
mass data process, memory database
Abstract

In large electric power data acquisition system, huge meter, data collector, concentrator real-time message processing and timely rapid response to database system efficiently, presents a high technical requirements. At present, single disk database is very difficult to meet the demand of high efficiency and low delay. In view of the requirement of massive data acquisition system in real time processing of massive data, a new data processing framework based on massive data in memory database is proposed. We comprehensive compare the single disk database with the improvement method, and illustrate the advantage of new framework through the experiment.

Copyright
© 2016, 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/).

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Volume Title
Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-189-6
ISSN
2352-5401
DOI
10.2991/icamcs-16.2016.110How to use a DOI?
Copyright
© 2016, 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  - Daqiang Xiao
AU  - Qi Qian
AU  - Jianhua Yang
AU  - Guang Chen
PY  - 2016/06
DA  - 2016/06
TI  - Memory Database Application in the Processing of Huge Amounts of Data
BT  - Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
PB  - Atlantis Press
SP  - 534
EP  - 540
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamcs-16.2016.110
DO  - 10.2991/icamcs-16.2016.110
ID  - Xiao2016/06
ER  -