Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

The Research of Relational Database Query Processing Based on Cloud Platform

Authors
Wei GU
Corresponding Author
Wei GU
Available Online July 2017.
DOI
10.2991/eia-17.2017.21How to use a DOI?
Keywords
cloud platform; query processing; relational database
Abstract

Big Data is now increasing rapidly, It need for more servers to handle large amounts of data, resulting in a number of different ways to improve the operation of data processing time, Cloud data processing platform is the most popular way of operation, Non-structured data using a cloud environment, in the form of key-value store, but because many enterprises use relational database structure to store data currently, and therefore cannot directly migrate from these databases to the cloud platform. In this paper, based on the cloud platform relational database, relational database with the new data separation and polymerization techniques, query processing optimization algorithms using MapReduce architecture to build a relational database query processing mechanism under the cloud platform.

Copyright
© 2017, 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 2017 International Conference on Electronic Industry and Automation (EIA 2017)
Series
Advances in Intelligent Systems Research
Publication Date
July 2017
ISBN
10.2991/eia-17.2017.21
ISSN
1951-6851
DOI
10.2991/eia-17.2017.21How to use a DOI?
Copyright
© 2017, 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  - Wei GU
PY  - 2017/07
DA  - 2017/07
TI  - The Research of Relational Database Query Processing Based on Cloud Platform
BT  - Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
PB  - Atlantis Press
SP  - 95
EP  - 98
SN  - 1951-6851
UR  - https://doi.org/10.2991/eia-17.2017.21
DO  - 10.2991/eia-17.2017.21
ID  - GU2017/07
ER  -