A Database Optimization Strategy for Massive Data Based Information System

DOI

10.2991/mmsta-19.2019.47How to use a DOI?

Keywords

database optimization; massive data optimization; database structure optimization; data division

Abstract

With the rapid arrival of the information explosion era, the amount of data stored in a single table of an enterprise information management system is getting more and more common. Therefore, efficiency optimization of SQL based on the massive data is an essential task to break the bottleneck in current enterprise information management systems. This paper proposes single table optimization methods for massive database. These methods including: physical optimization, index optimization and query statement optimization. Each optimization method is integrated into the database design process, and a set of optimization programs for the massive database design process is proposed. In the test environment, the size of the databases file is over 200G and single table records is over 80 million, the proposed optimization methods break the bottleneck of query efficiency and improve the database query efficiency of tens of times.

Copyright

© 2019, 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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TY  - CONF
AU  - Qianglai Xie
AU  - Wei Yang
AU  - Leiyue Yao
PY  - 2019/12
DA  - 2019/12
TI  - A Database Optimization Strategy for Massive Data Based Information System
BT  - Proceedings of the 2019 2nd International Conference on Mathematics, Modeling and Simulation Technologies and Applications (MMSTA 2019)
PB  - Atlantis Press
SP  - 221
EP  - 225
SN  - 2352-538X
UR  - https://doi.org/10.2991/mmsta-19.2019.47
DO  - 10.2991/mmsta-19.2019.47
ID  - Xie2019/12
ER  -