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/).
Cite this article
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 -