Optimization for massive data query method in database
- 10.2991/amcce-15.2015.272How to use a DOI?
- Database; inquiry; correlation clustering;
The massive data query methods in database is studied to improve accuracy of query. In the process of data querying in the database, once the data volume is overflow and thetype of data becomes complex, the query requires a lot of restrictions, resulting in time-consuming and low query accuracy rate for data query. To this end, optimization for massive data query method in database based oncorrelation clustering algorithm is proposed. Correlation clustering is processed to all the data in the database to obtain the correlation between different data. Query for the specified categories of data to achieve query optimization of massive data in database. Experimental results show that the proposed method for mass data query in database can improve the accuracy and efficiency of the query, and reduce time for querying.
- © 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 - Xiao dong Xie AU - Jinping Zou AU - Xi Huang PY - 2015/04 DA - 2015/04 TI - Optimization for massive data query method in database BT - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/amcce-15.2015.272 DO - 10.2991/amcce-15.2015.272 ID - Xie2015/04 ER -