计算机工程与应用2012，Vol.48Issue(8)：16-20,27,6.DOI:10.3778/j.issn.1002-8331.2012.08.005
基于轻量数据挖掘方法的数据库锁表优化
Database lock table optimization based on light weight data mining.Computer Engineering and Applications
摘要
Abstract
To make database systems always provide consistent high performance under various workload conditions, it is necessary to optimize database system settings. With the system becoming more complex and workloads becoming more fluctuating, it is very hard for DBA to quickly analyze performance data and optimize the system properly, and people resort to promising database system self-optimization techniques to solve the performance problem. A data mining based optimization scheme for lock table of database systems is presented. After training with performance data, a neural network becomes intelligent enough to predict system performance with newly provided configuration parameters. During system running, performance data are collected continuously for a rule engine, which choose the proper parameter of the lock table for adjusting, and the rule engine relies on the trained neural network to precisely provide the amount of adjustment. The selected parameter is adjusted according to the quantitative hints provided with the expectation that the system will perform better. The scheme is tested with TPC-C workload, the system' s throughput increases by about 16 percent.关键词
数据库自我优化/锁表/规则引擎/神经网络/预测器/数据挖掘Key words
database self-optimization/ lock table/ rule engine/ neural network/ predictor/ data mining分类
信息技术与安全科学引用本文复制引用
周晓云,覃雄派..基于轻量数据挖掘方法的数据库锁表优化[J].计算机工程与应用,2012,48(8):16-20,27,6.基金项目
国家自然科学基金(No.61070054,60873017,61170013). （No.61070054,60873017,61170013）
