摘要
随着高校之间数据库共享技术的出现,对于多校共享平台的身份认证技术要求也越来越高,随着高校数据联盟的出现,形成了一个超大数据库,身份认证快速性能要求的不断增加,人员信息的属性越来越多,形成了海量数据环境。为了保证认证的快速性,提出一种基于多目标查询优化的多校共享平台中海量数据快速查询技术。通过设定合理的空间索引,设计最优目标适应度函数,运用遗传算法优化查询过程,计算最优查询解空间,保证认证的快速性。实验证明,该方法能够较好地满足实时性和准确性的要求,对海量数据有着较好的查询效果。
With the database sharing between the emergence of the technology, the school of sharing platform of identity authentication technology requirements also more and more high, with the emergence of the data alliance, formed a large database, identity authentication fast performance requirements＇s unceasing increase, more and more researchers＇ information attributes. Formation of the massive data environment. In order to ensure the authentication of rapidity. This paper puts forward a multi-objective query optimization based on the sharing platform of the mass data fast query technique. Through the set reasonable space index, and design the optimal target fitness function, using genetic algorithm to optimize the query process, calculating optimal inquires the solution space, to ensure that the authentication of rapidity. The experiment shows that this method can better meet the requirement of real-time and accuracy of mass data has a good effect of inquires.
出处
《科技通报》
北大核心
2013年第12期82-84,共3页
Bulletin of Science and Technology
关键词
多校共享平台
身份认证
海量数据查询
many school sharing platform
identity authentication
mass data inquires
