分布式空间数据库中有效数据频繁项实时检测研究

当前数据频繁项检测方法往往具有数据存储结构复杂、维护困难和复杂度高的弊端;针对这种情况,提出一种新的分布式空间数据库中有效数据频繁项实时检测方法。对事物数据进行分配,建立全局VFP树,将最近窗口中全部项集添加至全局VFP树,通过临时表对项集信息进行保存,利用遍历全局树实时检测有效数据的频繁项。通过滑动窗口的初始化阶段与滑动阶段对最旧一批项集临时表进行处理,实现维护。实验结果表明,所提方法能够有效实现分布式空间数据库中有效数据频繁项的实时检测;和其他方法相比,复杂度低、检测可靠性高。

Research on Real Time Detection of Active Data Frequent Items in Distributed Spatial Database

Current data frequent item detection methods often have the drawbacks of complex data storage structure, difficult maintenance and high complexity. In view of this situation, a new method for real-time detection of frequent data of valid data in distributed spatial database is proposed. The object data is allocated, a global VFP tree is established, all the itemsets in the most recent window are added to the global VFP tree, the itemset information is saved through a temporary table, and the frequent items of valid data are detected by traversing the global tree in real time. Through the sliding window initialization phase and sliding phase of the oldest batch of items temporary table processing, maintenance. The experimental results show that the proposed method can effectively detect real-time frequent items of valid data in distributed spatial database, which has lower complexity and higher reliability than other methods.