基于分区的部分最值查询优化算法

大规模数据库的建立和海量数据的不断涌现，需要从海量数据库和大量繁杂信息中提取有价值的知识，可以进一步提高网络安全信息的利用率. 另一方面，网络信息安全分析在面临海量数据时，其查询效率会大大降低. 分区技术使用户可以将大表分解为更小且更易管理的分区，从而解决海量数据带来的一些问题. 本文讨论了分区条件下部分最值的查询方法，介绍了一种用于提高这种查询效率的RBP-T （rank bisection partition tree）树型结构，并给出了相应的搜索算法. 通过实验证明，我们的方法对解决海量数据情况下的部分最值查询问题是有效的.

Optimization algorithm for partial-max/min queries based on partition

With the establishment of large database and the constantly emerging of mass data, people need to extract useful information, knowledge from huge database, and to improve the utilization rate of the information further. Network information security analysis is facing the problem of inefficient query with massive data. Partitioning technologies allow users to divide a big table into some smaller partitions can manage more easily, so it can solve some of the problems of mass of data. This paper discussed the partial-max/min query optimization for the partitioned tables. We introduce the RBP-T (rank bisection partition tree) structure to improve the efficiency of this class of query. The experimental results show that our method to solve the partial-max/min query in the massive data cases is effective.