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Indexing temporal data using existing B~+ -trees

机译：使用现有的B〜+树索引时间数据

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摘要

Research in temporal databases has largely focused on extensions of existing data models for the proper handling of temporal information. One approach is to store temporal data on existing DBMS and build some new indexes to provide support for the efficient retrieval of temporal data. This paper describes mapping strategies to linearize the data such that existing B~+ -trees can be used directly. With such an implementation, a temporal relation is mapped to points in a multi-dimensional space, with each time interval being translated to a two-dimensional coordinate, and a temporal selection operation is constructed as a spatial search operation. The proposed approach has two advantages. First, mapping a temporal relation to a multi-dimensional space provides a uniform framework for dealing with temporal queries involving transaction and valid time, as well as other non-temporal attributes. Second, linearization of the multi-dimensional search space allows classical indexing methods (such as the B~+ -tree) to be used; this means that index support for temporal selection can be accomplished without modification to the underlying storage components of the DBMS. Both analytical and simulation study show that the proposed indexing scheme is more efficient than the time index in both its disk utilization and access time.
机译：时态数据库的研究主要集中在现有数据模型的扩展上，以正确处理时态信息。一种方法是将时态数据存储在现有的DBMS上，并建立一些新索引以为时态数据的有效检索提供支持。本文描述了将数据线性化的映射策略，以便可以直接使用现有的B〜+树。通过这种实施方式，时间关系被映射到多维空间中的点，每个时间间隔被转换为二维坐标，并且时间选择操作被构造为空间搜索操作。所提出的方法具有两个优点。首先，将时间关系映射到多维空间提供了一个统一的框架，用于处理涉及事务和有效时间以及其他非时间属性的时间查询。其次，多维搜索空间的线性化允许使用经典的索引方法（例如B〜+ -tree）；这意味着无需修改DBMS的基础存储组件就可以实现对时间选择的索引支持。分析和仿真研究均表明，所提出的索引方案在磁盘利用率和访问时间方面都比时间索引更有效。

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