基于R树的方向关系查询处理

方向关系描述了对象间的空间顺序关系.近年来,方向关系查询处理逐渐受到空间数据挖掘和地理信息系统等空间数据库应用领域研究者的关注.方向关系查询处理需要执行方向连接操作,目前有关空间连接的研究主要集中在拓扑关系和距离关系方面,而较少考虑方向关系.研究了基于R树的方向关系查询处理方法,定义了四元组模型表示对象MBR间的方向关系,提出了基于R树的处理方向关系查询过滤(filter)步骤的方法,并将提炼(refinement)步骤细化为3种不同的操作.所提出的方法能够高效处理任意对象间的方向关系查询.考虑到空间数据挖掘中方向关系查询通常是在满足一定距离约束条件的对象之间进行,还提出了一种同时利用方向和距离约束限制R树搜索空间的查询处理算法.实验证明,与不利用R树的方向关系查询处理方法相比,所提出的方法在I/O开销和CPU开销两方面都具有很高的性能.

Direction Relation Query Processing Using R-Trees

Direction relations deal with order in space. Recently, direction relation query processing has gradually gained attention in geospatial databases applications, such as Spatial Data Mining (SDM) and GIS (geographic information system). The processing of direction relation queries needs spatial join operations. Until now, the research work on processing of spatial joins has primarily focused on topological and distance relations. There is little work on processing joins with direction predicates. This paper presents an efficient method for processing direction relation queries using R-trees. The quad-tuples model is defined to represent direction relations between MBRs (minimum bounding rectangles) of spatial objects. An algorithm of processing the filter step using R-trees is given and the refinement step is further decomposed into three different operations. The method presented can efficiently process direction relation queries between objects of any data types in a 2D space. Using both direction and distance constraints restricting the search space when traversing R-trees, this paper also presents an algorithm of direction relation query processing in SDM. Performance evaluation of the proposed method is conducted using real world datasets and the experiment results show that it performs well with respect to both I/O- and CPU-time.