Compressed Spatial Hierarchical Bitmap (cSHB) Indexes for Efficiently Processing Spatial Range Query Workloads ∗ Parth Nagarkar K. Selçuk Candan Aneesha Bhat Arizona State University Arizona State University Arizona State University Tempe, AZ 85287-8809, USA Tempe, AZ 85287-8809, USA Tempe, AZ 85287-8809, USA
[email protected] [email protected] [email protected] ABSTRACT terms of their coordinates in 2D space. Queries in this 2D In most spatial data management applications, objects are space are then processed using multidimensional/spatial in- represented in terms of their coordinates in a 2-dimensional dex structures that help quick access to the data [28]. space and search queries in this space are processed using spatial index structures. On the other hand, bitmap-based 1.1 Spatial Data Structures indexing, especially thanks to the compression opportuni- The key principle behind most indexing mechanisms is to ties bitmaps provide, has been shown to be highly effective ensure that data objects closer to each other in the data for query processing workloads including selection and ag- space are also closer to each other on the storage medium. gregation operations. In this paper, we show that bitmap- In the case of 1D data, this task is relatively easy as the based indexing can also be highly effective for managing total order implicit in the 1D space helps sorting the ob- spatial data sets. More specifically, we propose a novel com- jects so that they can be stored in a way that satisfies the pressed spatial hierarchical bitmap (cSHB) index structure above principle. When the space in which the objects are to support spatial range queries.