There Goes the Neighborhood: Relational Algebra for Spatial Data Search

TL;DR

This paper presents relational algebra techniques for efficient spatial data search in databases, using hierarchical tessellations, bucketing, and DNF constraints, compatible with standard SQL systems.

Contribution

Introduces novel relational algebra methods for spatial search that integrate with existing SQL systems without requiring new spatial access methods.

Findings

Efficient point-in-region query algorithms developed.

Zone and multi-scale zone-pyramid schemes significantly improve speed.

Approaches are successfully used in real-world astronomical databases.

Abstract

We explored ways of doing spatial search within a relational database: (1) hierarchical triangular mesh (a tessellation of the sphere), (2) a zoned bucketing system, and (3) representing areas as disjunctive-normal form constraints. Each of these approaches has merits. They all allow efficient point-in-region queries. A relational representation for regions allows Boolean operations among them and allows quick tests for point-in-region, regions-containing-point, and region-overlap. The speed of these algorithms is much improved by a zone and multi-scale zone-pyramid scheme. The approach has the virtue that the zone mechanism works well on B-Trees native to all SQL systems and integrates naturally with current query optimizers - rather than requiring a new spatial access method and concomitant query optimizer extensions. Over the last 5 years, we have used these techniques extensively in our work on SkyServer.sdss.org, and SkyQuery.net.