3D Spatial Engine Intersection Query Processing
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Solution Overview
Problem
Conventional database systems lack effective support for query processing of three-dimensional surfaces and solids, particularly in identifying intersections, which is crucial for applications like geographic information systems, VLSI design, and robotics.
Innovation Solution
The implementation of a three-dimensional spatial engine within a relational database management system that uses a unique data type, such as SDO_GEOMETRY, to store three-dimensional geometry objects and employs a two-stage approach involving filtering and exact matching to determine intersections, utilizing spatial indices like R-Trees to efficiently process queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional database systems store three dimensional data types, then data storage capability is improved, but query processing support for surface and solid intersections deteriorates
Solution Approach 1:
The query processing is divided into two distinct stages: a filtering stage that uses bounding volume hierarchies to quickly eliminate non-intersecting geometries, and an exact matching stage that performs precise intersection tests only on candidate geometries. This segmentation allows the system to maintain comprehensive 3D data storage while providing efficient intersection query processing.
Solution Approach 2:
Bounding volume hierarchies serve as an intermediary structure between the stored 3D geometry data and the intersection query processing. These hierarchies provide a intermediate representation that enables efficient filtering before exact matching, thus resolving the contradiction between comprehensive data storage and efficient query processing.
2Measurement precision
If exact intersection detection is performed on all stored geometries, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
Before performing exact intersection detection, the system performs a preliminary filtering action using bounding volume hierarchies to identify only those geometry pairs that have potential for intersection. This preliminary action eliminates the majority of non-intersecting pairs, allowing exact detection to be performed only on a small subset of candidates, thus maintaining precision while improving productivity.
Solution Approach 2:
The system performs exact intersection testing partially - only on geometries that pass the bounding volume filtering stage - rather than on all stored geometries. This partial application of exact matching maintains measurement precision for relevant cases while dramatically improving overall query processing productivity.
Data Source
AI summary
Systems, methods, and other embodiments associated with determining whether geometries represented by geometry objects intersect are described. One example method recursively decomposes a higher order geometry (e.g., solid) into a set of lower order geometries (e.g., surfaces) and examines the lower order geometries, continuing the recursion until an intersection decision is reached. The example method includes accessing geometry objects and accessing a spatial index that stores MBVs associated with the geometry objects. The method includes extracting candidate pairs of intersecting features upon determining MBVs associated with the geometry objects intersect and providing the candidate features to a feature-feature logic. The method includes providing an intersection signal based on a features intersection signal provided by the feature-feature logic.