Spatial Database Types of Spatial Data
Ø Point Data
Points in a multidimensional space
E.g., Raster data such as satellite imagery, where each pixel stores a measured value
E.g., Feature vectors extracted from text
Ø Region Data
Objects have spatial extent with location and boundary.
DB typically uses geometric approximations constructed using line segments, polygons, etc., called vector data.
Types of Spatial Queries
Ø Spatial Range Queries
Find all cities within 50 miles of Madison Query has associated region (location, boundary)
Answer includes ovelapping or contained data regions
Ø Nearest-Neighbor Queries
Find the 10 cities nearest to Madison Results must be ordered by proximity
Ø Spatial Join Queries
Find all cities near a lake
Expensive, join condition involves regions and proximity
Applications of Spatial Data
Ø Geographic Information Systems (GIS)
E.g., ESRI‘s ArcInfo; OpenGIS Consortium
All classes of spatial queries and data are common
Ø Computer-Aided Design/Manufacturing
Store spatial objects such as surface of airplane fuselage Range queries and spatial join queries are common
Ø Multimedia Databases
Images, video, text, etc. stored and retrieved by content First converted to feature vector form; high dimensionality Nearest-neighbor queries are the most common
B+ trees are fundamentally single-dimensional indexes.
When we create a composite search key B+ tree, e.g., an index on <age, sal>, we effectively linearize the 2-dimensional space since we sort entries first by age and then by sal.
Consider entries: <11, 80>, <12, 10> <12, 20>, <13, 75>
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