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Chapter: Database Management Systems - Trends In Database Technology

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Spatial Database Types of Spatial Data

Points in a multidimensional space E.g., Raster data such as satellite imagery, where each pixel stores a measured value

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

Geospatial information

 

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

 

Single-Dimensional Indexes

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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