Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Portable High-Performance Indexing for Vector Product Format Spatial Databases

Portable High-Performance Indexing for Vector Product Format Spatial Databases

Colak, Engin

Paperback

General Education

ISBN10: 1288369190
ISBN13: 9781288369195
Publisher: Biblioscholar
Published: Nov 29 2012
Pages: 126
Weight: 0.53
Height: 0.27 Width: 7.44 Depth: 9.69
Language: English
Geo-spatial databases have an overall performance problem because of their complexity and large size. For this reason, many researchers seek new ways to improve the overall performance of geo-spatial databases. Typically, these research efforts are focused on complex indexing structures and query processing methods to capture the relationships between the individual features of fully-functional geo-spatial databases. Visualization applications, such as combat simulators and mission planning tools, suffer from the general performance problems associated with geo-spatial databases. This research focuses on building a high-performance geo-spatial database for visualization applications. The main approach is to simplify the complex data model and to index it with high-performance indexing structures. Complex features are reduced to simple primitives, then indexed using a combination of a disk-based array and B+-Trees. Test results show that there is a significant performance improvement gained by the new data model and indexing schema for low to medium zoom levels. For high zoom levels, there is a performance drop due to the indexing schema's overhead.

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