武大空间数据库CH1

Value of SDBMS – Users, Application Domains
Many important application domains have spatial data and queries. Some Examples follow: Army Field Commander: Has there been any significant enemy troop movement since last night? Insurance Risk Manager: Which homes are most likely to be affected in the next great flood on the Mississippi? Medical Doctor: Based on this patient's MRI, have we treated somebody with a similar condition ? Molecular Biologist:Is the topology of the amino acid biosynthesis gene in the genome found in any other sequence feature map in the database ? Astronomer:Find all blue galaxies within 2 arcmin of quasars.
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Overview – Why spatial database
Spatial databases provide structures for storage and analysis of spatial data Spatial data is comprised of objects in multi-dimensional space Storing spatial data in a standard database would require excessive amounts of space Queries to retrieve and analyze spatial data from a standard database would be long and cumbersome leaving a lot of room for error Spatial databases provide much more efficient storage, retrieval, and analysis of spatial data
Elements of Spatial Database
Prof Dr Qingyun Du
Semester I, 2013-2014
1.1 Overview – Why spatial database
A common technology for some Applications:
GIS (geographic/geo-referenced data) CAD/CAM VLSI design (geometric data) modeling complex phenomena (spatial data)on
A database system
A group of inter-related files under the control of a database management system (DBMS)
A spatial database system
Spatial Queries:
List the names of all bookstores within ten miles of Santa Barbara List all customers who live in Tennessee and its adjoining states
Structure in space: e.g., POINT, LINE, REGION Relationships among them: (l intersects r)
Supports SDT in its implementation providing at least
spatial indexing (retrieving objects in particular area without scanning the whole space) efficient algorithms for spatial joins (not simply filtering the cartesian product)
1970s: Relational data model, relational DBMS implementation
1980s: RDBMS, advanced data models (extended-relational, OO, deductive, etc.) and application-oriented DBMS (spatial, scientific, engineering, etc.) 1990s—2000s: Data mining and data warehousing, multimedia databases, and Web databases
Non-spatial queries:
List the names of all bookstore with more than ten thousand titles. List the names of ten customers, in terms of sales, in the year 2001
Time series databases
A database that contains data for each point in time. Stock market, trajectories, etc
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1.3 What is a SDBMS ?
A SDBMS is a software module that can work with an underlying DBMS supports spatial data models, spatial abstract data types (ADTs) and a query language from which these ADTs are callable supports spatial indexing, efficient algorithms for processing spatial operations, and domain specific rules for query optimization Example: Oracle Spatial data cartridge, ESRI SDE can work with Oracle DBMS Has spatial data types (e.g. polygon), operations (e.g. overlap) callable from SQL query language Has spatial indices, e.g. R-trees
Spatio-temporal Database
-Moving objects, changing regions, etc
Multimedia and medical databases
A multimedia system can store and retrieve objects/documents with text, voice, images, video clips, etc
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Various Databases
Spatial Database Systems
GIS, CAD/CAM, AM/FM, Manages points, lines and regions
Temporal Database Systems
Billing, medical records
Exercise: List two ways you have used spatial data. Which software did you use to manipulate spatial data?
1.2 Basics of Database
1960s: Data collection, database creation, IMS and network DBMS
Core Functionality Interface to application
Taxonomy Data types Operations Query language Algorithms Access methods
Interface to DBMS
application
Fig 1.2
DBMS
All need to manage large collections of relatively simple spatial objects Spatial DB vs. Image/pictorial DB
Spatial DB contains objects “ in ” the space Image DB contains representations “ of ” a space (images, pictures,… : raster data)
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Value of SDBMS
Traditional (non-spatial) database management systems provide: Persistence across failures Allows concurrent access to data Scalability to search queries on very large datasets which do not fit inside main memories of computers Efficient for non-spatial queries, but not for spatial queries