CD column diagram-based method for estimating spatial query selectivity

A spatial query and histogram technology, applied in computing, special data processing applications, instruments, etc., can solve the problem of uneven distribution of spatial data in large continuous geographical areas, achieve high accuracy, improve accuracy, and ensure the effect of estimation accuracy
CN101826076BInactive Publication Date: 2012-11-07INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS +2
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
Publication Date
2012-11-07
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention relates to a CD column diagram-based method for estimating spatial query selectivity and belongs to the technical field of spatial data query and processing. The method comprises the following steps of: establishing four CD column diagrams for vector data to be queried; and calculating estimated values of a top right corner point, a top left corner point, a bottom right corner pointand a bottom left corner point on a query region in LL, LR, UL and UR column diagrams by using a basic value correcting module for a rectangular spatial query region specified by a user and recordingthe estimated values as S1, S2, S3 and S4 respectively, wherein a selectivity estimated value of a spatial object in the query region is S1-S2-S3+S4. The query selectivity value in any spatial regioncan be estimated without adding additional assumed condition and storage capacity; and the method is generally suitable for a plurality of vector data types, such as scattered distribution, geographic area continuous distribution and the like.
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Description

technical field

[0001] The invention belongs to the technical field of spatial data query and processing, and relates to a CD histogram-based spatial query selectivity estimation method. Background technique

[0002] In a database, query processing can be divided into four stages: query analysis, query inspection, query optimization, and query execution. Each query has many execution strategies and operation algorithms to choose from. Query optimization is to choose an efficient query processing strategy. Query cost estimation (model) is a commonly used query optimization method.

[0003] At present, the research on query cost estimation in relational databases is relatively mature; while the research on spatial query cost estimation methods in spatial databases is still in the research stage. The cost of a spatial query depends on two factors. The first factor is the CPU cost and I / O cost of the specific query processing algorithm used; the second factor is the I / O cost ...

Claims

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