A method and apparatus for designing a database range filter based on a binary decision tree
By designing a database range filter based on a binary decision tree, the growth of nodes is determined by data density and skewness. Combined with access frequency pruning and compression coding, the performance problem of database range filters under uneven data conditions is solved, and efficient data processing and storage optimization are achieved.
CN117668000BActive Publication Date: 2026-07-24HUAZHONG UNIV OF SCI & TECH
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUAZHONG UNIV OF SCI & TECH
- Filing Date
- 2023-12-26
- Publication Date
- 2026-07-24
AI Technical Summary
Technical Problem
Existing database range filters perform poorly when dealing with uneven data, have a high false positive rate, and consume a large amount of space.
Method used
The database range filter design method based on binary decision trees constructs an initial binary decision tree offline, determines node growth based on data density and skewness, prunes based on access frequency, and performs compression encoding.
Benefits of technology
It improves query performance, reduces false positive rate, and reduces storage space usage in the case of uneven data.
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Abstract
The application discloses a database range filter design method and device based on a binary decision tree, and belongs to the technical field of database query. The method considers that data sets to be processed in a database are not uniform in most application scenarios, and an initial binary decision tree is constructed offline according to the distribution characteristics of the data sets. Each node of the initial binary decision tree is a range, and a root node represents a range interval of keys in the entire data set. Simulated online query is performed by using the initial binary decision tree, and pruning is performed according to the access frequencies of leaf nodes. Finally, compression coding is performed to obtain a database range filter. In the process of constructing the binary decision tree, the binary tree is grown according to data density and skew degree, so that the problem of high false positive rate in the case of uneven data distribution can be solved. The pruning operation of the binary tree according to the access frequency can reduce the space occupation. Finally, the database range filter can efficiently process data in the case of uneven data.
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