Database Table Selection for Statistical Information Fixation
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Solution Overview
Problem
Existing database management systems face challenges in selecting appropriate tables for fixing statistical information, leading to unnecessary work costs and performance degradation due to outdated statistical information.
Innovation Solution
An information processing apparatus that selects tables for statistical information fixation based on update frequency and record count thresholds, determining tables with high update frequency and record counts as targets for fixing statistical information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all tables are used as statistical information fixation targets, then query processing performance is stabilized, but work cost of post-fixation table management increases
Solution Approach 1:
The invention segments the set of all tables into two categories: tables with high update frequency (where statistical information is fixed) and tables with low update frequency (where statistical information is not fixed). This segmentation allows the system to apply statistical information fixation selectively rather than universally, thereby stabilizing query processing performance for critical tables while reducing table management work cost by excluding unnecessary tables from fixation.
2Reliability
If statistical information is fixed for tables with high update frequency, then performance degradation is prevented, but table management complexity increases
Solution Approach 1:
The invention uses update frequency as a key parameter to determine whether to fix statistical information for a table. By monitoring and comparing the update frequency parameter against a threshold, the system dynamically decides which tables require statistical information fixation. This parameter-based approach prevents performance degradation for high-update tables while simplifying table management by automatically excluding low-update tables from fixation, thus reducing overall management complexity.
3Measurement precision
If statistical information is updated frequently, then data state accuracy is maintained, but processing overhead increases
Solution Approach 1:
The invention implements a dynamic approach where the update frequency of statistical information is adjusted based on the actual data change rate of each table. For tables with high update frequency, statistical information is updated more frequently to maintain data state accuracy. For tables with low update frequency, updates are reduced or eliminated to minimize processing overhead. This dynamic adjustment optimizes the balance between accuracy and overhead by adapting update intensity to actual data characteristics.
Data Source
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AI summary
A storage device stores the update frequency of statistical information acquired for each of a plurality of tables included in a database and the number of records in each of the plurality of tables. A processing unit determines, among the plurality of tables, a table whose statistical information has an update frequency that is greater than a first threshold and in which the number of records is greater than a second threshold, as a statistical information fixation target.