Three-Level Storage Table for Database Lookup Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current database management methods based on lookup tables are inefficient, particularly when dealing with large datasets, as they struggle to handle complex operations effectively, leading to prolonged query times and reduced performance.
Innovation Solution
A database management method and apparatus that utilize a three-level storage table structure, comprising a page information table, a column information table, and a data table, to efficiently manage data operations such as insertion, update, and query by adjusting the table according to specific operation requests, thereby optimizing data storage and retrieval processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional lookup table methods are used for database management, then the system structure remains simple, but the query speed becomes slow and efficiency deteriorates when dealing with large datasets
Solution Approach 1:
The patent divides the traditional single-level lookup table into a three-level hierarchical structure consisting of a page information table, a column information table, and a data table. This segmentation allows the system to process and search data in smaller, more manageable units, significantly improving query speed when dealing with large datasets while maintaining systematic organization.
Solution Approach 2:
The patent transitions from a conventional flat lookup table structure to a multi-dimensional hierarchical structure with three distinct levels. This dimensional change enables more efficient data organization and retrieval by introducing intermediate indexing layers (page and column levels) between the top-level directory and the actual data storage, thereby reducing search time and improving query performance.
2Productivity
If complex data operations are performed on large datasets, then data management capability is tested, but traditional lookup table methods fail to handle operations effectively leading to reduced performance
Solution Approach 1:
By segmenting the data management system into three functional levels (page information table for organizational structure, column information table for data field management, and data table for actual storage), the patent enables more reliable handling of complex operations such as insertion, deletion, and updating. Each level can be independently optimized and managed, improving overall system reliability for large-scale data operations.
Solution Approach 2:
The patent introduces intermediate tables (page information table and column information table) that act as mediators between the user/request and the actual data storage. These intermediary structures buffer and organize data access patterns, reducing the direct burden on the underlying data table and improving both productivity and reliability when performing complex data management operations on large datasets.
3Quantity of substance
If the database storage capacity is increased to 15 TB, then the data storage capability is improved, but the query time increases to 33 hours for a full search
Solution Approach 1:
The patent applies segmentation by organizing 15 TB of data into a three-level hierarchical structure where the page information table divides data into manageable page units, the column information table organizes data by fields, and the data table stores actual records. This segmentation reduces the search space at each level, transforming a single 33-hour full search into multiple smaller, parallelizable search operations across different levels.
Solution Approach 2:
By transitioning to a multi-dimensional hierarchical structure, the patent creates intermediate indexing layers that reduce the effective search dimension. Instead of searching through all 15 TB linearly, the system performs hierarchical navigation through page and column levels first, dramatically reducing the time required to locate and retrieve data from large storage capacities.
Data Source
AI summary
Provided are a database management method and apparatus based on a lookup table. The method comprises: acquiring a data management operation request; retrieving a three-level storage table in response to the data management operation request; and adjusting the three-level storage table according to an operation requested by the data management operation request, so as to obtain the adjusted three-level storage table, wherein the three-level storage table includes: a page information table of data; the column information table of data; and the data table for recording information of a piece of data by means of a row of data. By means of the method, the problem of the low efficiency of existing database management based on a lookup table is solved, and the aim of simply and efficiently carrying out a lookup table operation is thus achieved.