Database Query Shortest Path Graph Traversal
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Solution Overview
Problem
As the number of data tables in a database increases, linking multiple data tables to query distributed fields becomes time-consuming and resource-intensive, hindering efficient data retrieval.
Innovation Solution
A system and method that generate a directed graph based on multiple data tables, determine target data tables, and traverse this graph to find the shortest paths between reference and target data tables, allowing for efficient querying without linking all data tables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple data tables are linked to query distributed fields, then query completeness is improved, but processing time and resource consumption increase
Solution Approach 1:
The patent segments the data table linking process by identifying and processing only the necessary target data tables rather than linking all tables. It divides the database into relevant and irrelevant components based on the query fields, processing only the segmented relevant portion to reduce time while maintaining completeness.
Solution Approach 2:
The patent extracts and identifies target data tables that contain the queried fields from the entire database. By taking out only the necessary tables through field-based identification and graph traversal, it eliminates unnecessary linking operations while preserving query completeness.
2Measurement precision
If all data tables are linked to ensure complete data retrieval, then query accuracy is improved, but system resource consumption increases
Solution Approach 1:
The system segments the database into target data tables containing queried fields and non-target tables. By processing only the segmented target tables identified through graph traversal, it maintains query accuracy while reducing resource consumption to the minimum necessary level.
Solution Approach 2:
The patent applies partial action by linking only the necessary target data tables rather than all tables in the database. This partial linking approach is sufficient to achieve complete and accurate query results while significantly reducing system resource consumption.
3Quantity of substance
If the number of data tables increases, then database capacity is improved, but query efficiency deteriorates
Solution Approach 1:
The patent extracts target data tables from the large database through field-based identification and graph traversal. This extraction mechanism allows the system to handle large database capacity while maintaining query efficiency by processing only the extracted relevant tables rather than the entire database.
Solution Approach 2:
The patent introduces a directed graph as an intermediary structure to represent relationships between data tables. This intermediary enables efficient navigation and identification of target tables in large databases, maintaining query efficiency even as database capacity increases.
Data Source
AI summary
The present disclosure provides systems and methods for providing database query service to a user. The method may comprise: obtaining, a query request to query a database, wherein the database includes a plurality of data tables; determining one or more target data tables among the plurality of data tables based on the service request; generating a directed graph based on the plurality of data tables, wherein the directed graph includes one or more segment, each of which links two data tables; determining a reference data table among the one or more target data tables; for each of the one or more target data tables, traversing the directed graph to determine a target path with the shortest distance between the reference data table and a target data table; and, querying the database based on one or more target paths with the shortest paths.