Graph Database Search Using Physical Location Pointers
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Solution Overview
Problem
Conventional graph database search algorithms, such as those using B-tree indices and join algorithms, suffer from decreased search efficiency as data size increases, leading to high disk read costs and inefficient storage usage.
Innovation Solution
A data searching method that utilizes a storage unit to store graph data with physical location information for vertices and edges, allowing for efficient searching by using a pointer-based system that updates location information only when necessary, and includes a global index to optimize storage location updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If B-tree index is used for graph search, then data can be organized in structured manner, but search efficiency decreases as data size increases due to increased disk read costs
Solution Approach 1:
The patent creates a copy of the graph data in memory with physical location information (pointers) that directly reference the storage locations of vertices and edges. This in-memory copy allows rapid access without repeated disk I/O operations, resolving the contradiction between structured organization and search efficiency.
Solution Approach 2:
The patent pre-computes and stores physical location information (pointers) for all vertices and edges during data loading. This preliminary action enables direct access to graph elements during search operations, eliminating the need for sequential disk reads and significantly improving search efficiency while maintaining data integrity.
2Ease of operation
If conventional graph search algorithms are used, then search operations can be performed, but storage space is not efficiently utilized due to redundant data storage
Solution Approach 1:
The patent merges the graph data storage with physical location information into a unified structure. By combining vertex/edge data with their storage location pointers in a single in-memory representation, the system eliminates redundant storage while maintaining full search operation capability.
3Reliability
If data is updated in conventional databases, then data consistency is maintained, but update costs increase due to frequent physical location updates
Solution Approach 1:
The patent implements a self-updating pointer system where the global index automatically tracks and updates physical location information when data is added, deleted, or modified. This self-service mechanism maintains data consistency without requiring manual intervention or expensive update operations, as the system automatically manages pointer validity.
Solution Approach 2:
The global index provides continuous feedback about the current storage locations of graph elements. When data is updated, the system receives feedback about location changes and automatically adjusts pointers accordingly, maintaining data consistency while minimizing update costs through automated location tracking.
Data Source
AI summary
The present invention provides a data searching method of database, apparatus and computer program for the same. The data searching apparatus of a database includes: a storage unit configured to store graph data; and a controller configured to store physical location information in which vertex and edge information included in the graph data is stored in the storage unit, and perform a search for the vertex and the edge based on the physical location information. Thereby, it is possible to efficiently search the data by improving a search speed of a graph, minimize the update of the information even when a storage location of the data is changed, and facilitate query by the graph data regardless of types of the database and a storage structure, and efficiently use a storage space.