Interactive Database Query Trees for Contextual Investigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current database query investigation methods lack the ability to manage queries and result sets in context and hierarchy, leading to inefficient and error-prone non-linear investigations, with no effective way to navigate between historical queries and their results.
Innovation Solution
A tree graph is used to visually represent and persist all executed queries and their results, allowing investigators to navigate and modify queries while maintaining the query history and relationships, enabling efficient navigation and documentation of investigation paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If query history is stored linearly in timeline order, then query execution history is maintained, but query hierarchy and contextual relationships are lost
Solution Approach 1:
The patent segments query history into a hierarchical tree structure where each query is a node and parent-child relationships represent refinement steps. This segmentation allows the system to maintain both linear execution history and hierarchical context, resolving the contradiction by organizing information in multiple dimensions simultaneously.
Solution Approach 2:
The patent implements nesting by allowing queries to have parent-child relationships where child queries are refinements of parent queries. This nested structure enables the system to preserve contextual relationships while maintaining execution history, as each query contains references to its parent query within the same data structure.
2Adaptability or versatility
If investigators manually copy queries to external documents, then query modification flexibility is improved, but time consumption and error risk increase
Solution Approach 1:
The patent implements self-service by enabling investigators to directly modify queries within the tree structure without copying to external documents. The system automatically maintains the hierarchical relationships and execution history, allowing flexible query development while eliminating manual copying operations and reducing time consumption.
3Loss of information
If full query history is stored in SIEM systems, then query timeline is maintained, but query results are not preserved and re-execution is required
Solution Approach 1:
The patent merges query history storage with result set preservation by storing both the query definition and its execution results together in the tree structure. This combination allows the system to maintain execution context and avoid re-execution, significantly improving investigation efficiency while preserving complete query execution information.
4Ease of operation
If queries are executed sequentially without history tracking, then system simplicity is maintained, but inability to navigate between queries prevents efficient investigation
Solution Approach 1:
The patent applies preliminary action by automatically capturing and storing query execution context, result sets, and hierarchical relationships as queries are executed. This preliminary storage of navigation information enables fast retrieval and navigation between queries without adding complexity to the execution process, as the infrastructure is built beforehand.
Data Source
AI summary
A computer-implemented method is presented for querying a database system. The technical problem is to find a method for querying a database system that allows the user to automatically keep track of both queries and results. The problem is solved by a computer-implemented method for querying a database system, comprising: presenting a tree graph on a display of a computer system, where the tree graph represents related queries on the database system; receiving a selection of a given node in the tree graph displayed on the display from a user of the database system; presenting a given query, along with results for the given query, on the display, where the given query is associated with the given node; receiving a modification to the given query from the user of the database system, thereby forming a new query; and updating the tree graph with the new query.