Query Engine for Recursive Searches in Self-Describing Data Systems
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Solution Overview
Problem
Current search technologies face challenges in formulating and executing recursive search queries in relational databases, particularly when dealing with dynamic data models, as they require iterative reformulation and are hindered by schema changes, leading to errors and inefficiencies in generating query answers for complex product configurations.
Innovation Solution
A query engine for recursive searches in a self-describing data system that retrieves information from a self-referencing data model, generates a solution space based on compatibility constraints, and presents it in a user interface, using a system architecture that includes a database server, backend server with query engine, and frontend for user input and output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If recursive search queries are formulated and executed in relational databases, then search functionality can be implemented on data in relational databases, but the queries require iterative and repetitive reformulation and are hindered by schema changes, resulting in errors and inefficiencies
Solution Approach 1:
The patent introduces an intermediary layer (the query system described in the patent) that mediates between the user's search requirements and the relational database. This intermediary handles the complexity of recursive queries and schema adaptations, shielding users from these issues while maintaining reliable query execution despite schema changes
2Adaptability or versatility
If the data model is made dynamic to accommodate changing product configurations, then the system can handle variability problems, but existing search technologies cannot execute queries across dynamic data models, resulting in errors
Solution Approach 1:
The patent implements a dynamic query formulation mechanism that can adapt to changing data models. The system dynamically adjusts query structures based on the current schema state, enabling reliable execution across dynamic data models without requiring static, pre-defined query templates
3Adaptability or versatility
If the number of product features and options is increased to meet customer expectations, then product configurability is improved, but the number of parts to search and combinations of parts increases to thousands, millions, and billions, resulting in search inefficiency
Solution Approach 1:
The patent segments the large-scale search problem into manageable components by organizing the search process into distinct phases: query formulation, recursive execution, and result aggregation. This segmentation enables efficient handling of billions of parts and combinations through systematic processing rather than brute-force search
Data Source
AI summary
A method for operating a product configuration service, wherein the method comprises: receiving a query pertaining to a scope of searching for a configuration of a product; retrieving, based on the query, information from a self-referencing data model that stores the information as items having item types, wherein the information comprises: variables associated with an entity and values for the variables defined by files of the entity, wherein variables are defined by features that are linked to a source of the files, rules that specify compatibility constraints between the variables, and the information is used during runtime and not persisted to memory; generating, based on the rules and the variables, a solution space comprising the values; and presenting the solution space in a user interface of a computing device of a user.