Algebraic Data Model Mapping for Cross-Format Query Optimization
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Solution Overview
Problem
Conventional database systems are limited by predefined schema and structures that do not optimize for data storage and retrieval, leading to inefficiencies in processing and accessing data across different formats, such as relational and XML data.
Innovation Solution
The system employs a universal data model based on extended set theory to capture and process data in various formats, using algebraic relations to optimize storage and access, allowing for adaptive data restructuring and parallel processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional database systems use predefined schema and structures, then data storage and retrieval can be organized, but processing efficiency and access performance deteriorate due to redundant operations and non-optimized structures
Solution Approach 1:
The patent applies dynamics by transforming static predefined schemas into dynamic algebraic expressions that can be optimized at query time. The system represents data relationships as algebraic expressions that can be manipulated and optimized based on actual query requirements, rather than being constrained by fixed schema definitions. This allows the system to adapt its structure dynamically to optimize processing efficiency for each specific query operation.
Solution Approach 2:
The system changes parameters by representing data relationships in terms of algebraic expressions with可变 parameters rather than fixed schema constraints. The algebraic expressions allow for parameter optimization where the same data relationship can be expressed in multiple equivalent forms, and the system selects the form that optimizes query performance. This parameter flexibility enables efficient query processing without being bound by rigid predefined structures.
2Adaptability or versatility
If data is stored in predetermined schema formats, then data organization is achieved, but the ability to capture and process data in various original formats deteriorates
Solution Approach 1:
The patent introduces algebraic expressions as an intermediary layer between the original diverse data formats and the internal storage system. Instead of directly converting all data into predetermined schema formats, the system uses algebraic expressions to represent relationships between data elements, preserving the essential structural information while enabling flexible processing. This intermediary representation maintains adaptability to various input formats while organizing data for efficient retrieval.
Solution Approach 2:
The system achieves universality by using a unified algebraic expression framework that can represent relationships across different data formats (relational, XML, flat files, CSV). The algebraic expression system serves multiple functions: it captures the structure of diverse data formats, enables optimized query processing, and provides a common representation for different data types. This multi-functional approach allows the system to handle various data formats without losing essential structural information.
3Speed
If multiple accesses to storage are required for a single query, then data retrieval can be completed, but processing time increases significantly due to the disparity between processing speeds and storage access speeds
Solution Approach 1:
The system applies preliminary action by pre-computing and caching algebraic expressions that represent data relationships. When queries are executed, the system can reuse these pre-computed expressions and their results, avoiding repeated access to storage for the same data relationships. The algebraic expression framework allows results to be cached and reused across multiple queries, significantly reducing storage access time and improving query response speed.
Solution Approach 2:
The patent merges multiple storage accesses into fewer operations by using algebraic expressions to represent complex data relationships. Instead of requiring separate storage accesses for each piece of related data, the algebraic expressions allow the system to combine multiple data elements and their relationships into unified representations that can be retrieved and processed more efficiently. This merging reduces the number of storage accesses required and improves overall query performance.
Data Source
AI summary
Systems and methods for data storage and retrieval using data model mapping. Statements may be presented to the system based on different schema and data models. Algebraic relations between data sets may be composed from the statements. Mappings are provided between the different schema and data models to allow algebraic relations based on one schema and data model to be used in providing a requested data set based on a different schema and data model. Algebraic optimization may also be performed to select among algebraic relations to be used for providing the requested data set, including algebraic relations based on different schemas and data models. As a result, optimization may be performed across a broader set of possible algebraic relations to provide the requested data set.