Minimum Superset Construction for Relational Database Referential Integrity
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Solution Overview
Problem
Developers spend a significant amount of time managing data-related tasks, particularly in constructing test data subsets from relational databases that ensure referential integrity, which is complex and time-consuming, impacting IT costs and application development efficiency.
Innovation Solution
A computer-implemented method for constructing a minimum superset of data that complies with referential integrity rules, involving an iterative process of selecting tables, identifying parent or child relationships, evaluating these relationships asynchronously, and creating registry tables to ensure all necessary records are included, thereby improving performance by evaluating relationships concurrently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional sequential methods are used to construct test data subsets ensuring referential integrity, then data completeness and integrity are maintained, but time consumption and processing duration increase significantly
Solution Approach 1:
The patent divides the database into multiple tables with identified parent-child relationships. The construction process segments the evaluation into independent table-level operations, where each table can be evaluated separately for referential integrity. This segmentation enables parallel processing while maintaining overall data consistency, thus reducing total processing time without compromising integrity.
Solution Approach 2:
The patent performs preliminary identification of parent-child relationships between tables before the actual data construction process. Registry tables are pre-created to store records that must be included in the minimum superset. This preliminary structuring allows the main construction process to proceed more efficiently by avoiding repeated relationship analysis during execution.
2Reliability
If a complete subset of data is constructed to ensure all referential relationships are satisfied, then data completeness is improved, but the size and complexity of the data subset increases
Solution Approach 1:
The patent extracts only the essential records needed to satisfy referential integrity constraints from the original database. By focusing specifically on parent-child relationship requirements and using registry tables to track necessary records, the method extracts a minimal superset that contains only what is needed for completeness, excluding redundant data.
Solution Approach 2:
The patent applies partial action by constructing a minimum superset rather than copying the entire database. It processes only the specific tables and records implicated by referential integrity rules, performing just enough action to satisfy completeness requirements without unnecessary overhead. The iterative process stops when all integrity constraints are satisfied, avoiding excessive data inclusion.
3Reliability
If traditional data subset construction methods are used, then referential integrity is maintained, but developer productivity and application development efficiency decrease
Solution Approach 1:
The patent changes the execution parameter from sequential to parallel/async processing. By evaluating multiple tables asynchronously and concurrently where possible, the method maintains referential integrity through proper synchronization while dramatically reducing the time required for data subset construction, thus improving developer productivity.
Solution Approach 2:
The patent implements an automated iterative process that self-manages the complex task of constructing minimum supersets with referential integrity. The system automatically identifies relationships, evaluates tables, creates registry tables, and iterates until completeness is achieved, freeing developers from manual data management tasks and improving their productivity.
Data Source
AI summary
A computer-implemented method is provided for constructing a minimum superset of data that complies with referential completeness as well as other specified data relationships. Given extraction criteria for the data, an iterative process analyzes the database for records to be included in the minimal superset. The iterative process includes: selecting a given table from a listing of tables implicated by the extraction criteria; identifying tables in the relational database having either a parent or a child relationship with the given table; evaluating concurrently and asynchronously each of the identified tables; and repeating these steps for each of the tables in the listing of tables.