Parallel Synthetic Data Generation with Relational Integrity
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Solution Overview
Problem
Generating a large volume of synthetic data for complex computer systems while maintaining relational integrity is challenging, especially when customizing systems for specific users, as it requires complex logic and can be error-prone and time-consuming.
Innovation Solution
A computing system that uses a processor to execute multiple threads and a relational database structure component to generate synthetic data in parallel, utilizing a simplified two-level relationship model to create field and values records, ensuring relational integrity and allowing for easy customization of data ranges and values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synthetic data is generated using complex logic to maintain relational integrity, then data accuracy is improved, but generation time and complexity increase
Solution Approach 1:
The patent segments the data generation process into multiple independent threads, each responsible for generating data for specific tables or relationships. This allows parallel execution while maintaining relational integrity through coordinated thread management and transaction control, thereby reducing overall generation time without sacrificing data accuracy.
Solution Approach 2:
The patent performs preliminary actions by first analyzing the database schema and relationship structure before actual data generation. It pre-configures generation parameters, validates relationship constraints, and prepares thread execution plans in advance, which streamlines the subsequent parallel data generation process and reduces execution time.
2Productivity
If multiple threads execute simultaneously to generate synthetic data, then productivity is improved, but maintaining relational integrity becomes more difficult
Solution Approach 1:
The patent implements feedback mechanisms where thread execution status, data generation progress, and relationship constraint satisfaction are continuously monitored and reported. This feedback enables dynamic coordination between threads, allowing the system to maintain relational integrity through real-time awareness of parallel execution states and及时调整 thread behavior as needed.
Solution Approach 2:
The patent introduces intermediary components such as transaction managers, relationship validators, and coordination layers that mediate between multiple parallel threads and the underlying database system. These intermediaries ensure that relational constraints are maintained by coordinating thread operations, managing transactions, and validating data integrity without preventing parallel execution.
3Adaptability or versatility
If the system is highly customized to meet specific user requirements, then adaptability is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal data generation framework that can handle multiple database types, relationship structures, and customization requirements through a single unified system. The framework provides configurable parameters and plugins that allow adaptation to specific user needs without requiring separate specialized systems, thereby managing complexity while maintaining high adaptability.
Solution Approach 2:
The patent enables customization through parameter changes rather than structural modifications. Users can adjust generation parameters, data ranges, relationship configurations, and thread settings to meet specific requirements, allowing the same core system to adapt to different scenarios without increasing inherent system complexity.
Data Source
AI summary
A system and method are provided that facilitate generation of a large volume of customized synthetic data for testing operations using a parallel synthetic data creation technique while ensuring relational integrity of the generated data. In some examples, values for primary keys and foreign keys as well as relationships in the metadata are created in a way that allows a user to easily change the value or range of values for any suitable field.