Concurrent Enterprise System Testing via Virtual Schema Views
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Solution Overview
Problem
Current methods for testing updated or customized enterprise systems require copying large amounts of production data, leading to significant downtime, increased hardware needs, and manpower requirements, as well as inconsistent data during testing.
Innovation Solution
Implementing a concurrent testing method using a test database schema with read-only and union views that allows for simultaneous production use and testing without data copying, utilizing triggers to manage access and data merging between production and local tables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If production data is copied to a test system for testing modified enterprise systems, then testing can be performed with production data, but significant memory consumption and setup time occur
Solution Approach 1:
The patent creates a virtual copy of the production database schema in the test environment using view definitions. Instead of physically copying terabytes of data, the system uses SQL view definitions that reference production data tables, creating a lightweight virtual representation that consumes minimal memory while maintaining data consistency for testing purposes.
Solution Approach 2:
The patent introduces a schema conversion layer that acts as an intermediary between the test system and production database. This layer translates test system database operations into equivalent production database operations, allowing the test system to work with a lightweight schema representation while production data remains in its original location, eliminating the need for large data copies.
2Reliability
If production data is copied to a test system, then testing can be performed, but significant setup time and production downtime occur
Solution Approach 1:
The patent pre-generates SQL view definitions that capture the production database schema structure before testing begins. These view definitions are stored and can be quickly applied to the test environment, eliminating the need for time-consuming data copying and setup during production downtime. The schema representation is prepared in advance and can be rapidly deployed.
Solution Approach 2:
Instead of copying actual data which takes hours or days, the patent copies only the schema structure through view definitions, which occurs in minutes. This lightweight copying approach maintains testing accuracy by preserving the production data structure while dramatically reducing setup time and eliminating the need for production halts.
3Reliability
If a test system is set up with production data copy, then testing can be performed, but the test environment requires as much memory and computing power as the production system
Solution Approach 1:
The patent creates a virtual schema copy using view definitions that reference production tables, reducing hardware requirements from terabytes of storage and equivalent computing power to minimal resources needed to store and execute view definitions. The test system only needs to maintain the lightweight schema representation, not the actual data.
Solution Approach 2:
The patent extracts only the essential schema structure from the production database and represents it through view definitions in the test environment. This extraction eliminates the need for the test system to have full production-capable hardware, as only the structural metadata is needed for testing, not the actual data volume.
4Reliability
If production data is copied to a test system, then testing can be performed, but inconsistent data occurs during the copy process
Solution Approach 1:
The patent copies the schema structure through view definitions that dynamically reference production data tables. This ensures the test system always sees the current production schema structure without the inconsistency problems of traditional copying, as the view definitions are regenerated as needed to match the current production state.
Solution Approach 2:
The schema conversion layer acts as an intermediary that queries production data tables in real-time or near-real-time, ensuring the test system works with current, consistent schema information. This eliminates the window of inconsistency that occurs during traditional copy procedures, as the production data structure is referenced directly rather than through a stale copy.
Data Source
AI summary
Implementations of the present disclosure include methods, systems, and computer-readable storage mediums for concurrent production use of an enterprise system and testing of a modified enterprise system. Actions include receiving a test schema that provides one or more application views to application tables of production data in a database, at least one application view including a read-only view, providing one or more local tables for local test data provided during execution of the modified enterprise system, providing one or more triggers to the at least one application view, and executing the enterprise system based on a production database schema and concurrently executing the modified enterprise system based on the test database schema.