Replicated Data Validation via Snapshot Rewinding
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Solution Overview
Problem
Existing data replication systems face challenges in validating replicated data without interrupting the replication process, especially when validation procedures modify the data, requiring full synchronization and human intervention.
Innovation Solution
A method and system that suspend updating of the data replica, record update requests, and use a rewinder to restore the replica to a previous state before validation, allowing for data modification during validation without interrupting replication, and resume updates after validation is complete.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If validation procedures are performed on the data replica, then data validity can be verified, but the replication process must be suspended and full synchronization is required
Solution Approach 1:
The system performs preliminary actions by capturing change information before validation begins. Change information is collected and stored in advance, allowing the validation process to proceed without suspending replication. The captured changes are later applied to the replica after validation, ensuring continuous operation while maintaining data validity verification.
Solution Approach 2:
The validation process is segmented from the replication process. Validation operates on a snapshot of data at a specific point in time, while replication continues independently in the background. This segmentation allows both processes to run concurrently without interfering with each other, eliminating the need to suspend replication for validation.
2Reliability
If validation procedures modify the data replica, then validation can be performed, but the replica cannot be restored to its previous state
Solution Approach 1:
The system captures change information before validation modifies the replica. This preliminary capture of changes allows the replica to be restored to its pre-validation state by replaying the captured changes in reverse order, thus maintaining both validation capability and data restoration capability.
Solution Approach 2:
The system creates a copy of the change information before validation. This copy serves as a record of what changes were made during validation, enabling the replica to be restored to its previous state by applying the reverse of these captured changes, thus preserving both validation and restoration capabilities.
3Reliability
If full synchronization is performed after validation, then the replica is updated, but the process takes significant time and disrupts operational continuity
Solution Approach 1:
The system performs preliminary capture of change information before validation. This allows the replica to be updated with the captured changes immediately after validation without requiring a time-consuming full synchronization process, thus reducing time loss while maintaining data consistency.
Solution Approach 2:
The system extracts only the necessary change information from the full data set before validation. By working with this extracted change information rather than the entire data set, the system can update the replica efficiently after validation without requiring full synchronization, thereby reducing time loss while maintaining consistency.
4Reliability
If replication is suspended for validation, then validation can be performed accurately, but operational continuity is interrupted
Solution Approach 1:
The system performs preliminary capture of change information before validation begins. This allows validation to proceed with accurate data snapshots while replication continues in the background, eliminating the need to suspend replication and thus maintaining operational continuity without compromising validation accuracy.
Solution Approach 2:
The system maintains continuity of useful action by allowing both validation and replication to proceed simultaneously. Validation operates on captured change information while replication continues to capture and apply changes in the background, ensuring both validation accuracy and operational continuity without interruption.
Data Source
AI summary
An approach to validating replicated data allows use of a validation procedure that may modify the data replica. The approach features suspension of updating of the data replica for data replication and enabling restoration of the data replica to a state prior to any modification of the data as a result of the validation procedure. After validation, the data replica is restored before resuming updating for data replication.


