Corrupted Volume Recovery via Backup Table and Selective Data Set Validation
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Solution Overview
Problem
Current methods for recovering corrupted volumes in computing environments often result in the loss of updates since the last backup, as they either attempt to recover the entire volume or require manual checks, lacking efficient techniques to differentiate between valid and corrupted data sets.
Innovation Solution
A method that detects data corruption in volumes, diagnoses the volume table, accesses a backup volume table to bring it to a current state, and moves valid data sets to a recovery volume, while initiating recovery operations for invalid data sets, utilizing previous backups and data set records to determine valid portions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire volume is recovered using traditional methods, then data loss is minimized, but productivity and efficiency deteriorate due to unnecessary recovery of valid data sets
Solution Approach 1:
The patent segments the volume into individual data sets and evaluates each one's validity separately. Instead of treating the entire volume as a single unit that must be recovered or discarded, the system divides the volume table into individual data set records, checks each for corruption independently, and recovers only those that are valid. This segmentation allows selective recovery, improving productivity by avoiding unnecessary processing of already-valid data sets while maintaining reliability by thoroughly checking each segment.
Solution Approach 2:
The patent applies local quality by treating different parts of the volume differently based on their individual validity status. Each data set is assessed locally for corruption, and the recovery process applies different operations to different parts: valid data sets are preserved as-is, corrupted data sets are recovered from backups, and the volume table is selectively updated. This local differentiation optimizes the recovery process by focusing resources only where needed.
2Productivity
If manual checks are performed to identify valid data sets, then productivity improves by avoiding recovery of valid data, but device complexity increases due to manual intervention requirements
Solution Approach 1:
The patent implements self-service by enabling the system to automatically detect corruption, evaluate data set validity, and perform selective recovery without requiring manual intervention. The system uses automated corruption detection mechanisms to assess each data set, independently determines which ones are valid, and executes the recovery process autonomously. This eliminates the need for administrators to manually check volumes while maintaining high productivity through efficient automated validation and selective recovery operations.
3Device complexity
If the volume table is not validated, then device complexity is reduced, but loss of information increases due to inability to identify corrupted data sets
Solution Approach 1:
The patent applies preliminary action by validating the volume table and checking data set integrity before initiating the recovery process. The system performs preliminary corruption detection on the volume table and individual data sets, identifies which ones are valid, and only then proceeds with selective recovery. This preliminary validation step, while adding some complexity to the process, prevents information loss by ensuring that only truly corrupted data sets are recovered, avoiding unnecessary overwriting of valid data.
Data Source
AI summary
Provided are a computer program product, system, and method for recovering a volume table and data sets from a corrupted volume. Data corruption is detected in a volume having data sets. A volume table having information on the data sets allocated in the volume is diagnosed. A backup volume table comprising a most recent valid backup of the volume table is accessed from a backup of the volume in response to determining that the diagnosed volume table is not valid. Content from the backup volume table is processed to bring to a current state in a recovery volume table for a recovery volume. The data sets in the volume are processed to determine whether they are valid. The valid data sets are moved to the recovery volume. A data recovery operation is initiated for the data sets determined not to be valid.