Historical Table Recovery Using Partition File Reassociation
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Solution Overview
Problem
Conventional data recovery techniques for historical table data in database systems are resource-intensive, slow, and inefficient, involving multiple manual steps that are error-prone and difficult to manage during large-scale recovery, especially in the event of system failures or user mistakes.
Innovation Solution
The disclosed data recovery techniques utilize a DR manager to automate the recovery process by associating recovered data files of a table with a newly recovered table without copying data, reducing manual steps and involving fewer resources, thus enabling efficient and error-proof failsafe recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional data recovery techniques are used, then data can be recovered, but the process is resource-intensive and slow
Solution Approach 1:
The patent uses copying by creating a new table structure and associating recovered data files with this new table rather than restoring to the original table structure. This allows the recovery process to work with a simplified target structure, significantly reducing the resources and time needed for recovery operations.
Solution Approach 2:
The patent extracts only the necessary data files for recovery and separates them from the full database structure. By taking out just the partition files that need recovery and processing them independently, the system reduces the overall resource consumption and speed up the recovery process.
2Reliability
If manual data recovery steps are performed, then data can be recovered, but the process is error-prone and difficult to manage
Solution Approach 1:
The system performs self-service by automatically detecting deleted tables, identifying recoverable data files, and executing the recovery process without requiring manual intervention. The automated recovery manager handles all recovery operations autonomously, eliminating human errors and simplifying operation.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors the recovery process, verifies data integrity, and provides status updates. This feedback loop ensures accurate recovery while making the process transparent and manageable, reducing operational complexity.
3Productivity
If data files are recovered and associated with a new table, then recovery efficiency improves, but the original table structure is not restored
Solution Approach 1:
The patent creates a copy of the table structure (the new table) rather than restoring the original. This copied structure is then associated with the recovered data files, enabling efficient recovery while accepting that the original table structure cannot be fully restored if it was corrupted or if the table was dropped.
Solution Approach 2:
Instead of restoring the original table structure and then populating it with recovered data (the conventional approach), the patent inverts the process by first creating a new table structure and then associating recovered files with it. This inversion simplifies the recovery operation and improves efficiency.
Data Source
AI summary
A system is disclosed for recovering historical table data in a database environment. The system includes at least one hardware processor and at least one memory. The memory stores instructions that, when executed, cause the system to receive a request to recover historical table data of a source table. The historical table data includes multiple partition files, and each partition file includes a deleted file designation. The system performs a recovery process on the partition files by determining a recoverable time range for the source table based on lifecycle information and restoring the partition files based on the recoverable time range. The system retrieves a schema associated with the historical table data and generates metadata corresponding to the schema. The metadata is associated with the recovered partition files to reconstruct the historical table data. This approach allows efficient and reliable recovery of deleted or lost table data.