Database Workload Recovery by Priority Grouping
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Solution Overview
Problem
Database recovery processes are time-consuming and inefficient, especially as database size increases, due to the lack of prioritization and concurrent recovery strategies in existing systems.
Innovation Solution
The method involves dividing a database workload into multiple workload groups based on priority, allowing for selective recovery of high-priority groups first, concurrent recovery of other groups, and dynamic adjustment of recovery priorities based on resource usage and requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If database recovery is performed on the entire database system, then all data is restored to a consistent state, but the recovery time increases significantly as database size increases
Solution Approach 1:
The patent divides the database workload into multiple workload groups (e.g., OLTP, OLAP, batch processing) that can be recovered independently. Each workload group is assigned a recovery priority level, allowing the system to restore critical workloads first while less critical workloads are recovered subsequently. This segmentation enables parallel recovery operations and significantly reduces overall recovery time while maintaining data consistency within each group.
Solution Approach 2:
The system performs preliminary classification of workloads into priority groups before recovery begins. Recovery priorities are predetermined based on workload criticality, allowing the database management system to immediately initiate recovery of high-priority workloads upon failure detection, without needing to analyze or determine priorities during the recovery process itself.
2Reliability
If the entire database is recovered simultaneously, then complete system restoration is achieved, but resource utilization during recovery is inefficient
Solution Approach 1:
The database workload is segmented into multiple recoverable units (workload groups) with different priority levels. The system recovers these segments in parallel according to their priority assignments, allowing efficient utilization of available computing resources. High-priority workloads receive maximum resource allocation first, while lower-priority workloads utilize remaining resources, thereby maximizing overall recovery productivity.
Solution Approach 2:
The recovery process dynamically adjusts resource allocation based on workload priority levels. The database management system continuously monitors recovery progress and resource availability, reallocating resources from completed low-priority workloads to remaining high-priority workloads. This dynamic resource management optimizes recovery efficiency while ensuring critical workloads are restored first.
Data Source
AI summary
Database recovery is based on workload priorities. A database workload is divided into a plurality of workload groups. A workload group of the plurality of workload groups is selected for recovery, in which the selecting is based on a priority of the workload group. One or more recovery actions are performed for the workload group selected for recovery.