Database Partition Reorganization via Fragmentation Ranking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current database partition reorganization methods lack control over the number of partitions to be reorganized and fail to estimate resource requirements and performance improvements effectively, leading to potential delays and inefficiencies, especially during low usage periods.
Innovation Solution
A method involving a logic unit with modules for evaluating fragmentation, ranking partitions, and reorganizing them in order, along with estimation and recommendation modules to determine the optimal subset of partitions to reorganize, ensuring informed decision-making and efficient resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all database partitions are reorganized to eliminate fragmentation, then database retrieval performance is improved, but the time required and computing resources consumed increase significantly
Solution Approach 1:
The patent applies partial action by reorganizing only a subset of database partitions rather than all partitions. The system identifies and selects specific partitions that meet certain criteria (such as fragmentation threshold, access frequency, or size) for reorganization, while leaving other partitions unchanged. This approach achieves performance improvement for the most problematic partitions without incurring the full cost of reorganizing the entire database, thus resolving the contradiction between performance improvement and time/resource consumption.
Solution Approach 2:
The patent utilizes parameter changes by introducing configurable thresholds and parameters that control the reorganization process. These parameters include fragmentation thresholds, minimum partition size, maximum reorganization time, and priority levels. By adjusting these parameters, the system can dynamically control the scope and intensity of reorganization activities, allowing optimization of the balance between performance improvement and resource consumption based on specific operational requirements.
2Reliability
If database partitions are reorganized during low usage periods, then performance improvement is achieved, but the control over the number of partitions to be reorganized is lost
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor database partition characteristics such as fragmentation levels, access patterns, and size metrics. This feedback information is used to dynamically adjust reorganization decisions and parameters. The system provides feedback loops that allow administrators to review identified partitions, adjust thresholds, and control the reorganization process based on actual database state and performance requirements, thereby maintaining both performance improvement and operational control.
Solution Approach 2:
The patent applies dynamics by making the reorganization process adaptive and flexible rather than static. The system dynamically identifies partitions requiring reorganization based on current database state, dynamically adjusts reorganization parameters based on usage patterns and resource availability, and dynamically schedules reorganization activities. This dynamic approach enables the system to maintain control over reorganization scope while achieving performance improvements based on actual database conditions.
3Adaptability or versatility
If the read head is repositioned for each non-contiguous area, then data can be retrieved from scattered locations, but the total retrieval time increases
Solution Approach 1:
The patent applies merging by consolidating scattered database fields into contiguous storage locations through partition reorganization. The system identifies fields that are currently stored in non-contiguous locations and relocates them to adjacent blocks within the same partition, effectively merging scattered data into a continuous sequence. This eliminates the need for multiple read head repositioning operations, thereby reducing retrieval time while maintaining the ability to access all required data.
Data Source
AI summary
A method is disclosed for reorganizing a set of database partitions based on a ranked set of database partitions. The method includes a step to determine a fragmentation indicator for each database partition within a set of database partitions. A step ranks the set of database partitions according to a rank criteria. The rank criteria includes, at a minimum, the fragmentation indicator. A step reorganizes a subset of the database partitions in the ranked set of database partitions. The subset is selected, at least in part, by a rank order for the ranked set of database partitions. The subset may be selected such that ranked database partitions satisfying a reorganization threshold are included in the subset.