Database Heatmap Tracking for Inactive Data Management
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Solution Overview
Problem
Existing database management systems face challenges in efficiently managing inactive data due to limitations in tracking database activity at a fine granularity level, leading to increased storage costs and performance degradation.
Innovation Solution
A database management system that tracks row and object-level database activity and generates block-level heatmaps, allowing for accurate identification and management of inactive data without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If third party archiving solutions are used to offload inactive data, then storage costs are reduced, but the ability to selectively archive individual database elements is lost due to file-level granularity limitations
Solution Approach 1:
The patent segments the database into fine-grained units (rows, columns, objects) and tracks access patterns at this level. The archiving system divides database files into blocks and maintains bitmaps at the block level, allowing selective identification of inactive data elements within files. This segmentation enables precise identification of archivable data without requiring manual file-level operations.
Solution Approach 2:
The patent introduces bitmaps as an intermediary data structure between the database files and the archiving system. These bitmaps track access patterns at the block level, serving as a mediator that enables the archiving system to identify inactive data elements with fine granularity without requiring direct file-level access control. The bitmaps act as a bridge between file-based storage and row/column-level data management.
2Measurement precision
If manual separation of active and inactive data objects is implemented, then archiving precision is improved, but database administration burden increases significantly
Solution Approach 1:
The patent implements self-service by automatically tracking data access patterns through bitmaps and identifying inactive data blocks without requiring manual intervention. The system autonomously determines which data blocks are candidates for archiving based on access pattern analysis, eliminating the need for database administrators to manually separate active and inactive data objects. The archiving process is self-managed through automated bitmap analysis and block-level identification.
Solution Approach 2:
The patent performs preliminary action by continuously tracking and recording data access patterns in bitmaps before archiving decisions are made. This advance tracking of access patterns allows the system to pre-identify inactive data blocks, so when archiving is needed, the system already has the information required to selectively archive only the appropriate blocks without requiring last-minute manual analysis or separation operations.
3Measurement precision
If fine granularity tracking of database activity is implemented, then identification accuracy of inactive data is improved, but system overhead increases
Solution Approach 1:
The patent adds another dimension to data organization by introducing block-level bitmaps as a separate layer between files and data elements. Instead of tracking at the file level (one dimension) or requiring complex row-level tracking (multiple dimensions), the system uses bitmaps as an additional dimensional layer that efficiently captures access patterns at the block level. This dimensional addition enables fine-grained tracking with manageable overhead by organizing tracking information in a hierarchical structure.
Solution Approach 2:
The patent applies local quality by maintaining bitmaps at the block level rather than uniformly tracking all data at the same granularity throughout the system. Different portions of the database (blocks) have their own localized bitmap tracking structures, allowing the system to track access patterns with fine granularity only where needed while avoiding the overhead of uniform fine-grained tracking across the entire database. This localized approach optimizes the balance between tracking precision and system overhead.
Data Source
AI summary
A method, apparatus, and system for tracking row and object database activity into block level heatmaps is provided. Database activity including reads, writes, and creates can be tracked by a database management system at the finest possible level of granularity, or the row and object level. To efficiently record the tracked database activity, a two-part structure is described for writing the activity into heatmaps. A hierarchical in-memory component may use a dynamically allocated sparse pool of bitmap blocks. Periodically, the in-memory component is persisted to a stored representation component, sharable with multiple database instances, which may include consolidated last access times and/or a history of heatmap snapshots to reflect access over time. The heatmaps may then be externalized to database users and applications to provide and support a variety of features.