Versioned Database Scenario Deletion for Memory Reclamation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Database administrators face challenges in reducing the memory footprint of versioned databases due to shared data between scenarios, making it difficult to determine which scenarios to delete to reclaim memory effectively.
Innovation Solution
A method and system utilizing a version visibility data structure (VVDS) to analyze combinations of scenarios for deletion, determining the best scenarios to delete to free up memory, by generating a VVDS from a version graph and scenario structure, evaluating memory reclaim, and executing deletions to achieve memory reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If scenarios are deleted to reduce memory footprint, then memory usage decreases, but determining which scenarios to delete becomes complex due to data sharing between scenarios
Solution Approach 1:
The patent segments the database into versions and scenarios, creating a hierarchical structure where versions contain data and scenarios reference versions. This segmentation allows tracking which scenarios reference which versions, enabling precise identification of deleteable scenarios without manual analysis of complex sharing relationships.
Solution Approach 2:
The patent introduces a version reference table as an intermediary data structure that mediates between scenarios and versions. This table explicitly stores which scenarios reference which versions, providing a clear mapping that simplifies the determination of which scenarios can be safely deleted to free up memory.
2Quantity of substance
If all scenario combinations are evaluated to find optimal memory reclamation, then memory reclamation effectiveness improves, but computational complexity increases exponentially
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing the version reference relationships in a structured table before deletion decisions are made. This pre-organization of data allows for efficient evaluation of deletion scenarios without requiring complex real-time analysis of all scenario combinations.
Solution Approach 2:
The patent evaluates deletions at the individual scenario level rather than requiring exhaustive evaluation of all possible scenario combinations. By assessing each scenario's impact independently using the version reference table, the system achieves effective memory reclamation without exponential computational complexity.
3Adaptability or versatility
If data is shared between multiple scenarios, then data reusability improves, but memory cannot be freed when individual scenarios are deleted
Solution Approach 1:
The patent implements feedback through the version reference table, which provides real-time information about which scenarios reference which versions. This feedback mechanism allows the system to accurately determine when a version can be freed (when no scenarios reference it) while maintaining data sharing capabilities when scenarios do reference the version.
Solution Approach 2:
The patent creates a dynamic relationship between scenarios and versions through the version reference table, where the referencability of a version changes based on scenario deletions. This dynamic tracking allows the system to maintain data sharing when appropriate while automatically enabling memory reclamation when scenarios are deleted and no longer reference the data.
Data Source
AI summary
Systems and methods for deleting data in a versioned database, comprising: generating a version visibility data structure (VVDS) from a version graph and scenario structure; determining each combination of feasible scenarios that when deleted, delete memory; evaluating an amount of memory reclaimed for each combination of feasible scenarios; and deleting one or more combination of scenarios to free up a specific amount of memory.