Graph Data Store Baseline Management for Version Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems managing graph data structures face challenges in efficiently implementing interdependent changes without compromising the integrity of the graph, leading to performance degradation and difficulties in reverting to earlier states due to lack of previous state information, and require significant memory for storing multiple versions.
Innovation Solution
A computing device organizes edit revisions into a data structure, generating baselines that include pointers to edit revisions, allowing for efficient management of multiple versions, quick identification of change history, and simultaneous provision of different materializations to users with reduced memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple versions of graph data structure are stored to enable reverting to earlier states, then the ability to correct errors and maintain historical states is improved, but the memory resources required increase significantly
Solution Approach 1:
The patent creates materializations (copies) of the graph data structure at different points in time through baselines. Instead of storing complete graph versions continuously, it captures snapshots (materializations) that can be reverted to, reducing memory usage while maintaining the ability to recover earlier states.
Solution Approach 2:
The system proactively creates baselines and materializations at predetermined intervals or upon significant changes, preparing historical states in advance. This allows rapid recovery to earlier states without needing to reconstruct them during error correction, improving reliability while managing memory resources efficiently.
2Reliability
If interdependent changes are applied to the graph in a particular order at scheduled times to maintain integrity, then the consistency of the graph is improved, but the complexity of managing change sequences increases
Solution Approach 1:
The patent divides changes into discrete edit revisions that can be independently tracked and applied. Each edit revision represents a atomic unit of change that can be managed separately, reducing the complexity of coordinating interdependent changes while maintaining graph consistency through the baseline system.
Solution Approach 2:
The baseline acts as an intermediary structure that mediates between multiple edit revisions and the final graph state. It provides a reference point that helps manage the sequencing and coordination of interdependent changes, simplifying the complexity of change management while ensuring consistency.
3Speed
If complete graph data structure is replicated for each version to enable simultaneous user access, then the speed of user access is improved, but the memory resources required increase significantly
Solution Approach 1:
The patent creates materializations (copies) of the graph data structure at different points in time through baselines. Instead of storing complete graph versions continuously, it captures snapshots (materializations) that can be reverted to, reducing memory usage while maintaining the ability to recover earlier states.
4Adaptability or versatility
If frequent changes are made to the graph including adding and removing thousands of items, then the adaptability of the system is improved, but the time required to maintain graph integrity increases
Solution Approach 1:
The system proactively creates baselines and materializations at predetermined intervals or upon significant changes, preparing historical states in advance. This allows rapid recovery to earlier states without needing to reconstruct them during error correction, improving reliability while managing memory resources efficiently.
Data Source
AI summary
Systems and methods are directed to a computing device and methods for generating baselines of a data structure, such as a graph. A baseline may define a materialization of the data structure and may include pointers to a set of immutable edit revisions to the data structure that are associated with that materialization. The computing device may receive a request to change a materialization of the data structure defined by a first baseline having pointers to a first set of immutable edit revisions. The computing device may identify a second set of edit revisions to the data structure based at least in part on the requested change and the first set of immutable edit revisions. The computing device may then generate a second baseline defining a second materialization of the data structure, and the second baseline may include pointers to the second set of edit revisions.