Coalescing Data Between Events Prior to Temporal Window
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Solution Overview
Problem
Data stored prior to a temporal window consumes excessive storage space, leading to premature discarding of important information and potential loss of needed data due to storage limitations.
Innovation Solution
A method and system that coalesce data between events prior to and after a temporal window using a direction-agnostic roll algorithm, which includes determining a temporal window based on user and automatically generated data, coalescing data using a processor and physical memory, and capturing data after the window, while generating a coalescing policy to reduce storage requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data prior to the temporal window is stored without coalescing, then data recovery capability is improved, but storage space consumption increases excessively
Solution Approach 1:
The patent merges multiple data sets containing overlapping information between events prior to the temporal window into a single coalesced data set. This consolidation reduces storage space consumption while preserving the ability to recover data, as the merged data set contains the essential information needed for recovery without redundant copies.
Solution Approach 2:
The patent selectively discards redundant data during the coalescing process while maintaining the capability to recover necessary information. By identifying and removing duplicate or overlapping data segments that do not contribute to recovery capability, the system reduces storage requirements without compromising the ability to restore data when needed.
2Quantity of substance
If storage space is limited, then storage cost is reduced, but important information may be prematurely discarded
Solution Approach 1:
The patent applies different retention strategies to different portions of data based on their importance and overlap characteristics. Rather than uniformly discarding or retaining all data prior to the temporal window, the system selectively coalesces data segments, preserving important information while discarding redundant portions. This localized approach to data quality management ensures important information is retained while optimizing storage space utilization.
3Quantity of substance
If data coalescing is performed on all operations, then storage efficiency is improved, but processing complexity increases due to handling overlapping and non-overlapping sectors
Solution Approach 1:
The patent segments data operations into overlapping and non-overlapping sectors, applying coalescing operations selectively rather than uniformly to all data. This segmentation allows the system to handle complex overlapping regions with specialized algorithms while leaving non-overlapping regions unchanged, thereby reducing overall processing complexity while still achieving storage efficiency improvements in the critical overlapping portions.
Data Source
AI summary
Systems and methods of coalescing and capturing data between events prior to and after a temporal window are disclosed. In an embodiment, a method includes determining a temporal window based on one or more of a user data and an automatically generated data, coalescing data between events prior to the temporal window using a processor and a physical memory and capturing data between events after the temporal window. The coalescing data between events prior to the temporal window may be determined by a set of overlapping operations to a data set, wherein certain operations have non-overlapping sectors which are not coalesced. Shifting a data view around a recovery point through a direction-agnostic roll algorithm that may use a roll-forward algorithm to shift the data view to a time after the recovery point and/or a roll-backward algorithm to shift the data view to a time before the recovery point.