Pre-computed Search Result Validity Management
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Solution Overview
Problem
Existing database systems face challenges in efficiently managing pre-computed search results due to their tendency to become outdated, especially when underlying data changes, leading to incorrect responses. Current solutions either rely on resource-intensive sampling or external signaling for real-time events, which may not always be feasible.
Innovation Solution
A method is introduced that uses a re-computation controller to determine validity trends and instantaneous validity rates of pre-computed search results, adjusting validity probabilities and prioritizing re-computation based on these rates, thereby reducing the need for resource-intensive sampling and external signaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If pre-computed search results are maintained to reduce response time, then response time is improved, but the search results become outdated when underlying data changes
Solution Approach 1:
The system dynamically adjusts the validity probability of pre-computed search results based on observed changes in instantaneous validity rates compared to trend values. When underlying data changes are detected through this comparison mechanism, the system adapts by updating validity probabilities and triggering re-computations accordingly, making the static pre-computed results dynamically responsive to data changes.
2Measurement precision
If external signaling or sampling is used to detect real-time events, then detection accuracy is improved, but resource consumption increases
Solution Approach 1:
The system performs self-detection by comparing its own observed instantaneous validity rates against pre-established trend values. This self-service mechanism eliminates the need for external signaling or resource-intensive sampling, as the system uses its existing re-computation observations to automatically detect validity decreases and trigger appropriate updates.
Solution Approach 2:
The system implements feedback by continuously monitoring the difference between instantaneous validity rates and trend values from past re-computations. This feedback loop enables the system to detect when underlying data changes occur and automatically adjust validity probabilities and trigger re-computations without external intervention or additional resource consumption.
3Manufacturing precision
If validity probabilities are adjusted based on trend and instantaneous rate comparison, then update accuracy is improved, but computational complexity increases
Solution Approach 1:
The system performs preliminary action by pre-computing trend values from historical re-computation data and establishing validity probability models before actual data changes occur. This preliminary preparation enables the system to quickly compare instantaneous rates against pre-established trends and immediately trigger accurate updates when changes are detected, improving update accuracy while managing computational complexity through advance preparation.
Data Source
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AI summary
Pre-computed search results stored in a search platform are subdivided into a plurality of shares of related pre-computed search results including a first share D. A re-computation controller controls re-computation of the pre-computed search results on the basis of validity probabilities. The re-computation controller determines a validity trend λi indicating a change rate of the validity probability of a pre-computed search result i over time and an instantaneous validity rate λ̂i for the pre-computed search result i. In response to determining a difference between the instantaneous validity rate λ̂i and the validity trend λi exceeding a given extent, the re-computation controller adjusts the validity probabilities being associated with other pre-computed search results included in a second share D' being correlated to the first share D. The re-computation controller issues re-computation orders to a computation platform to re-compute a part of the pre-computed search results, the part being selected by the re-computation controller on the basis of the validity probabilities associated with the pre-computed search results.