Pre-computed Search Result Validity Management
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Solution Overview
Problem
Pre-computed search results in database systems become outdated due to changes in underlying data, leading to incorrect responses, and existing update strategies are inefficient in managing re-computation resources, especially when dealing with asynchronous real-time events that affect validity.
Innovation Solution
A method that determines a validity trend and instantaneous validity rate for pre-computed search results, adjusting validity probabilities and re-computation orders based on these rates to efficiently re-compute only necessary results, without relying on external signaling or resource-intensive sampling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If pre-computed search results are maintained to shorten response times, then response speed is improved, but the search results become outdated when underlying data changes, reducing reliability
Solution Approach 1:
The system dynamically adjusts the validity probability of pre-computed search results based on the age of the underlying data. As data ages, the validity probability decreases, triggering re-computation when thresholds are exceeded. This dynamic approach balances maintaining up-to-date results with avoiding unnecessary re-computations, resolving the contradiction between response speed and result validity.
2Reliability
If frequent re-computation is performed to maintain validity, then reliability is improved, but computational resources and time are wasted on re-computing already valid results, reducing productivity
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring the age of underlying data and adjusting validity probabilities accordingly. This feedback loop ensures re-computation is triggered only when necessary, based on actual data freshness rather than fixed schedules, optimizing the balance between maintaining reliability and avoiding wasteful re-computations.
Solution Approach 2:
The system changes the parameter of validity probability based on data age. By adjusting this parameter dynamically, the system determines when re-computation is necessary, preventing both premature and delayed re-computations, thus improving overall re-computation efficiency while maintaining result reliability.
3Measurement precision
If validity monitoring and adjustment mechanisms are implemented, then accuracy of re-computation timing is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-computing search results and storing them with associated validity probabilities before they are needed. This allows the system to quickly serve pre-computed results while having already established the framework for validity monitoring, reducing the complexity of real-time validation while maintaining measurement precision.
Data Source
AI summary
Methods, systems, and computer program products for re-computing pre-computed search results, such as pre-computed priced recommendations. Pre-computed search results stored in a search platform are subdivided into shares of related pre-computed search results including a first share. A re-computation controller determines a validity trend indicating a change rate of a validity probability of a pre-computed search result over time and an instantaneous validity rate for the pre-computed search results. If a difference between the instantaneous validity rate and the validity trend exceeds a given extent, the re-computation controller adjusts the validity probabilities being associated with other pre-computed search results included in a second share correlated with the first share. 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.