Latency Predictor for Data Persistence Bottleneck Analysis
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Solution Overview
Problem
High latency during data persistence operations in systems, such as fsync, complicates performance and can lead to application timeouts due to the involvement of multiple system components and configurations, making it difficult to identify and address the underlying factors.
Innovation Solution
A method that monitors data persistence operations, records system states, and uses a trained predictor to estimate latency, identifying key states contributing to high latency and providing targeted suggestions for improvement with minimal impact on user business operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data persistence operations are performed to ensure data reliability, then data reliability is improved, but latency increases and system performance deteriorates
Solution Approach 1:
The system performs preliminary actions by flushing dirty pages to disk in advance before they are strictly needed, using background threads to proactively manage data persistence. This reduces the impact of latency on foreground operations by preparing data persistence ahead of time.
Solution Approach 2:
The patent introduces intermediary components including a latency predictor that estimates future latency, a page cache manager that mediates between dirty pages and disk, and background flush threads that act as intermediaries to smooth out persistence operations. These intermediaries buffer and manage the data flow to reduce latency spikes.
2Measurement precision
If system state monitoring and latency prediction are implemented to identify high latency factors, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically monitoring its own state, predicting latency using trained predictors, and identifying high latency factors without external intervention. The latency prediction mechanism and state monitoring are self-contained components that autonomously analyze system conditions and provide insights.
Solution Approach 2:
The patent implements feedback mechanisms where the latency predictor continuously receives system state measurements, updates its predictions, and feeds back latency estimates to the page cache manager. This closed-loop feedback enables dynamic adjustment of persistence strategies based on real-time system conditions.
Data Source
AI summary
Embodiments of the present disclosure relate to a method, a device, and a computer program product for latency processing. The method includes: in response to that a data persistence operation occurs in a system, acquiring a record for the operation, wherein the record includes an actual latency of the operation and a group of measurements of a group of states of the system within a predetermined time period of the occurrence of the operation. The method further includes: in response to that the actual latency of the operation is greater than a first threshold, generating an estimated latency of the operation by using a trained predictor on the basis of the group of measurements. The method further includes: determining a difference between the actual latency and the estimated latency, and in response to that the difference is less than a second threshold, identifying one or more states from the group of states on the basis of the record and the estimated latency. When there is a high-latency problem in the data persistence operation of the system, the solution of the present disclosure can identify the most major factors that lead to this problem, and thus can provide targeted repair measures to users.