Real-Time Data Completeness Metric for Distributed Processing
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Solution Overview
Problem
Existing real-time data processing technologies fail to provide a clear progress evaluation, leading to inaccurate decision-making due to constantly changing data and loss of data beyond specified timeout periods.
Innovation Solution
A method and apparatus for real-time data processing that collect and aggregate data based on predetermined conditions across nodes in a distributed system, calculating a degree of completeness to indicate the proportion of processed data, allowing for accurate progress evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time data is continuously collected and processed without timeout, then data integrity is maintained, but data loss occurs when timeout periods are specified
Solution Approach 1:
The patent implements a feedback mechanism by continuously monitoring the processing status of real-time data and dynamically adjusting the timeout period. The system tracks whether data has been processed within the timeout period and provides feedback to extend or reset the timeout, preventing data loss while maintaining data integrity. This is achieved through a timeout management module that receives processing status information and updates timeout periods accordingly.
Solution Approach 2:
The timeout period is transformed from a static fixed value to a dynamic parameter that changes based on processing status. The system allows timeout periods to be extended or reset dynamically when data processing is ongoing, adapting to real-time conditions. This dynamic timeout mechanism ensures that data is not lost due to rigid timeout constraints while maintaining system responsiveness.
2Productivity
If data processing progress is not tracked, then processing speed is maintained, but accurate decision-making cannot be made
Solution Approach 1:
The patent implements a comprehensive feedback mechanism that tracks and reports data processing progress in real-time. The system monitors which data has been processed, which is pending, and which has timed out, providing continuous feedback to both the processing engine and users. This enables accurate decision-making without compromising processing speed, as the feedback is generated asynchronously and does not block the main processing flow.
Solution Approach 2:
The patent introduces an intermediary timeout management module that acts as a mediator between the data processing engine and the timeout control system. This intermediary tracks processing status and manages timeout periods without interfering with the core processing speed. It maintains a mapping between data and timeout periods, allowing progress evaluation to be made without slowing down the actual data processing operations.
3Loss of time
If timeout period is set short, then response time is reduced, but data loss increases
Solution Approach 1:
The timeout period is made dynamic rather than fixed, allowing the system to adjust timeout lengths based on actual processing progress. When data is being processed, the timeout period is extended or reset, preventing data loss. When processing is complete or stalled, the timeout period remains short to ensure quick response. This dynamic adjustment resolves the contradiction between short response time and data loss prevention.
Solution Approach 2:
The system uses feedback from processing status to dynamically adjust timeout periods. When data processing is ongoing, feedback triggers an extension or reset of the timeout period, preventing premature data loss. When processing completes successfully, the timeout returns to its base short value, maintaining quick response times. This feedback-driven timeout management ensures both fast response and data integrity.
4Loss of substance
If timeout period is set long, then data loss is prevented, but response time increases
Solution Approach 1:
The timeout period dynamically adapts based on processing status rather than being uniformly long. The system starts with a base timeout period and extends it only when necessary based on processing progress feedback. This means that in normal operation, the effective timeout remains short for fast response, while extending to longer periods only when data processing is ongoing, thus preventing data loss without permanently increasing response time.
Solution Approach 2:
Feedback mechanisms trigger timeout extensions only when processing is actively occurring. The system monitors processing status and extends the timeout period selectively based on this feedback, rather than using a uniformly long timeout. This feedback-driven approach prevents data loss during processing while maintaining short effective timeout periods for completed operations, resolving the contradiction between data loss prevention and response time.
Data Source
AI summary
A real-time data processing method and an apparatus thereof are provided. The method includes collecting real-time data received by one or more nodes in a distributed system; aggregating real-time data that satisfies a same predetermined condition on all the nodes to obtain a total amount of real-time data corresponding to the same predetermined condition, wherein the predetermined condition is used for representing a time at which the real-time data is collected; and calculating a degree of completeness of the real-time data that satisfies the same predetermined condition, wherein the degree of completeness is used for indicating a ratio between processed real-time data that satisfies the same predetermined conditions and the real-time data aggregated on all the nodes. Using the present disclosure, problems caused by failing to know a progress of real-time data processing in existing technologies are resolved, thereby adding a dimension of evaluation of the real-time data processing.