Validation Record Linking for Low-Latency Data Processing
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Solution Overview
Problem
Existing data processing systems face challenges in validating large amounts of data in real-time, leading to increased latency and inefficiencies, especially in web-based services and systems where errors can quickly compound due to corrupted data propagation.
Innovation Solution
A data processing stage with a communications interface and processor that receives input data chunks with validation records, creates an output validation record, and computes output chunks while inspecting validation records, allowing for the dropping or emission of chunks based on validation status, enabling low-latency processing without waiting for complete validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional validation processes are used to validate large amounts of data, then data accuracy and quality are improved, but processing latency increases significantly and the system cannot scale up appropriately
Solution Approach 1:
The system performs validation actions in advance by pre-computing validation records for input data chunks before they are processed. The validation stage creates validation records that can be quickly referenced during the data processing stage, eliminating the need to perform validation in real-time and thus reducing processing latency while maintaining data accuracy.
Solution Approach 2:
The validation record acts as an intermediary between the validation stage and the data processing stage. Instead of the processing stage performing validation directly, it references pre-computed validation records stored in memory, which mediates the validation process and enables fast decision-making without real-time validation computations.
2Reliability
If validation is performed on all input data chunks, then error detection is improved, but processing speed decreases due to the lengthy and complex validation process
Solution Approach 1:
Validation computations are performed in advance during the validation stage, creating validation records that store the results. When data is processed, the system simply references these pre-computed validation records rather than performing the full validation process again, thus maintaining error detection capability while significantly improving processing speed.
Solution Approach 2:
The system creates a copy of validation information in the form of validation records that reference the actual validation data. This allows the processing stage to work with lightweight references rather than the full validation computations, improving speed while preserving the ability to detect errors through the validation record inspections.
3Reliability
If intermediate validation is performed between processing stages, then error propagation is reduced, but system complexity increases
Solution Approach 1:
The validation functionality is extracted into a separate validation stage that operates independently from the data processing stages. This stage creates validation records that are then referenced by processing stages, which simplifies the overall system architecture by separating validation concerns from processing logic while still preventing error propagation.
Solution Approach 2:
Validation records serve as intermediaries that connect the validation stage with multiple processing stages. Instead of each processing stage performing its own validation, they all reference the same validation records, reducing redundancy and simplifying the system while maintaining comprehensive error prevention across all stages.
Data Source
AI summary
A data processing stage is described which has a communications interface arranged to receive a plurality of input data chunks. Each input data chunk has a pointer to a validation record, where the validation records are stored at a memory accessible to the data processing stage. A processor of the data processing stage is configured to create an output validation record at the memory, and to link the output validation record to the validation records of the input chunks. The processor is configured to compute an output chunk from the input chunks in a manner which ignores data of the input chunks identified as invalid through inspection of the output validation record.