Data Translation Pipeline for Delimited Format Acceleration
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Solution Overview
Problem
Delimited data formats, such as CSV, pose processing challenges due to their serial nature, leading to bottlenecks in data throughput as software systems need to analyze each byte to identify field and record delimiters, hindering efficient data processing and validation operations.
Innovation Solution
The implementation of a data translation pipeline that converts delimited data into structured formats like fixed field or mapped variable field formats, allowing downstream processing to directly access specific fields without analyzing all preceding bytes, utilizing reconfigurable logic and modular pipelines for accelerated processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If delimited data format is used for data transmission, then platform independence and data organization are improved, but data processing throughput deteriorates due to serial byte-by-byte analysis requirement
Solution Approach 1:
The patent segments the data processing task by introducing a translation pipeline that divides delimited data into fixed-field records with explicit field identifiers. Each field is tagged with metadata (field name, data type, length) that enables independent processing without sequential analysis of all preceding bytes, thus resolving the throughput bottleneck while maintaining data organization.
Solution Approach 2:
The patent introduces an intermediary translation layer (translation pipeline) that converts delimited data format into a structured fixed-field format. This intermediary component performs the costly byte-by-byte delimiter analysis once during translation, allowing downstream processing systems to access fields directly via field identifiers without repeating the serial analysis, thereby improving throughput while preserving platform independence.
2Ease of manufacture
If software-based processing is used for delimited data, then ease of implementation is improved, but processing speed deteriorates due to sequential byte analysis bottleneck
Solution Approach 1:
The patent replaces the mechanical sequential byte-by-byte processing mechanism with a hardware-accelerated translation pipeline that uses parallel processing and field tagging. The translation pipeline employs dedicated hardware components (field identifier generators, length calculators, validation units) that operate concurrently to transform delimited data into structured format, achieving speeds unattainable by software while maintaining implementation feasibility through modular design.
3Reliability
If field validation is performed in delimited data format, then data accuracy is improved, but processing time deteriorates due to requirement to analyze all preceding bytes
Solution Approach 1:
The patent applies preliminary action by performing field tagging and structure transformation before validation operations. The translation pipeline pre-processes delimited data into structured fixed-field records with explicit field identifiers and length metadata, enabling validation to start immediately at the target field without requiring analysis of all preceding bytes. This preliminary structuring preserves data accuracy while eliminating the time penalty of sequential analysis.
Data Source
AI summary
Various methods and apparatuses are described for performing high speed format translations of incoming data, where the incoming data is arranged in a delimited data format. As an example, the data in the delimited data format can be translated to a mapped variable field format using pipelined operations. A reconfigurable logic device can be used in exemplary embodiments as a platform for the format translation.