Record Format Detection via Validation Tests
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Solution Overview
Problem
Data processing systems face challenges in managing and processing data from various sources with different record formats, as existing systems often require conversion or have specific formats that are not universally compatible.
Innovation Solution
A method and system for determining a target record format by analyzing data against candidate formats through validation tests, using a parser based on known data types, or generating a constructed format from data characteristics, allowing for partial matches and user input to ensure compatibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data from multiple different systems with various record formats is processed, then the system can handle diverse data sources, but the complexity of managing and determining the correct record format increases
Solution Approach 1:
The system performs self-service by automatically analyzing incoming data to determine its record format through validation tests against stored candidate formats. The data itself provides the information needed for format identification through its structural characteristics, eliminating the need for manual format specification or complex external format management systems.
Solution Approach 2:
The system changes parameters by analyzing multiple candidate record formats with different field specifications and validation rules. By testing the incoming data against varying format parameters (field counts, data types, validation criteria), the system dynamically identifies the correct format without requiring pre-configured knowledge of all possible source formats.
2Measurement precision
If validation tests are performed against multiple candidate record formats to accurately identify the target format, then the precision of format determination improves, but the processing time increases
Solution Approach 1:
The system applies partial action by performing validation tests against multiple candidate formats simultaneously rather than sequentially. By evaluating several formats in parallel and using partial matches to narrow down candidates, the system achieves precise format determination without the time cost of exhaustive sequential testing of all possible formats.
3Measurement precision
If the system requires exact match between data and candidate record formats, then the accuracy of format identification is high, but the adaptability to handle variations decreases
Solution Approach 1:
The system accepts partial matches between incoming data and candidate record formats as valid identifications. By allowing formats to match with partial rather than complete correspondence, the system maintains high accuracy for standard formats while gaining adaptability to handle variations, modifications, or extensions of known formats without requiring exact template matches.
Data Source
AI summary
Data is prepared for processing in a data processing system using format information. Data is received that includes records that have values for fields over an input device or port. A target record format for processing the data is determined. Multiple records are analyzed according to validation tests to determine whether the data matches candidate record formats. Each candidate record format specifies a format for each field, and each validation test corresponds to at least one candidate record format. In response to receiving results of the validation tests, the target record format is associated with the data based on at least one of: a candidate record format for which at least a partial match was determined according to at least one validation test, a parsed record format selected according to a data type associated with the data, and a constructed record format generated from an analysis of data characteristics.