Data Specification Device for Parallel Aggregation Error Reduction
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Solution Overview
Problem
In information process systems, parallel execution of aggregation jobs can lead to errors in aggregation results due to incorrect data division, causing delays and incorrect calculations, particularly when data is not properly classified during the extraction process.
Innovation Solution
The system specifies data groups for classification during the extraction process, allowing for accurate data division and reducing errors by matching type numbers of values in extraction data with those in aggregation data, ensuring correct data rows are used for aggregation, thereby enabling parallel execution of jobs without errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parallel execution of aggregation jobs is implemented, then processing speed is improved, but errors in aggregation results occur due to incorrect data division
Solution Approach 1:
The patent applies preliminary action by performing data classification and specifying data groups during the extraction process before parallel aggregation execution. Type numbers are assigned to values in advance, and data is divided into specified data groups based on these type numbers, ensuring correct data division is established before parallel processing begins.
Solution Approach 2:
The patent introduces type numbers as an intermediary element that mediates between raw extraction data and aggregation operations. These type numbers serve as classification markers that enable the system to correctly identify and group related data values across different data groups, ensuring accurate aggregation even when data is distributed across multiple parallel processes.
2Ease of operation
If data is not properly classified during extraction, then processing simplicity is maintained, but aggregation results contain errors
Solution Approach 1:
The patent applies parameter changes by introducing type numbers as a new parameter for classifying data values. Instead of requiring complex classification logic, the system changes the data structure by adding type number parameters that automatically identify value types, simplifying the classification process while ensuring accurate aggregation results.
3Reliability
If sequential processing is used, then data accuracy is maintained, but processing time increases
Solution Approach 1:
The patent applies segmentation by dividing the data processing task into separate specified data groups based on type numbers. Each data group can be processed independently in parallel while maintaining data accuracy through the type number classification system, thus reducing processing time without sacrificing reliability.
Data Source
AI summary
A data specification method executed by a computer, the method including obtaining a plurality of data groups, specifying a number of types of a plurality of values included in each of the plurality of data groups, obtaining a result of a calculation process using a plurality of values included in a specified data group, specifying a number of types of the plurality of values included in the specified data group, selecting one or more data groups based on the number of types of the plurality of values included in the specified data group and based on the number of types of the plurality of values included in each of the plurality of data groups, and specifying a corresponding data group corresponding to the specified data group from among the selected one or more data groups.