Data Consumption Efficiency Program for Processor Bottleneck Resolution
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Solution Overview
Problem
Processor performance is adversely affected by unnecessary data exchange between applications and databases, as data requests often return more data than is actually needed, leading to performance degradation.
Innovation Solution
A method and system, including a Data Consumption Efficiency (DCE) program, that analyzes the utilization of data by determining the amount of data received from a data source and identifying the portion used by a data-consuming program, producing reports on data usage metrics to optimize processor performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data requests return more data than is actually needed, then data completeness is improved, but processor performance deteriorates
Solution Approach 1:
The patent extracts only the necessary data fields from the database query results and transmits them to the client application. By using selective field retrieval instead of retrieving all available data, the system maintains data completeness for the fields that are actually needed while significantly reducing the overall data volume transferred and processed, thereby resolving the contradiction between data completeness and processor performance.
Solution Approach 2:
The patent segments the data retrieval process by allowing the client application to specify which particular fields or data segments are needed. The system then retrieves only those segmented portions of data from the database rather than the entire dataset, enabling both complete information for required fields and improved processing efficiency by excluding unnecessary data.
2Loss of information
If more data is received from data sources, then data availability is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by having the client application define its data requirements in advance before the data retrieval operation executes. The application specifies which fields are needed, and the system uses this pre-defined information to construct targeted queries that retrieve only the necessary data, thereby reducing processing time while ensuring data availability for the required fields.
Solution Approach 2:
The system extracts only the necessary data fields based on pre-defined requirements rather than retrieving all available data. This selective extraction approach ensures that data availability is maintained for the fields the application needs while significantly reducing the total data volume that requires processing, thus decreasing processing time.
3Adaptability or versatility
If data exchange between applications uses APIs, then system connectivity is improved, but data processing load increases
Solution Approach 1:
The patent modifies API data exchange by implementing selective field retrieval where the consuming application specifies exactly which data fields are needed. The API then extracts and transmits only those necessary fields from the data source, reducing the data processing load on servers and clients while maintaining full system connectivity and adaptability through the standardized API interface.
Solution Approach 2:
The patent changes the parameters of data exchange by allowing the application to define the specific field selection criteria as query parameters. This enables the API to adapt its data retrieval behavior based on the consuming application's needs, maintaining versatile connectivity while reducing processing load by customizing the data volume and type transferred for each API call.
Data Source
AI summary
One or more processors determine a first amount of data that was provided to a program by a data source. One or more processors analyze a degree of usage of the first amount of data by the program. One or more processors determine a second amount of data that was used by the program based, at least in part, on the degree of usage. The second amount of data is a portion of the first amount of data.