Adaptive Query Partitioning for Database Response Latency
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Solution Overview
Problem
Current database systems face inefficiencies and delays when handling large data sets, leading to poor responsiveness and the potential for stale data, particularly in environments like healthcare where timely data access is critical.
Innovation Solution
A computerized method and system that uses adaptive query modification to partition data based on selected fields, determining partitioning values to restrict the data set size within a predetermined range, thereby optimizing query performance and minimizing data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a query requests a large data set from a database, then the user can access comprehensive information, but the system experiences delays and poor responsiveness
Solution Approach 1:
The patent divides a large data set into smaller partitions based on selected fields and partitioning values. Instead of returning the entire data set in one query, the system segments it into manageable chunks that can be processed and returned more quickly, reducing the overall query response time while still providing comprehensive information through multiple smaller responses.
2Loss of information
If the database system processes and transfers large data sets, then complete information is available to the user, but the burden on the database management system increases and data transfer is maximized
Solution Approach 1:
The patent extracts only the necessary portion of the data set based on partitioning values and predetermined size ranges. Instead of transferring the entire large data set, the system extracts and returns only the relevant partitions that meet the specified criteria, reducing data transfer burden while maintaining data completeness for the requested information.
3Quantity of substance
If the system returns the entire data set in one response, then the user receives all information at once, but the user interface may not have sufficient display capabilities to handle large data sets
Solution Approach 1:
The system segments the large data set into smaller partitions that are sized appropriately for display capabilities. Each partition contains a manageable amount of information that can be easily rendered on various user interfaces, while the segmentation allows users to navigate through multiple partitions to access the complete information set, improving ease of operation across different display devices.
Data Source
AI summary
Systems and methods are presented for retrieving records from a database and presenting them to a user through a timely and efficient query restricting process. The query request is then modified through the use of a determined partitioning field and a modified query which partitions the field relative to a partitioning value. Records are retrieved from the database. A small set of records is presented to the user, as is a prompt to retrieve more records. An application which receives query requests determines: restricting fields, partition size and whether or not the partition is within a predetermined range. The application returns a data set and receives requests for more records. These systems and methods provide a storage efficient solution that is particularly useful for maintaining a time efficient user response for a dynamic database.