Dynamic Database Query Processing with Multi-Stage Computation
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Solution Overview
Problem
Database systems face significant load and high computation costs when processing open database requests with broad parameter ranges, requiring efficient mechanisms for large data look-ups and dynamic data computation.
Innovation Solution
A dynamic processing method involving a computation engine that evaluates static and dynamic data in multiple stages to efficiently compute and return database responses, including initial incomplete, intermediate completed, and finalized result sets, with optional adjustment of dynamic data pieces based on rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If open database requests with broad parameter ranges are processed, then comprehensive data retrieval is achieved, but significant load on database server and high computation resources are consumed
Solution Approach 1:
The patent segments the database processing into multiple stages: first retrieving static data independently, then dynamically computing only the necessary data pieces based on search parameters. This segmentation allows the system to handle broad parameter ranges by processing data in manageable chunks rather than all at once, reducing peak computation resource consumption while maintaining comprehensive retrieval capability.
Solution Approach 2:
The system performs preliminary retrieval of static data before dynamic computation. By pre-fetching and caching static data that doesn't change frequently, the system reduces the computation burden during the actual query processing, allowing comprehensive data retrieval without consuming excessive resources at any single moment.
2Measurement precision
If dynamic computing is performed to determine response records based on rules and underlying basic data, then accurate and up-to-date responses are produced, but computation resources and response times increase significantly
Solution Approach 1:
The patent divides dynamic computing into computing only specific data pieces that are actually needed for the current search parameters, rather than computing all possible data. This selective computation maintains response accuracy while significantly reducing computation time and resources compared to comprehensive dynamic computing.
Solution Approach 2:
The system performs partial dynamic computing - only computing the specific data pieces necessary for the current query rather than all possible data. This partial action approach maintains sufficient response accuracy for the given search parameters while avoiding the excessive computation time that would result from computing all possible data pieces.
3Adaptability or versatility
If multiple back-and-forth communications occur between computation engine and database during query processing, then dynamic data computation can be performed, but response time and resource consumption increase
Solution Approach 1:
The patent merges the retrieval of static data and the computation of dynamic data pieces into a single integrated processing pass. Instead of multiple separate communications between the computation engine and database, the system combines these operations, reducing communication overhead and response time while maintaining the capability to perform dynamic data computation.
Data Source
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AI summary
A computation engine dynamically computes results in response to a database request indicating at least one search parameter. The computation engine determines, based on an initial result database, an initial incomplete result set with a number of results which include static data pieces that correspond to the at least one search parameter; computes at least one dynamic data piece for each result in the initial incomplete result set based on a number of dynamic computation rules, thereby obtaining an intermediate completed result set, wherein each result of the inter-mediate completed result set includes the at least one static data piece and the computed at least one dynamic data piece; computes an adjustment of the at least one dynamic data piece for at least a sub-set of the intermediate completed result set based on a number of adjustment computation rules, thereby obtaining a finalized completed result set; and returns at least a subset of the finalized completed result set to the client.