Batch Database Modification System for Distributed Software Updates
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Solution Overview
Problem
Existing database modification processes consume significant computing resources and diminish performance due to the need for repeated rebuilding and removal of databases during updates, especially when handling multiple plugins and patches that apply individual modifications to structural elements.
Innovation Solution
A method and system for batch database modification that identifies and combines multiple alterations to structural elements, resolving redundant or conflicting changes into a single combined alteration, which is then applied as a database statement to update the database structure efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If individual database modifications are applied separately for each software update, then each modification can be applied precisely, but computing resources are significantly consumed and database performance diminishes due to repeated rebuilding and removal operations
Solution Approach 1:
The patent combines multiple individual database modifications into a single batch modification operation. Instead of applying each software update's database alteration separately, the system aggregates multiple ALTER statements into one consolidated batch operation, thereby maintaining modification precision while eliminating repeated database rebuilds and performance degradation.
2Adaptability or versatility
If multiple individual modifications are applied sequentially, then each alteration can be processed independently, but the computational load increases and resource consumption rises
Solution Approach 1:
The system merges multiple independent database modifications into a single batch operation. The patent processes multiple ALTER statements together in one database update cycle, reducing computational overhead and resource consumption while preserving the ability to handle different types of modifications (table additions, column modifications, index creations) within the unified batch process.
3Reliability
If database updates are performed frequently to maintain software currency, then the system stays updated, but database performance diminishes due to repeated modification operations
Solution Approach 1:
The patent implements preliminary action by combining and preparing multiple database modifications into a single batch operation before execution. The system aggregates pending ALTER statements from multiple software updates and applies them together in one consolidated database update, thereby maintaining software currency while minimizing the frequency and impact of database modification operations.
4Adaptability or versatility
If redundant and conflicting alterations are not resolved, then all modifications can be attempted, but the database update process becomes complex and error-prone
Solution Approach 1:
The patent applies preliminary action by resolving redundant and conflicting alterations during the batch combination phase before database execution. The system pre-processes multiple ALTER statements to identify and eliminate conflicts (such as duplicate table creations or contradictory column modifications), thereby maintaining comprehensive modification coverage while simplifying the update process and reducing errors.
Data Source
AI summary
Altering a database structure based on software updates in a distributed computing system can include identifying a plurality of software updates that include alterations to structural elements in the database structure and identifying, for the plurality of software updates, a plurality of alterations corresponding to a first structural element of the structural elements. A combined alteration can be generated by combining the plurality of alterations. A database statement can be generated for altering the first structural element according to the combined alteration. The database structure can then be updated using the database statement. The structural elements can define logical relationships between data stored in the database structure. The alterations can be expressed using a markup language and the database statement can be expressed using a query language.