Database Schedule Module Parallel Execution Logic
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing techniques for upgrading database systems often result in significant downtime due to the need for serial execution of database object modification methods, which can be computationally expensive and time-consuming, leading to prolonged unavailability of database objects during the upgrade process.
Innovation Solution
A computer system with a schedule module that analyzes the original execution logic and generates a modified schedule to enable parallel execution of selected database object modification methods, reducing downtime by executing only necessary components in parallel while maintaining the dependencies and order specified in the original schedule.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If serial execution of database object modification methods is used, then execution order and dependencies are maintained, but downtime is prolonged and productivity decreases
Solution Approach 1:
The patent segments the database object modification methods into different batches and identifies independent tasks within each batch that can be executed in parallel. By dividing the monolithic serial execution into smaller, independent units of work, the system maintains execution order for dependent tasks while enabling concurrent execution of independent tasks, thereby resolving the contradiction between maintaining execution order and improving upgrade speed.
Solution Approach 2:
The patent dynamically adjusts the execution schedule by analyzing dependencies between modification methods and determining which tasks can be executed in parallel at any given moment. This dynamic scheduling approach allows the system to adaptively optimize execution order while enabling parallel processing where safe, thus improving productivity without compromising the reliability of execution order maintenance.
2Productivity
If parallel execution of database object modification methods is implemented, then productivity and upgrade speed improve, but system complexity increases and execution order control becomes difficult
Solution Approach 1:
The patent introduces a schedule modification module as an intermediary that automatically analyzes dependencies, determines parallel execution opportunities, and generates optimized execution schedules. This intermediary component manages the complexity of parallel execution control, allowing the system to benefit from parallel processing while the intermediary handles the intricate scheduling logic, thus improving productivity without proportionally increasing operational complexity.
Solution Approach 2:
The patent changes the execution mode parameter from strictly serial to a hybrid model that allows parallel execution of independent tasks while maintaining serial execution for dependent tasks. By dynamically adjusting execution parameters based on dependency analysis, the system achieves higher productivity through parallel processing without overwhelming complexity, as the parameter changes are guided by automated dependency detection.
3Manufacturing precision
If computationally expensive algorithms are used to modify database objects, then manufacturing precision and data integrity are maintained, but loss of time and downtime increase
Solution Approach 1:
The patent performs preliminary analysis of modification dependencies and identifies parallel execution opportunities before the actual modification process begins. By pre-processing the execution plan and determining which tasks can run concurrently, the system prepares the groundwork for optimized execution, allowing computationally expensive algorithms to be applied accurately while minimizing overall upgrade duration through parallel processing of independent tasks.
Solution Approach 2:
The patent ensures continuous useful action by maintaining parallel execution of independent modification tasks without idle time. While computationally expensive algorithms are applied to ensure data modification accuracy, the system continuously processes multiple independent tasks in parallel rather than sequentially, eliminating waiting time and reducing total upgrade duration while preserving the precision of the modification algorithms.
Data Source
AI summary
An original schedule module configured to receive an original schedule configured to trigger execution of a first original batch of entries including a set of object modification methods and a corresponding set of database objects before triggering execution of a second original batch of entries including a set of object modification methods and a corresponding set of database objects. An analysis module can be configured to determine logic for execution of each entry from the first original batch of entries based on the original schedule. A schedule generator can be configured to define, based on the logic for execution and based on the original schedule, a modified schedule configured to trigger parallel execution of a first modified batch of entries including less than all of the first original batch of entries, and a second modified batch of entries including less than all of the second original batch of entries.