Database Transaction Prediction for Throughput Optimization
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Solution Overview
Problem
Current database transaction execution methods are inefficient, leading to low transaction throughput due to the inability to determine necessary database operation commands in advance, resulting in sequential execution and high network resource consumption.
Innovation Solution
A database operation method and apparatus that uses a prediction algorithm to acquire and record database operation commands and predicted execution data during transaction execution, allowing for advanced determination of the next command and efficient execution of transactions based on locally recorded data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If database operation commands are determined during sequential execution, then transaction execution can proceed with basic logic, but transaction throughput remains low and execution efficiency is poor
Solution Approach 1:
The patent applies preliminary action by executing a prediction algorithm during the transaction execution process to acquire and record all database operation commands that need to be executed in advance. This allows the system to determine the complete set of commands before actual execution, enabling batch processing and significantly improving transaction throughput while reducing execution time.
2Loss of energy
If database operation commands are determined sequentially during execution, then the system can handle conditional logic, but network resource consumption increases
Solution Approach 1:
The prediction algorithm executes in advance during the transaction process to determine all required database operation commands before actual execution. This preliminary determination reduces network resource consumption by minimizing communication overhead between the application server and database during the execution phase, while still handling conditional logic effectively.
3Productivity
If all database operation commands are executed sequentially, then execution accuracy is maintained, but transaction execution efficiency decreases
Solution Approach 1:
The prediction algorithm performs preliminary execution of all database operation commands during the transaction process to acquire predicted execution results. After actual execution, the system compares actual results with predicted results to verify accuracy. This approach maintains reliability through verification while significantly improving execution efficiency by enabling batch processing of pre-determined commands.
Solution Approach 2:
The system implements feedback by comparing actual execution results with predicted execution results after transaction completion. This feedback mechanism verifies the accuracy of the prediction algorithm and ensures transaction execution correctness, maintaining reliability while enabling efficient batch processing of commands.
Data Source
AI summary
The disclosure provides a database operation method and apparatus. The method comprises: sequentially acquiring, during a process of executing a target transaction by an application server, database operation commands executed by the application server for the target transaction; executing a prediction algorithm on the database operation commands, returning predicted execution results to the application server so that the application server determines a next to-be-executed database operation command, and locally recording the database operation commands and predicted execution data generated from the executing of the prediction; and when acquiring a transaction commit command regarding the target transaction, controlling a database corresponding to the application server to actually execute the target transaction according to the locally recorded database operation commands and the predicted execution data. The disclosed embodiments improve transaction execution efficiency and increase transaction throughput.