Query Response Time Prediction Using Emulated Database Access Patterns
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Solution Overview
Problem
During application development, predicting query response time for large databases is challenging due to resource constraints and the need for extensive storage, which affects performance and requires efficient testing without additional resource consumption.
Innovation Solution
A system and method that predicts elapsed response time by executing queries on a small database, emulating the database, classifying query access modes, determining access patterns and parameters, and calculating input-output access time using classification-specific techniques to estimate response time for varying database sizes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a fraction of database is used to test the application, then resource consumption is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent creates a copy of the database structure and schema from the production database, then populates it with synthetic data that preserves the statistical properties and access patterns. This copy can be tested with while consuming fewer resources, and the results can predict production behavior accurately.
Solution Approach 2:
The system changes the parameters of the test database by adjusting the data distribution, size, and composition to match the statistical characteristics of the production database. This allows accurate prediction of query response times on large databases while using a smaller test environment.
2Reliability
If large and powerful storage servers are required to store huge mass of data, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential elements needed for accurate testing - the database schema, data distribution patterns, and access characteristics - from the full production database. This extraction allows testing to be performed on a simplified structure without requiring the complete storage infrastructure.
3Measurement precision
If huge records are used for testing, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by pre-generating synthetic data that matches production characteristics before testing begins. The data is prepared in advance with the correct distribution and properties, eliminating the need for time-consuming data loading during the testing phase.
Data Source
AI summary
A system, method and computer program product to predict elapsed response time of a query during an application stage is disclosed. The query is executed over a database and is classified based on a mode of access of the database by the query. The database is emulated to obtain an emulated database. After classification, an access pattern of the database by the query along with one or more parameters is determined. By applying a classification specific technique over the access pattern and the one or more parameters, an input-access time of the query on the emulated database is then calculated to determine the elapsed response time of the query.