Classification Model Access Path Selection
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Solution Overview
Problem
Modern database systems face inefficiencies in selecting the optimal access path for high-cost and complex queries, leading to resource wastage and poor query performance due to the elimination of potential paths without proper cost estimation, especially when costs appear infinite or are poorly differentiated.
Innovation Solution
A computer-implemented method is introduced that builds a classification model to identify the lowest cost access path by generating an access map, collecting data for each potential path, classifying queries, and selecting the most efficient path based on estimated costs, thereby preventing the dropping of more efficient paths and improving overall database system efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional cost-based optimization eliminates potential access paths when costs appear infinite or are poorly differentiated, then device complexity is reduced, but query performance deteriorates due to loss of potentially efficient paths
Solution Approach 1:
The system performs preliminary actions by generating multiple potential access paths and collecting cost data for each path before making the final selection. This includes building an access map, collecting data for each potential access path, and using a classification model to identify the lowest cost path, rather than immediately eliminating paths with infinite or poorly differentiated costs.
Solution Approach 2:
A classification model is introduced as an intermediary between cost estimation and access path selection. This model collects data for each potential access path and classifies them to identify the lowest cost path, acting as a mediator that resolves the uncertainty in cost differentiation and prevents premature elimination of efficient paths.
2Measurement precision
If the system evaluates all potential access paths with proper cost estimation, then measurement precision of path costs is improved, but loss of time increases due to extended evaluation process
Solution Approach 1:
The system performs preliminary cost data collection and classification for all potential access paths before query execution. By building the access map and collecting cost data in advance, the system achieves precise cost measurement without extending the actual query processing time, as the classification model is prepared beforehand.
Solution Approach 2:
The classification model serves itself by automatically collecting data for each potential access path and classifying them to identify the lowest cost path. This self-service mechanism eliminates the need for manual or iterative cost estimation, achieving both high measurement precision and efficient time utilization.
3Manufacturing precision
If the system uses a classification model to identify the lowest cost access path, then manufacturing precision of path selection is improved, but device complexity increases due to additional model components
Solution Approach 1:
The classification model acts as an intermediary layer between the access map generation and final path selection. It collects data for each potential access path and classifies them to identify the lowest cost path, providing precise path selection while managing complexity through a structured intermediate processing stage.
Solution Approach 2:
The system segments the access path selection process into distinct stages: generating the access map, collecting data for each potential path, classifying the paths using the classification model, and selecting the lowest cost path. This segmentation improves selection accuracy by addressing each aspect separately while managing overall system complexity.
Data Source
AI summary
A computer-implemented method selects an access path for high cost and/or complex queries. The method includes building a classification model configured to identify a lowest cost access path. The method further includes receiving a query, where the query is configured to retrieve a set of data from a database. The method also includes generating an access map for the query, where the access map includes one or more potential access paths to execute the query. The method includes collecting, for the query, a set of data for each potential access path. The method further includes classifying, by the classification model, the query. The method also includes selecting a first access path of the one or more potential access paths and executing the query.