Expression Macros for Database Query Optimization
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Solution Overview
Problem
Database query languages like SQL face inefficiencies in processing queries due to resource-intensive calculations executed row by row, leading to performance issues and reduced accuracy, especially in complex calculations and aggregations.
Innovation Solution
Implementing expression macros (EMs) within queries to enable aggregation before calculation, allowing for flexible order of operations and optimizing query processing by transforming raw parse trees into consumable parse trees for efficient execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If calculations are executed row by row in SQL, then calculations can be performed close to the data, but processing power and time requirements increase significantly
Solution Approach 1:
The patent applies preliminary action by performing aggregation operations before calculations. The system rewrites query expressions to execute GROUP BY and aggregation functions first, then performs calculations on the aggregated results rather than on individual rows. This is achieved through expression macro expansion that transforms calculation expressions to operate on aggregated data, significantly reducing the number of rows processed and improving processing efficiency.
2Manufacturing precision
If complex calculations are performed row by row, then detailed calculations can be executed, but the impact on processing performance increases
Solution Approach 1:
The patent applies segmentation by dividing the query processing into distinct phases: aggregation phase and calculation phase. The expression macro mechanism segments the original row-by-row calculation into a two-stage process where data is first aggregated into grouped results, then calculations are performed on these aggregated results. This segmentation maintains calculation precision while dramatically improving performance by reducing the data volume subjected to complex calculations.
3Reliability
If SQL processes calculations in traditional order, then standard query processing is maintained, but flexibility in order of operations is reduced
Solution Approach 1:
The patent applies dynamics by introducing expression macros that enable dynamic reordering of query operations. The system maintains compatibility with standard SQL processing while allowing flexible operation ordering through macro expansion. The query optimizer can dynamically choose to expand expression macros and reorder operations based on the specific query characteristics, data distribution, and performance requirements, providing adaptability without sacrificing standard processing reliability.
Data Source
AI summary
Implementations of the present disclosure include receiving a query, the query including an expression macro (EM), processing the query to provide a raw parse tree, the raw parse tree including an initial node representative of the EM, retrieving metadata corresponding to the EM, the metadata including a definition string, replacing the initial node with a node based on the definition string to provide a consumable parse tree, and executing the query within the database system using the consumable parse tree to provide a query result.