Expression Pushdown Optimization for Federated Database Query Efficiency
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Solution Overview
Problem
Federated database systems face inefficiencies in extracting and processing data due to incompatibilities between common query languages and data source query languages, leading to excessive data transmission and processing costs, as well as outdated data storage issues.
Innovation Solution
The Expression Pushdown Optimization (EPO) system determines which query processing can be pushed down to data sources by converting target queries into forms supported by each data source, allowing for efficient evaluation of expressions at the data source level, thereby minimizing data transmission and processing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If all data is extracted and stored locally in a federated database system, then query processing can be performed efficiently, but data transmission costs and storage requirements increase significantly
Solution Approach 1:
The patent segments query processing into two parts: expressions that can be pushed down to data sources are evaluated there, while other expressions are evaluated locally after data retrieval. This segmentation allows the system to optimize for each type of expression separately, reducing unnecessary data transmission while maintaining query processing efficiency.
Solution Approach 2:
The system performs preliminary analysis to determine which expressions can be pushed down to data sources before actual query execution. By pre-identifying pushable expressions and converting them to appropriate formats, the system prepares the query in advance to minimize data transmission requirements.
2Loss of energy
If query expressions are pushed down to data sources, then data transmission is reduced, but incompatibilities between query languages prevent pushdown in many cases
Solution Approach 1:
The patent introduces an expression pushdown optimization system that acts as an intermediary between the federated database system and diverse data sources. This intermediary converts expressions from the common query language into formats supported by specific data sources, enabling pushdown optimization while handling language incompatibilities through automated conversion.
Solution Approach 2:
The system changes the parameters of expressions by converting them from one format (common query language) to another format (data source-specific language). This parameter transformation allows expressions to be evaluated at the data source level despite language differences, enabling pushdown optimization across heterogeneous data sources.
3Measurement precision
If manual query development is performed for each data source, then precise data extraction is achieved, but time and cost increase significantly
Solution Approach 1:
The expression pushdown optimization system enables automated query optimization without requiring manual intervention for each data source. The system automatically analyzes expressions, determines pushdown feasibility, performs conversions, and generates optimized queries, allowing the system to serve itself rather than requiring continuous manual configuration.
Solution Approach 2:
The patent creates a universal optimization system that handles multiple data sources with different query languages through a single common interface. This multi-functional system can process expressions for various data sources using the same pushdown optimization mechanism, eliminating the need for separate manual query development for each data source.
Data Source
AI summary
A system for query optimization by a federation engine is provided. When a data source supports a target feature of an expression of a query in the common query language, the system executes a converter for the data source to convert the target feature to the corresponding feature of the data source query language. The system then submits to the data source a query with the expression with the converted target feature so that the expression is evaluated at the data source and receives query results. When a data source does not support the target feature of the expression, the system submits to the data source a query without the expression and evaluates the expression on the query results returned by the data source. The system then combines the query results based on the evaluation of the expression as the query results of the query.