Generic Operator Framework for SQL Query Extensibility
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Solution Overview
Problem
Conventional query optimization techniques are complex, time-consuming, and lack the ability for developers to specify procedures for calculating desired results, making it difficult to manage and optimize query execution plans effectively in computing environments.
Innovation Solution
A generic operator framework is introduced to generate new operators for SQL, including a knowledge-based container and optimization rules, which increases the extensibility of the query optimizer by allowing the creation of new operators and applying optimization rules based on a generic operator structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional query optimization techniques are used, then query execution plans can be optimized for efficiency, but the system becomes complex and time-consuming to manage
Solution Approach 1:
The patent segments the query optimization system into distinct components: a query optimizer module, a generic operator framework, and a set of optimization rules. This segmentation allows each component to be developed and managed independently, reducing overall system complexity while maintaining optimization efficiency.
Solution Approach 2:
The patent introduces a universal generic operator framework that can handle multiple types of query operations through a single standardized structure. This framework provides multi-functional capabilities for operator generation, knowledge-based container management, and optimization rule application, eliminating the need for separate specialized modules for each operation type.
2Adaptability or versatility
If manual query optimization management is performed, then optimization can be tailored to specific needs, but it becomes highly complex and time consuming
Solution Approach 1:
The patent implements self-service optimization through automated optimization rules that are applied automatically by the query optimizer. The system includes built-in knowledge-based containers that automatically select and apply appropriate optimization strategies without requiring manual intervention, thereby reducing management time while maintaining adaptability through configurable optimization parameters.
Solution Approach 2:
The patent enables tailored optimization by allowing parameter changes in the generic operator structure and optimization rules. Users can modify optimization parameters such as cost functions, heuristics, and execution strategies without rewriting core system code, providing adaptability while minimizing manual management time through parameter-based configuration.
3Adaptability or versatility
If the query optimizer structure is extended with new operators, then extensibility is improved, but existing functionality may be altered
Solution Approach 1:
The patent uses a nested structure where new operators are encapsulated within the generic operator framework as separate, modular components. The framework contains nested knowledge-based containers that hold operator definitions, allowing new operators to be added without affecting the outer framework structure. This nesting ensures that existing functionality remains stable while enabling extensibility through independent operator modules.
Solution Approach 2:
The patent implements preliminary action through pre-defined optimization rules and generic operator templates that are prepared in advance. When new operators are added, the system automatically applies pre-established optimization patterns and structures, ensuring that existing functionality is preserved while new capabilities are integrated through standardized procedures rather than ad-hoc modifications.
Data Source
AI summary
In accordance with aspects of the disclosure, systems and methods are provided for query optimization including generating a knowledge based container for one or more new operators, building a generic operator structure for the knowledge based container generated for each new operator, and applying optimization rules to each new operator based on the generic operator structure built for each new operator to thereby increase extensibility of the query optimizer using a structured query language (SQL).