Query Language Conversion with Native Commands and Node Trees
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Solution Overview
Problem
Incompatibilities arise when different components within a system support different versions of a query language, leading to operational failures, and direct conversion or backward compatibility approaches are inefficient, particularly due to the need for more processing and memory usage.
Innovation Solution
A hybrid approach using a query conversion system with a tokenizer, parser, code converter, and compatibility library to convert commands between query language versions, ensuring native command support and backward compatibility by creating a second node tree with native or compatibility library functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If direct conversion or backward compatibility approaches are used to handle different query language versions, then compatibility between components is improved, but processing overhead and memory usage increase
Solution Approach 1:
The system performs preliminary actions by pre-parsing the incoming query string into a standardized node tree structure before conversion. This pre-processing step organizes the query components in a uniform format that facilitates efficient conversion to different query language versions, reducing the computational burden during the actual conversion and execution phases
Solution Approach 2:
The system changes parameters by maintaining a mapping between different query language versions and their corresponding node tree structures. By transforming the query representation from version-specific syntax to an abstract node tree and back to the target version, the system achieves compatibility while optimizing processing efficiency through parameter transformation rather than direct complex conversion
2Productivity
If native commands are used instead of backward compatibility commands, then execution performance is improved, but compatibility with older query language versions deteriorates
Solution Approach 1:
The node tree structure serves as an intermediary representation between the incoming query string in any version and the native commands of the current query language version. The conversion system transforms the query into this intermediate node tree format, which can then be efficiently executed using native commands, thereby achieving both high performance and broad compatibility
Solution Approach 2:
The system segments the query processing into distinct phases: parsing the query string into a node tree, converting the node tree to the target query language version, and executing with native commands. This segmentation allows each phase to be optimized independently, enabling the use of efficient native commands while maintaining compatibility through the structured conversion process
Data Source
AI summary
Systems and methods are described for a query conversion system to convert a first query string from a first version of a query language to a second version of the query language. The query conversion system may be associated with a tokenizer and parser, code converter, compatibility library, and a query formatter. The tokenizer and parser may tokenize and parse a query string to create a first node tree with commands. The code converter may parse the first node tree while using the compatibility library to convert the commands and generate a second node tree. The query formatter may create a second query string executable by the second version of the query language.