Data Warehouse Migration via Abstract Syntax Tree Canonicalization
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Solution Overview
Problem
Current data warehouse migration processes are complex, time-consuming, and costly due to the need for manual conversion of code between different vendor platforms, often lacking documentation and resulting in errors and incompatibilities.
Innovation Solution
A system and method utilizing a processing subsystem with modules for parsing, canonicalization, tree optimization, and input translation to automatically convert and optimize SQL constructs between different syntactical dialects, ensuring compatibility and reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual conversion of code between different vendor platforms is performed, then compatibility with destination platform is achieved, but time consumption and cost increase significantly
Solution Approach 1:
The patent introduces an intermediary translation system that includes a parser, abstract syntax tree generator, and code generator. This intermediary automatically converts source platform code to destination platform code through standardized intermediate representations, eliminating the need for manual conversion while ensuring platform compatibility.
Solution Approach 2:
The patent replaces the mechanical manual process of code conversion with an automated computational system. The translation system uses domain-specific language parsers and algorithmic code generation to substitute human manual effort, dramatically reducing migration time while maintaining compatibility.
2Ease of manufacture
If manual conversion of code is performed by multiple people, then code conversion is completed, but accuracy decreases due to lack of standardization
Solution Approach 1:
The patent creates a universal translation system that handles multiple source and destination platforms through a common intermediate representation. This single standardized system replaces multiple manual conversion processes, ensuring consistent and accurate conversions across different platform combinations without relying on individual converter expertise.
Solution Approach 2:
The patent replaces human manual conversion processes with an automated computational translation system. This substitution eliminates variability in human performance and ensures standardized, accurate code conversion through algorithmic processing rather than manual intervention.
3Reliability
If features and constructs from source platform are preserved in migration, then functionality is maintained, but compatibility with destination platform is compromised
Solution Approach 1:
The patent uses an intermediary translation system that acts as a mediator between source and destination platforms. The system parses source code, converts it to an abstract syntax tree, and generates destination platform code that preserves the original functionality while adapting to destination platform constraints and features.
Data Source
AI summary
The system includes a parsing module to receive one or more input constructs from a source database in a first syntactical dialect, parse the one or more input constructs received in the first syntactical dialect using an external domain specific language parser, converts the one or more input constructs upon parsing into an abstract syntax tree corresponding to the first syntactical dialect of the source database. A canonicalization module transforms the abstract syntax tree into a canonical abstract syntax tree by utilizing a library of a plurality of operators and expressions corresponding to the first syntactical dialect. A tree optimization module optimizes the canonical abstract syntax tree by utilizing a set of optimization rules. An input translation module converts the canonical abstract syntax tree into an output code corresponding to a second syntactical dialect associated with a target database for compatibility using a translation layer.