Dynamic ORM Query Translation via Expression Tree Transformation
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Solution Overview
Problem
Conventional approaches to specifying queries in object-relational mapping (ORM) systems are limited to the database schema known at compile time, making it impossible to address dynamic data added by users.
Innovation Solution
A software facility that performs object-relational model queries against databases with fields and tables defined at runtime, using a runtime object syntax expression tree translation architecture called Rosetta, which transforms abstract queries into concrete queries in a target ORM query language like Microsoft LINQ, enabling interaction with dynamic data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional ORM query approaches are used, then queries can be executed against the database, but the queries are limited to the database schema known at compile time and cannot address dynamic data
Solution Approach 1:
The patent implements dynamic query capabilities by allowing the database schema to be modified at runtime through user actions. New tables and columns can be added dynamically, and the ORM system adapts to these changes without requiring recompilation. The query system transitions from a static compile-time schema model to a dynamic runtime schema model, enabling queries against dynamically added data while maintaining the familiar ORM interface.
Solution Approach 2:
The patent introduces an intermediary layer between the user-defined dynamic data and the ORM query system. This intermediary component translates user actions into database schema modifications and bridges the gap between dynamic data structures and the static ORM query framework, enabling seamless integration without requiring fundamental changes to the ORM architecture.
2Productivity
If the database schema is fixed at compile time, then ORM queries can be statically typed and optimized, but user-defined dynamic data cannot be queried
Solution Approach 1:
The patent changes the temporal parameter of schema definition from compile-time to runtime. By allowing schema parameters (tables, columns, data types) to be defined and modified at runtime based on user actions, the system enables flexible data definition while maintaining type safety through dynamic type inference and validation mechanisms in the ORM layer.
3Adaptability or versatility
If dynamic data is added by users, then the database becomes more flexible and adaptable, but conventional ORM queries cannot access this dynamic data
Solution Approach 1:
The patent makes the ORM query system universal by enabling it to handle both traditional static database schemas and dynamic user-defined data through a unified query interface. The same ORM query mechanisms work for both compile-time defined tables and runtime added tables, eliminating the need for separate query systems and maintaining ease of operation while expanding functionality.
Data Source
AI summary
A system can generate an expression tree hierarchy based on a database query that refers to dynamic data of a database having a data model. The dynamic data is undefined in the data model of the database. The system can invoke a process that traverses the expression tree hierarchy to transform the expression tree hierarchy and iteratively or recursively translate multiple expression fragments of the expression tree hierarchy in accordance with the process while maintaining a contextual type stack. A particular iteration or recursion operates on a particular expression fragment of the multiple expression fragments to convert the particular expression fragment into another expression fragment for another expression tree hierarchy.