Multi-language Object Cache for Data Analysis Workbooks
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Solution Overview
Problem
Existing data analysis workbooks are limited by their compatibility with specific programming languages and application programming interfaces (APIs), preventing seamless interoperability and data sharing across different frameworks.
Innovation Solution
The implementation of a system that allows data analysis workbooks to access and manipulate data using multiple programming languages and APIs through language delegates, which cache and convert objects to ensure compatibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data analysis workbooks use specific programming languages and APIs, then data manipulation capabilities are provided, but interoperability between different frameworks is prevented
Solution Approach 1:
The patent introduces language delegates as intermediary components that act as translators between different programming language object representations and a universal base object representation. Each language delegate (e.g., Python delegate, R delegate) converts language-specific objects to a common base object format, enabling interoperability without direct complexity between different language frameworks. This mediator pattern resolves the contradiction by providing adaptability through conversion while containing system complexity within isolated delegate components.
Solution Approach 2:
The system segments the data manipulation functionality into independent language-specific delegates, each handling a specific programming language. This segmentation allows each delegate to be developed and maintained independently, reducing overall system complexity while enabling versatile support for multiple languages. The base object representation serves as a common interface that all delegates implement, providing interoperability without requiring complex integration logic between different language implementations.
2Loss of information
If object conversions between programming languages are performed, then data sharing across frameworks is enabled, but conversion overhead is introduced
Solution Approach 1:
The system performs preliminary action by converting language-specific object representations to a universal base object representation immediately when objects are created or imported into the data analysis workbook. This upfront conversion ensures that data is immediately shareable across different programming language contexts without requiring repeated conversions during subsequent operations. The base object serves as a persistent universal format that eliminates future conversion needs, reducing overall conversion time overhead.
3Adaptability or versatility
If multiple language delegates are implemented, then support for different programming languages is provided, but cache management complexity increases
Solution Approach 1:
The patent merges the caching functionality of multiple language-specific delegates into a single unified global object cache. Instead of maintaining separate caches for each programming language delegate, the system implements one shared cache that stores base object representations accessible by all delegates. This consolidation reduces cache management complexity by eliminating the need to synchronize multiple separate caches while maintaining full language support, as all delegates operate on the same unified cache through the common base object interface.
Data Source
AI summary
Systems and methods provide an interface for accessing a data analysis workbook through which data is accessed and manipulated using a plurality of programming languages and application programming interfaces (APIs). Input data on which one or more data transformations are to be performed within the data analysis workbook is accessed, wherein the input data corresponds to a first object representation of a dataset, and wherein the one or more data transformations require the dataset to be a different, second object representation of the dataset. The second object representation of the dataset can be extracted from the first object representation of the dataset through a first language delegate that manages data associated with the first object representation. The one or more data transformations can be applied to the extracted second object representation of the dataset through a different, second language delegate that manages data associated with the second object representation.