Interoperable Containerization for Feature Frameworks

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Solution Overview

Problem

Enterprise-scale feature engineering faces significant scaling issues in containerized environments, leading to inefficiencies and sub-optimal performance due to compatibility challenges between different data processing frameworks.

Innovation Solution

The use of interoperable containers that convert and transform data into engineered features, allowing seamless communication and operation across various data frameworks by connecting to existing frameworks, retrieving feature values, and providing them to target frameworks for operations like learning or analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If different data processing frameworks are used for feature engineering, then versatility and adaptability are improved, but compatibility issues and system complexity increase

Engineering Contradiction:

Improveframework compatibilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces a containerization layer as an intermediary between different data processing frameworks. Each framework operates within its own containerized environment, which handles compatibility and communication protocols. This mediator layer enables multiple frameworks to coexist and interact without direct integration challenges, thus improving versatility while managing system complexity through standardized interfaces.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system segments different data processing frameworks into separate containerized units. Each framework is encapsulated in its own container with isolated dependencies and configurations. This segmentation allows each framework to maintain its unique characteristics and requirements while being part of a larger integrated system, resolving the contradiction between framework diversity and system complexity.

Inventive Principle:

Principle #1Segmentation

2Productivity

If feature engineering operations are performed across multiple frameworks, then functionality and insights are improved, but computational overhead and processing time increase

Engineering Contradiction:

Improvefeature engineering capabilityVSAvoidprocessing time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent implements a registry or catalog of pre-configured containerized framework components that can be selected and deployed based on specific feature engineering needs. Rather than setting up and configuring frameworks ad hoc, the preliminary preparation of standardized, pre-integrated container images enables rapid deployment and reduces the time required to perform feature engineering operations across multiple frameworks.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The containerization approach creates universal execution environments that can host multiple data processing frameworks with a single standardized interface. This multi-functionality allows the system to perform diverse feature engineering operations across different frameworks without requiring separate infrastructure setups for each framework, thereby improving productivity while minimizing the time loss associated with framework-specific configurations.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Adaptability or versatility

If ad hoc development is performed to ensure framework compatibility, then interoperability is improved, but development complexity and maintenance burden increase

Engineering Contradiction:

Improveframework interoperabilityVSAvoiddevelopment ease

Core Design Contradiction:

Adaptability or versatilityVSEase of manufacture

Solution Approach 1:

The patent utilizes container images as reusable templates or copies of configured framework environments. Once a containerized framework setup is created and tested for compatibility, it can be copied and deployed multiple times across different contexts without requiring reconfiguration. This copying mechanism standardizes interoperability solutions and eliminates the need for repeated ad hoc development, thereby improving framework interoperability while reducing development complexity and maintenance burden.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS12299428B2Interoperable containerization for feature framework

Publication Date: 2025.05.13 CAPITAL ONE SERVICES LLC

AI summary

A method includes obtaining a container image associated with a target framework, a built distribution including a feature conversion class and a set of transform classes, and a configuration package. The method also includes executing the executables in a sequence indicated by the configuration package in a container based on the container image and generating an intermediate data structure by providing values of a source data framework to a feature conversion object constructed from the feature conversion class. The method also includes obtaining an identifier of a feature synthesis operation indicating the set of transform classes and, in response to obtaining the identifier of the feature synthesis operation, generating a transform output by providing a set of values of the intermediate data structure to a set of transform objects constructed from the set of transform classes.