Feature Store Lineage Tracking for Consistent Model Development
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Solution Overview
Problem
Maintaining relationships among data for use across multiple models in big data processing systems is resource-intensive and prone to inconsistencies due to the complexity and scale of model development, leading to inefficiencies and potential human errors.
Innovation Solution
A feature store system that integrates tracking and management of features, including their lineage and characteristics, to ensure consistency and availability for training and deployment of models, reducing the likelihood of errors and improving efficiency by providing a centralized repository for features and their metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data relationships are maintained in memory for use across multiple models, then model development efficiency is improved, but resource consumption increases significantly
Solution Approach 1:
The patent extracts and stores data relationships in a persistent feature store database separate from memory, allowing models to access pre-computed features without loading entire datasets into memory. This reduces memory resource consumption while maintaining efficient access to data relationships through the feature store's indexing and caching mechanisms.
Solution Approach 2:
The system performs preliminary computation of data relationships and stores them as reusable features in the feature store before model training begins. This pre-processing eliminates the need to re-compute relationships during model development, improving efficiency while reducing the resource intensity of actual model training operations.
2Stability of the object's composition
If data relationships are maintained across multiple models, then consistency is improved, but human errors increase due to complexity
Solution Approach 1:
The feature store automatically manages data relationships through version control, lineage tracking, and automated validation rules. This self-service capability ensures consistency across models without requiring manual intervention, thereby reducing human errors while maintaining stable data composition across the model development lifecycle.
Solution Approach 2:
The system implements automated feedback mechanisms that validate data relationships and detect inconsistencies across models. When changes are made to features or data relationships, the system automatically notifies affected models and validates compatibility, preventing human errors while maintaining consistency through continuous monitoring and validation.
3Measurement precision
If features are stored with complete lineage information, then data management accuracy is improved, but storage complexity increases
Solution Approach 1:
The patent segments lineage information into hierarchical levels: feature metadata, data source provenance, and transformation history. This segmentation allows the system to store complete lineage information with high accuracy while organizing complexity into manageable, queryable segments that can be accessed at different granularities based on user needs.
Solution Approach 2:
The feature store acts as an intermediary layer between raw data sources and models, managing lineage information through standardized schemas and automated tracking. This intermediary structure simplifies storage complexity by providing a unified interface for lineage management while maintaining detailed accuracy through automated tracking of data provenance and transformations.
Data Source
AI summary
The present application discloses a method, system, and computer system for managing a plurality of features and storing lineage information pertaining to the features. The method includes obtaining one or more datasets, determining a first feature, wherein the first feature is determined based at least in part on the one or more datasets, and storing the first feature in a feature store. The first feature is stored in association with a dataset indication of the one or more datasets from which the first feature is determined. The feature store comprises a plurality of features.