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Awesome GitHub RepositoriesRequest-Time Data Sources
Input columns supplied alongside entity rows or DataFrames so on-demand transformations can incorporate values provided at query time.
Distinct from Row-Level Feature Transformations: Distinct from Row-Level Feature Transformations: focuses on the data source mechanism (passing request-time columns) rather than the transformation logic itself.
Explore 1 awesome GitHub repository matching data & databases · Request-Time Data Sources. Refine with filters or upvote what's useful.
Awesome Request-Time Data Sources GitHub Repositories
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- feast-dev/feast
feast-dev/feast
6,727在 GitHub 上查看Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma
Feast supplies input columns alongside entity rows or entity DataFrames so transformations can incorporate values provided at query time.
Pythonbig-datadata-engineeringdata-quality
