Registry
The Feast feature registry is a central catalog of all feature definitions and their related metadata. Feast uses the registry to store all applied Feast objects (e.g. Feature views, entities, etc). It allows data scientists to search, discover, and collaborate on new features. The registry exposes methods to apply, list, retrieve and delete these objects, and is an abstraction with multiple implementations.
Feast comes with built-in file-based and sql-based registry implementations. By default, Feast uses a file-based registry, which stores the protobuf representation of the registry as a serialized file in the local file system. For more details on which registries are supported, please see Registries.
Updating the registry
We recommend users store their Feast feature definitions in a version controlled repository, which then via CI/CD automatically stays synced with the registry. Users will often also want multiple registries to correspond to different environments (e.g. dev vs staging vs prod), with staging and production registries with locked down write access since they can impact real user traffic. See Running Feast in Production for details on how to set this up.
Deleting objects from the registry
Simply removing a feature definition from your code and running feast apply or FeatureStore.apply() does not delete the object from the registry. You must explicitly delete objects using the dedicated delete methods or CLI commands.
Using the CLI
The simplest way to delete objects is using the feast delete command:
# Delete any Feast object by name
feast delete my_feature_view
feast delete my_entity
feast delete my_feature_serviceSee the CLI documentation for more details.
Using the Python SDK
To delete objects programmatically, use the explicit delete methods provided by the FeatureStore class:
Deleting feature views
Deleting feature services
Deleting entities, data sources, and other objects
For entities, data sources, and other registry objects, you can use the registry methods directly:
Accessing the registry from clients
Users can specify the registry through a feature_store.yaml config file, or programmatically. We often see teams preferring the programmatic approach because it makes notebook driven development very easy:
Option 1: programmatically specifying the registry
Option 2: specifying the registry in the project's feature_store.yaml file
feature_store.yaml fileInstantiating a FeatureStore object can then point to this:
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