API
Contents
Credentials configuration
To be able to read data from different data sources, you need to pass
Starting the client
Once your Python environment is ready, run:
Default naming rules
Feature Store is configured to adhere to the following restrictions on
Authentication
Feature Store CLI provides 3 forms of authentication:
Permissions
Permissions determine the level of access that a user has to various components of the Feature Store. For example, depending on the level of permission granted, a user may be authorized to edit feature sets, while another user with limited view-only permission can only observe the feature set.
Projects API
Listing projects
Schema API
A schema is extracted from a [data
Feature set API
Registering a feature set
Feature API
Feature statistics
Ingest API
Feature store ensures that data for each specific feature set does not
Ingest history API
Getting the ingestion history
Retrieve API
To retrieve the data, first run:
Jobs API
Listing jobs
Create new feature set version API
A feature set is a collection of features. Users can create a new version of an existing feature set for various reasons.
Asynchronous methods
Several methods in the Feature Store Client API have asynchronous
Spark dependencies
If you want to interact with Feature Store from a Spark session, several
Recommendation API
A Recommendation API can be used to suggest personalized recommendations based on the data stored in the feature sets.
Feature set schedule API
You can schedule an ingestion job from Feature Store by using API
Feature view API
Creating a feature view
Feature set review API
The feature set review process involves the reviewer's acceptance. Depending on the system configuration, all feature sets or only sensitive ones may be subject to review.
Dashboard API
Dashboard provides a short summary about the usage of Feature store.
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