Note
Access to this page requires authorization. You can try signing in or changing directories.
Access to this page requires authorization. You can try changing directories.
The Databricks Feature Engineering Python client (databricks-feature-engineering) provides APIs for working with feature tables and online stores. This page links to the API reference and describes the client packages, including the deprecated legacy databricks-feature-store.
Note
As of version 0.17.0, databricks-feature-store has been deprecated. All existing modules from this package are now available in databricks-feature-engineering version 0.2.0 and later. For information about migrating to databricks-feature-engineering, see Migrate to databricks-feature-engineering.
Compatibility matrix
The package and client you should use depend on where your feature tables are located and what Databricks Runtime ML version you are running, as shown in the following table.
To identify the package version that is built in to your Databricks Runtime ML version, see the Feature Engineering compatibility matrix.
| Databricks Runtime version | For feature tables in | Use package | Use Python client |
|---|---|---|---|
| Databricks Runtime 14.3 ML and above | Unity Catalog | databricks-feature-engineering |
FeatureEngineeringClient |
| Databricks Runtime 14.3 ML and above | Workspace | databricks-feature-engineering |
FeatureStoreClient |
| Databricks Runtime 14.2 ML and below | Unity Catalog | databricks-feature-engineering |
FeatureEngineeringClient |
| Databricks Runtime 14.2 ML and below | Workspace | databricks-feature-store |
FeatureStoreClient |
Note
databricks-feature-engineering<=0.7.0is not compatible withmlflow>=2.18.0. To usedatabricks-feature-engineeringwith MLflow 2.18.0 and above, upgrade todatabricks-feature-engineeringversion 0.8.0 or above.
Release notes
See Databricks Feature Store and legacy Workspace Feature Store release notes.
Feature Engineering Python API reference
See the Feature Engineering Python API reference.
Workspace Feature Store Python API reference (deprecated)
Note
- As of version 0.17.0,
databricks-feature-storehas been deprecated. All existing modules from this package are now available indatabricks-feature-engineeringversion 0.2.0 and later.
For databricks-feature-store v0.17.0, see Databricks FeatureStoreClient in Feature Engineering Python API reference for the latest Workspace Feature Store API reference.
For v0.16.3 and below, use the links in the table to download or display the Feature Store Python API reference. To determine the pre-installed version for your Databricks Runtime ML version, see the compatibility matrix.
| Version | Download PDF | Online API reference |
|---|---|---|
| v0.3.5 to v0.16.3 | Feature Store Python API 0.16.3 reference PDF | Online API reference |
| v0.3.5 and below | Feature Store Python API 0.3.5 reference PDF | Online API reference not available |
Python package
This section describes how to install the Python packages to use Databricks Feature Engineering and Databricks Workspace Feature Store.
Feature Engineering
Note
- As of version 0.2.0,
databricks-feature-engineeringcontains modules for working with feature tables in both Unity Catalog and Workspace Feature Store.databricks-feature-engineeringbelow version 0.2.0 only works with feature tables in Unity Catalog.
The Databricks Feature Engineering APIs are available through the Python client package databricks-feature-engineering. The client is available on PyPI and is pre-installed in Databricks Runtime 13.3 LTS ML and above.
For a reference of which client version corresponds to which runtime version, see the compatibility matrix.
To install the client in Databricks Runtime: