feature-engineering command group
This information applies to Databricks CLI versions 0.205 and above. The Databricks CLI is in Public Preview.
Databricks CLI use is subject to the Databricks License and Databricks Privacy Notice, including any Usage Data provisions.
The feature-engineering command group within the Databricks CLI allows you to manage features in your Databricks feature store.
databricks feature-engineering create-feature
Create a feature.
databricks feature-engineering create-feature FULL_NAME SOURCE INPUTS FUNCTION TIME_WINDOW [flags]
Arguments
FULL_NAME
The full three-part name (catalog, schema, name) of the feature.
SOURCE
The data source of the feature.
INPUTS
The input columns from which the feature is computed.
FUNCTION
The function by which the feature is computed.
TIME_WINDOW
The time window in which the feature is computed.
Options
--description string
The description of the feature.
--json JSON
The inline JSON string or the @path to the JSON file with the request body.
Examples
The following example creates a feature:
databricks feature-engineering create-feature my_catalog.my_schema.my_feature my_source my_inputs my_function my_time_window --description "My feature description"
databricks feature-engineering delete-feature
Delete a feature.
databricks feature-engineering delete-feature FULL_NAME [flags]
Arguments
FULL_NAME
Name of the feature to delete.
Examples
The following example deletes a feature:
databricks feature-engineering delete-feature my_catalog.my_schema.my_feature
databricks feature-engineering get-feature
Get a feature.
databricks feature-engineering get-feature FULL_NAME [flags]
Arguments
FULL_NAME
Name of the feature to get.
Examples
The following example gets a feature:
databricks feature-engineering get-feature my_catalog.my_schema.my_feature
databricks feature-engineering list-features
List features.
databricks feature-engineering list-features [flags]
Options
--page-size int
The maximum number of results to return.
--page-token string
Pagination token to go to the next page based on a previous query.
Examples
The following example lists all features:
databricks feature-engineering list-features
databricks feature-engineering update-feature
Update a feature's description (all other fields are immutable).
databricks feature-engineering update-feature FULL_NAME UPDATE_MASK SOURCE INPUTS FUNCTION TIME_WINDOW [flags]
Arguments
FULL_NAME
The full three-part name (catalog, schema, name) of the feature.
UPDATE_MASK
The list of fields to update.
SOURCE
The data source of the feature.
INPUTS
The input columns from which the feature is computed.
FUNCTION
The function by which the feature is computed.
TIME_WINDOW
The time window in which the feature is computed.
Options
--description string
The description of the feature.
--json JSON
The inline JSON string or the @path to the JSON file with the request body.
Examples
The following example updates a feature's description:
databricks feature-engineering update-feature my_catalog.my_schema.my_feature description my_source my_inputs my_function my_time_window --description "Updated description"
Global flags
--debug
Whether to enable debug logging.
-h or --help
Display help for the Databricks CLI or the related command group or the related command.
--log-file string
A string representing the file to write output logs to. If this flag is not specified then the default is to write output logs to stderr.
--log-format format
The log format type, text or json. The default value is text.
--log-level string
A string representing the log format level. If not specified then the log format level is disabled.
-o, --output type
The command output type, text or json. The default value is text.
-p, --profile string
The name of the profile in the ~/.databrickscfg file to use to run the command. If this flag is not specified then if it exists, the profile named DEFAULT is used.
--progress-format format
The format to display progress logs: default, append, inplace, or json
-t, --target string
If applicable, the bundle target to use