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title titleSuffix description services ms.service ms.subservice ms.topic author ms.author ms.reviewer ms.date ms.custom
CLI (v2) feature store YAML schema
Azure Machine Learning
Reference documentation for the CLI (v2) feature store YAML schema.
machine-learning
machine-learning
mldata
reference
fbsolo-ms1
franksolomon
qiax
05/23/2023
cliv2, build-2023

CLI (v2) feature store YAML schema

[!INCLUDE cli v2]

[!INCLUDE schema note]

YAML syntax

Key Type Description Allowed values Default value
$schema string The YAML schema. If you use the Azure Machine Learning VS Code extension to author the YAML file, including $schema at the top of your file enables you to invoke schema and resource completions.
name string Required. Name of the feature store.
compute_runtime object The compute runtime configuration used for materialization job.
compute_runtime.spark_runtime_version string The Azure Machine Learning Spark runtime version. 3.2 3.2
offline_store object
offline_store.type string Required if offline_store is provided. The type of offline store. Only data lake gen2 type of storage is supported. azure_data_lake_gen2
offline_store.target string Required if offline_store is provided. The datalake Gen2 storage URI in the format of /subscriptions/<subscription_id>/resourceGroups/<resource_group>/providers/Microsoft.Storage/storageAccounts/<account>/blobServices/default/containers/<container>.
materialization_identity object The user-assigned managed identity that used for the materialization job. This identity needs to be granted necessary roles to access Feature Store service, the data source and the offline storage.
materialization_identity.client_id string The client ID for your user-assigned managed identity.
materialization_identity.resource_id string The resource ID for your user-assigned managed identity.
materialization_identity.principal_id string the principal ID for your user-assigned managed identity.
description string Description of the feature store.
tags object Dictionary of tags for the feature store.
display_name string Display name of the feature store in the studio UI. Can be nonunique within the resource group.
location string The location of the feature store. The resource group location.
resource_group string The resource group containing the feature store. If the resource group doesn't exist, a new one is created.

You can include other workspace properties.

Remarks

The az ml feature-store command can be used for managing Azure Machine Learning feature store workspaces.

Examples

Examples are available in the examples GitHub repository. Some common examples are shown in below.

YAML basic

$schema: http://azureml/sdk-2-0/FeatureStore.json
name: mktg-feature-store
location: eastus

YAML with offline store configuration

$schema: http://azureml/sdk-2-0/FeatureStore.json
name: mktg-feature-store

compute_runtime:
    spark_runtime_version: 3.2

offline_store:
    type: azure_data_lake_gen2
    target: /subscriptions/<sub-id>/resourceGroups/<rg>/providers/Microsoft.Storage/storageAccounts/<account_name>/blobServices/default/containers/<container_name>

materialization_identity:
    client_id: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
    resource_id: /subscriptions/<sub-id>/resourceGroups/<rg>/providers/Microsoft.ManagedIdentity/userAssignedIdentities/<uai-name>

# Many of workspace parameters will also be supported:
location: eastus
display_name: marketing feature store
tags:
  foo: bar

Next steps