FeatureStoreOperations Class
FeatureStoreOperations.
You should not instantiate this class directly. Instead, you should create an MLClient instance that instantiates it for you and attaches it as an attribute.
- Inheritance
-
azure.ai.ml.operations._workspace_operations_base.WorkspaceOperationsBaseFeatureStoreOperations
Constructor
FeatureStoreOperations(operation_scope: OperationScope, service_client: AzureMachineLearningWorkspaces, all_operations: OperationsContainer, credentials: TokenCredential | None = None, **kwargs: Dict)Parameters
| Name | Description |
|---|---|
|
operation_scope
Required
|
|
|
service_client
Required
|
|
|
all_operations
Required
|
|
|
credentials
|
Default value: None
|
Methods
| begin_create |
Create a new FeatureStore. Returns the feature store if already exists. |
| begin_delete |
Delete a FeatureStore. |
| begin_provision_network |
Triggers the feature store to provision the managed network. Specifying spark enabled as true prepares the feature store managed network for supporting Spark. |
| begin_update |
Update friendly name, description, online store connection, offline store connection, materialization identities or tags of a feature store. |
| get |
Get a feature store by name. |
| list |
List all feature stores that the user has access to in the current resource group or subscription. |
begin_create
Create a new FeatureStore.
Returns the feature store if already exists.
begin_create(feature_store: FeatureStore, *, grant_materialization_permissions: bool = True, update_dependent_resources: bool = False, **kwargs: Dict) -> LROPoller[FeatureStore]Parameters
| Name | Description |
|---|---|
|
feature_store
Required
|
FeatureStore definition. |
Keyword-Only Parameters
| Name | Description |
|---|---|
|
grant_materialization_permissions
|
Whether or not to grant materialization permissions. Defaults to True. |
|
update_dependent_resources
|
Whether or not to update dependent resources. Defaults to False. |
Returns
| Type | Description |
|---|---|
|
An instance of LROPoller that returns a FeatureStore. |
begin_delete
Delete a FeatureStore.
begin_delete(name: str, *, delete_dependent_resources: bool = False, **kwargs: Any) -> LROPoller[None]Parameters
| Name | Description |
|---|---|
|
name
Required
|
Name of the FeatureStore |
Keyword-Only Parameters
| Name | Description |
|---|---|
|
delete_dependent_resources
|
Whether to delete resources associated with the feature store, i.e., container registry, storage account, key vault, and application insights. The default is False. Set to True to delete these resources. |
Returns
| Type | Description |
|---|---|
|
A poller to track the operation status. |
begin_provision_network
Triggers the feature store to provision the managed network. Specifying spark enabled as true prepares the feature store managed network for supporting Spark.
begin_provision_network(*, feature_store_name: str | None = None, include_spark: bool = False, **kwargs: Any) -> LROPoller[ManagedNetworkProvisionStatus]Keyword-Only Parameters
| Name | Description |
|---|---|
|
feature_store_name
|
Name of the feature store. |
|
include_spark
|
Whether to include spark in the network provisioning. Defaults to False. |
Returns
| Type | Description |
|---|---|
|
An instance of LROPoller. |
begin_update
Update friendly name, description, online store connection, offline store connection, materialization identities or tags of a feature store.
begin_update(feature_store: FeatureStore, *, grant_materialization_permissions: bool = True, update_dependent_resources: bool = False, **kwargs: Any) -> LROPoller[FeatureStore]Parameters
| Name | Description |
|---|---|
|
feature_store
Required
|
FeatureStore resource. |
Keyword-Only Parameters
| Name | Description |
|---|---|
|
grant_materialization_permissions
|
Whether or not to grant materialization permissions. Defaults to True. |
|
update_dependent_resources
|
gives your consent to update the feature store dependent resources. Note that updating the feature store attached Azure Container Registry resource may break lineage of previous jobs or your ability to rerun earlier jobs in this feature store. Also, updating the feature store attached Azure Application Insights resource may break lineage of deployed inference endpoints this feature store. Only set this argument if you are sure that you want to perform this operation. If this argument is not set, the command to update Azure Container Registry and Azure Application Insights will fail. |
|
application_insights
|
Application insights resource for feature store. Defaults to None. |
|
container_registry
|
Container registry resource for feature store. Defaults to None. |
Returns
| Type | Description |
|---|---|
|
An instance of LROPoller that returns a FeatureStore. |
get
Get a feature store by name.
get(name: str, **kwargs: Any) -> FeatureStoreParameters
| Name | Description |
|---|---|
|
name
Required
|
Name of the feature store. |
Keyword-Only Parameters
| Name | Description |
|---|---|
|
grant_materialization_permissions
|
Whether or not to grant materialization permissions. Defaults to True. |
|
update_dependent_resources
|
Whether or not to update dependent resources. Defaults to False. |
Returns
| Type | Description |
|---|---|
|
The feature store with the provided name. |
Exceptions
| Type | Description |
|---|---|
|
Raised if the corresponding name and version cannot be retrieved from the service. |
list
List all feature stores that the user has access to in the current resource group or subscription.
list(*, scope: str = 'resource_group', **kwargs: Dict) -> Iterable[FeatureStore]Keyword-Only Parameters
| Name | Description |
|---|---|
|
scope
|
scope of the listing, "resource_group" or "subscription", defaults to "resource_group" |
Returns
| Type | Description |
|---|---|
|
An iterator like instance of FeatureStore objects |
Azure SDK for Python