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Featurestore(
featurestore_name: str,
project: Optional[str] = None,
location: Optional[str] = None,
credentials: Optional[google.auth.credentials.Credentials] = None,
)
Managed featurestore resource for Vertex AI.
Inheritance
builtins.object > google.cloud.aiplatform.base.VertexAiResourceNoun > builtins.object > google.cloud.aiplatform.base.FutureManager > google.cloud.aiplatform.base.VertexAiResourceNounWithFutureManager > FeaturestoreMethods
Featurestore
Featurestore(
featurestore_name: str,
project: Optional[str] = None,
location: Optional[str] = None,
credentials: Optional[google.auth.credentials.Credentials] = None,
)
Retrieves an existing managed featurestore given a featurestore resource name or a featurestore ID.
Example Usage:
my_featurestore = aiplatform.Featurestore(
featurestore_name='projects/123/locations/us-central1/featurestores/my_featurestore_id'
)
or
my_featurestore = aiplatform.Featurestore(
featurestore_name='my_featurestore_id'
)
Name | Description |
featurestore_name |
str
Required. A fully-qualified featurestore resource name or a featurestore ID. Example: "projects/123/locations/us-central1/featurestores/my_featurestore_id" or "my_featurestore_id" when project and location are initialized or passed. |
project |
str
Optional. Project to retrieve featurestore from. If not set, project set in aiplatform.init will be used. |
location |
str
Optional. Location to retrieve featurestore from. If not set, location set in aiplatform.init will be used. |
credentials |
auth_credentials.Credentials
Optional. Custom credentials to use to retrieve this Featurestore. Overrides credentials set in aiplatform.init. |
delete_entity_types
delete_entity_types(entity_type_ids: List[str], sync: bool = True)
Deletes entity_type resources in this Featurestore given their entity_type IDs. WARNING: This deletion is permanent.
Name | Description |
entity_type_ids |
List[str]
Required. The list of entity_type IDs to be deleted. |
sync |
bool
Optional. Whether to execute this deletion synchronously. If False, this method will be executed in concurrent Future and any downstream object will be immediately returned and synced when the Future has completed. |
get_entity_type
get_entity_type(entity_type_id: str)
Retrieves an existing managed entityType in this Featurestore.
Name | Description |
entity_type_id |
str
Required. The managed entityType resource ID in this Featurestore. |
list_entity_types
list_entity_types(filter: Optional[str] = None, order_by: Optional[str] = None)
Lists existing managed entityType resources in this Featurestore.
Example Usage:
my_featurestore = aiplatform.Featurestore(
featurestore_name='my_featurestore_id',
)
my_featurestore.list_entity_types()
Name | Description |
filter |
str
Optional. Lists the EntityTypes that match the filter expression. The following filters are supported: - |
order_by |
str
Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: - |
update
update(
labels: Optional[Dict[str, str]] = None,
request_metadata: Optional[Sequence[Tuple[str, str]]] = (),
)
Updates an existing managed featurestore resource.
Example Usage:
my_featurestore = aiplatform.Featurestore(
featurestore_name='my_featurestore_id',
)
my_featurestore.update(
labels={'update my key': 'update my value'},
)
Name | Description |
labels |
Dict[str, str]
Optional. The labels with user-defined metadata to organize your Featurestores. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. |
request_metadata |
Sequence[Tuple[str, str]]
Optional. Strings which should be sent along with the request as metadata. |
update_online_store
update_online_store(
fixed_node_count: int, request_metadata: Optional[Sequence[Tuple[str, str]]] = ()
)
Updates the online store of an existing managed featurestore resource.
Example Usage:
my_featurestore = aiplatform.Featurestore(
featurestore_name='my_featurestore_id',
)
my_featurestore.update_online_store(
fixed_node_count=2,
)
Name | Description |
fixed_node_count |
int
Required. Config for online serving resources, can only update the node count to >= 1. |
request_metadata |
Sequence[Tuple[str, str]]
Optional. Strings which should be sent along with the request as metadata. |