GoogleCloudAiplatformV1Featurestore
import type { GoogleCloudAiplatformV1Featurestore } from "https://googleapis.deno.dev/v1/aiplatform:v1.ts";
Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.
§Properties
Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key.
Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
Optional. The labels with user-defined metadata to organize your Featurestore. 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 Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
Output only. Name of the Featurestore. Format:
projects/{project}/locations/{location}/featurestores/{featurestore}
Optional. Config for online storage resources. The field should not
co-exist with the field of OnlineStoreReplicationConfig
. If both of it
and OnlineStoreReplicationConfig are unset, the feature store will not have
an online store and cannot be used for online serving.
Optional. TTL in days for feature values that will be stored in online
serving storage. The Feature Store online storage periodically removes
obsolete feature values older than online_storage_ttl_days
since the
feature generation time. Note that online_storage_ttl_days
should be less
than or equal to offline_storage_ttl_days
for each EntityType under a
featurestore. If not set, default to 4000 days