--- title: "POST /v1/{+parent}/featureViews" method: POST path: "/v1/{+parent}/featureViews" tags: ["projects"] --- # POST /v1/{+parent}/featureViews `POST /v1/{+parent}/featureViews` Creates a new FeatureView in a given FeatureOnlineStore. ## Path parameters - `parent` string, required ## Query parameters - `featureViewId` string - `runSyncImmediately` boolean ## Request body - GoogleCloudAiplatformV1FeatureView — FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig. - `vertexRagSource` GoogleCloudAiplatformV1FeatureViewVertexRagSource — A Vertex Rag source for features that need to be synced to Online Store. - `uri` string — Required. The BigQuery view/table URI that will be materialized on each manual sync trigger. The table/view is expected to have the following columns and types at least: - `corpus_id` (STRING, NULLABLE/REQUIRED) - `file_id` (STRING, NULLABLE/REQUIRED) - `chunk_id` (STRING, NULLABLE/REQUIRED) - `chunk_data_type` (STRING, NULLABLE/REQUIRED) - `chunk_data` (STRING, NULLABLE/REQUIRED) - `embeddings` (FLOAT, REPEATED) - `file_original_uri` (STRING, NULLABLE/REQUIRED) - `ragCorpusId` string, int64 — Optional. The RAG corpus id corresponding to this FeatureView. - `etag` string — Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. - `updateTime` string, google-datetime — Output only. Timestamp when this FeatureView was last updated. - `bigtableMetadata` GoogleCloudAiplatformV1FeatureViewBigtableMetadata — Metadata for the Cloud Bigtable that supports directly interacting Bigtable instances. - `readAppProfile` string — Output only. The Bigtable App Profile to use for reading from Bigtable. - `featureRegistrySource` GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource — A Feature Registry source for features that need to be synced to Online Store. - `featureGroups` GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup[] — Required. List of features that need to be synced to Online Store. - `featureGroupId` string — Required. Identifier of the feature group. - `featureIds` string[] — Required. Identifiers of features under the feature group. - `projectNumber` string, int64 — Optional. The project number of the parent project of the Feature Groups. - `labels` object — Optional. The labels with user-defined metadata to organize your FeatureViews. 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 FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. - `optimizedConfig` GoogleCloudAiplatformV1FeatureViewOptimizedConfig — Configuration for FeatureViews created in Optimized FeatureOnlineStore. - `automaticResources` GoogleCloudAiplatformV1AutomaticResources — A description of resources that to large degree are decided by Agent Platform, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines. - `minReplicaCount` integer — Immutable. The minimum number of replicas that will be always deployed on. If traffic against it increases, it may dynamically be deployed onto more replicas up to max_replica_count, and as traffic decreases, some of these extra replicas may be freed. If the requested value is too large, the deployment will error. - `maxReplicaCount` integer — Immutable. The maximum number of replicas that may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale to that many replicas is guaranteed (barring service outages). If traffic increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, a no upper bound for scaling under heavy traffic will be assume, though Agent Platform may be unable to scale beyond certain replica number. - `createTime` string, google-datetime — Output only. Timestamp when this FeatureView was created. - `bigQuerySource` GoogleCloudAiplatformV1FeatureViewBigQuerySource - `uri` string — Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig. - `entityIdColumns` string[] — Required. Columns to construct entity_id / row keys. - `syncConfig` GoogleCloudAiplatformV1FeatureViewSyncConfig — Configuration for Sync. Only one option is set. - `cron` string — Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *". - `continuous` boolean — Optional. If true, syncs the FeatureView in a continuous manner to Online Store. - `serviceAccountEmail` string — Output only. A Service Account unique to this FeatureView. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to sync data to the online store. - `satisfiesPzs` boolean — Output only. Reserved for future use. - `indexConfig` GoogleCloudAiplatformV1FeatureViewIndexConfig — Configuration for vector indexing. - `treeAhConfig` GoogleCloudAiplatformV1FeatureViewIndexConfigTreeAHConfig — Configuration options for the tree-AH algorithm. - `leafNodeEmbeddingCount` string, int64 — Optional. Number of embeddings on each leaf node. The default value is 1000 if not set. - `bruteForceConfig` GoogleCloudAiplatformV1FeatureViewIndexConfigBruteForceConfig — Configuration options for using brute force search. - `crowdingColumn` string — Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response. - `embeddingDimension` integer — Optional. The number of dimensions of the input embedding. - `distanceMeasureType` 'DISTANCE_MEASURE_TYPE_UNSPECIFIED' | 'SQUARED_L2_DISTANCE' | 'COSINE_DISTANCE' | 'DOT_PRODUCT_DISTANCE' — Optional. The distance measure used in nearest neighbor search. - `embeddingColumn` string — Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search. - `filterColumns` string[] — Optional. Columns of features that're used to filter vector search results. - `serviceAgentType` 'SERVICE_AGENT_TYPE_UNSPECIFIED' | 'SERVICE_AGENT_TYPE_PROJECT' | 'SERVICE_AGENT_TYPE_FEATURE_VIEW' — Optional. Service agent type used during data sync. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureView within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_VIEW`. This will generate a separate service account to access the BigQuery source table. - `name` string — Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}` - `satisfiesPzi` boolean — Output only. Reserved for future use. ## Response `200` Successful response --- [API](https://skmtc.net/google/apis/aiplatform.md) · [All operations](https://skmtc.net/google/apis/aiplatform/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/google/aiplatform/versions/b608d71b91f0/schema)