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<h1><a href="aiplatform_v1.html">Vertex AI API</a> . <a href="aiplatform_v1.projects.html">projects</a> . <a href="aiplatform_v1.projects.locations.html">locations</a> . <a href="aiplatform_v1.projects.locations.featureOnlineStores.html">featureOnlineStores</a> . <a href="aiplatform_v1.projects.locations.featureOnlineStores.featureViews.html">featureViews</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
<code><a href="aiplatform_v1.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.html">featureViewSyncs()</a></code>
</p>
<p class="firstline">Returns the featureViewSyncs Resource.</p>
<p class="toc_element">
<code><a href="aiplatform_v1.projects.locations.featureOnlineStores.featureViews.operations.html">operations()</a></code>
</p>
<p class="firstline">Returns the operations Resource.</p>
<p class="toc_element">
<code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
<code><a href="#create">create(parent, body=None, featureViewId=None, runSyncImmediately=None, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a new FeatureView in a given FeatureOnlineStore.</p>
<p class="toc_element">
<code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes a single FeatureView.</p>
<p class="toc_element">
<code><a href="#fetchFeatureValues">fetchFeatureValues(featureView, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Fetch feature values under a FeatureView.</p>
<p class="toc_element">
<code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Gets details of a single FeatureView.</p>
<p class="toc_element">
<code><a href="#list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists FeatureViews in a given FeatureOnlineStore.</p>
<p class="toc_element">
<code><a href="#list_next">list_next()</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<p class="toc_element">
<code><a href="#patch">patch(name, body=None, updateMask=None, x__xgafv=None)</a></code></p>
<p class="firstline">Updates the parameters of a single FeatureView.</p>
<p class="toc_element">
<code><a href="#searchNearestEntities">searchNearestEntities(featureView, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Search the nearest entities under a FeatureView. Search only works for indexable feature view; if a feature view isn't indexable, returns Invalid argument response.</p>
<p class="toc_element">
<code><a href="#sync">sync(featureView, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Triggers on-demand sync for the FeatureView.</p>
<h3>Method Details</h3>
<div class="method">
<code class="details" id="close">close()</code>
<pre>Close httplib2 connections.</pre>
</div>
<div class="method">
<code class="details" id="create">create(parent, body=None, featureViewId=None, runSyncImmediately=None, x__xgafv=None)</code>
<pre>Creates a new FeatureView in a given FeatureOnlineStore.
Args:
parent: string, Required. The resource name of the FeatureOnlineStore to create FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}` (required)
body: object, The request body.
The object takes the form of:
{ # FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
"bigQuerySource": { # Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.
"entityIdColumns": [ # Required. Columns to construct entity_id / row keys.
"A String",
],
"uri": "A String", # Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.
},
"createTime": "A String", # Output only. Timestamp when this FeatureView was created.
"etag": "A String", # Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"featureRegistrySource": { # A Feature Registry source for features that need to be synced to Online Store. # Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.
"featureGroups": [ # Required. List of features that need to be synced to Online Store.
{ # Features belonging to a single feature group that will be synced to Online Store.
"featureGroupId": "A String", # Required. Identifier of the feature group.
"featureIds": [ # Required. Identifiers of features under the feature group.
"A String",
],
},
],
"projectNumber": "A String", # Optional. The project number of the parent project of the Feature Groups.
},
"indexConfig": { # Configuration for vector indexing. # Optional. Configuration for index preparation for vector search. It contains the required configurations to create an index from source data, so that approximate nearest neighbor (a.k.a ANN) algorithms search can be performed during online serving.
"bruteForceConfig": { # Configuration options for using brute force search. # Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.
},
"crowdingColumn": "A 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.
"distanceMeasureType": "A String", # Optional. The distance measure used in nearest neighbor search.
"embeddingColumn": "A 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.
"embeddingDimension": 42, # Optional. The number of dimensions of the input embedding.
"filterColumns": [ # Optional. Columns of features that're used to filter vector search results.
"A String",
],
"treeAhConfig": { # Configuration options for the tree-AH algorithm. # Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
"leafNodeEmbeddingCount": "A String", # Optional. Number of embeddings on each leaf node. The default value is 1000 if not set.
},
},
"labels": { # 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.
"a_key": "A String",
},
"name": "A String", # Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`
"syncConfig": { # Configuration for Sync. Only one option is set. # Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.
"cron": "A 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 * * * *".
},
"updateTime": "A String", # Output only. Timestamp when this FeatureView was last updated.
}
featureViewId: string, Required. The ID to use for the FeatureView, which will become the final component of the FeatureView's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a FeatureOnlineStore.
runSyncImmediately: boolean, Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}</pre>
</div>
<div class="method">
<code class="details" id="delete">delete(name, x__xgafv=None)</code>
<pre>Deletes a single FeatureView.
Args:
name: string, Required. The name of the FeatureView to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}</pre>
</div>
<div class="method">
<code class="details" id="fetchFeatureValues">fetchFeatureValues(featureView, body=None, x__xgafv=None)</code>
<pre>Fetch feature values under a FeatureView.
Args:
featureView: string, Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}` (required)
body: object, The request body.
The object takes the form of:
{ # Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned.
"dataFormat": "A String", # Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE will be used.
"dataKey": { # Lookup key for a feature view. # Optional. The request key to fetch feature values for.
"compositeKey": { # ID that is comprised from several parts (columns). # The actual Entity ID will be composed from this struct. This should match with the way ID is defined in the FeatureView spec.
"parts": [ # Parts to construct Entity ID. Should match with the same ID columns as defined in FeatureView in the same order.
"A String",
],
},
"key": "A String", # String key to use for lookup.
},
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Response message for FeatureOnlineStoreService.FetchFeatureValues
"dataKey": { # Lookup key for a feature view. # The data key associated with this response. Will only be populated for FeatureOnlineStoreService.StreamingFetchFeatureValues RPCs.
"compositeKey": { # ID that is comprised from several parts (columns). # The actual Entity ID will be composed from this struct. This should match with the way ID is defined in the FeatureView spec.
"parts": [ # Parts to construct Entity ID. Should match with the same ID columns as defined in FeatureView in the same order.
"A String",
],
},
"key": "A String", # String key to use for lookup.
},
"keyValues": { # Response structure in the format of key (feature name) and (feature) value pair. # Feature values in KeyValue format.
"features": [ # List of feature names and values.
{ # Feature name & value pair.
"name": "A String", # Feature short name.
"value": { # Value for a feature. # Feature value.
"boolArrayValue": { # A list of boolean values. # A list of bool type feature value.
"values": [ # A list of bool values.
True or False,
],
},
"boolValue": True or False, # Bool type feature value.
"bytesValue": "A String", # Bytes feature value.
"doubleArrayValue": { # A list of double values. # A list of double type feature value.
"values": [ # A list of double values.
3.14,
],
},
"doubleValue": 3.14, # Double type feature value.
"int64ArrayValue": { # A list of int64 values. # A list of int64 type feature value.
"values": [ # A list of int64 values.
"A String",
],
},
"int64Value": "A String", # Int64 feature value.
"metadata": { # Metadata of feature value. # Metadata of feature value.
"generateTime": "A String", # Feature generation timestamp. Typically, it is provided by user at feature ingestion time. If not, feature store will use the system timestamp when the data is ingested into feature store. For streaming ingestion, the time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future.
},
"stringArrayValue": { # A list of string values. # A list of string type feature value.
"values": [ # A list of string values.
"A String",
],
},
"stringValue": "A String", # String feature value.
},
},
],
},
"protoStruct": { # Feature values in proto Struct format.
"a_key": "", # Properties of the object.
},
}</pre>
</div>
<div class="method">
<code class="details" id="get">get(name, x__xgafv=None)</code>
<pre>Gets details of a single FeatureView.
Args:
name: string, Required. The name of the FeatureView resource. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
"bigQuerySource": { # Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.
"entityIdColumns": [ # Required. Columns to construct entity_id / row keys.
"A String",
],
"uri": "A String", # Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.
},
"createTime": "A String", # Output only. Timestamp when this FeatureView was created.
"etag": "A String", # Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"featureRegistrySource": { # A Feature Registry source for features that need to be synced to Online Store. # Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.
"featureGroups": [ # Required. List of features that need to be synced to Online Store.
{ # Features belonging to a single feature group that will be synced to Online Store.
"featureGroupId": "A String", # Required. Identifier of the feature group.
"featureIds": [ # Required. Identifiers of features under the feature group.
"A String",
],
},
],
"projectNumber": "A String", # Optional. The project number of the parent project of the Feature Groups.
},
"indexConfig": { # Configuration for vector indexing. # Optional. Configuration for index preparation for vector search. It contains the required configurations to create an index from source data, so that approximate nearest neighbor (a.k.a ANN) algorithms search can be performed during online serving.
"bruteForceConfig": { # Configuration options for using brute force search. # Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.
},
"crowdingColumn": "A 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.
"distanceMeasureType": "A String", # Optional. The distance measure used in nearest neighbor search.
"embeddingColumn": "A 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.
"embeddingDimension": 42, # Optional. The number of dimensions of the input embedding.
"filterColumns": [ # Optional. Columns of features that're used to filter vector search results.
"A String",
],
"treeAhConfig": { # Configuration options for the tree-AH algorithm. # Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
"leafNodeEmbeddingCount": "A String", # Optional. Number of embeddings on each leaf node. The default value is 1000 if not set.
},
},
"labels": { # 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.
"a_key": "A String",
},
"name": "A String", # Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`
"syncConfig": { # Configuration for Sync. Only one option is set. # Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.
"cron": "A 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 * * * *".
},
"updateTime": "A String", # Output only. Timestamp when this FeatureView was last updated.
}</pre>
</div>
<div class="method">
<code class="details" id="list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</code>
<pre>Lists FeatureViews in a given FeatureOnlineStore.
Args:
parent: string, Required. The resource name of the FeatureOnlineStore to list FeatureViews. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}` (required)
filter: string, Lists the FeatureViews that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `>=`, and `<=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `>=`, and `<=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time > \"2020-01-31T15:30:00.000000Z\" OR update_time > \"2020-01-31T15:30:00.000000Z\"` --> FeatureViews created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --> FeatureViews having both (active: yes) and (env: prod) labels. * `labels.env: *` --> Any FeatureView which has a label with 'env' as the key.
orderBy: string, A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `feature_view_id` * `create_time` * `update_time`
pageSize: integer, The maximum number of FeatureViews to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViews will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000.
pageToken: string, A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViews call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViews must match the call that provided the page token.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Response message for FeatureOnlineStoreAdminService.ListFeatureViews.
"featureViews": [ # The FeatureViews matching the request.
{ # FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
"bigQuerySource": { # Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.
"entityIdColumns": [ # Required. Columns to construct entity_id / row keys.
"A String",
],
"uri": "A String", # Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.
},
"createTime": "A String", # Output only. Timestamp when this FeatureView was created.
"etag": "A String", # Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"featureRegistrySource": { # A Feature Registry source for features that need to be synced to Online Store. # Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.
"featureGroups": [ # Required. List of features that need to be synced to Online Store.
{ # Features belonging to a single feature group that will be synced to Online Store.
"featureGroupId": "A String", # Required. Identifier of the feature group.
"featureIds": [ # Required. Identifiers of features under the feature group.
"A String",
],
},
],
"projectNumber": "A String", # Optional. The project number of the parent project of the Feature Groups.
},
"indexConfig": { # Configuration for vector indexing. # Optional. Configuration for index preparation for vector search. It contains the required configurations to create an index from source data, so that approximate nearest neighbor (a.k.a ANN) algorithms search can be performed during online serving.
"bruteForceConfig": { # Configuration options for using brute force search. # Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.
},
"crowdingColumn": "A 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.
"distanceMeasureType": "A String", # Optional. The distance measure used in nearest neighbor search.
"embeddingColumn": "A 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.
"embeddingDimension": 42, # Optional. The number of dimensions of the input embedding.
"filterColumns": [ # Optional. Columns of features that're used to filter vector search results.
"A String",
],
"treeAhConfig": { # Configuration options for the tree-AH algorithm. # Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
"leafNodeEmbeddingCount": "A String", # Optional. Number of embeddings on each leaf node. The default value is 1000 if not set.
},
},
"labels": { # 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.
"a_key": "A String",
},
"name": "A String", # Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`
"syncConfig": { # Configuration for Sync. Only one option is set. # Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.
"cron": "A 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 * * * *".
},
"updateTime": "A String", # Output only. Timestamp when this FeatureView was last updated.
},
],
"nextPageToken": "A String", # A token, which can be sent as ListFeatureViewsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.
}</pre>
</div>
<div class="method">
<code class="details" id="list_next">list_next()</code>
<pre>Retrieves the next page of results.
Args:
previous_request: The request for the previous page. (required)
previous_response: The response from the request for the previous page. (required)
Returns:
A request object that you can call 'execute()' on to request the next
page. Returns None if there are no more items in the collection.
</pre>
</div>
<div class="method">
<code class="details" id="patch">patch(name, body=None, updateMask=None, x__xgafv=None)</code>
<pre>Updates the parameters of a single FeatureView.
Args:
name: string, Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}` (required)
body: object, The request body.
The object takes the form of:
{ # FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
"bigQuerySource": { # Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.
"entityIdColumns": [ # Required. Columns to construct entity_id / row keys.
"A String",
],
"uri": "A String", # Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.
},
"createTime": "A String", # Output only. Timestamp when this FeatureView was created.
"etag": "A String", # Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"featureRegistrySource": { # A Feature Registry source for features that need to be synced to Online Store. # Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.
"featureGroups": [ # Required. List of features that need to be synced to Online Store.
{ # Features belonging to a single feature group that will be synced to Online Store.
"featureGroupId": "A String", # Required. Identifier of the feature group.
"featureIds": [ # Required. Identifiers of features under the feature group.
"A String",
],
},
],
"projectNumber": "A String", # Optional. The project number of the parent project of the Feature Groups.
},
"indexConfig": { # Configuration for vector indexing. # Optional. Configuration for index preparation for vector search. It contains the required configurations to create an index from source data, so that approximate nearest neighbor (a.k.a ANN) algorithms search can be performed during online serving.
"bruteForceConfig": { # Configuration options for using brute force search. # Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.
},
"crowdingColumn": "A 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.
"distanceMeasureType": "A String", # Optional. The distance measure used in nearest neighbor search.
"embeddingColumn": "A 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.
"embeddingDimension": 42, # Optional. The number of dimensions of the input embedding.
"filterColumns": [ # Optional. Columns of features that're used to filter vector search results.
"A String",
],
"treeAhConfig": { # Configuration options for the tree-AH algorithm. # Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
"leafNodeEmbeddingCount": "A String", # Optional. Number of embeddings on each leaf node. The default value is 1000 if not set.
},
},
"labels": { # 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.
"a_key": "A String",
},
"name": "A String", # Identifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`
"syncConfig": { # Configuration for Sync. Only one option is set. # Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.
"cron": "A 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 * * * *".
},
"updateTime": "A String", # Output only. Timestamp when this FeatureView was last updated.
}
updateMask: string, Field mask is used to specify the fields to be overwritten in the FeatureView resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `serviceAgentType`
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}</pre>
</div>
<div class="method">
<code class="details" id="searchNearestEntities">searchNearestEntities(featureView, body=None, x__xgafv=None)</code>
<pre>Search the nearest entities under a FeatureView. Search only works for indexable feature view; if a feature view isn't indexable, returns Invalid argument response.
Args:
featureView: string, Required. FeatureView resource format `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureView}` (required)
body: object, The request body.
The object takes the form of:
{ # The request message for FeatureOnlineStoreService.SearchNearestEntities.
"query": { # A query to find a number of similar entities. # Required. The query.
"embedding": { # The embedding vector. # Optional. The embedding vector that be used for similar search.
"value": [ # Optional. Individual value in the embedding.
3.14,
],
},
"entityId": "A String", # Optional. The entity id whose similar entities should be searched for. If embedding is set, search will use embedding instead of entity_id.
"neighborCount": 42, # Optional. The number of similar entities to be retrieved from feature view for each query.
"parameters": { # Parameters that can be overrided in each query to tune query latency and recall. # Optional. Parameters that can be set to tune query on the fly.
"approximateNeighborCandidates": 42, # Optional. The number of neighbors to find via approximate search before exact reordering is performed; if set, this value must be > neighbor_count.
"leafNodesSearchFraction": 3.14, # Optional. The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0.
},
"perCrowdingAttributeNeighborCount": 42, # Optional. Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than sper_crowding_attribute_neighbor_count of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity.
"stringFilters": [ # Optional. The list of string filters.
{ # String filter is used to search a subset of the entities by using boolean rules on string columns. For example: if a query specifies string filter with 'name = color, allow_tokens = {red, blue}, deny_tokens = {purple}',' then that query will match entities that are red or blue, but if those points are also purple, then they will be excluded even if they are red/blue. Only string filter is supported for now, numeric filter will be supported in the near future.
"allowTokens": [ # Optional. The allowed tokens.
"A String",
],
"denyTokens": [ # Optional. The denied tokens.
"A String",
],
"name": "A String", # Required. Column names in BigQuery that used as filters.
},
],
},
"returnFullEntity": True or False, # Optional. If set to true, the full entities (including all vector values and metadata) of the nearest neighbors are returned; otherwise only entity id of the nearest neighbors will be returned. Note that returning full entities will significantly increase the latency and cost of the query.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Response message for FeatureOnlineStoreService.SearchNearestEntities
"nearestNeighbors": { # Nearest neighbors for one query. # The nearest neighbors of the query entity.
"neighbors": [ # All its neighbors.
{ # A neighbor of the query vector.
"distance": 3.14, # The distance between the neighbor and the query vector.
"entityId": "A String", # The id of the similar entity.
"entityKeyValues": { # Response message for FeatureOnlineStoreService.FetchFeatureValues # The attributes of the neighbor, e.g. filters, crowding and metadata Note that full entities are returned only when "return_full_entity" is set to true. Otherwise, only the "entity_id" and "distance" fields are populated.
"dataKey": { # Lookup key for a feature view. # The data key associated with this response. Will only be populated for FeatureOnlineStoreService.StreamingFetchFeatureValues RPCs.
"compositeKey": { # ID that is comprised from several parts (columns). # The actual Entity ID will be composed from this struct. This should match with the way ID is defined in the FeatureView spec.
"parts": [ # Parts to construct Entity ID. Should match with the same ID columns as defined in FeatureView in the same order.
"A String",
],
},
"key": "A String", # String key to use for lookup.
},
"keyValues": { # Response structure in the format of key (feature name) and (feature) value pair. # Feature values in KeyValue format.
"features": [ # List of feature names and values.
{ # Feature name & value pair.
"name": "A String", # Feature short name.
"value": { # Value for a feature. # Feature value.
"boolArrayValue": { # A list of boolean values. # A list of bool type feature value.
"values": [ # A list of bool values.
True or False,
],
},
"boolValue": True or False, # Bool type feature value.
"bytesValue": "A String", # Bytes feature value.
"doubleArrayValue": { # A list of double values. # A list of double type feature value.
"values": [ # A list of double values.
3.14,
],
},
"doubleValue": 3.14, # Double type feature value.
"int64ArrayValue": { # A list of int64 values. # A list of int64 type feature value.
"values": [ # A list of int64 values.
"A String",
],
},
"int64Value": "A String", # Int64 feature value.
"metadata": { # Metadata of feature value. # Metadata of feature value.
"generateTime": "A String", # Feature generation timestamp. Typically, it is provided by user at feature ingestion time. If not, feature store will use the system timestamp when the data is ingested into feature store. For streaming ingestion, the time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future.
},
"stringArrayValue": { # A list of string values. # A list of string type feature value.
"values": [ # A list of string values.
"A String",
],
},
"stringValue": "A String", # String feature value.
},
},
],
},
"protoStruct": { # Feature values in proto Struct format.
"a_key": "", # Properties of the object.
},
},
},
],
},
}</pre>
</div>
<div class="method">
<code class="details" id="sync">sync(featureView, body=None, x__xgafv=None)</code>
<pre>Triggers on-demand sync for the FeatureView.
Args:
featureView: string, Required. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}` (required)
body: object, The request body.
The object takes the form of:
{ # Request message for FeatureOnlineStoreAdminService.SyncFeatureView.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Respose message for FeatureOnlineStoreAdminService.SyncFeatureView.
"featureViewSync": "A String", # Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}`
}</pre>
</div>
</body></html>