google.cloud.gcp_vertexai_feature_online_store_featureview module – Creates a GCP VertexAI.FeatureOnlineStoreFeatureview resource

access_token

string

The access token used to authenticate.

auth_kind

string / required

The type of credential used.

Choices:

• "accesstoken"
• "application"
• "machineaccount"
• "serviceaccount"

big_query_source

dictionary

Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.

entity_id_columns

list / elements=string / required

Columns to construct entityId / row keys.

Start by supporting 1 only.

uri

string / required

The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.

env_type

string

Specifies which Ansible environment you’re running this module within.

This should not be set unless you know what you’re doing.

This only alters the User Agent string for any API requests.

feature_online_store

string / required

The name of the FeatureOnlineStore to use for the featureview.

feature_registry_source

dictionary

Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.

feature_groups

list / elements=dictionary / required

List of features that need to be synced to Online Store.

feature_group_id

string / required

Identifier of the feature group.

feature_ids

list / elements=string / required

Identifiers of features under the feature group.

project_number

string

The project number of the parent project of the feature Groups.

labels

dictionary

A set of key/value label pairs to assign to this FeatureView.

name

string

Name of the FeatureView.

This value may be up to 60 characters, and valid characters are [a-z0-9_].

The first character cannot be a number.

project

string

The Google Cloud Platform project to use.

region

string / required

The region for the resource.

It should be the same as the featureonlinestore region.

scopes

list / elements=string

Array of scopes to be used.

service_account_contents

jsonarg

The contents of a Service Account JSON file,

either in a dictionary or as a JSON string that represents it.

service_account_email

string

An optional service account email address if machineaccount is

selected and the user does not wish to use the default email.

service_account_file

path

The path of a Service Account JSON file if serviceaccount

is selected as type.

state

string

Whether the resource should exist in GCP.

Choices:

• "present" ← (default)
• "absent"

sync_config

dictionary

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.

continuous

boolean

If true, syncs the FeatureView in a continuous manner to Online Store.

Choices:

• false
• true

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}”.

vector_search_config

dictionary

Configuration 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.

brute_force_config

dictionary

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.

crowding_column

string

Column of crowding.

This column contains crowding attribute which is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k’ of the k neighbors returned have the same value of crowdingAttribute.

distance_measure_type

string

The distance measure used in nearest neighbor search.

For details on allowed values, see the [API documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1beta1/projects.locations.featureOnlineStores.featureViews#DistanceMeasureType).

Choices:

• "SQUARED_L2_DISTANCE"
• "COSINE_DISTANCE"
• "DOT_PRODUCT_DISTANCE"

embedding_column

string / required

Column of embedding.

This column contains the source data to create index for vector search.

embedding_dimension

integer

The number of dimensions of the input embedding.

filter_columns

list / elements=string

Columns of features that are used to filter vector search results.

tree_ah_config

dictionary

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.

leaf_node_embedding_count

string

Number of embeddings on each leaf node.

The default value is 1000 if not set.

changed

boolean

Whether the resource was changed.

Returned: always

createTime

string

The timestamp of when the featureOnlinestore was created in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits.

Returned: success

state

string

The current state of the resource.

Returned: always

updateTime

string

The timestamp of when the featureOnlinestore was last updated in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits.

Returned: success