google.cloud.gcp_vertexai_feature_online_store_featureview module – Creates a GCP VertexAI.FeatureOnlineStoreFeatureview resource
Note
This module is part of the google.cloud collection (version 1.12.0).
You might already have this collection installed if you are using the ansible package.
It is not included in ansible-core.
To check whether it is installed, run ansible-galaxy collection list.
To install it, use: ansible-galaxy collection install google.cloud.
You need further requirements to be able to use this module,
see Requirements for details.
To use it in a playbook, specify: google.cloud.gcp_vertexai_feature_online_store_featureview.
Synopsis
FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
Requirements
The below requirements are needed on the host that executes this module.
python >= 3.8
requests >= 2.18.4
google-auth >= 2.25.1
Parameters
Parameter |
Comments |
|---|---|
The access token used to authenticate. |
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The type of credential used. Choices:
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Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore. |
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Columns to construct entityId / row keys. Start by supporting 1 only. |
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The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig. |
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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. |
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The name of the FeatureOnlineStore to use for the featureview. |
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Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore. |
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List of features that need to be synced to Online Store. |
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Identifier of the feature group. |
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Identifiers of features under the feature group. |
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The project number of the parent project of the feature Groups. |
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A set of key/value label pairs to assign to this FeatureView. |
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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. |
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The Google Cloud Platform project to use. |
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The region for the resource. It should be the same as the featureonlinestore region. |
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Array of scopes to be used. |
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The contents of a Service Account JSON file, either in a dictionary or as a JSON string that represents it. |
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An optional service account email address if machineaccount is selected and the user does not wish to use the default email. |
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The path of a Service Account JSON file if serviceaccount is selected as type. |
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Whether the resource should exist in GCP. Choices:
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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. |
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If true, syncs the FeatureView in a continuous manner to Online Store. Choices:
|
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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}”. |
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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. |
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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. |
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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. |
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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:
|
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Column of embedding. This column contains the source data to create index for vector search. |
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The number of dimensions of the input embedding. |
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Columns of features that are used to filter vector search results. |
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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. |
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Number of embeddings on each leaf node. The default value is 1000 if not set. |
Notes
Note
API Reference: https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featureOnlineStores.featureViews
Official Documentation Guide: https://cloud.google.com/vertex-ai/docs
For authentication, you can set auth_kind using the
GCP_AUTH_KINDenv variable.For authentication, you can set service_account_file using the
GCP_SERVICE_ACCOUNT_FILEenv variable.For authentication, you can set service_account_contents using the
GCP_SERVICE_ACCOUNT_CONTENTSenv variable.For authentication, you can set service_account_email using the
GCP_SERVICE_ACCOUNT_EMAILenv variable.For authentication, you can set access_token using the
GCP_ACCESS_TOKENenv variable.For authentication, you can set scopes using the
GCP_SCOPESenv variable.Environment variables values will only be used if the playbook values are not set.
The
service_account_email,service_account_file,service_account_fileandaccess_tokenoptions are mutually exclusive.
Examples
- name: Create Feature Online Store Featureview
google.cloud.gcp_vertexai_feature_online_store_featureview:
state: present
name: my_feature_online_store_featureview
feature_online_store: my_feature_online_store
sync_config:
cron: "0 0 * * *"
big_query_source:
uri: "bq://{{ gcp_project }}.my_dataset.my_table"
region: us-central1
project: "{{ gcp_project }}"
auth_kind: "{{ gcp_cred_kind }}"
service_account_file: "{{ gcp_cred_file }}"
Return Values
Common return values are documented here, the following are the fields unique to this module:
Key |
Description |
|---|---|
Whether the resource was changed. Returned: always |
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The timestamp of when the featureOnlinestore was created in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits. Returned: success |
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The current state of the resource. Returned: always |
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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 |