@pulumi/gcp
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A Pulumi package for creating and managing Google Cloud Platform resources.
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JavaScript
"use strict";
// *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
// *** Do not edit by hand unless you're certain you know what you are doing! ***
Object.defineProperty(exports, "__esModule", { value: true });
exports.AiFeatureOnlineStoreFeatureview = void 0;
const pulumi = require("@pulumi/pulumi");
const utilities = require("../utilities");
/**
* FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
*
* To get more information about FeatureOnlineStoreFeatureview, see:
*
* * [API documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featureOnlineStores.featureViews)
* * How-to Guides
* * [Official Documentation](https://cloud.google.com/vertex-ai/docs)
*
* ## Example Usage
*
* ### Vertex Ai Featureonlinestore Featureview
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
*
* const featureonlinestore = new gcp.vertex.AiFeatureOnlineStore("featureonlinestore", {
* name: "example_feature_view",
* labels: {
* foo: "bar",
* },
* region: "us-central1",
* bigtable: {
* autoScaling: {
* minNodeCount: 1,
* maxNodeCount: 2,
* cpuUtilizationTarget: 80,
* },
* },
* });
* const tf_test_dataset = new gcp.bigquery.Dataset("tf-test-dataset", {
* datasetId: "example_feature_view",
* friendlyName: "test",
* description: "This is a test description",
* location: "US",
* });
* const tf_test_table = new gcp.bigquery.Table("tf-test-table", {
* deletionProtection: false,
* datasetId: tf_test_dataset.datasetId,
* tableId: "example_feature_view",
* schema: ` [
* {
* "name": "entity_id",
* "mode": "NULLABLE",
* "type": "STRING",
* "description": "Test default entity_id"
* },
* {
* "name": "test_entity_column",
* "mode": "NULLABLE",
* "type": "STRING",
* "description": "test secondary entity column"
* },
* {
* "name": "feature_timestamp",
* "mode": "NULLABLE",
* "type": "TIMESTAMP",
* "description": "Default timestamp value"
* }
* ]
* `,
* });
* const featureview = new gcp.vertex.AiFeatureOnlineStoreFeatureview("featureview", {
* name: "example_feature_view",
* region: "us-central1",
* featureOnlineStore: featureonlinestore.name,
* syncConfig: {
* cron: "0 0 * * *",
* },
* bigQuerySource: {
* uri: pulumi.interpolate`bq://${tf_test_table.project}.${tf_test_table.datasetId}.${tf_test_table.tableId}`,
* entityIdColumns: ["test_entity_column"],
* },
* });
* const project = gcp.organizations.getProject({});
* ```
* ### Vertex Ai Featureonlinestore Featureview Feature Registry
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
*
* const featureonlinestore = new gcp.vertex.AiFeatureOnlineStore("featureonlinestore", {
* name: "example_feature_view_feature_registry",
* labels: {
* foo: "bar",
* },
* region: "us-central1",
* bigtable: {
* autoScaling: {
* minNodeCount: 1,
* maxNodeCount: 2,
* cpuUtilizationTarget: 80,
* },
* },
* });
* const sampleDataset = new gcp.bigquery.Dataset("sample_dataset", {
* datasetId: "example_feature_view_feature_registry",
* friendlyName: "test",
* description: "This is a test description",
* location: "US",
* });
* const sampleTable = new gcp.bigquery.Table("sample_table", {
* deletionProtection: false,
* datasetId: sampleDataset.datasetId,
* tableId: "example_feature_view_feature_registry",
* schema: `[
* {
* "name": "feature_id",
* "type": "STRING",
* "mode": "NULLABLE"
* },
* {
* "name": "example_feature_view_feature_registry",
* "type": "STRING",
* "mode": "NULLABLE"
* },
* {
* "name": "feature_timestamp",
* "type": "TIMESTAMP",
* "mode": "NULLABLE"
* }
* ]
* `,
* });
* const sampleFeatureGroup = new gcp.vertex.AiFeatureGroup("sample_feature_group", {
* name: "example_feature_view_feature_registry",
* description: "A sample feature group",
* region: "us-central1",
* labels: {
* "label-one": "value-one",
* },
* bigQuery: {
* bigQuerySource: {
* inputUri: pulumi.interpolate`bq://${sampleTable.project}.${sampleTable.datasetId}.${sampleTable.tableId}`,
* },
* entityIdColumns: ["feature_id"],
* },
* });
* const sampleFeature = new gcp.vertex.AiFeatureGroupFeature("sample_feature", {
* name: "example_feature_view_feature_registry",
* region: "us-central1",
* featureGroup: sampleFeatureGroup.name,
* description: "A sample feature",
* labels: {
* "label-one": "value-one",
* },
* });
* const featureviewFeatureregistry = new gcp.vertex.AiFeatureOnlineStoreFeatureview("featureview_featureregistry", {
* name: "example_feature_view_feature_registry",
* region: "us-central1",
* featureOnlineStore: featureonlinestore.name,
* syncConfig: {
* cron: "0 0 * * *",
* },
* featureRegistrySource: {
* featureGroups: [{
* featureGroupId: sampleFeatureGroup.name,
* featureIds: [sampleFeature.name],
* }],
* },
* });
* ```
* ### Vertex Ai Featureonlinestore Featureview Cross Project
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
* import * as time from "@pulumi/time";
*
* const testProject = gcp.organizations.getProject({});
* const project = new gcp.organizations.Project("project", {
* projectId: "tf-test_35305",
* name: "tf-test_62793",
* orgId: "123456789",
* billingAccount: "000000-0000000-0000000-000000",
* deletionPolicy: "DELETE",
* });
* const wait60Seconds = new time.index.Sleep("wait_60_seconds", {createDuration: "60s"}, {
* dependsOn: [project],
* });
* const vertexai = new gcp.projects.Service("vertexai", {
* service: "aiplatform.googleapis.com",
* project: project.projectId,
* disableOnDestroy: false,
* }, {
* dependsOn: [wait60Seconds],
* });
* const featureonlinestore = new gcp.vertex.AiFeatureOnlineStore("featureonlinestore", {
* name: "example_cross_project_featureview",
* project: project.projectId,
* labels: {
* foo: "bar",
* },
* region: "us-central1",
* bigtable: {
* autoScaling: {
* minNodeCount: 1,
* maxNodeCount: 2,
* cpuUtilizationTarget: 80,
* },
* },
* }, {
* dependsOn: [vertexai],
* });
* const sampleDataset = new gcp.bigquery.Dataset("sample_dataset", {
* datasetId: "example_cross_project_featureview",
* friendlyName: "test",
* description: "This is a test description",
* location: "US",
* });
* const viewer = new gcp.bigquery.DatasetIamMember("viewer", {
* project: testProject.then(testProject => testProject.projectId),
* datasetId: sampleDataset.datasetId,
* role: "roles/bigquery.dataViewer",
* member: pulumi.interpolate`serviceAccount:service-${project.number}@gcp-sa-aiplatform.iam.gserviceaccount.com`,
* }, {
* dependsOn: [featureonlinestore],
* });
* const wait30Seconds = new time.index.Sleep("wait_30_seconds", {createDuration: "30s"}, {
* dependsOn: [viewer],
* });
* const sampleTable = new gcp.bigquery.Table("sample_table", {
* deletionProtection: false,
* datasetId: sampleDataset.datasetId,
* tableId: "example_cross_project_featureview",
* schema: `[
* {
* "name": "feature_id",
* "type": "STRING",
* "mode": "NULLABLE"
* },
* {
* "name": "example_cross_project_featureview",
* "type": "STRING",
* "mode": "NULLABLE"
* },
* {
* "name": "feature_timestamp",
* "type": "TIMESTAMP",
* "mode": "NULLABLE"
* }
* ]
* `,
* });
* const sampleFeatureGroup = new gcp.vertex.AiFeatureGroup("sample_feature_group", {
* name: "example_cross_project_featureview",
* description: "A sample feature group",
* region: "us-central1",
* labels: {
* "label-one": "value-one",
* },
* bigQuery: {
* bigQuerySource: {
* inputUri: pulumi.interpolate`bq://${sampleTable.project}.${sampleTable.datasetId}.${sampleTable.tableId}`,
* },
* entityIdColumns: ["feature_id"],
* },
* });
* const sampleFeature = new gcp.vertex.AiFeatureGroupFeature("sample_feature", {
* name: "example_cross_project_featureview",
* region: "us-central1",
* featureGroup: sampleFeatureGroup.name,
* description: "A sample feature",
* labels: {
* "label-one": "value-one",
* },
* });
* const crossProjectFeatureview = new gcp.vertex.AiFeatureOnlineStoreFeatureview("cross_project_featureview", {
* name: "example_cross_project_featureview",
* project: project.projectId,
* region: "us-central1",
* featureOnlineStore: featureonlinestore.name,
* syncConfig: {
* cron: "0 0 * * *",
* },
* featureRegistrySource: {
* featureGroups: [{
* featureGroupId: sampleFeatureGroup.name,
* featureIds: [sampleFeature.name],
* }],
* projectNumber: testProject.then(testProject => testProject.number),
* },
* }, {
* dependsOn: [
* vertexai,
* wait30Seconds,
* ],
* });
* ```
* ### Vertex Ai Featureonlinestore Featureview With Vector Search
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
*
* const featureonlinestore = new gcp.vertex.AiFeatureOnlineStore("featureonlinestore", {
* name: "example_feature_view_vector_search",
* labels: {
* foo: "bar",
* },
* region: "us-central1",
* bigtable: {
* autoScaling: {
* minNodeCount: 1,
* maxNodeCount: 2,
* cpuUtilizationTarget: 80,
* },
* },
* embeddingManagement: {
* enabled: true,
* },
* });
* const tf_test_dataset = new gcp.bigquery.Dataset("tf-test-dataset", {
* datasetId: "example_feature_view_vector_search",
* friendlyName: "test",
* description: "This is a test description",
* location: "US",
* });
* const tf_test_table = new gcp.bigquery.Table("tf-test-table", {
* deletionProtection: false,
* datasetId: tf_test_dataset.datasetId,
* tableId: "example_feature_view_vector_search",
* schema: `[
* {
* "name": "test_primary_id",
* "mode": "NULLABLE",
* "type": "STRING",
* "description": "primary test id"
* },
* {
* "name": "embedding",
* "mode": "REPEATED",
* "type": "FLOAT",
* "description": "embedding column for primary_id column"
* },
* {
* "name": "country",
* "mode": "NULLABLE",
* "type": "STRING",
* "description": "country"
* },
* {
* "name": "test_crowding_column",
* "mode": "NULLABLE",
* "type": "INTEGER",
* "description": "test crowding column"
* },
* {
* "name": "entity_id",
* "mode": "NULLABLE",
* "type": "STRING",
* "description": "Test default entity_id"
* },
* {
* "name": "test_entity_column",
* "mode": "NULLABLE",
* "type": "STRING",
* "description": "test secondary entity column"
* },
* {
* "name": "feature_timestamp",
* "mode": "NULLABLE",
* "type": "TIMESTAMP",
* "description": "Default timestamp value"
* }
* ]
* `,
* });
* const featureviewVectorSearch = new gcp.vertex.AiFeatureOnlineStoreFeatureview("featureview_vector_search", {
* name: "example_feature_view_vector_search",
* region: "us-central1",
* featureOnlineStore: featureonlinestore.name,
* syncConfig: {
* cron: "0 0 * * *",
* },
* bigQuerySource: {
* uri: pulumi.interpolate`bq://${tf_test_table.project}.${tf_test_table.datasetId}.${tf_test_table.tableId}`,
* entityIdColumns: ["test_entity_column"],
* },
* vectorSearchConfig: {
* embeddingColumn: "embedding",
* filterColumns: ["country"],
* crowdingColumn: "test_crowding_column",
* distanceMeasureType: "DOT_PRODUCT_DISTANCE",
* treeAhConfig: {
* leafNodeEmbeddingCount: "1000",
* },
* embeddingDimension: 2,
* },
* });
* const project = gcp.organizations.getProject({});
* ```
*
* ## Import
*
* FeatureOnlineStoreFeatureview can be imported using any of these accepted formats:
*
* * `projects/{{project}}/locations/{{region}}/featureOnlineStores/{{feature_online_store}}/featureViews/{{name}}`
*
* * `{{project}}/{{region}}/{{feature_online_store}}/{{name}}`
*
* * `{{region}}/{{feature_online_store}}/{{name}}`
*
* * `{{feature_online_store}}/{{name}}`
*
* When using the `pulumi import` command, FeatureOnlineStoreFeatureview can be imported using one of the formats above. For example:
*
* ```sh
* $ pulumi import gcp:vertex/aiFeatureOnlineStoreFeatureview:AiFeatureOnlineStoreFeatureview default projects/{{project}}/locations/{{region}}/featureOnlineStores/{{feature_online_store}}/featureViews/{{name}}
* ```
*
* ```sh
* $ pulumi import gcp:vertex/aiFeatureOnlineStoreFeatureview:AiFeatureOnlineStoreFeatureview default {{project}}/{{region}}/{{feature_online_store}}/{{name}}
* ```
*
* ```sh
* $ pulumi import gcp:vertex/aiFeatureOnlineStoreFeatureview:AiFeatureOnlineStoreFeatureview default {{region}}/{{feature_online_store}}/{{name}}
* ```
*
* ```sh
* $ pulumi import gcp:vertex/aiFeatureOnlineStoreFeatureview:AiFeatureOnlineStoreFeatureview default {{feature_online_store}}/{{name}}
* ```
*/
class AiFeatureOnlineStoreFeatureview extends pulumi.CustomResource {
/**
* Get an existing AiFeatureOnlineStoreFeatureview resource's state with the given name, ID, and optional extra
* properties used to qualify the lookup.
*
* @param name The _unique_ name of the resulting resource.
* @param id The _unique_ provider ID of the resource to lookup.
* @param state Any extra arguments used during the lookup.
* @param opts Optional settings to control the behavior of the CustomResource.
*/
static get(name, id, state, opts) {
return new AiFeatureOnlineStoreFeatureview(name, state, Object.assign(Object.assign({}, opts), { id: id }));
}
/**
* Returns true if the given object is an instance of AiFeatureOnlineStoreFeatureview. This is designed to work even
* when multiple copies of the Pulumi SDK have been loaded into the same process.
*/
static isInstance(obj) {
if (obj === undefined || obj === null) {
return false;
}
return obj['__pulumiType'] === AiFeatureOnlineStoreFeatureview.__pulumiType;
}
constructor(name, argsOrState, opts) {
let resourceInputs = {};
opts = opts || {};
if (opts.id) {
const state = argsOrState;
resourceInputs["bigQuerySource"] = state ? state.bigQuerySource : undefined;
resourceInputs["createTime"] = state ? state.createTime : undefined;
resourceInputs["effectiveLabels"] = state ? state.effectiveLabels : undefined;
resourceInputs["featureOnlineStore"] = state ? state.featureOnlineStore : undefined;
resourceInputs["featureRegistrySource"] = state ? state.featureRegistrySource : undefined;
resourceInputs["labels"] = state ? state.labels : undefined;
resourceInputs["name"] = state ? state.name : undefined;
resourceInputs["project"] = state ? state.project : undefined;
resourceInputs["pulumiLabels"] = state ? state.pulumiLabels : undefined;
resourceInputs["region"] = state ? state.region : undefined;
resourceInputs["syncConfig"] = state ? state.syncConfig : undefined;
resourceInputs["updateTime"] = state ? state.updateTime : undefined;
resourceInputs["vectorSearchConfig"] = state ? state.vectorSearchConfig : undefined;
}
else {
const args = argsOrState;
if ((!args || args.featureOnlineStore === undefined) && !opts.urn) {
throw new Error("Missing required property 'featureOnlineStore'");
}
if ((!args || args.region === undefined) && !opts.urn) {
throw new Error("Missing required property 'region'");
}
resourceInputs["bigQuerySource"] = args ? args.bigQuerySource : undefined;
resourceInputs["featureOnlineStore"] = args ? args.featureOnlineStore : undefined;
resourceInputs["featureRegistrySource"] = args ? args.featureRegistrySource : undefined;
resourceInputs["labels"] = args ? args.labels : undefined;
resourceInputs["name"] = args ? args.name : undefined;
resourceInputs["project"] = args ? args.project : undefined;
resourceInputs["region"] = args ? args.region : undefined;
resourceInputs["syncConfig"] = args ? args.syncConfig : undefined;
resourceInputs["vectorSearchConfig"] = args ? args.vectorSearchConfig : undefined;
resourceInputs["createTime"] = undefined /*out*/;
resourceInputs["effectiveLabels"] = undefined /*out*/;
resourceInputs["pulumiLabels"] = undefined /*out*/;
resourceInputs["updateTime"] = undefined /*out*/;
}
opts = pulumi.mergeOptions(utilities.resourceOptsDefaults(), opts);
const secretOpts = { additionalSecretOutputs: ["effectiveLabels", "pulumiLabels"] };
opts = pulumi.mergeOptions(opts, secretOpts);
super(AiFeatureOnlineStoreFeatureview.__pulumiType, name, resourceInputs, opts);
}
}
exports.AiFeatureOnlineStoreFeatureview = AiFeatureOnlineStoreFeatureview;
/** @internal */
AiFeatureOnlineStoreFeatureview.__pulumiType = 'gcp:vertex/aiFeatureOnlineStoreFeatureview:AiFeatureOnlineStoreFeatureview';
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