"use strict";
// *** WARNING: this file was generated by pulumi-language-nodejs. ***
// *** 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 "@pulumiverse/time";
 *
 * const testProject = gcp.organizations.getProject({});
 * const project = new gcp.organizations.Project("project", {
 *     projectId: "tf-test_9329",
 *     name: "tf-test_37135",
 *     orgId: "123456789",
 *     billingAccount: "000000-0000000-0000000-000000",
 *     deletionPolicy: "DELETE",
 * });
 * const wait60Seconds = new time.Sleep("wait_60_seconds", {createDuration: "60s"}, {
 *     dependsOn: [project],
 * });
 * const vertexai = new gcp.projects.Service("vertexai", {
 *     service: "aiplatform.googleapis.com",
 *     project: project.projectId,
 * }, {
 *     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-${project.number}@gcp-sa-aiplatform.iam.gserviceaccount.com`,
 * }, {
 *     dependsOn: [featureonlinestore],
 * });
 * const wait30Seconds = new time.Sleep("wait_30_seconds", {createDuration: "30s"}, {
 *     dependsOn: [viewer],
 * });
 * const sampleTable = new gcp.bigquery.Table("sample_table", {
 *     deletionProtection: false,
 *     datasetId: sampleDataset.datasetId,
 *     tableId: "example_cross_project_featureview",
 *     schema: `[
 *     {
 *         "name": "feature_id",
 *         "type": "STRING",
 *         "mode": "NULLABLE"
 *     },
 *     {
 *         "name": "example_cross_project_featureview",
 *         "type": "STRING",
 *         "mode": "NULLABLE"
 *     },
 *     {
 *         "name": "feature_timestamp",
 *         "type": "TIMESTAMP",
 *         "mode": "NULLABLE"
 *     }
 * ]
 * `,
 * });
 * const sampleFeatureGroup = new gcp.vertex.AiFeatureGroup("sample_feature_group", {
 *     name: "example_cross_project_featureview",
 *     description: "A sample feature group",
 *     region: "us-central1",
 *     labels: {
 *         "label-one": "value-one",
 *     },
 *     bigQuery: {
 *         bigQuerySource: {
 *             inputUri: pulumi.interpolate`bq://${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",
 *     optimized: {},
 *     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, { ...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?.bigQuerySource;
            resourceInputs["createTime"] = state?.createTime;
            resourceInputs["effectiveLabels"] = state?.effectiveLabels;
            resourceInputs["featureOnlineStore"] = state?.featureOnlineStore;
            resourceInputs["featureRegistrySource"] = state?.featureRegistrySource;
            resourceInputs["labels"] = state?.labels;
            resourceInputs["name"] = state?.name;
            resourceInputs["project"] = state?.project;
            resourceInputs["pulumiLabels"] = state?.pulumiLabels;
            resourceInputs["region"] = state?.region;
            resourceInputs["syncConfig"] = state?.syncConfig;
            resourceInputs["updateTime"] = state?.updateTime;
            resourceInputs["vectorSearchConfig"] = state?.vectorSearchConfig;
        }
        else {
            const args = argsOrState;
            if (args?.featureOnlineStore === undefined && !opts.urn) {
                throw new Error("Missing required property 'featureOnlineStore'");
            }
            resourceInputs["bigQuerySource"] = args?.bigQuerySource;
            resourceInputs["featureOnlineStore"] = args?.featureOnlineStore;
            resourceInputs["featureRegistrySource"] = args?.featureRegistrySource;
            resourceInputs["labels"] = args?.labels;
            resourceInputs["name"] = args?.name;
            resourceInputs["project"] = args?.project;
            resourceInputs["region"] = args?.region;
            resourceInputs["syncConfig"] = args?.syncConfig;
            resourceInputs["vectorSearchConfig"] = args?.vectorSearchConfig;
            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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