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feat(samples): add feature values apis samples (#341)
* added create-featurestore-sample.js and create-featurestore-sample.test.js * feat(samples): added createFeaturestore sample (#313) * feat(samples): added remaining featurestore samples (#313) * removed the extraneous files * feat(samples): add feature-values apis samples (#313) * feat(samples): add feature values apis samples (#313) * 🦉 Updates from OwlBot post-processor See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md * feat(samples): update dependency featurevalues apis (#313) * 🦉 Updates from OwlBot post-processor See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com> Co-authored-by: junkourata <[email protected]>
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‎ai-platform/snippets/batch-read-feature-values-sample.js

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/*
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* Copyright 2022 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* https://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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/*
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* Batch reads Feature values from a Featurestore.
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* See https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
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* the code snippet
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*/
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'use strict';
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async function main(
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project,
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featurestoreId,
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inputCsvFile,
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destinationTableUri,
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location = 'us-central1',
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apiEndpoint = 'us-central1-aiplatform.googleapis.com',
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timeout = 300000
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) {
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// [START aiplatform_batch_read_feature_values_sample]
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/**
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* TODO(developer): Uncomment these variables before running the sample.\
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* (Not necessary if passing values as arguments)
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*/
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// const project = 'YOUR_PROJECT_ID';
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// const featurestoreId = 'YOUR_FEATURESTORE_ID';
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// const inputCsvFile = 'YOUR_INPUT_CSV_FILE_URI';
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// const destinationTableUri = 'YOUR_BQ_DESTINATION_TABLE_URI';
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// const location = 'YOUR_PROJECT_LOCATION';
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// const apiEndpoint = 'YOUR_API_ENDPOINT';
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// const timeout = <TIMEOUT_IN_MILLI_SECONDS>;
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// Imports the Google Cloud Featurestore Service Client library
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const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
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// Specifies the location of the api endpoint
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const clientOptions = {
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apiEndpoint: apiEndpoint,
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};
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// Instantiates a client
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const featurestoreServiceClient = new FeaturestoreServiceClient(
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clientOptions
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);
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async function batchReadFeatureValues() {
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// Configure the featurestoreId resource
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const featurestore = `projects/${project}/locations/${location}/featurestores/${featurestoreId}`;
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const csvReadInstances = {
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gcsSource: {
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uris: [inputCsvFile],
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},
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};
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const destination = {
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bigqueryDestination: {
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// # Output to BigQuery table created earlier
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outputUri: destinationTableUri,
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},
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};
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const usersFeatureSelector = {
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idMatcher: {
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ids: [
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// features, use "*" if you want to select all features within this entity type
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'age',
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'gender',
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'liked_genres',
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],
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},
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};
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const usersEntityTypeSpec = {
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// Read the 'age', 'gender' and 'liked_genres' features from the 'perm_users' entity
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entityTypeId: 'perm_users',
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featureSelector: usersFeatureSelector,
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};
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const moviesFeatureSelector = {
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idMatcher: {
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ids: ['*'],
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},
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};
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const moviesEntityTypeSpec = {
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// Read the all features from the 'perm_movies' entity
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entityTypeId: 'perm_movies',
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featureSelector: moviesFeatureSelector,
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};
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const entityTypeSpecs = [usersEntityTypeSpec, moviesEntityTypeSpec];
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// Construct request
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const request = {
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featurestore: featurestore,
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csvReadInstances: csvReadInstances,
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destination: destination,
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entityTypeSpecs: entityTypeSpecs,
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};
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// Batch Read Feature Values Request
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const [operation] = await featurestoreServiceClient.batchReadFeatureValues(
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request,
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{timeout: Number(timeout)}
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);
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const [response] = await operation.promise();
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console.log('Batch read feature values response');
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console.log('Raw response:');
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console.log(JSON.stringify(response, null, 2));
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}
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batchReadFeatureValues();
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// [END aiplatform_batch_read_feature_values_sample]
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}
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process.on('unhandledRejection', err => {
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console.error(err.message);
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process.exitCode = 1;
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});
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main(...process.argv.slice(2));

‎ai-platform/snippets/export-feature-values-sample.js

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/*
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* Copyright 2022 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* https://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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/*
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* Exports Feature values from all the entities of a target EntityType.
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* See https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
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* the code snippet
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*/
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'use strict';
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async function main(
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project,
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featurestoreId,
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entityTypeId,
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destinationTableUri,
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location = 'us-central1',
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apiEndpoint = 'us-central1-aiplatform.googleapis.com',
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timeout = 300000
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) {
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// [START aiplatform_export_feature_values_sample]
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/**
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* TODO(developer): Uncomment these variables before running the sample.\
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* (Not necessary if passing values as arguments)
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*/
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// const project = 'YOUR_PROJECT_ID';
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// const featurestoreId = 'YOUR_FEATURESTORE_ID';
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// const entityTypeId = 'YOUR_ENTITY_TYPE_ID';
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// const destinationTableUri = 'YOUR_BQ_DESTINATION_TABLE_URI';
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// const location = 'YOUR_PROJECT_LOCATION';
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// const apiEndpoint = 'YOUR_API_ENDPOINT';
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// const timeout = <TIMEOUT_IN_MILLI_SECONDS>;
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// Imports the Google Cloud Featurestore Service Client library
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const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
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// Specifies the location of the api endpoint
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const clientOptions = {
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apiEndpoint: apiEndpoint,
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};
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// Instantiates a client
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const featurestoreServiceClient = new FeaturestoreServiceClient(
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clientOptions
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);
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async function exportFeatureValues() {
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// Configure the entityType resource
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const entityType = `projects/${project}/locations/${location}/featurestores/${featurestoreId}/entityTypes/${entityTypeId}`;
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const destination = {
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bigqueryDestination: {
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// # Output to BigQuery table created earlier
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outputUri: destinationTableUri,
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},
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};
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const featureSelector = {
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idMatcher: {
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ids: ['age', 'gender', 'liked_genres'],
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},
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};
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const request = {
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entityType: entityType,
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destination: destination,
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featureSelector: featureSelector,
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fullExport: {},
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};
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// Export Feature Values Request
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const [operation] = await featurestoreServiceClient.exportFeatureValues(
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request,
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{timeout: Number(timeout)}
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);
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const [response] = await operation.promise();
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console.log('Export feature values response');
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console.log('Raw response:');
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console.log(JSON.stringify(response, null, 2));
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}
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exportFeatureValues();
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// [END aiplatform_export_feature_values_sample]
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}
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process.on('unhandledRejection', err => {
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console.error(err.message);
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process.exitCode = 1;
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});
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main(...process.argv.slice(2));

‎ai-platform/snippets/export-feature-values-snapshot-sample.js

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/*
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* Copyright 2022 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* https://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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/*
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* Exports Feature values with snapshot from all the entities of a target EntityType.
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* See https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
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* the code snippet
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*/
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'use strict';
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async function main(
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project,
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featurestoreId,
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entityTypeId,
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destinationTableUri,
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timestamp,
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location = 'us-central1',
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apiEndpoint = 'us-central1-aiplatform.googleapis.com',
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timeout = 300000
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) {
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// [START aiplatform_export_feature_values_snapshot_sample]
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/**
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* TODO(developer): Uncomment these variables before running the sample.\
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* (Not necessary if passing values as arguments)
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*/
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// const project = 'YOUR_PROJECT_ID';
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// const featurestoreId = 'YOUR_FEATURESTORE_ID';
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// const entityTypeId = 'YOUR_ENTITY_TYPE_ID';
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// const destinationTableUri = 'YOUR_BQ_DESTINATION_TABLE_URI';
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// const timestamp = <STARTING_TIMESTAMP_OF_SNAPSHOT_IN_SECONDS>;
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// const location = 'YOUR_PROJECT_LOCATION';
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// const apiEndpoint = 'YOUR_API_ENDPOINT';
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// const timeout = <TIMEOUT_IN_MILLI_SECONDS>;
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// Imports the Google Cloud Featurestore Service Client library
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const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;
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// Specifies the location of the api endpoint
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const clientOptions = {
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apiEndpoint: apiEndpoint,
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};
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// Instantiates a client
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const featurestoreServiceClient = new FeaturestoreServiceClient(
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clientOptions
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);
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async function exportFeatureValuesSnapshot() {
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// Configure the entityType resource
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const entityType = `projects/${project}/locations/${location}/featurestores/${featurestoreId}/entityTypes/${entityTypeId}`;
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const destination = {
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bigqueryDestination: {
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// # Output to BigQuery table created earlier
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outputUri: destinationTableUri,
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},
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};
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const featureSelector = {
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idMatcher: {
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ids: ['age', 'gender', 'liked_genres'],
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},
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};
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const snapshotExport = {
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startTime: {
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seconds: Number(timestamp),
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},
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};
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const request = {
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entityType: entityType,
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destination: destination,
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featureSelector: featureSelector,
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snapshotExport: snapshotExport,
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};
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// Export Feature Values Request
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const [operation] = await featurestoreServiceClient.exportFeatureValues(
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request,
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{timeout: Number(timeout)}
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);
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const [response] = await operation.promise();
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console.log('Export feature values snapshot response');
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console.log('Raw response:');
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console.log(JSON.stringify(response, null, 2));
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}
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exportFeatureValuesSnapshot();
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// [END aiplatform_export_feature_values_snapshot_sample]
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}
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process.on('unhandledRejection', err => {
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console.error(err.message);
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process.exitCode = 1;
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});
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main(...process.argv.slice(2));

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