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feat(samples): add feature values apis samples (#341)
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* 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

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Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>
Co-authored-by: junkourata <102059808+junkourata@users.noreply.github.com>
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136 changes: 136 additions & 0 deletions ai-platform/snippets/batch-read-feature-values-sample.js
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/*
* Copyright 2022 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

/*
* Batch reads Feature values from a Featurestore.
* See https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
* the code snippet
*/

'use strict';

async function main(
project,
featurestoreId,
inputCsvFile,
destinationTableUri,
location = 'us-central1',
apiEndpoint = 'us-central1-aiplatform.googleapis.com',
timeout = 300000
) {
// [START aiplatform_batch_read_feature_values_sample]
/**
* TODO(developer): Uncomment these variables before running the sample.\
* (Not necessary if passing values as arguments)
*/

// const project = 'YOUR_PROJECT_ID';
// const featurestoreId = 'YOUR_FEATURESTORE_ID';
// const inputCsvFile = 'YOUR_INPUT_CSV_FILE_URI';
// const destinationTableUri = 'YOUR_BQ_DESTINATION_TABLE_URI';
// const location = 'YOUR_PROJECT_LOCATION';
// const apiEndpoint = 'YOUR_API_ENDPOINT';
// const timeout = <TIMEOUT_IN_MILLI_SECONDS>;

// Imports the Google Cloud Featurestore Service Client library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

// Specifies the location of the api endpoint
const clientOptions = {
apiEndpoint: apiEndpoint,
};

// Instantiates a client
const featurestoreServiceClient = new FeaturestoreServiceClient(
clientOptions
);

async function batchReadFeatureValues() {
// Configure the featurestoreId resource
const featurestore = `projects/${project}/locations/${location}/featurestores/${featurestoreId}`;
const csvReadInstances = {
gcsSource: {
uris: [inputCsvFile],
},
};

const destination = {
bigqueryDestination: {
// # Output to BigQuery table created earlier
outputUri: destinationTableUri,
},
};

const usersFeatureSelector = {
idMatcher: {
ids: [
// features, use "*" if you want to select all features within this entity type
'age',
'gender',
'liked_genres',
],
},
};

const usersEntityTypeSpec = {
// Read the 'age', 'gender' and 'liked_genres' features from the 'perm_users' entity
entityTypeId: 'perm_users',
featureSelector: usersFeatureSelector,
};

const moviesFeatureSelector = {
idMatcher: {
ids: ['*'],
},
};

const moviesEntityTypeSpec = {
// Read the all features from the 'perm_movies' entity
entityTypeId: 'perm_movies',
featureSelector: moviesFeatureSelector,
};

const entityTypeSpecs = [usersEntityTypeSpec, moviesEntityTypeSpec];

// Construct request
const request = {
featurestore: featurestore,
csvReadInstances: csvReadInstances,
destination: destination,
entityTypeSpecs: entityTypeSpecs,
};

// Batch Read Feature Values Request
const [operation] = await featurestoreServiceClient.batchReadFeatureValues(
request,
{timeout: Number(timeout)}
);
const [response] = await operation.promise();

console.log('Batch read feature values response');
console.log('Raw response:');
console.log(JSON.stringify(response, null, 2));
}
batchReadFeatureValues();
// [END aiplatform_batch_read_feature_values_sample]
}

process.on('unhandledRejection', err => {
console.error(err.message);
process.exitCode = 1;
});

main(...process.argv.slice(2));
105 changes: 105 additions & 0 deletions ai-platform/snippets/export-feature-values-sample.js
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/*
* Copyright 2022 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

/*
* Exports Feature values from all the entities of a target EntityType.
* See https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
* the code snippet
*/

'use strict';

async function main(
project,
featurestoreId,
entityTypeId,
destinationTableUri,
location = 'us-central1',
apiEndpoint = 'us-central1-aiplatform.googleapis.com',
timeout = 300000
) {
// [START aiplatform_export_feature_values_sample]
/**
* TODO(developer): Uncomment these variables before running the sample.\
* (Not necessary if passing values as arguments)
*/

// const project = 'YOUR_PROJECT_ID';
// const featurestoreId = 'YOUR_FEATURESTORE_ID';
// const entityTypeId = 'YOUR_ENTITY_TYPE_ID';
// const destinationTableUri = 'YOUR_BQ_DESTINATION_TABLE_URI';
// const location = 'YOUR_PROJECT_LOCATION';
// const apiEndpoint = 'YOUR_API_ENDPOINT';
// const timeout = <TIMEOUT_IN_MILLI_SECONDS>;

// Imports the Google Cloud Featurestore Service Client library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

// Specifies the location of the api endpoint
const clientOptions = {
apiEndpoint: apiEndpoint,
};

// Instantiates a client
const featurestoreServiceClient = new FeaturestoreServiceClient(
clientOptions
);

async function exportFeatureValues() {
// Configure the entityType resource
const entityType = `projects/${project}/locations/${location}/featurestores/${featurestoreId}/entityTypes/${entityTypeId}`;

const destination = {
bigqueryDestination: {
// # Output to BigQuery table created earlier
outputUri: destinationTableUri,
},
};

const featureSelector = {
idMatcher: {
ids: ['age', 'gender', 'liked_genres'],
},
};

const request = {
entityType: entityType,
destination: destination,
featureSelector: featureSelector,
fullExport: {},
};

// Export Feature Values Request
const [operation] = await featurestoreServiceClient.exportFeatureValues(
request,
{timeout: Number(timeout)}
);
const [response] = await operation.promise();

console.log('Export feature values response');
console.log('Raw response:');
console.log(JSON.stringify(response, null, 2));
}
exportFeatureValues();
// [END aiplatform_export_feature_values_sample]
}

process.on('unhandledRejection', err => {
console.error(err.message);
process.exitCode = 1;
});

main(...process.argv.slice(2));
113 changes: 113 additions & 0 deletions ai-platform/snippets/export-feature-values-snapshot-sample.js
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/*
* Copyright 2022 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

/*
* Exports Feature values with snapshot from all the entities of a target EntityType.
* See https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
* the code snippet
*/

'use strict';

async function main(
project,
featurestoreId,
entityTypeId,
destinationTableUri,
timestamp,
location = 'us-central1',
apiEndpoint = 'us-central1-aiplatform.googleapis.com',
timeout = 300000
) {
// [START aiplatform_export_feature_values_snapshot_sample]
/**
* TODO(developer): Uncomment these variables before running the sample.\
* (Not necessary if passing values as arguments)
*/

// const project = 'YOUR_PROJECT_ID';
// const featurestoreId = 'YOUR_FEATURESTORE_ID';
// const entityTypeId = 'YOUR_ENTITY_TYPE_ID';
// const destinationTableUri = 'YOUR_BQ_DESTINATION_TABLE_URI';
// const timestamp = <STARTING_TIMESTAMP_OF_SNAPSHOT_IN_SECONDS>;
// const location = 'YOUR_PROJECT_LOCATION';
// const apiEndpoint = 'YOUR_API_ENDPOINT';
// const timeout = <TIMEOUT_IN_MILLI_SECONDS>;

// Imports the Google Cloud Featurestore Service Client library
const {FeaturestoreServiceClient} = require('@google-cloud/aiplatform').v1;

// Specifies the location of the api endpoint
const clientOptions = {
apiEndpoint: apiEndpoint,
};

// Instantiates a client
const featurestoreServiceClient = new FeaturestoreServiceClient(
clientOptions
);

async function exportFeatureValuesSnapshot() {
// Configure the entityType resource
const entityType = `projects/${project}/locations/${location}/featurestores/${featurestoreId}/entityTypes/${entityTypeId}`;

const destination = {
bigqueryDestination: {
// # Output to BigQuery table created earlier
outputUri: destinationTableUri,
},
};

const featureSelector = {
idMatcher: {
ids: ['age', 'gender', 'liked_genres'],
},
};

const snapshotExport = {
startTime: {
seconds: Number(timestamp),
},
};

const request = {
entityType: entityType,
destination: destination,
featureSelector: featureSelector,
snapshotExport: snapshotExport,
};

// Export Feature Values Request
const [operation] = await featurestoreServiceClient.exportFeatureValues(
request,
{timeout: Number(timeout)}
);
const [response] = await operation.promise();

console.log('Export feature values snapshot response');
console.log('Raw response:');
console.log(JSON.stringify(response, null, 2));
}
exportFeatureValuesSnapshot();
// [END aiplatform_export_feature_values_snapshot_sample]
}

process.on('unhandledRejection', err => {
console.error(err.message);
process.exitCode = 1;
});

main(...process.argv.slice(2));
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