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feat(samples): add all feature values samples (#981)
* feat(samples): add all feature values samples * feat(samples): update all feature values samples * feat(samples): update big query dependency in pom.xml * feat(samples): code review changes * feat(samples): updated feature values samples with close method call and list variable * 🦉 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>
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samples/snippets/src/main/java/aiplatform/BatchCreateFeaturesSample.java
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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 | ||
* | ||
* http://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. | ||
* | ||
* | ||
* Create features in bulk for an existing entity type. See | ||
* https://cloud.google.com/vertex-ai/docs/featurestore/setup | ||
* before running the code snippet | ||
*/ | ||
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package aiplatform; | ||
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// [START aiplatform_batch_create_features_sample] | ||
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import com.google.api.gax.longrunning.OperationFuture; | ||
import com.google.cloud.aiplatform.v1.BatchCreateFeaturesOperationMetadata; | ||
import com.google.cloud.aiplatform.v1.BatchCreateFeaturesRequest; | ||
import com.google.cloud.aiplatform.v1.BatchCreateFeaturesResponse; | ||
import com.google.cloud.aiplatform.v1.CreateFeatureRequest; | ||
import com.google.cloud.aiplatform.v1.EntityTypeName; | ||
import com.google.cloud.aiplatform.v1.Feature; | ||
import com.google.cloud.aiplatform.v1.Feature.ValueType; | ||
import com.google.cloud.aiplatform.v1.FeaturestoreServiceClient; | ||
import com.google.cloud.aiplatform.v1.FeaturestoreServiceSettings; | ||
import java.io.IOException; | ||
import java.util.ArrayList; | ||
import java.util.List; | ||
import java.util.concurrent.ExecutionException; | ||
import java.util.concurrent.TimeUnit; | ||
import java.util.concurrent.TimeoutException; | ||
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public class BatchCreateFeaturesSample { | ||
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public static void main(String[] args) | ||
throws IOException, InterruptedException, ExecutionException, TimeoutException { | ||
// TODO(developer): Replace these variables before running the sample. | ||
String project = "YOUR_PROJECT_ID"; | ||
String featurestoreId = "YOUR_FEATURESTORE_ID"; | ||
String entityTypeId = "YOUR_ENTITY_TYPE_ID"; | ||
String location = "us-central1"; | ||
String endpoint = "us-central1-aiplatform.googleapis.com:443"; | ||
int timeout = 300; | ||
batchCreateFeaturesSample(project, featurestoreId, entityTypeId, location, endpoint, timeout); | ||
} | ||
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static void batchCreateFeaturesSample( | ||
String project, | ||
String featurestoreId, | ||
String entityTypeId, | ||
String location, | ||
String endpoint, | ||
int timeout) | ||
throws IOException, InterruptedException, ExecutionException, TimeoutException { | ||
FeaturestoreServiceSettings featurestoreServiceSettings = | ||
FeaturestoreServiceSettings.newBuilder().setEndpoint(endpoint).build(); | ||
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// Initialize client that will be used to send requests. This client only needs to be created | ||
// once, and can be reused for multiple requests. After completing all of your requests, call | ||
// the "close" method on the client to safely clean up any remaining background resources. | ||
try (FeaturestoreServiceClient featurestoreServiceClient = | ||
FeaturestoreServiceClient.create(featurestoreServiceSettings)) { | ||
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List<CreateFeatureRequest> createFeatureRequests = new ArrayList<>(); | ||
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Feature titleFeature = | ||
Feature.newBuilder() | ||
.setDescription("The title of the movie") | ||
.setValueType(ValueType.STRING) | ||
.build(); | ||
Feature genresFeature = | ||
Feature.newBuilder() | ||
.setDescription("The genres of the movie") | ||
.setValueType(ValueType.STRING) | ||
.build(); | ||
Feature averageRatingFeature = | ||
Feature.newBuilder() | ||
.setDescription("The average rating for the movie, range is [1.0-5.0]") | ||
.setValueType(ValueType.DOUBLE) | ||
.build(); | ||
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createFeatureRequests.add( | ||
CreateFeatureRequest.newBuilder().setFeature(titleFeature).setFeatureId("title").build()); | ||
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createFeatureRequests.add( | ||
CreateFeatureRequest.newBuilder() | ||
.setFeature(genresFeature) | ||
.setFeatureId("genres") | ||
.build()); | ||
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createFeatureRequests.add( | ||
CreateFeatureRequest.newBuilder() | ||
.setFeature(averageRatingFeature) | ||
.setFeatureId("average_rating") | ||
.build()); | ||
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BatchCreateFeaturesRequest batchCreateFeaturesRequest = | ||
BatchCreateFeaturesRequest.newBuilder() | ||
.setParent( | ||
EntityTypeName.of(project, location, featurestoreId, entityTypeId).toString()) | ||
.addAllRequests(createFeatureRequests) | ||
.build(); | ||
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OperationFuture<BatchCreateFeaturesResponse, BatchCreateFeaturesOperationMetadata> | ||
batchCreateFeaturesFuture = | ||
featurestoreServiceClient.batchCreateFeaturesAsync(batchCreateFeaturesRequest); | ||
System.out.format( | ||
"Operation name: %s%n", batchCreateFeaturesFuture.getInitialFuture().get().getName()); | ||
System.out.println("Waiting for operation to finish..."); | ||
BatchCreateFeaturesResponse batchCreateFeaturesResponse = | ||
batchCreateFeaturesFuture.get(timeout, TimeUnit.SECONDS); | ||
System.out.println("Batch Create Features Response"); | ||
System.out.println(batchCreateFeaturesResponse); | ||
featurestoreServiceClient.close(); | ||
} | ||
} | ||
} | ||
// [END aiplatform_batch_create_features_sample] |
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