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>
GoogleCloudPlatform · Aug 3, 2022 · 09ae767 · 09ae767
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diff --git a/aiplatform/snippets/pom.xml b/aiplatform/snippets/pom.xml
@@ -62,6 +62,10 @@
       <artifactId>proto-google-cloud-aiplatform-v1beta1</artifactId>
       <version>0.17.0</version>
     </dependency>
-
+	<dependency>
+	  <groupId>com.google.cloud</groupId>
+	  <artifactId>google-cloud-bigquery</artifactId>
+	  <version>2.13.6</version>
+	</dependency>
   </dependencies>
 </project>
diff --git a/aiplatform/snippets/src/main/java/aiplatform/BatchCreateFeaturesSample.java b/aiplatform/snippets/src/main/java/aiplatform/BatchCreateFeaturesSample.java
@@ -0,0 +1,128 @@
+/*
+ * 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
+ */
+
+package aiplatform;
+
+// [START aiplatform_batch_create_features_sample]
+
+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;
+
+public class BatchCreateFeaturesSample {
+
+  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);
+  }
+
+  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();
+
+    // 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)) {
+
+      List<CreateFeatureRequest> createFeatureRequests = new ArrayList<>();
+
+      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();
+
+      createFeatureRequests.add(
+          CreateFeatureRequest.newBuilder().setFeature(titleFeature).setFeatureId("title").build());
+
+      createFeatureRequests.add(
+          CreateFeatureRequest.newBuilder()
+              .setFeature(genresFeature)
+              .setFeatureId("genres")
+              .build());
+
+      createFeatureRequests.add(
+          CreateFeatureRequest.newBuilder()
+              .setFeature(averageRatingFeature)
+              .setFeatureId("average_rating")
+              .build());
+
+      BatchCreateFeaturesRequest batchCreateFeaturesRequest =
+          BatchCreateFeaturesRequest.newBuilder()
+              .setParent(
+                  EntityTypeName.of(project, location, featurestoreId, entityTypeId).toString())
+              .addAllRequests(createFeatureRequests)
+              .build();
+
+      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]
diff --git a/aiplatform/snippets/src/main/java/aiplatform/BatchReadFeatureValuesSample.java b/aiplatform/snippets/src/main/java/aiplatform/BatchReadFeatureValuesSample.java
@@ -0,0 +1,135 @@
+/*
+ * 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.
+ *
+ *
+ * Batch read feature values from a featurestore, as determined by your
+ * read instances list file, to export data. See
+ * https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
+ * the code snippet
+ */
+
+package aiplatform;
+
+// [START aiplatform_batch_read_feature_values_sample]
+
+import com.google.api.gax.longrunning.OperationFuture;
+import com.google.cloud.aiplatform.v1.BatchReadFeatureValuesOperationMetadata;
+import com.google.cloud.aiplatform.v1.BatchReadFeatureValuesRequest;
+import com.google.cloud.aiplatform.v1.BatchReadFeatureValuesRequest.EntityTypeSpec;
+import com.google.cloud.aiplatform.v1.BatchReadFeatureValuesResponse;
+import com.google.cloud.aiplatform.v1.BigQueryDestination;
+import com.google.cloud.aiplatform.v1.CsvSource;
+import com.google.cloud.aiplatform.v1.FeatureSelector;
+import com.google.cloud.aiplatform.v1.FeatureValueDestination;
+import com.google.cloud.aiplatform.v1.FeaturestoreName;
+import com.google.cloud.aiplatform.v1.FeaturestoreServiceClient;
+import com.google.cloud.aiplatform.v1.FeaturestoreServiceSettings;
+import com.google.cloud.aiplatform.v1.GcsSource;
+import com.google.cloud.aiplatform.v1.IdMatcher;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import java.util.concurrent.ExecutionException;
+import java.util.concurrent.TimeUnit;
+import java.util.concurrent.TimeoutException;
+
+public class BatchReadFeatureValuesSample {
+
+  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 inputCsvFile = "YOU_INPUT_CSV_FILE";
+    String destinationTableUri = "YOUR_DESTINATION_TABLE_URI";
+    List<String> featureSelectorIds = Arrays.asList("title", "genres", "average_rating");
+    String location = "us-central1";
+    String endpoint = "us-central1-aiplatform.googleapis.com:443";
+    int timeout = 300;
+    batchReadFeatureValuesSample(
+        project,
+        featurestoreId,
+        entityTypeId,
+        inputCsvFile,
+        destinationTableUri,
+        featureSelectorIds,
+        location,
+        endpoint,
+        timeout);
+  }
+
+  static void batchReadFeatureValuesSample(
+      String project,
+      String featurestoreId,
+      String entityTypeId,
+      String inputCsvFile,
+      String destinationTableUri,
+      List<String> featureSelectorIds,
+      String location,
+      String endpoint,
+      int timeout)
+      throws IOException, InterruptedException, ExecutionException, TimeoutException {
+    FeaturestoreServiceSettings featurestoreServiceSettings =
+        FeaturestoreServiceSettings.newBuilder().setEndpoint(endpoint).build();
+
+    // 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)) {
+
+      List<EntityTypeSpec> entityTypeSpecs = new ArrayList<>();
+
+      FeatureSelector featureSelector =
+          FeatureSelector.newBuilder()
+              .setIdMatcher(IdMatcher.newBuilder().addAllIds(featureSelectorIds).build())
+              .build();
+      EntityTypeSpec entityTypeSpec =
+          EntityTypeSpec.newBuilder()
+              .setEntityTypeId(entityTypeId)
+              .setFeatureSelector(featureSelector)
+              .build();
+
+      entityTypeSpecs.add(entityTypeSpec);
+
+      BigQueryDestination bigQueryDestination =
+          BigQueryDestination.newBuilder().setOutputUri(destinationTableUri).build();
+      GcsSource gcsSource = GcsSource.newBuilder().addUris(inputCsvFile).build();
+      BatchReadFeatureValuesRequest batchReadFeatureValuesRequest =
+          BatchReadFeatureValuesRequest.newBuilder()
+              .setFeaturestore(FeaturestoreName.of(project, location, featurestoreId).toString())
+              .setCsvReadInstances(CsvSource.newBuilder().setGcsSource(gcsSource))
+              .setDestination(
+                  FeatureValueDestination.newBuilder().setBigqueryDestination(bigQueryDestination))
+              .addAllEntityTypeSpecs(entityTypeSpecs)
+              .build();
+
+      OperationFuture<BatchReadFeatureValuesResponse, BatchReadFeatureValuesOperationMetadata>
+          batchReadFeatureValuesFuture =
+              featurestoreServiceClient.batchReadFeatureValuesAsync(batchReadFeatureValuesRequest);
+      System.out.format(
+          "Operation name: %s%n", batchReadFeatureValuesFuture.getInitialFuture().get().getName());
+      System.out.println("Waiting for operation to finish...");
+      BatchReadFeatureValuesResponse batchReadFeatureValuesResponse =
+          batchReadFeatureValuesFuture.get(timeout, TimeUnit.SECONDS);
+      System.out.println("Batch Read Feature Values Response");
+      System.out.println(batchReadFeatureValuesResponse);
+      featurestoreServiceClient.close();
+    }
+  }
+}
+// [END aiplatform_batch_read_feature_values_sample]
diff --git a/aiplatform/snippets/src/main/java/aiplatform/ExportFeatureValuesSample.java b/aiplatform/snippets/src/main/java/aiplatform/ExportFeatureValuesSample.java
@@ -0,0 +1,119 @@
+/*
+ * 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.
+ *
+ *
+ * Bulk export feature values from a featurestore. See
+ * https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
+ * the code snippet
+ */
+
+package aiplatform;
+
+// [START aiplatform_export_feature_values_sample]
+
+import com.google.api.gax.longrunning.OperationFuture;
+import com.google.cloud.aiplatform.v1.BigQueryDestination;
+import com.google.cloud.aiplatform.v1.EntityTypeName;
+import com.google.cloud.aiplatform.v1.ExportFeatureValuesOperationMetadata;
+import com.google.cloud.aiplatform.v1.ExportFeatureValuesRequest;
+import com.google.cloud.aiplatform.v1.ExportFeatureValuesRequest.FullExport;
+import com.google.cloud.aiplatform.v1.ExportFeatureValuesResponse;
+import com.google.cloud.aiplatform.v1.FeatureSelector;
+import com.google.cloud.aiplatform.v1.FeatureValueDestination;
+import com.google.cloud.aiplatform.v1.FeaturestoreServiceClient;
+import com.google.cloud.aiplatform.v1.FeaturestoreServiceSettings;
+import com.google.cloud.aiplatform.v1.IdMatcher;
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.List;
+import java.util.concurrent.ExecutionException;
+import java.util.concurrent.TimeUnit;
+import java.util.concurrent.TimeoutException;
+
+public class ExportFeatureValuesSample {
+
+  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 destinationTableUri = "YOUR_DESTINATION_TABLE_URI";
+    List<String> featureSelectorIds = Arrays.asList("title", "genres", "average_rating");
+    String location = "us-central1";
+    String endpoint = "us-central1-aiplatform.googleapis.com:443";
+    int timeout = 300;
+    exportFeatureValuesSample(
+        project,
+        featurestoreId,
+        entityTypeId,
+        destinationTableUri,
+        featureSelectorIds,
+        location,
+        endpoint,
+        timeout);
+  }
+
+  static void exportFeatureValuesSample(
+      String project,
+      String featurestoreId,
+      String entityTypeId,
+      String destinationTableUri,
+      List<String> featureSelectorIds,
+      String location,
+      String endpoint,
+      int timeout)
+      throws IOException, InterruptedException, ExecutionException, TimeoutException {
+    FeaturestoreServiceSettings featurestoreServiceSettings =
+        FeaturestoreServiceSettings.newBuilder().setEndpoint(endpoint).build();
+
+    // 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)) {
+
+      FeatureSelector featureSelector =
+          FeatureSelector.newBuilder()
+              .setIdMatcher(IdMatcher.newBuilder().addAllIds(featureSelectorIds).build())
+              .build();
+
+      ExportFeatureValuesRequest exportFeatureValuesRequest =
+          ExportFeatureValuesRequest.newBuilder()
+              .setEntityType(
+                  EntityTypeName.of(project, location, featurestoreId, entityTypeId).toString())
+              .setDestination(
+                  FeatureValueDestination.newBuilder()
+                      .setBigqueryDestination(
+                          BigQueryDestination.newBuilder().setOutputUri(destinationTableUri)))
+              .setFeatureSelector(featureSelector)
+              .setFullExport(FullExport.newBuilder())
+              .build();
+
+      OperationFuture<ExportFeatureValuesResponse, ExportFeatureValuesOperationMetadata>
+          exportFeatureValuesFuture =
+              featurestoreServiceClient.exportFeatureValuesAsync(exportFeatureValuesRequest);
+      System.out.format(
+          "Operation name: %s%n", exportFeatureValuesFuture.getInitialFuture().get().getName());
+      System.out.println("Waiting for operation to finish...");
+      ExportFeatureValuesResponse exportFeatureValuesResponse =
+          exportFeatureValuesFuture.get(timeout, TimeUnit.SECONDS);
+      System.out.println("Export Feature Values Response");
+      System.out.println(exportFeatureValuesResponse);
+      featurestoreServiceClient.close();
+    }
+  }
+}
+// [END aiplatform_export_feature_values_sample]