samples: migrate code from googleapis/java-aiplatform

aiplatform/snippets/pom.xml

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+<?xml version='1.0' encoding='UTF-8'?>
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+  <groupId>com.google.cloud</groupId>
+  <artifactId>aiplatform-snippets</artifactId>
+  <packaging>jar</packaging>
+  <name>Google Cloud Vertex AI Snippets</name>
+  <url>https://github.com/googleapis/java-aiplatform</url>
+
+  <!--
+    The parent pom defines common style checks and testing strategies for our samples.
+    Removing or replacing it should not affect the execution of the samples in anyway.
+  -->
+  <parent>
+    <groupId>com.google.cloud.samples</groupId>
+    <artifactId>shared-configuration</artifactId>
+    <version>1.2.0</version>
+  </parent>
+
+  <properties>
+    <maven.compiler.target>1.8</maven.compiler.target>
+    <maven.compiler.source>1.8</maven.compiler.source>
+    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+  </properties>
+  <!-- [START aiplatform_install_with_bom] -->
+  <dependencies>
+    <dependency>
+      <groupId>com.google.cloud</groupId>
+      <artifactId>google-cloud-aiplatform</artifactId>
+      <version>3.4.1</version>
+    </dependency>
+    <!-- [END aiplatform_install_with_bom] -->
+    <dependency>
+      <groupId>com.google.cloud</groupId>
+      <artifactId>google-cloud-storage</artifactId>
+      <version>2.13.0</version>
+    </dependency>
+    <dependency>
+      <groupId>com.google.protobuf</groupId>
+      <artifactId>protobuf-java-util</artifactId>
+      <version>4.0.0-rc-2</version>
+    </dependency>
+    <dependency>
+      <groupId>com.google.code.gson</groupId>
+      <artifactId>gson</artifactId>
+      <version>2.9.1</version>
+    </dependency>
+    <dependency>
+      <groupId>junit</groupId>
+      <artifactId>junit</artifactId>
+      <version>4.13.2</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.google.truth</groupId>
+      <artifactId>truth</artifactId>
+      <version>1.1.3</version>
+      <scope>test</scope>
+    </dependency>
+    <dependency>
+      <groupId>com.google.api.grpc</groupId>
+      <artifactId>proto-google-cloud-aiplatform-v1beta1</artifactId>
+      <version>0.20.1</version>
+    </dependency>
+	<dependency>
+	  <groupId>com.google.cloud</groupId>
+	  <artifactId>google-cloud-bigquery</artifactId>
+	  <version>2.18.0</version>
+	</dependency>
+  </dependencies>
+</project>

aiplatform/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
+ */
+
+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]

aiplatform/snippets/src/main/java/aiplatform/BatchReadFeatureValuesSample.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.
+ *
+ *
+ * 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]

aiplatform/snippets/src/main/java/aiplatform/CancelBatchPredictionJobSample.java

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+/*
+ * Copyright 2021 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.
+ */
+
+package aiplatform;
+
+// [START aiplatform_cancel_batch_prediction_job_sample]
+
+import com.google.cloud.aiplatform.v1.BatchPredictionJobName;
+import com.google.cloud.aiplatform.v1.JobServiceClient;
+import com.google.cloud.aiplatform.v1.JobServiceSettings;
+import java.io.IOException;
+
+public class CancelBatchPredictionJobSample {
+
+  public static void main(String[] args) throws IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String project = "YOUR_PROJECT_ID";
+    String batchPredictionJobId = "YOUR_BATCH_PREDICTION_JOB_ID";
+    cancelBatchPredictionJobSample(project, batchPredictionJobId);
+  }
+
+  static void cancelBatchPredictionJobSample(String project, String batchPredictionJobId)
+      throws IOException {
+    JobServiceSettings jobServiceSettings =
+        JobServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .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 (JobServiceClient jobServiceClient = JobServiceClient.create(jobServiceSettings)) {
+      String location = "us-central1";
+      BatchPredictionJobName batchPredictionJobName =
+          BatchPredictionJobName.of(project, location, batchPredictionJobId);
+
+      jobServiceClient.cancelBatchPredictionJob(batchPredictionJobName);
+
+      System.out.println("Cancelled the Batch Prediction Job");
+    }
+  }
+}
+// [END aiplatform_cancel_batch_prediction_job_sample]