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feat(samples): add remaining featurestore api samples (#974)
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* Added Featurestore Samples

* feat(samples): add remaining featurestore api samples (googleapis#945)

* 🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

* feat(samples): update all featurestore samples

* 🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

* 🦉 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: Alice <65933803+alicejli@users.noreply.github.com>
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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 a featurestore resource to contain entity types and features. See
* https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
* the code snippet
*/

package aiplatform;

// [START aiplatform_create_featurestore_fixed_nodes_sample]

import com.google.api.gax.longrunning.OperationFuture;
import com.google.cloud.aiplatform.v1beta1.CreateFeaturestoreOperationMetadata;
import com.google.cloud.aiplatform.v1beta1.CreateFeaturestoreRequest;
import com.google.cloud.aiplatform.v1beta1.Featurestore;
import com.google.cloud.aiplatform.v1beta1.Featurestore.OnlineServingConfig;
import com.google.cloud.aiplatform.v1beta1.FeaturestoreServiceClient;
import com.google.cloud.aiplatform.v1beta1.FeaturestoreServiceSettings;
import com.google.cloud.aiplatform.v1beta1.LocationName;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;

public class CreateFeaturestoreFixedNodesSample {

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";
int fixedNodeCount = 1;
String location = "us-central1";
String endpoint = "us-central1-aiplatform.googleapis.com:443";
int timeout = 900;
createFeaturestoreFixedNodesSample(
project, featurestoreId, fixedNodeCount, location, endpoint, timeout);
}

static void createFeaturestoreFixedNodesSample(
String project,
String featurestoreId,
int fixedNodeCount,
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)) {

OnlineServingConfig.Builder builderValue =
OnlineServingConfig.newBuilder().setFixedNodeCount(fixedNodeCount);
Featurestore featurestore =
Featurestore.newBuilder().setOnlineServingConfig(builderValue).build();

CreateFeaturestoreRequest createFeaturestoreRequest =
CreateFeaturestoreRequest.newBuilder()
.setParent(LocationName.of(project, location).toString())
.setFeaturestore(featurestore)
.setFeaturestoreId(featurestoreId)
.build();

OperationFuture<Featurestore, CreateFeaturestoreOperationMetadata> featurestoreFuture =
featurestoreServiceClient.createFeaturestoreAsync(createFeaturestoreRequest);
System.out.format(
"Operation name: %s%n", featurestoreFuture.getInitialFuture().get().getName());
System.out.println("Waiting for operation to finish...");
Featurestore featurestoreResponse = featurestoreFuture.get(timeout, TimeUnit.SECONDS);
System.out.println("Create Featurestore Response");
System.out.format("Name: %s%n", featurestoreResponse.getName());
}
}
}
// [END aiplatform_create_featurestore_fixed_nodes_sample]
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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.
*
*
* Gets details of a single featurestore. See
* https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
* the code snippet
*/

package aiplatform;

// [START aiplatform_get_featurestore_sample]

import com.google.cloud.aiplatform.v1beta1.Featurestore;
import com.google.cloud.aiplatform.v1beta1.FeaturestoreName;
import com.google.cloud.aiplatform.v1beta1.FeaturestoreServiceClient;
import com.google.cloud.aiplatform.v1beta1.FeaturestoreServiceSettings;
import com.google.cloud.aiplatform.v1beta1.GetFeaturestoreRequest;
import java.io.IOException;

public class GetFeaturestoreSample {

public static void main(String[] args) throws IOException {
// TODO(developer): Replace these variables before running the sample.
String project = "YOUR_PROJECT_ID";
String featurestoreId = "YOUR_FEATURESTORE_ID";
String location = "us-central1";
String endpoint = "us-central1-aiplatform.googleapis.com:443";
getFeaturestoreSample(project, featurestoreId, location, endpoint);
}

static void getFeaturestoreSample(
String project, String featurestoreId, String location, String endpoint) throws IOException {

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)) {

GetFeaturestoreRequest getFeaturestoreRequest =
GetFeaturestoreRequest.newBuilder()
.setName(FeaturestoreName.of(project, location, featurestoreId).toString())
.build();

Featurestore featurestore = featurestoreServiceClient.getFeaturestore(getFeaturestoreRequest);
System.out.println("Get Featurestore Response");
System.out.println(featurestore);
}
}
}
// [END aiplatform_get_featurestore_sample]
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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.
*
*
* List available featurestore details. See
* https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
* the code snippet
*/

package aiplatform;

// [START aiplatform_list_featurestores_async_sample]

import com.google.cloud.aiplatform.v1.Featurestore;
import com.google.cloud.aiplatform.v1.FeaturestoreServiceClient;
import com.google.cloud.aiplatform.v1.FeaturestoreServiceSettings;
import com.google.cloud.aiplatform.v1.ListFeaturestoresRequest;
import com.google.cloud.aiplatform.v1.ListFeaturestoresResponse;
import com.google.cloud.aiplatform.v1.LocationName;
import com.google.common.base.Strings;
import java.io.IOException;

public class ListFeaturestoresAsyncSample {

public static void main(String[] args) throws IOException {
// TODO(developer): Replace these variables before running the sample.
String project = "YOUR_PROJECT_ID";
String location = "us-central1";
String endpoint = "us-central1-aiplatform.googleapis.com:443";
listFeaturestoresAsyncSample(project, location, endpoint);
}

static void listFeaturestoresAsyncSample(String project, String location, String endpoint)
throws IOException {
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)) {

ListFeaturestoresRequest listFeaturestoresRequest =
ListFeaturestoresRequest.newBuilder()
.setParent(LocationName.of(project, location).toString())
.build();
System.out.println("List Featurestores Async Response");
while (true) {
ListFeaturestoresResponse listFeaturestoresResponse =
featurestoreServiceClient.listFeaturestoresCallable().call(listFeaturestoresRequest);
for (Featurestore element : listFeaturestoresResponse.getFeaturestoresList()) {
System.out.println(element);
}
String nextPageToken = listFeaturestoresResponse.getNextPageToken();
if (!Strings.isNullOrEmpty(nextPageToken)) {
listFeaturestoresRequest =
listFeaturestoresRequest.toBuilder().setPageToken(nextPageToken).build();
} else {
break;
}
}
}
}
}
// [END aiplatform_list_featurestores_async_sample]
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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.
*
*
* List available featurestore details. See
* https://cloud.google.com/vertex-ai/docs/featurestore/setup before running
* the code snippet
*/

package aiplatform;

// [START aiplatform_list_featurestores_sample]

import com.google.cloud.aiplatform.v1.Featurestore;
import com.google.cloud.aiplatform.v1.FeaturestoreServiceClient;
import com.google.cloud.aiplatform.v1.FeaturestoreServiceSettings;
import com.google.cloud.aiplatform.v1.ListFeaturestoresRequest;
import com.google.cloud.aiplatform.v1.LocationName;
import java.io.IOException;

public class ListFeaturestoresSample {

public static void main(String[] args) throws IOException {
// TODO(developer): Replace these variables before running the sample.
String project = "YOUR_PROJECT_ID";
String location = "us-central1";
String endpoint = "us-central1-aiplatform.googleapis.com:443";
listFeaturestoresSample(project, location, endpoint);
}

static void listFeaturestoresSample(String project, String location, String endpoint)
throws IOException {
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)) {

ListFeaturestoresRequest listFeaturestoresRequest =
ListFeaturestoresRequest.newBuilder()
.setParent(LocationName.of(project, location).toString())
.build();

System.out.println("List Featurestores Response");
for (Featurestore element :
featurestoreServiceClient.listFeaturestores(listFeaturestoresRequest).iterateAll()) {
System.out.println(element);
}
}
}
}
// [END aiplatform_list_featurestores_sample]
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