use of com.google.cloud.aiplatform.v1.DatasetName in project java-automl by googleapis.
the class ImportDataset method importDataset.
// Import a dataset
static void importDataset(String projectId, String datasetId, String path) throws IOException, ExecutionException, InterruptedException, TimeoutException {
Duration totalTimeout = Duration.ofMinutes(45);
RetrySettings retrySettings = RetrySettings.newBuilder().setTotalTimeout(totalTimeout).build();
AutoMlSettings.Builder builder = AutoMlSettings.newBuilder();
builder.importDataSettings().setRetrySettings(retrySettings).build();
AutoMlSettings settings = builder.build();
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create(settings)) {
// Get the complete path of the dataset.
DatasetName datasetFullId = DatasetName.of(projectId, "us-central1", datasetId);
// Get multiple Google Cloud Storage URIs to import data from
GcsSource gcsSource = GcsSource.newBuilder().addAllInputUris(Arrays.asList(path.split(","))).build();
// Import data from the input URI
InputConfig inputConfig = InputConfig.newBuilder().setGcsSource(gcsSource).build();
System.out.println("Processing import...");
// Start the import job
OperationFuture<Empty, OperationMetadata> operation = client.importDataAsync(datasetFullId, inputConfig);
System.out.format("Operation name: %s%n", operation.getName());
// If you want to wait for the operation to finish, adjust the timeout appropriately. The
// operation will still run if you choose not to wait for it to complete. You can check the
// status of your operation using the operation's name.
Empty response = operation.get(45, TimeUnit.MINUTES);
System.out.format("Dataset imported. %s%n", response);
} catch (TimeoutException e) {
System.out.println("The operation's polling period was not long enough.");
System.out.println("You can use the Operation's name to get the current status.");
System.out.println("The import job is still running and will complete as expected.");
throw e;
}
}
use of com.google.cloud.aiplatform.v1.DatasetName in project java-automl by googleapis.
the class TablesImportDataset method importDataset.
// Import a dataset via BigQuery or Google Cloud Storage
static void importDataset(String projectId, String datasetId, String path) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the complete path of the dataset.
DatasetName datasetFullId = DatasetName.of(projectId, "us-central1", datasetId);
InputConfig.Builder inputConfigBuilder = InputConfig.newBuilder();
// Determine which source type was used for the input path (BigQuery or GCS)
if (path.startsWith("bq")) {
// Get training data file to be imported from a BigQuery source.
BigQuerySource.Builder bigQuerySource = BigQuerySource.newBuilder();
bigQuerySource.setInputUri(path);
inputConfigBuilder.setBigquerySource(bigQuerySource);
} else {
// Get multiple Google Cloud Storage URIs to import data from
GcsSource gcsSource = GcsSource.newBuilder().addAllInputUris(Arrays.asList(path.split(","))).build();
inputConfigBuilder.setGcsSource(gcsSource);
}
// Import data from the input URI
System.out.println("Processing import...");
Empty response = client.importDataAsync(datasetFullId, inputConfigBuilder.build()).get();
System.out.format("Dataset imported. %s%n", response);
}
}
use of com.google.cloud.aiplatform.v1.DatasetName in project java-automl by googleapis.
the class DeleteDataset method deleteDataset.
// Delete a dataset
static void deleteDataset(String projectId, String datasetId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the dataset.
DatasetName datasetFullId = DatasetName.of(projectId, "us-central1", datasetId);
Empty response = client.deleteDatasetAsync(datasetFullId).get();
System.out.format("Dataset deleted. %s\n", response);
}
}
use of com.google.cloud.aiplatform.v1.DatasetName in project java-automl by googleapis.
the class ImportDataset method importDataset.
// Import a dataset
static void importDataset(String projectId, String datasetId, String path) throws IOException, ExecutionException, InterruptedException, TimeoutException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the complete path of the dataset.
DatasetName datasetFullId = DatasetName.of(projectId, "us-central1", datasetId);
// Get multiple Google Cloud Storage URIs to import data from
GcsSource gcsSource = GcsSource.newBuilder().addAllInputUris(Arrays.asList(path.split(","))).build();
// Import data from the input URI
InputConfig inputConfig = InputConfig.newBuilder().setGcsSource(gcsSource).build();
System.out.println("Processing import...");
// Start the import job
OperationFuture<Empty, OperationMetadata> operation = client.importDataAsync(datasetFullId, inputConfig);
System.out.format("Operation name: %s%n", operation.getName());
// If you want to wait for the operation to finish, adjust the timeout appropriately. The
// operation will still run if you choose not to wait for it to complete. You can check the
// status of your operation using the operation's name.
Empty response = operation.get(45, TimeUnit.MINUTES);
System.out.format("Dataset imported. %s%n", response);
} catch (TimeoutException e) {
System.out.println("The operation's polling period was not long enough.");
System.out.println("You can use the Operation's name to get the current status.");
System.out.println("The import job is still running and will complete as expected.");
throw e;
}
}
use of com.google.cloud.aiplatform.v1.DatasetName in project java-aiplatform by googleapis.
the class ImportDataVideoObjectTrackingSampleTest method tearDown.
@After
public void tearDown() throws InterruptedException, ExecutionException, IOException {
// delete the temp dataset
if (datasetId != null) {
DatasetServiceSettings datasetServiceSettings = DatasetServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
try (DatasetServiceClient datasetServiceClient = DatasetServiceClient.create(datasetServiceSettings)) {
DatasetName datasetName = DatasetName.of(PROJECT, LOCATION, datasetId);
OperationFuture<Empty, DeleteOperationMetadata> operationFuture = datasetServiceClient.deleteDatasetAsync(datasetName);
operationFuture.get();
}
}
System.out.flush();
System.setOut(originalPrintStream);
}
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