Examples with BigQuerySource com.google.cloud.aiplatform.v1.BigQuerySource used on opensource projects

Example 1 with BigQuerySource

use of com.google.cloud.aiplatform.v1.BigQuerySource in project java-automl by googleapis.

the class TablesBatchPredictBigQuery method batchPredict.

static void batchPredict(String projectId, String modelId, String inputUri, String outputUri) throws IOException, ExecutionException, InterruptedException {
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient client = PredictionServiceClient.create()) {
        // Get the full path of the model.
        ModelName name = ModelName.of(projectId, "us-central1", modelId);
        // Configure the source of the file from BigQuery
        BigQuerySource bigQuerySource = BigQuerySource.newBuilder().setInputUri(inputUri).build();
        BatchPredictInputConfig inputConfig = BatchPredictInputConfig.newBuilder().setBigquerySource(bigQuerySource).build();
        // Configure where to store the output in BigQuery
        BigQueryDestination bigQueryDestination = BigQueryDestination.newBuilder().setOutputUri(outputUri).build();
        BatchPredictOutputConfig outputConfig = BatchPredictOutputConfig.newBuilder().setBigqueryDestination(bigQueryDestination).build();
        // Build the request that will be sent to the API
        BatchPredictRequest request = BatchPredictRequest.newBuilder().setName(name.toString()).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
        // Start an asynchronous request
        OperationFuture<BatchPredictResult, OperationMetadata> future = client.batchPredictAsync(request);
        System.out.println("Waiting for operation to complete...");
        BatchPredictResult response = future.get();
        System.out.println("Batch Prediction results saved to BigQuery.");
    }
}

Example 2 with BigQuerySource

use of com.google.cloud.aiplatform.v1.BigQuerySource 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);
    }
}

Example 3 with BigQuerySource

use of com.google.cloud.aiplatform.v1.BigQuerySource in project java-retail by googleapis.

the class ImportProductsBigQueryTable method getImportProductsBigQueryRequest.

public static ImportProductsRequest getImportProductsBigQueryRequest(ReconciliationMode reconciliationMode) {
    BigQuerySource bigQuerySource = BigQuerySource.newBuilder().setProjectId(PROJECT_ID).setDatasetId(DATASET_ID).setTableId(TABLE_ID).setDataSchema(DATA_SCHEMA).build();
    ProductInputConfig inputConfig = ProductInputConfig.newBuilder().setBigQuerySource(bigQuerySource).build();
    ImportProductsRequest importRequest = ImportProductsRequest.newBuilder().setParent(DEFAULT_CATALOG).setReconciliationMode(reconciliationMode).setInputConfig(inputConfig).build();
    System.out.printf("Import products from big query table request: %s%n", importRequest);
    return importRequest;
}

Example 4 with BigQuerySource

use of com.google.cloud.aiplatform.v1.BigQuerySource in project java-aiplatform by googleapis.

the class GetBatchPredictionJobSample method getBatchPredictionJobSample.

static void getBatchPredictionJobSample(String project, String batchPredictionJobId) throws IOException {
    JobServiceSettings jobServiceSettings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // 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);
        BatchPredictionJob batchPredictionJob = jobServiceClient.getBatchPredictionJob(batchPredictionJobName);
        System.out.println("Get Batch Prediction Job Response");
        System.out.format("\tName: %s\n", batchPredictionJob.getName());
        System.out.format("\tDisplay Name: %s\n", batchPredictionJob.getDisplayName());
        System.out.format("\tModel: %s\n", batchPredictionJob.getModel());
        System.out.format("\tModel Parameters: %s\n", batchPredictionJob.getModelParameters());
        System.out.format("\tState: %s\n", batchPredictionJob.getState());
        System.out.format("\tCreate Time: %s\n", batchPredictionJob.getCreateTime());
        System.out.format("\tStart Time: %s\n", batchPredictionJob.getStartTime());
        System.out.format("\tEnd Time: %s\n", batchPredictionJob.getEndTime());
        System.out.format("\tUpdate Time: %s\n", batchPredictionJob.getUpdateTime());
        System.out.format("\tLabels: %s\n", batchPredictionJob.getLabelsMap());
        InputConfig inputConfig = batchPredictionJob.getInputConfig();
        System.out.println("\tInput Config");
        System.out.format("\t\tInstances Format: %s\n", inputConfig.getInstancesFormat());
        GcsSource gcsSource = inputConfig.getGcsSource();
        System.out.println("\t\tGcs Source");
        System.out.format("\t\t\tUris: %s\n", gcsSource.getUrisList());
        BigQuerySource bigquerySource = inputConfig.getBigquerySource();
        System.out.println("\t\tBigquery Source");
        System.out.format("\t\t\tInput Uri: %s\n", bigquerySource.getInputUri());
        OutputConfig outputConfig = batchPredictionJob.getOutputConfig();
        System.out.println("\tOutput Config");
        System.out.format("\t\tPredictions Format: %s\n", outputConfig.getPredictionsFormat());
        GcsDestination gcsDestination = outputConfig.getGcsDestination();
        System.out.println("\t\tGcs Destination");
        System.out.format("\t\t\tOutput Uri Prefix: %s\n", gcsDestination.getOutputUriPrefix());
        BigQueryDestination bigqueryDestination = outputConfig.getBigqueryDestination();
        System.out.println("\t\tBigquery Destination");
        System.out.format("\t\t\tOutput Uri: %s\n", bigqueryDestination.getOutputUri());
        OutputInfo outputInfo = batchPredictionJob.getOutputInfo();
        System.out.println("\tOutput Info");
        System.out.format("\t\tGcs Output Directory: %s\n", outputInfo.getGcsOutputDirectory());
        System.out.format("\t\tBigquery Output Dataset: %s\n", outputInfo.getBigqueryOutputDataset());
        Status status = batchPredictionJob.getError();
        System.out.println("\tError");
        System.out.format("\t\tCode: %s\n", status.getCode());
        System.out.format("\t\tMessage: %s\n", status.getMessage());
        List<Any> detailsList = status.getDetailsList();
        for (Status partialFailure : batchPredictionJob.getPartialFailuresList()) {
            System.out.println("\tPartial Failure");
            System.out.format("\t\tCode: %s\n", partialFailure.getCode());
            System.out.format("\t\tMessage: %s\n", partialFailure.getMessage());
            List<Any> details = partialFailure.getDetailsList();
        }
        ResourcesConsumed resourcesConsumed = batchPredictionJob.getResourcesConsumed();
        System.out.println("\tResources Consumed");
        System.out.format("\t\tReplica Hours: %s\n", resourcesConsumed.getReplicaHours());
        CompletionStats completionStats = batchPredictionJob.getCompletionStats();
        System.out.println("\tCompletion Stats");
        System.out.format("\t\tSuccessful Count: %s\n", completionStats.getSuccessfulCount());
        System.out.format("\t\tFailed Count: %s\n", completionStats.getFailedCount());
        System.out.format("\t\tIncomplete Count: %s\n", completionStats.getIncompleteCount());
    }
}

Example 5 with BigQuerySource

use of com.google.cloud.aiplatform.v1.BigQuerySource in project java-aiplatform by googleapis.

the class CreateBatchPredictionJobVideoClassificationSample method createBatchPredictionJobVideoClassification.

static void createBatchPredictionJobVideoClassification(String batchPredictionDisplayName, String modelId, String gcsSourceUri, String gcsDestinationOutputUriPrefix, String project) throws IOException {
    JobServiceSettings jobServiceSettings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient jobServiceClient = JobServiceClient.create(jobServiceSettings)) {
        String location = "us-central1";
        LocationName locationName = LocationName.of(project, location);
        VideoClassificationPredictionParams modelParamsObj = VideoClassificationPredictionParams.newBuilder().setConfidenceThreshold(((float) 0.5)).setMaxPredictions(10000).setSegmentClassification(true).setShotClassification(true).setOneSecIntervalClassification(true).build();
        Value modelParameters = ValueConverter.toValue(modelParamsObj);
        ModelName modelName = ModelName.of(project, location, modelId);
        GcsSource.Builder gcsSource = GcsSource.newBuilder();
        gcsSource.addUris(gcsSourceUri);
        InputConfig inputConfig = InputConfig.newBuilder().setInstancesFormat("jsonl").setGcsSource(gcsSource).build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setPredictionsFormat("jsonl").setGcsDestination(gcsDestination).build();
        BatchPredictionJob batchPredictionJob = BatchPredictionJob.newBuilder().setDisplayName(batchPredictionDisplayName).setModel(modelName.toString()).setModelParameters(modelParameters).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
        BatchPredictionJob batchPredictionJobResponse = jobServiceClient.createBatchPredictionJob(locationName, batchPredictionJob);
        System.out.println("Create Batch Prediction Job Video Classification Response");
        System.out.format("\tName: %s\n", batchPredictionJobResponse.getName());
        System.out.format("\tDisplay Name: %s\n", batchPredictionJobResponse.getDisplayName());
        System.out.format("\tModel %s\n", batchPredictionJobResponse.getModel());
        System.out.format("\tModel Parameters: %s\n", batchPredictionJobResponse.getModelParameters());
        System.out.format("\tState: %s\n", batchPredictionJobResponse.getState());
        System.out.format("\tCreate Time: %s\n", batchPredictionJobResponse.getCreateTime());
        System.out.format("\tStart Time: %s\n", batchPredictionJobResponse.getStartTime());
        System.out.format("\tEnd Time: %s\n", batchPredictionJobResponse.getEndTime());
        System.out.format("\tUpdate Time: %s\n", batchPredictionJobResponse.getUpdateTime());
        System.out.format("\tLabels: %s\n", batchPredictionJobResponse.getLabelsMap());
        InputConfig inputConfigResponse = batchPredictionJobResponse.getInputConfig();
        System.out.println("\tInput Config");
        System.out.format("\t\tInstances Format: %s\n", inputConfigResponse.getInstancesFormat());
        GcsSource gcsSourceResponse = inputConfigResponse.getGcsSource();
        System.out.println("\t\tGcs Source");
        System.out.format("\t\t\tUris %s\n", gcsSourceResponse.getUrisList());
        BigQuerySource bigQuerySource = inputConfigResponse.getBigquerySource();
        System.out.println("\t\tBigquery Source");
        System.out.format("\t\t\tInput_uri: %s\n", bigQuerySource.getInputUri());
        OutputConfig outputConfigResponse = batchPredictionJobResponse.getOutputConfig();
        System.out.println("\tOutput Config");
        System.out.format("\t\tPredictions Format: %s\n", outputConfigResponse.getPredictionsFormat());
        GcsDestination gcsDestinationResponse = outputConfigResponse.getGcsDestination();
        System.out.println("\t\tGcs Destination");
        System.out.format("\t\t\tOutput Uri Prefix: %s\n", gcsDestinationResponse.getOutputUriPrefix());
        BigQueryDestination bigQueryDestination = outputConfigResponse.getBigqueryDestination();
        System.out.println("\t\tBig Query Destination");
        System.out.format("\t\t\tOutput Uri: %s\n", bigQueryDestination.getOutputUri());
        BatchDedicatedResources batchDedicatedResources = batchPredictionJobResponse.getDedicatedResources();
        System.out.println("\tBatch Dedicated Resources");
        System.out.format("\t\tStarting Replica Count: %s\n", batchDedicatedResources.getStartingReplicaCount());
        System.out.format("\t\tMax Replica Count: %s\n", batchDedicatedResources.getMaxReplicaCount());
        MachineSpec machineSpec = batchDedicatedResources.getMachineSpec();
        System.out.println("\t\tMachine Spec");
        System.out.format("\t\t\tMachine Type: %s\n", machineSpec.getMachineType());
        System.out.format("\t\t\tAccelerator Type: %s\n", machineSpec.getAcceleratorType());
        System.out.format("\t\t\tAccelerator Count: %s\n", machineSpec.getAcceleratorCount());
        ManualBatchTuningParameters manualBatchTuningParameters = batchPredictionJobResponse.getManualBatchTuningParameters();
        System.out.println("\tManual Batch Tuning Parameters");
        System.out.format("\t\tBatch Size: %s\n", manualBatchTuningParameters.getBatchSize());
        OutputInfo outputInfo = batchPredictionJobResponse.getOutputInfo();
        System.out.println("\tOutput Info");
        System.out.format("\t\tGcs Output Directory: %s\n", outputInfo.getGcsOutputDirectory());
        System.out.format("\t\tBigquery Output Dataset: %s\n", outputInfo.getBigqueryOutputDataset());
        Status status = batchPredictionJobResponse.getError();
        System.out.println("\tError");
        System.out.format("\t\tCode: %s\n", status.getCode());
        System.out.format("\t\tMessage: %s\n", status.getMessage());
        List<Any> details = status.getDetailsList();
        for (Status partialFailure : batchPredictionJobResponse.getPartialFailuresList()) {
            System.out.println("\tPartial Failure");
            System.out.format("\t\tCode: %s\n", partialFailure.getCode());
            System.out.format("\t\tMessage: %s\n", partialFailure.getMessage());
            List<Any> partialFailureDetailsList = partialFailure.getDetailsList();
        }
        ResourcesConsumed resourcesConsumed = batchPredictionJobResponse.getResourcesConsumed();
        System.out.println("\tResources Consumed");
        System.out.format("\t\tReplica Hours: %s\n", resourcesConsumed.getReplicaHours());
        CompletionStats completionStats = batchPredictionJobResponse.getCompletionStats();
        System.out.println("\tCompletion Stats");
        System.out.format("\t\tSuccessful Count: %s\n", completionStats.getSuccessfulCount());
        System.out.format("\t\tFailed Count: %s\n", completionStats.getFailedCount());
        System.out.format("\t\tIncomplete Count: %s\n", completionStats.getIncompleteCount());
    }
}