Crea una configurazione di trasferimento dati

Crea una configurazione di trasferimento in BigQuery Data Transfer Service per pianificare i trasferimenti di dati ricorrenti da un'origine dati supportata a un set di dati BigQuery.

Per saperne di più

Per la documentazione dettagliata che include questo esempio di codice, vedi quanto segue:

Esempio di codice

Java

Prima di provare questo esempio, segui le istruzioni di configurazione di Java nella guida rapida di BigQuery per l'utilizzo delle librerie client. Per saperne di più, consulta la documentazione di riferimento dell'API BigQuery Java.

Per eseguire l'autenticazione in BigQuery, configura le Credenziali predefinite dell'applicazione. Per saperne di più, vedi Configurare l'autenticazione per le librerie client. 

import com.google.api.gax.rpc.ApiException;
import com.google.cloud.bigquery.datatransfer.v1.CreateTransferConfigRequest;
import com.google.cloud.bigquery.datatransfer.v1.DataTransferServiceClient;
import com.google.cloud.bigquery.datatransfer.v1.ProjectName;
import com.google.cloud.bigquery.datatransfer.v1.TransferConfig;
import com.google.protobuf.Struct;
import com.google.protobuf.Value;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;

// Sample to create google cloud storage transfer config
public class CreateCloudStorageTransfer {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    final String projectId = "MY_PROJECT_ID";
    String datasetId = "MY_DATASET_ID";
    String tableId = "MY_TABLE_ID";
    // GCS Uri
    String sourceUri = "gs://cloud-samples-data/bigquery/us-states/us-states.csv";
    String fileFormat = "CSV";
    String fieldDelimiter = ",";
    String skipLeadingRows = "1";
    Map<String, Value> params = new HashMap<>();
    params.put(
        "destination_table_name_template", Value.newBuilder().setStringValue(tableId).build());
    params.put("data_path_template", Value.newBuilder().setStringValue(sourceUri).build());
    params.put("write_disposition", Value.newBuilder().setStringValue("APPEND").build());
    params.put("file_format", Value.newBuilder().setStringValue(fileFormat).build());
    params.put("field_delimiter", Value.newBuilder().setStringValue(fieldDelimiter).build());
    params.put("skip_leading_rows", Value.newBuilder().setStringValue(skipLeadingRows).build());
    TransferConfig transferConfig =
        TransferConfig.newBuilder()
            .setDestinationDatasetId(datasetId)
            .setDisplayName("Your Google Cloud Storage Config Name")
            .setDataSourceId("google_cloud_storage")
            .setParams(Struct.newBuilder().putAllFields(params).build())
            .setSchedule("every 24 hours")
            .build();
    createCloudStorageTransfer(projectId, transferConfig);
  }

  public static void createCloudStorageTransfer(String projectId, TransferConfig transferConfig)
      throws IOException {
    try (DataTransferServiceClient client = DataTransferServiceClient.create()) {
      ProjectName parent = ProjectName.of(projectId);
      CreateTransferConfigRequest request =
          CreateTransferConfigRequest.newBuilder()
              .setParent(parent.toString())
              .setTransferConfig(transferConfig)
              .build();
      TransferConfig config = client.createTransferConfig(request);
      System.out.println("Cloud storage transfer created successfully :" + config.getName());
    } catch (ApiException ex) {
      System.out.print("Cloud storage transfer was not created." + ex.toString());
    }
  }
}

Node.js

Prima di provare questo esempio, segui le istruzioni di configurazione di Node.js nella guida rapida di BigQuery per l'utilizzo delle librerie client. Per saperne di più, consulta la documentazione di riferimento dell'API BigQuery Node.js.

Per eseguire l'autenticazione in BigQuery, configura le Credenziali predefinite dell'applicazione. Per saperne di più, vedi Configurare l'autenticazione per le librerie client. 

const {DataTransferServiceClient} =
  require('@google-cloud/bigquery-data-transfer').v1;
const {status} = require('@grpc/grpc-js');

const client = new DataTransferServiceClient();

/**
 * Creates a transfer configuration for a Google Cloud Storage transfer.
 *
 * This sample demonstrates how to create a transfer configuration that appends
 * data from Google Cloud Storage to a BigQuery dataset.
 *
 * @param {string} projectId The Google Cloud project ID. (for example, 'example-project-id')
 * @param {string} location The BigQuery location where the transfer config should be created. (for example, 'us-central1')
 * @param {string} sourceDataCloudStorageUri The source data to be transferred into BigQuery.
 *   Expects a Cloud Storage object URI. (for example, 'gs://example-bucket/example-data.csv')
 * @param {string} destinationDatasetId The destination BigQuery dataset ID. (for example, 'example_dataset')
 * @param {string} destinationTableName The destination table in the BigQuery dataset. (for example, 'example_destination_table')
 * @param {string} serviceAccountName The service account used by the data transfer process to read data from Google Cloud Storage.
 *   Make sure it has IAM read access to the sourceDataCloudStorageUri [example IAM role: roles/storage.objectViewer]. (for example, 'data-transfer-service-account@example-project-id.iam.gserviceaccount.com')
 */
async function createTransferConfig(
  projectId,
  location,
  sourceDataCloudStorageUri,
  destinationDatasetId,
  destinationTableName,
  serviceAccountName,
) {
  const transferConfig = {
    destinationDatasetId,
    displayName: 'Example Cloud Storage Transfer',
    dataSourceId: 'google_cloud_storage',
    // Params are in google.protobuf.Struct format.
    params: {
      fields: {
        data_path_template: {stringValue: sourceDataCloudStorageUri},
        destination_table_name_template: {stringValue: destinationTableName},
        file_format: {stringValue: 'CSV'},
        skip_leading_rows: {stringValue: '1'},
      },
    },
  };

  const request = {
    parent: `projects/${projectId}/locations/${location}`,
    transferConfig,
    serviceAccountName,
  };

  try {
    const [config] = await client.createTransferConfig(request);
    console.log(`Created transfer config: ${config.name}`);
    console.log(`  Display Name: ${config.displayName}`);
    console.log(`  Data Source ID: ${config.dataSourceId}`);
    console.log(`  Destination Dataset ID: ${config.destinationDatasetId}`);
  } catch (err) {
    if (err.code === status.INVALID_ARGUMENT) {
      console.error(
        `Error: Invalid argument provided for creating Migration '${transferConfig.displayName}'. ` +
          `Details: ${err.message}. Make sure request parameters are valid.`,
      );
      console.error(err);
    } else {
      console.error('Error creating transfer config:', err);
    }
  }
}

Python

Prima di provare questo esempio, segui le istruzioni di configurazione di Python nella guida rapida di BigQuery per l'utilizzo delle librerie client. Per saperne di più, consulta la documentazione di riferimento dell'API BigQuery Python.

Per eseguire l'autenticazione in BigQuery, configura le Credenziali predefinite dell'applicazione. Per saperne di più, vedi Configurare l'autenticazione per le librerie client. 

import google.api_core.exceptions
from google.cloud import bigquery_datatransfer_v1
from google.protobuf import struct_pb2

client = bigquery_datatransfer_v1.DataTransferServiceClient()


def create_transfer_config(
    project_id: str,
    location: str,
    source_cloud_storage_uri: str,
    destination_dataset_id: str,
    destination_table_name: str,
    service_account: str = None,
) -> None:
    """Creates a transfer configuration for a Google Cloud Storage transfer.

    This sample demonstrates how to create a transfer configuration for a
    one-time Google Cloud Storage transfer. It specifies the source data path,
    destination table, and other parameters for the transfer.

    Args:
        project_id: The Google Cloud project ID.
        location: The geographic location of the transfer config, for example "us-central1"
        source_data_path: The Cloud Storage URL of the source data, for example "gs://example-bucket/example-data.csv"
        destination_dataset_id: The BigQuery dataset ID to which data is transferred.
        destination_table_name: The BigQuery table name to which data is transferred.
            Cloud Storage transfers support runtime parameters https://docs.cloud.google.com/bigquery/docs/gcs-transfer-parameters
        service_account: The optional IAM Service Account to use as the transfer owner. Otherwise, the current user is the owner.
    """

    parent = f"projects/{project_id}/locations/{location}"
    data_source_id = "google_cloud_storage"
    params = struct_pb2.Struct()
    params.update(
        {
            "data_path_template": source_cloud_storage_uri,
            "destination_table_name_template": destination_table_name,
            "file_format": "CSV",
            "skip_leading_rows": "1",  # assumes the first line in the CSV is the header
        }
    )
    transfer_config = bigquery_datatransfer_v1.TransferConfig(
        display_name="My Cloud Storage Data Transfer",
        data_source_id=data_source_id,
        destination_dataset_id=destination_dataset_id,
        params=params,
    )

    try:
        request = bigquery_datatransfer_v1.CreateTransferConfigRequest(
            parent=parent,
            transfer_config=transfer_config,
            service_account_name=service_account,
        )

        response = client.create_transfer_config(request=request)
        print(f"Created transfer config: {response.name}")
    except google.api_core.exceptions.InvalidArgument as e:
        print(
            f"Error: Could not create transfer config due to an invalid argument: {e}. Please check the destination dataset and other parameters."
        )
    except google.api_core.exceptions.GoogleAPICallError as e:
        print(f"Error: Could not create transfer config: {e}")

Passaggi successivi

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