Blob Storage transfers

The BigQuery Data Transfer Service for Azure Blob Storage lets you automatically schedule and manage recurring load jobs from Blob Storage into BigQuery.

Before you begin

Before you create a Blob Storage transfer, do the following:

Required permissions

To create a Blob Storage transfer, you need the bigquery.transfers.update Identity and Access Management (IAM) permission. You also need the bigquery.datasets.get and bigquery.datasets.update permissions on the target dataset.

The predefined bigquery.admin IAM role includes the permissions that you need in order to create a Blob Storage transfer.

For more information about BigQuery IAM, see Access control with IAM.

To confirm you have the correct permissions in Blob Storage to enable the transfer, see Shared access signature (SAS).

If you intend to set up transfer run notifications for Pub/Sub, you must have the pubsub.topics.setIamPolicy permission. Pub/Sub permissions are not required for email notifications only. For more information, see BigQuery Data Transfer Service run notifications.

Limitations

Blob Storage transfers are subject to the following limitations:

Set up a Blob Storage data transfer

Select one of the following options:

Console

  1. In the Google Cloud console, go to the BigQuery page.

    Go to BigQuery

  2. In the BigQuery navigation menu, click Data transfers.

  3. Click Create transfer.

  4. On the Create transfer page, do the following:

    • In the Source type section, for Source, choose Azure Blob Storage.

      Transfer source type

    • In the Transfer config name section, for Display name, enter a name for the transfer.

    • In the Schedule options section:

      • Select a Repeat frequency. If you select Hours, Days, Weeks, or Months, you must also specify a frequency. You can also select Custom to specify a custom repeat frequency. If you select On-demand, then this transfer runs when you manually trigger the transfer.

      • If applicable, select either Start now or Start at set time and provide a start date and run time.

    • In the Destination settings section, for Dataset, choose the dataset you created to store your data.

    • In the Data source details section, do the following:

      • For Destination table, enter the name of the table you created to store the data in BigQuery. Destination table names support parameters.
      • For Azure storage account name, enter the Blob Storage account name.
      • For Container name, enter the Blob Storage container name.
      • For Data path, enter the path to filter files to be transferred. See examples.
      • For SAS token, enter the Azure SAS token.
      • For File format, choose your source data format.
      • For Write disposition, select WRITE_APPEND to incrementally append new data to the destination table, or WRITE_TRUNCATE to overwrite data in the destination table during each transfer run. WRITE_APPEND is the default value for Write disposition.

      For more information about how BigQuery Data Transfer Service ingests data using either WRITE_APPEND or WRITE_TRUNCATE, see Data ingestion for Azure Blob transfers. For more information about the writeDisposition field, see JobConfigurationLoad.

      Data source details

    • In the Transfer options section, do the following:

      • For Number of errors allowed, enter an integer value for the maximum number of bad records that can be ignored. The default value is 0.
      • (Optional) For Decimal target types, enter a comma-separated list of possible SQL data types that decimal values in the source data are converted to. Which SQL data type is selected for conversion depends on the following conditions:
        • In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in your specified list and if it supports the precision and the scale.
        • If none of your listed data types support the precision and the scale, the data type supporting the widest range in your specified list is selected. If a value exceeds the supported range when reading the source data, an error is thrown.
        • The data type STRING supports all precision and scale values.
        • If this field is left empty, the data type defaults to NUMERIC,STRING for ORC, and NUMERIC for other file formats.
        • This field cannot contain duplicate data types.
        • The order of the data types that you list is ignored.

    • If you chose CSV or JSON as your file format, in the JSON, CSV section, check Ignore unknown values to accept rows that contain values that do not match the schema.

    • If you chose CSV as your file format, in the CSV section enter any additional CSV options for loading data.

      CSV options

    • In the Notification options section, you can choose to enable email notifications and Pub/Sub notifications.

      • When you enable email notifications, the transfer administrator receives an email notification when a transfer run fails.
      • When you enable Pub/Sub notifications, choose a topic name to publish to or click Create a topic to create one.

    • If you use CMEKs, in the Advanced options section, select Customer-managed key. A list of your available CMEKs appears for you to choose from. For information about how CMEKs work with the BigQuery Data Transfer Service, see Specify encryption key with transfers.

  5. Click Save.

bq

Use the bq mk --transfer_config command to create a Blob Storage transfer:

bq mk \
  --transfer_config \
  --project_id=PROJECT_ID \
  --data_source=DATA_SOURCE \
  --display_name=DISPLAY_NAME \
  --target_dataset=DATASET \
  --destination_kms_key=DESTINATION_KEY \
  --params=PARAMETERS

Replace the following:

  • PROJECT_ID: (Optional) the project ID containing your target dataset. If not specified, your default project is used.
  • DATA_SOURCE: azure_blob_storage.
  • DISPLAY_NAME: the display name for the transfer configuration. The transfer name can be any value that allows you to easily identify the transfer if you need to modify it later.
  • DATASET: the target dataset for the transfer configuration.
  • DESTINATION_KEY: (Optional) the Cloud KMS key resource ID— for example, projects/project_name/locations/us/keyRings/key_ring_name/cryptoKeys/key_name.
  • PARAMETERS: the parameters for the transfer configuration, listed in JSON format. For example, --params={"param1":"value1", "param2":"value2"}. The following are the parameters for a Blob Storage transfer:
    • destination_table_name_template: Required. The name of your destination table.
    • storage_account: Required. The Blob Storage account name.
    • container: Required. The Blob Storage container name.
    • data_path: Optional. The path to filter files to be transferred. See examples.
    • sas_token: Required. The Azure SAS token.
    • file_format: Optional. The type of files you wish to transfer: CSV, JSON, AVRO, PARQUET, or ORC. The default value is CSV.
    • write_disposition: Optional. Select WRITE_APPEND to append data to the destination table, or WRITE_TRUNCATE, to overwrite data in the destination table. The default value is WRITE_APPEND.
    • max_bad_records: Optional. The number of allowed bad records. The default value is 0.
    • decimal_target_types: Optional. A comma-separated list of possible SQL data types that decimal values in the source data are converted to. If this field is not provided, the data type defaults to NUMERIC,STRING for ORC, and NUMERIC for the other file formats.
    • ignore_unknown_values: Optional, and ignored if file_format is not JSON or CSV. Set to true to accept rows that contain values that do not match the schema.
    • field_delimiter: Optional, and applies only when file_format is CSV. The character that separates fields. The default value is ,.
    • skip_leading_rows: Optional, and applies only when file_format is CSV. Indicates the number of header rows that you don't want to import. The default value is 0.
    • allow_quoted_newlines: Optional, and applies only when file_format is CSV. Indicates whether to allow newlines within quoted fields.
    • allow_jagged_rows: Optional, and applies only when file_format is CSV. Indicates whether to accept rows that are missing trailing optional columns. The missing values are filled in with NULL.

For example, the following creates a Blob Storage transfer called mytransfer:

bq mk \
  --transfer_config \
  --data_source=azure_blob_storage \
  --display_name=mytransfer \
  --target_dataset=mydataset \
  --destination_kms_key=projects/myproject/locations/us/keyRings/mykeyring/cryptoKeys/key1
  --params={"destination_table_name_template":"mytable",
      "storage_account":"myaccount",
      "container":"mycontainer",
      "data_path":"myfolder/*.csv",
      "sas_token":"my_sas_token_value",
      "file_format":"CSV",
      "max_bad_records":"1",
      "ignore_unknown_values":"true",
      "field_delimiter":"|",
      "skip_leading_rows":"1",
      "allow_quoted_newlines":"true",
      "allow_jagged_rows":"false"}

Java

Before trying this sample, follow the Java setup instructions in the BigQuery quickstart using client libraries. For more information, see the BigQuery Java API reference documentation.

To authenticate to BigQuery, set up Application Default Credentials. For more information, see Set up authentication for client libraries. 


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 azure blob storage transfer config.
public class CreateAzureBlobStorageTransfer {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    final String projectId = "MY_PROJECT_ID";
    final String displayName = "MY_TRANSFER_DISPLAY_NAME";
    final String datasetId = "MY_DATASET_ID";
    String tableId = "MY_TABLE_ID";
    String storageAccount = "MY_AZURE_STORAGE_ACCOUNT_NAME";
    String containerName = "MY_AZURE_CONTAINER_NAME";
    String dataPath = "MY_AZURE_FILE_NAME_OR_PREFIX";
    String sasToken = "MY_AZURE_SAS_TOKEN";
    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("storage_account", Value.newBuilder().setStringValue(storageAccount).build());
    params.put("container", Value.newBuilder().setStringValue(containerName).build());
    params.put("data_path", Value.newBuilder().setStringValue(dataPath).build());
    params.put("sas_token", Value.newBuilder().setStringValue(sasToken).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());
    createAzureBlobStorageTransfer(projectId, displayName, datasetId, params);
  }

  public static void createAzureBlobStorageTransfer(
      String projectId, String displayName, String datasetId, Map<String, Value> params)
      throws IOException {
    TransferConfig transferConfig =
        TransferConfig.newBuilder()
            .setDestinationDatasetId(datasetId)
            .setDisplayName(displayName)
            .setDataSourceId("azure_blob_storage")
            .setParams(Struct.newBuilder().putAllFields(params).build())
            .setSchedule("every 24 hours")
            .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.
    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("Azure Blob Storage transfer created successfully: " + config.getName());
    } catch (ApiException ex) {
      System.out.print("Azure Blob Storage transfer was not created." + ex.toString());
    }
  }
}

Specify encryption key with transfers

You can specify customer-managed encryption keys (CMEKs) to encrypt data for a transfer run. You can use a CMEK to support transfers from Azure Blob Storage.

When you specify a CMEK with a transfer, the BigQuery Data Transfer Service applies the CMEK to any intermediate on-disk cache of ingested data so that the entire data transfer workflow is CMEK compliant.

You cannot update an existing transfer to add a CMEK if the transfer was not originally created with a CMEK. For example, you cannot change a destination table that was originally default encrypted to now be encrypted with CMEK. Conversely, you also cannot change a CMEK-encrypted destination table to have a different type of encryption.

You can update a CMEK for a transfer if the transfer configuration was originally created with a CMEK encryption. When you update a CMEK for a transfer configuration, the BigQuery Data Transfer Service propagates the CMEK to the destination tables at the next run of the transfer, where the BigQuery Data Transfer Service replaces any outdated CMEKs with the new CMEK during the transfer run. For more information, see Update a transfer.

You can also use project default keys. When you specify a project default key with a transfer, the BigQuery Data Transfer Service uses the project default key as the default key for any new transfer configurations.

Troubleshoot transfer setup

If you are having issues setting up your transfer, see Blob Storage transfer issues.

What's next