Load PostgreSQL data into BigQuery

To schedule recurring data transfers from PostgreSQL to BigQuery, you can create a transfer configuration to specify what data objects to transfer, and how often to schedule the data transfer. After you set up the transfer configuration, the BigQuery Data Transfer Service transfers the latest data into a BigQuery table on the specified schedule.

For general information about PostgreSQL transfers, including configuration options, see Introduction to PostgreSQL data transfers.

Limitations

PostgreSQL data transfers are subject to following limitations:

• The maximum number of simultaneous transfer runs to a single PostgreSQL database is determined by the maximum number of concurrent connections supported by the PostgreSQL database. The number of concurrent transfer jobs should be limited to a value less than the maximum number of concurrent connections supported by the PostgreSQL database.

• A single transfer configuration can only support one data transfer run at a given time. When a second data transfer is scheduled to run before the first transfer is completed, then only the first data transfer completes while any other data transfers that overlap with the first transfer are skipped.

  To avoid skipped transfers within a single transfer configuration, we recommend that you increase the duration of time between large data transfers by configuring the repeat frequency.

• During a data transfer, the PostgreSQL connector identifies indexed and partitioned key columns to transfer your data in parallel batches. For this reason, we recommend that you specify primary key columns or use indexed columns in your table to improve the performance and reduce the error rate in your data transfers. Consider the following:

  • If you have indexed or primary key constraints, only the following column types are supported for creating parallel batches:
    • INTEGER
    • TINYINT
    • SMALLINT
    • FLOAT
    • REAL
    • DOUBLE
    • NUMERIC
    • BIGINT
    • DECIMAL
    • DATE
  • PostgreSQL data transfers that don't use primary key or indexed columns can't support more than 2,000,000 records per table.

Incremental transfer limitations

Incremental PostgreSQL transfers are subject to the following limitations:

• You can only choose TIMESTAMP columns as watermark columns.
• Incremental ingestion is only supported for assets with valid watermark columns.
• Values in a watermark column must be monotonically increasing.
• Incremental transfers cannot sync delete operations in the source table.
• A single transfer configuration can only support either incremental or full ingestion.
• You cannot update objects in the asset list after the first incremental ingestion run.
• You cannot change the write mode in a transfer configuration after the first incremental ingestion run.
• You cannot change the watermark column or the primary key after the first incremental ingestion run.
• The destination BigQuery table is clustered using the provided primary key and is subject to clustered table limitations.

• When you update an existing transfer configuration to the incremental ingestion mode for the first time, the first data transfer after that update transfers all available data from your data source. Any subsequent incremental data transfers will transfer only the new and updated rows from your data source.

• We recommend that you create indexes on the watermark column. This connector uses watermark columns for filters in incremental transfers, so indexing these columns can improve performance.

• When making an incremental transfer, you must use the updated data type mapping.

Before you begin

• Create a user in the PostgreSQL database.
• Verify that you have completed all the actions that are required to enable the BigQuery Data Transfer Service.
• Create a BigQuery dataset to store your data.
• Ensure you have the required roles to complete the tasks in this document.

Required roles

If you intend to set up transfer run notifications for Pub/Sub, ensure that you have the pubsub.topics.setIamPolicy Identity and Access Management (IAM) permission. Pub/Sub permissions are not required if you only set up email notifications. For more information, see BigQuery Data Transfer Service run notifications.

To get the permissions that you need to create a BigQuery Data Transfer Service data transfer, ask your administrator to grant you the BigQuery Admin (roles/bigquery.admin) IAM role on your project. For more information about granting roles, see Manage access to projects, folders, and organizations.

This predefined role contains the permissions required to create a BigQuery Data Transfer Service data transfer. To see the exact permissions that are required, expand the Required permissions section:

Required permissions

The following permissions are required to create a BigQuery Data Transfer Service data transfer:

• BigQuery Data Transfer Service permissions:
  • bigquery.transfers.update
  • bigquery.transfers.get
• BigQuery permissions:
  • bigquery.datasets.get
  • bigquery.datasets.getIamPolicy
  • bigquery.datasets.update
  • bigquery.datasets.setIamPolicy
  • bigquery.jobs.create

You might also be able to get these permissions with custom roles or other predefined roles.

For more information, see Grant bigquery.admin access.

Network connections

If a public IP address is not available for the PostgreSQL database connection, you must set up a network attachment.

For detailed instructions on the required network setup, refer to the following documents:

• If you're transferring from Cloud SQL, see Configure Cloud SQL instance access.
• If you're transferring from AWS, see Set up the AWS-Google Cloud VPN and network attachment.
• If you're transferring from Azure, see Set up the Azure-Google Cloud VPN and network attachment.

Set up a PostgreSQL data transfer

Add PostgreSQL data into BigQuery by setting up a transfer configuration using one of the following options:

Console

1. Go to the Data transfers page.

   Go to Data transfers

2. Click Create transfer.

3. In the Source type section, for Source, select PostgreSQL.

4. In the Data source details section, do the following:

   • For Network attachment, select an existing network attachment or click Create Network Attachment. For more information, see the Network connections section of this document.
   • For Host, enter the hostname or IP address of the PostgreSQL database server.
   • For Port number, enter the port number for the PostgreSQL database server.
   • For Database name, enter the name of the PostgreSQL database.
   • For Username, enter the username of the PostgreSQL user initiating the PostgreSQL database connection.
   • For Password, enter the password of the PostgreSQL user initiating the PostgreSQL database connection.
   • For TLS Mode, select an option from the menu. For more information about TLS modes, see TLS configuration.
   • For Trusted PEM Certificate, enter the public certificate of the certificate authority (CA) that issued the TLS certificate of the database server. For more information, see Trusted Server Certificate (PEM).
   • For Enable legacy mapping, select true (default) to use the legacy data type mapping. Select false to use the updated data type mapping. If you are making an incremental transfer, this value must be false. For more information about the data type mapping updates, see March 16, 2027. database server.
   • For Ingestion type, select Full or Incremental.
     • If you select Incremental (Preview), for Write mode, select either Append or Upsert. For more information about the different write modes, see Full or incremental transfers.

   • For PostgreSQL objects to transfer, click Browse.

     Select any objects to be transferred to the BigQuery destination dataset. You can also manually enter any objects to include in the data transfer in this field.

     • If you have selected Append as your incremental write mode, you must select a column as the watermark column.
     • If you have selected Upsert as your incremental write mode, you must select a column as the watermark column, and then select one or more columns as the primary key.

5. In the Transfer config name section, for Display name, enter a name for the transfer. The transfer name can be any value that lets you identify the transfer if you need to modify it later.

6. In the Schedule options section, do the following:

   • Select a repeat frequency. If you select the Hours, Days (default), Weeks, or Months option, you must also specify a frequency. You can also select the Custom option to create a more specific repeat frequency. If you select the On-demand option, this data transfer only runs when you manually trigger the transfer.
   • If applicable, select either the Start now or Start at a set time option and provide a start date and run time.

7. In the Destination settings section, for Dataset, select the dataset that you created to store your data, or click Create new dataset and create one to use as the destination dataset.

8. Optional: In the Notification options section, do the following:

   • To enable email notifications, click the Email notifications toggle to the on position. When you enable this option, the transfer administrator receives an email notification when a transfer run fails.
   • To configure Pub/Sub run notifications for your transfer, click the Pub/Sub notifications toggle to the on position. You can select your topic name or click Create a topic to create one.

9. Click Save.

bq

Enter the bq mk command and supply the transfer creation flag --transfer_config:

bq mk
    --transfer_config
    --project_id=PROJECT_ID
    --data_source=DATA_SOURCE
    --display_name=DISPLAY_NAME
    --target_dataset=DATASET
    --params='PARAMETERS'

Replace the following:

• PROJECT_ID (optional): your Google Cloud project ID. If the --project_id flag isn't supplied to specify a particular project, the default project is used.
• DATA_SOURCE: the data source, which is postgresql.
• DISPLAY_NAME: the display name for the data transfer configuration. The transfer name can be any value that lets you identify the transfer if you need to modify it later.
• DATASET: the target dataset for the data transfer configuration.

• PARAMETERS: the parameters for the created transfer configuration in JSON format. For example: --params='{"param":"param_value"}'. The following are the parameters for a PostgreSQL transfer:

  • connector.networkAttachment (optional): the name of the network attachment to connect to the PostgreSQL database.
  • connector.database: the name of the PostgreSQL database.
  • connector.endpoint.host: the hostname or IP address of the database.
  • connector.endpoint.port: the port number of the database.
  • connector.authentication.username: the username of the database user.
  • connector.authentication.password: the password of the database user.
  • connector.tls.mode: specify a TLS configuration to use with this transfer:
    • ENCRYPT_VERIFY_CA_AND_HOST to encrypt data, and verify CA and hostname
    • ENCRYPT_VERIFY_CA to encrypt data, and verify CA only
    • ENCRYPT_VERIFY_NONE for data encryption only
    • DISABLE for no encryption or verification
  • connector.tls.trustedServerCertificate: (optional) provide one or more PEM-encoded certificates. Required only if connector.tls.mode is ENCRYPT_VERIFY_CA_AND_HOST or ENCRYPT_VERIFY_CA.
  • ingestionType: specify either full or incremental. Incremental transfers are supported in Preview. For more information, see Full or incremental transfers.
  • writeMode: specify either WRITE_MODE_APPEND or WRITE_MODE_UPSERT.
  • watermarkColumns: specify columns in your table as watermark columns. This field is required for incremental transfers.
  • primaryKeys: specify columns in your table as primary keys. This field is required for incremental transfers.
  • connector.legacyMapping: set to true (default) to use the legacy data type mapping. Set to false to use the updated data type mapping. If you are making an incremental transfer, this value must be false. For more information about the data type mapping updates, see March 16, 2027.
  • assets: a list of the names of the PostgreSQL tables to be transferred from the PostgreSQL database as part of the transfer.

For example, the following command creates a PostgreSQL transfer called My Transfer:

bq mk
    --transfer_config
    --target_dataset=mydataset
    --data_source=postgresql
    --display_name='My Transfer'
    --params='{"assets":["DB1/PUBLIC/DEPARTMENT","DB1/PUBLIC/EMPLOYEES"],
        "connector.authentication.username": "User1",
        "connector.authentication.password":"ABC12345",
        "connector.database":"DB1",
        "connector.endpoint.host":"192.168.0.1",
        "connector.endpoint.port":5432,
        "ingestionType":"incremental",
        "writeMode":"WRITE_MODE_APPEND",
        "watermarkColumns":["createdAt","createdAt"],
        "primaryKeys":[['dep_id'], ['report_by','report_title']],
        "connector.tls.mode": "ENCRYPT_VERIFY_CA_AND_HOST",
        "connector.tls.trustedServerCertificate": "PEM-encoded certificate"}'

When you specify multiple assets during an incremental transfer, the values of the watermarkColumns and primaryKeys fields correspond to the position of values in the assets field. In the following example, dep_id corresponds to the table DB1/USER1/DEPARTMENT, while report_by and report_title corresponds to the table DB1/USER1/EMPLOYEES.

      "primaryKeys":[['dep_id'], ['report_by','report_title']],
      "assets":["DB1/USER1/DEPARTMENT","DB1/USER1/EMPLOYEES"],
  

API

Use the projects.locations.transferConfigs.create method and supply an instance of the TransferConfig resource.

When you save the transfer configuration, the PostgreSQL connector automatically triggers a transfer run according to your schedule option. With every transfer run, the PostgreSQL connector transfers all available data from PostgreSQL into BigQuery.

To manually run a data transfer outside of your regular schedule, you can start a backfill run.

Troubleshoot

If you are having issues setting up your data transfer, see PostgreSQL transfer issues.

Transfer metadata

Preview

This product is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms. Pre-GA products are available "as is" and might have limited support. For more information, see the launch stage descriptions.

You can also use the PostgreSQL connector to transfer metadata to Knowledge Catalog. For more information, see Load PostgreSQL metadata into Knowledge Catalog.

What's next

• Read an overview about the BigQuery Data Transfer Service.
• Learn about managing transfers, including getting information about a transfer configuration, listing transfer configurations, and viewing a transfer's run history.
• Learn how to load data with BigQuery Omni operations.