BigQuery

The BigQuery connector lets you perform insert, delete, update, and read operations on Google BigQuery data.

Before you begin

Before using the BigQuery connector, do the following tasks:

• In your Google Cloud project:
  • Ensure that network connectivity is set up. For information about network patterns, see Network connectivity.
  • Grant the roles/connectors.admin IAM role to the user configuring the connector.
  • Grant the following IAM roles to the service account that you want to use for the connector:
    • roles/bigquery.dataEditor

    A service account is a special type of Google account intended to represent a non-human user that needs to authenticate and be authorized to access data in Google APIs. If you don't have a service account, you must create a service account. For more information, see Creating a service account.

  • Enable the following services:
    • secretmanager.googleapis.com (Secret Manager API)
    • connectors.googleapis.com (Connectors API)

    To understand how to enable services, see Enabling services.

  If these services or permissions have not been enabled for your project previously, you are prompted to enable them when configuring the connector.

Configure the connector

Configuring the connector requires you to create a connection to your data source (backend system). A connection is specific to a data source. It means that if you have many data sources, you must create a separate connection for each data source. To create a connection, do the following steps:

1. In the Cloud console, go to the Integration Connectors > Connections page and then select or create a Google Cloud project.

   Go to the Connections page

2. Click + CREATE NEW to open the Create Connection page.
3. In the Location section, choose the location for the connection.
   1. Region: Select a location from the drop-down list.

      For the list of all the supported regions, see Locations.

   2. Click NEXT.
4. In the Connection Details section, complete the following:
   1. Connector: Select BigQuery from the drop down list of available Connectors.
   2. Connector version: Select the Connector version from the drop down list of available versions.
   3. In the Connection Name field, enter a name for the Connection instance.

      Connection names must meet the following criteria:

      • Connection names can use letters, numbers, or hyphens.
      • Letters must be lower-case.
      • Connection names must begin with a letter and end with a letter or number.
      • Connection names cannot exceed 49 characters.
   4. Optionally, enter a Description for the connection instance.
   5. Optionally, enable Cloud logging, and then select a log level. By default, the log level is set to Error.
   6. Service Account: Select a service account that has the required roles.
   7. Optionally, configure the Connection node settings:
      • Minimum number of nodes: Enter the minimum number of connection nodes.
      • Maximum number of nodes: Enter the maximum number of connection nodes.

      A node is a unit (or replica) of a connection that processes transactions. More nodes are required to process more transactions for a connection and conversely, fewer nodes are required to process fewer transactions. To understand how the nodes affect your connector pricing, see Pricing for connection nodes. If you don't enter any values, by default the minimum nodes are set to 2 (for better availability) and the maximum nodes are set to 50.

   Note: You can customize the connection node values only if you are a Pay-as-you-go customer.
   8. Project ID: The ID of the Google Cloud project where the data resides.
   9. Dataset ID: The ID of the BigQuery Dataset.
   10. Use proxy: Select this checkbox to configure a proxy server for the connection and configure the following values:
   • Proxy Auth Scheme: Select the authentication type to authenticate with the proxy server. The following authentication types are supported:
     • Basic: Basic HTTP authentication.
     • Digest: Digest HTTP authentication.
   • Proxy User: A user name to be used to authenticate with the proxy server.
   • Proxy Password: The Secret manager secret of the user's password.
   • Proxy SSL Type: The SSL type to use when connecting to the proxy server. The following authentication types are supported:
     • Auto: Default setting. If the URL is an HTTPS URL, then the Tunnel option is used. If the URL is an HTTP URL, then the NEVER option is used.
     • Always: The connection is always SSL enabled.
     • Never: The connection is not SSL enabled.
     • Tunnel: The connection is through a tunneling proxy. The proxy server opens a connection to the remote host and traffic flows back and forth through the proxy.
   • In the Proxy Server section, enter details of the proxy server.
     1. Click + Add destination.
     2. Select a Destination Type.
        • Host address: Specify the hostname or IP address of the destination.

          If you want to establish a private connection to your backend system, do the following:

          • Create a PSC service attachment.
          • Create an endpoint attachment and then enter the details of the endpoint attachment in the Host address field.
   11. Optionally, click + ADD LABEL to add a label to the Connection in the form of a key/value pair.
   12. Click NEXT.
5. In the Authentication section, enter the authentication details.
   1. Select whether to authenticate with OAuth 2.0 - Authorization code or to proceed without authentication.

      To understand how to configure authentication, see Configure authentication.

   2. Click NEXT.
6. Review: Review your connection and authentication details.
7. Click Create.

Configure authentication

Enter the details based on the authentication you want to use.

• No Authentication: Select this option if you don't require authentication.
• OAuth 2.0 - Authorization code: Select this option to authenticate using a web-based user login flow. Specify the following details:
• Client ID: The client ID required to connect to your backend Google service.
• Scopes: A comma-separated list of desired scopes. To view all the supported OAuth 2.0 scopes for your required Google service, see the relevant section in the OAuth 2.0 Scopes for Google APIs page.
• Client secret: Select the Secret Manager secret. You must have created the Secret Manager secret prior configuring this authorization.
• Secret version: Secret Manager secret version for client secret.

For the Authorization code authentication type, after creating the connection, you must perform a few additional steps for configuring authentication. For more information, see Additional steps after connection creation.

Additional steps after connection creation

If you selected OAuth 2.0 - Authorization code for authentication, you must do the following additional steps after creating the connection:

1. In the Connections page, locate the newly created connection.

   Notice that the Status for the new connector will be Authorization required.

2. Click Authorization required.

   This shows the Edit authorization pane.

3. Copy the Redirect URI value to your external application.
4. Verify the authorization details.
5. Click Authorize.

   If the authorization is successful, the connection status will be set to Active in the Connections page.

Re-authorization for authorization code

If you are using Authorization code authentication type and have made any cofiguration changes in BigQuery, you must re-authorize your BigQuery connection. To re-authorize a connection, perform the following steps:

1. Click on the required connection in the Connections page.

   This opens the connection details page.

2. Click Edit to edit the connection details.
3. Verify the OAuth 2.0 - Authorization code details in the Authentication section.

   If required, make the necessary changes.

4. Click Save. This takes you to the connection details page.
5. Click Edit authorization in the Authentication section. This shows the Authorize pane.
6. Click Authorize.

   If the authorization is successful, the connection status will be set to Active in the Connections page.

Entities, operations, and actions

All the Integration Connectors provide a layer of abstraction for the objects of the connected application. You can access an application's objects only through this abstraction. The abstraction is exposed to you as entities, operations, and actions.

Note: You can view the entities, operations, and actions of a connector in the Connectors task.

• Entity: An entity can be thought of as an object, or a collection of properties, in the connected application or service. The definition of an entity differs from a connector to a connector. For example, in a database connector, tables are the entities, in a file server connector, folders are the entities, and in a messaging system connector, queues are the entities.

  However, it is possible that a connector doesn't support or have any entities, in which case the Entities list will be empty.

• Operation: An operation is the activity that you can perform on an entity. You can perform any of the following operations on an entity:
  • List
  • Get
  • Create
  • Update
  • Delete

  Selecting an entity from the available list, generates a list of operations available for the entity. For a detailed description of the operations, see the Connectors task's entity operations. However, if a connector doesn't support any of the entity operations, such unsupported operations aren't listed in the Operations list.

• Action: An action is a first class function that is made available to the integration through the connector interface. An action lets you make changes to an entity or entities, and vary from connector to connector. Normally, an action will have some input parameters, and an output parameter. However, it is possible that a connector doesn't support any action, in which case the Actions list will be empty.

Note: All entities and actions will have a schema associated with them. For example, an action schema will have the parameter details such as; the parameter names, and its corresponding data type. The schema (metadata) for entities and actions is fetched by the connection at runtime from your backend. If there are any updates to the schema, such updates won't be automatically reflected in your existing connections; you must manually refresh the schema. To refresh the schema for a connection, open the Connection details page of the connection, and then click Refresh connection schema.

System limitations

The BigQuery connector can process a maximum of 8 transactions per second, per node, and throttles any transactions beyond this limit. By default, Integration Connectors allocates 2 nodes (for better availability) for a connection.

For information on the limits applicable to Integration Connectors, see Limits.

Note: The number of Integration Connectors nodes will autoscale dynamically based on your usage. However, if you want to reserve capacity for large volumes without waiting for autoscaling, you can adjust the minimum node value for a connection. More nodes are required to process more transactions for a connection. Conversely, fewer nodes are required if a connection processes fewer transactions. To configure the node values, do the following:

• If you are a pay-as-you-go customer, configure the minimum and maximum node value in the edit connection page.
• If you are a subscription based customer, contact support.

The maximum transactions that a node can handle depends on various factors. So, before adjusting the minimum nodes for better throughput, it is recommended you check if your backend systems are set up optimally to handle the required traffic.

Supported data types

The following are the supported data types for this connector:

• BIGINT
• BINARY
• BIT
• BOOLEAN
• CHAR
• DATE
• DECIMAL
• DOUBLE
• FLOAT
• INTEGER
• LONGN VARCHAR
• LONG VARCHAR
• NCHAR
• NUMERIC
• NVARCHAR
• REAL
• SMALL INT
• TIME
• TIMESTAMP
• TINY INT
• VARBINARY
• VARCHAR

Known issues

The BigQuery connector doesn't support the primary key in a BigQuery table. It means that you can't perform the Get, Update, and Delete entity operations by using an entityId. Alternately, you can use the filter clause to filter records based on an ID.

Actions

This section describes the actions available in the BigQuery connector.

Note: The results of all the entity operations and actions will be available as a JSON response in the Connectors task's connectorOutputPayload response parameter after you run your integration.

CancelJob action

This action lets you cancel a running BigQuery job.

The following table describes the input parameters of the CancelJob action.

Parameter name	Data type	Description
JobId	String	The ID of the job you want to cancel. This is a mandatory field.
Region	String	The region where the job is currently executing. This is not required if the job is a US or EU region.

GetJob action

This action lets you retrieve the configuration information and execution state of an existing job.

The following table describes the input parameters of the GetJob action.

Parameter name	Data type	Description
JobId	String	The ID of the job for which you want to retrieve the configuration. This is a mandatory field.
Region	String	The region where the job is currently executing. This is not required if the job is a US or EU region.

InsertJob action

This action lets you insert a BigQuery job, which can then be selected later to retrieve the query results.

The following table describes the input parameters of the InsertJob action.

Parameter name	Data type	Description
Query	String	The query to submit to BigQuery. This is a mandatory field.
IsDML	String	Should be set to true if the query is a DML statement or false otherwise. The default value is false.
DestinationTable	String	The destination table for the query, in the DestProjectId:DestDatasetId.DestTable format.
WriteDisposition	String	Specifies how to write data to the destination table; such as truncate existing results, append existing results, or write only when the table is empty. Following are the supported values: WRITE_TRUNCATE WRITE_APPEND WRITE_EMPTY The default value is WRITE_TRUNCATE.
DryRun	String	Specifies if the job's execution is a dry run.
MaximumBytesBilled	String	Specifies the maximum bytes that can be processed by the job. BigQuery cancels the job if the job attempts to process more bytes than the specified value.
Region	String	Specifies the region where the job should execute.

InsertLoadJob action

This action lets you insert a BigQuery load job, which adds data from Google Cloud Storage into an existing table.

The following table describes the input parameters of the InsertLoadJob action.

Parameter name	Data type	Description
SourceURIs	String	A space-separated list of Google Cloud Storage URIs.
SourceFormat	String	The source format of the files. Following are the supported values: AVRO NEWLINE_DELIMITED_JSON DATASTORE_BACKUP PARQUET ORC CSV
DestinationTable	String	The destination table for the query, in the DestProjectId.DestDatasetId.DestTable format.
DestinationTableProperties	String	A JSON object specifying the table friendly name, description, and list of labels.
DestinationTableSchema	String	A JSON list specifying the fields used to create the table.
DestinationEncryptionConfiguration	String	A JSON object specifying the KMS encryption settings for the table.
SchemaUpdateOptions	String	A JSON list specifying the options to apply when updating the destination table schema.
TimePartitioning	String	A JSON object specifying the time partitioning type and field.
RangePartitioning	String	A JSON object specifying the range partitioning field and buckets.
Clustering	String	A JSON object specifying the fields to be used for clustering.
Autodetect	String	Specifies if options and schema should be automatically determined for JSON and CSV files.
CreateDisposition	String	Specifies if the destination table needs to be created if it doesn't already exist. Following are the supported values: CREATE_IF_NEEDED CREATE_NEVER The default value is CREATE_IF_NEEDED.
WriteDisposition	String	Specifies how to write data to the destination table, such as; truncate existing results, appending existing results, or writing only when the table is empty. Following are the supported values: WRITE_TRUNCATE WRITE_APPEND WRITE_EMPTY The default value is WRITE_APPEND.
Region	String	Specifies the region where the job should execute. Both the Google Cloud Storage resources and the BigQuery dataset must be in the same region.
DryRun	String	Specifies if the job's execution is a dry run. The default value is false.
MaximumBadRecords	String	Specifies the number of records that can be invalid before the entire job is canceled. By default all records must be valid. The default value is 0.
IgnoreUnknownValues	String	Specifies if the unknown fields must be ignored in the input file or treat them as errors. By default they are treated as errors. The default value is false.
AvroUseLogicalTypes	String	Specifies if AVRO logical types must be used to convert AVRO data to BigQuery types. The default value is true.
CSVSkipLeadingRows	String	Specifies how many rows to skip at the start of CSV files. This is usually used to skip header rows.
CSVEncoding	String	Encoding type of the CSV files. Following are the supported values: ISO-8859-1 UTF-8 The default value is UTF-8.
CSVNullMarker	String	If provided, this string is used for NULL values within CSV files. By default, CSV files cannot use NULL.
CSVFieldDelimiter	String	The character used to separate columns within CSV files. The default value is a comma (,).
CSVQuote	String	The character used for quoted fields in CSV files. May be set to empty to disable quoting. The default value is double quotes (").
CSVAllowQuotedNewlines	String	Specifies if the CSV files can contain newlines within quoted fields. The default value is false.
CSVAllowJaggedRows	String	Specifies if the CSV files can contain missing fields. The default value is false.
DSBackupProjectionFields	String	A JSON list of fields to load from a Cloud datastore backup.
ParquetOptions	String	A JSON object specifying the Parquet-specific import options.
DecimalTargetTypes	String	A JSON list giving the preference order applied to numeric types.
HivePartitioningOptions	String	A JSON object specifying the source-side partitioning options.

Execute custom SQL query

To create a custom query, follow these steps:

1. Follow the detailed instructions to add a connectors task.
2. When you configure the connector task, in the type of action you want to perform, select Actions.
3. In the Action list, select Execute custom query, and then click Done.

   

4. Expand the Task input section, and then do the following:
   1. In the Timeout after field, enter the number of seconds to wait till the query executes.

      Default value: 180 seconds.

   2. In the Maximum number of rows field, enter the maximum number of rows to be returned from the database.

      Default value: 25.

   3. To update the custom query, click Edit Custom Script. The Script editor dialog opens.

      

   4. In the Script editor dialog, enter the SQL query and click Save.

      You can use a question mark (?) in a SQL statement to represent a single parameter that must be specified in the query parameters list. For example, the following SQL query selects all rows from the Employees table that matches the values specified for the LastName column:

      SELECT * FROM Employees where LastName=?

      Note: Data manipulation language (DML) and data definition language (DDL) statements are supported.
   5. If you've used question marks in your SQL query, you must add the parameter by clicking + Add Parameter Name for each question mark. While executing the integration, these parameters replace the question marks (?) in the SQL query sequentially. For example, if you have added three question marks (?), then you must add three parameters in order of sequence.

      

      To add query parameters, do the following:

      1. From the Type list, select the data type of the parameter.
      2. In the Value field, enter the value of the parameter.
      3. To add multiple parameters, click + Add Query Parameter.

Use terraform to create connections

You can use the Terraform resource to create a new connection.

To learn how to apply or remove a Terraform configuration, see Basic Terraform commands.

To view a sample terraform template for connection creation, see sample template.

When creating this connection by using Terraform, you must set the following variables in your Terraform configuration file:

Parameter name	Data type	Required	Description
project_id	STRING	True	The ID of the project containing BigQuery dataset. e.g. myproject.
dataset_id	STRING	False	Dataset ID of the BigQuery dataset without the project name. e.g. mydataset.
proxy_enabled	BOOLEAN	False	Select this checkbox to configure a proxy server for the connection.
proxy_auth_scheme	ENUM	False	The authentication type to use to authenticate to the ProxyServer proxy. Supported values are: BASIC, DIGEST, NONE
proxy_user	STRING	False	A user name to be used to authenticate to the ProxyServer proxy.
proxy_password	SECRET	False	A password to be used to authenticate to the ProxyServer proxy.
proxy_ssltype	ENUM	False	The SSL type to use when connecting to the ProxyServer proxy. Supported values are: AUTO, ALWAYS, NEVER, TUNNEL

Use the BigQuery connection in an integration

After you create the connection, it becomes available in both Apigee Integration and Application Integration. You can use the connection in an integration through the Connectors task.

• To understand how to create and use the Connectors task in Apigee Integration, see Connectors task.
• To understand how to create and use the Connectors task in Application Integration, see Connectors task.

Get help from the Google Cloud community

You can post your questions and discuss this connector in the Google Cloud community at Cloud Forums.

What's next

• Understand how to suspend and resume a connection.
• Understand how to monitor connector usage.
• Understand how to view connector logs.