Pulling data from BigQuery is made straightforward with this connector. To learn more about how to get a JWT for access credentials if needed, please refer to Google’s documentation here. Settings Query: This should be a query that Selects a table or a view from withing Google Big Query. Please note Google Big Query will refuse to export tables if they have a lot of “Order” or “Group” statements or potentially if the table is poorly built in Google Big Query. Credentials (optional): If there are access restrictions on the Google Big Query data then you need to provide the json access credentials for a service account with access to that data here. Show File Content: When a user wants to review the uploaded credentials json file they can use this button. It will load a pop-up window within the browser that displays the file contents. Big Result (optional): This option is for users using legacy sql in their query to set the AllowLargeResults flag.

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To configure a connection to BigQuery:

1. In Google Cloud Platform, create and identify relevant resources:
   • Create or identify a GCP project containing BigQuery tables you would like to connect to.
   • Enable the BigQuery API. For more information, see Use the BigQuery Storage Read API to read table data .
2. In Google Cloud Platform, create and export service account credentials:You can use the BigQuery credentials wizard to expedite this step: Create credentials.To create a service account in GCP, follow the tutorial available in Create service accounts.
   • When selecting project, select the project containing your BigQuery table.
   • When selecting GCP IAM roles for your service account, add or create a role that would grant appropriate permissions to run BigQuery jobs to read, write or create BigQuery tables.
   To create credentials for your service account, follow the tutorial available in Create a service account key.
   • When selecting key type, select JSON.
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You should now have downloaded a JSON file with credentials for your service account. It should look similar to the following:

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‍{
 "type": "service_account",
 "project_id": "*****",
 "private_key_id": "*****",
 "private_key": "*****",
 "client_email": "*****",
 "client_id": "*****",
 "auth_uri": "https://accounts.google.com/o/oauth2/auth",
 "token_uri": "https://oauth2.googleapis.com/token",
 "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
 "client_x509_cert_url": "*****",
 "universe_domain": "googleapis.com"
}

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In InFlow, enter the following information in the Connector's Settings tab

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Selected

Dataset (required)

​Enter the name of an existing dataset from your Google Big Query project

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​

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Table (creates new if does not exist) (required)

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