How does Rasgo work with BigQuery?

Rasgo is a metadata-only product, meaning all of your actual rows and columns stay in your data warehouse and Rasgo interacts with your data via dynamically generating SQL.
Rasgo performs both reads and writes to BigQuery:
  • Rasgo catalogs tables and views in any project and dataset it has access to
  • Rasgo dynamically generates and executes SQL on behalf of the user to transform and analyze data
  • Rasgo can publish new tables and views into a single project.dataset location

Configure BigQuery for Rasgo

Step 1: Create the service account in Google Cloud Console

Follow these instructions in the BigQuery docs to create a service account and get a JSON service account key.

Step 2: Grant IAM permissions to the new service account

Rasgo needs the following IAM permissions to run:
IAM Permission
Editor permissions to read and write from a single project.dataset (i.e. analytics.rasgo )
User permissions to run queries in the same project as above
Viewer permissions to read from all projects and datasets that should be cataloged by Rasgo
Create CSVs for download
View CSVs for download

Step 3: Create a bucket for CSV exports

In Google Cloud storage console, create a bucket with default settings that you want Rasgo to use when exporting CSVs, and share the name of the bucket with Rasgo. Once configured, your users can trigger a CSV download through the Rasgo UI, and Rasgo will handle exporting query results to this bucket and generating a download URL

Step 4: Create an auto delete lifecycle for CSVs

After creating the bucket, go to the bucket's page and click on Lifecycle tab.
Add a new delete rule that removes the files on the bucket after age of 1 day.

Step 5: Connect via Rasgo

In the Rasgo UI, enter the BigQuery project and dataset that Rasgo should write to, as well as the service account key credentials.
Configuration is complete! You're ready to start using Rasgo.

Step 6 (Optional): Enable OAuth for your Users

Rasgo supports individual user credentials when executing queries on BigQuery via BigQuery OAuth integration. This is an optional step for extra security.
Setting up BigQuery OAuth with Rasgo
To configure the OAuth integration, you need to create a Client ID and Secret in Google Cloud Console. Here are Google's instructions on how to do that.
When working on the configuration for the new OAuth Client ID, use these values:
  • Application type: Web application
  • Name: Rasgo
  • Authorized JavaScript Origins:
  • Authorized redirect URIs:
Click Create to create the Client ID and Secret, and save the values for each. Share them with Rasgo to complete your configuration.

Great Job! You're all set.

Next up is importing tables: