.avif)
Overview
- Connect to a BigQuery project and read its tables
- Reference a table directly by
dataset.table - Refresh on a schedule with standard cron expressions
What you'll need
Two pieces of information connect Ridge to your project. Collect these from Google Cloud before you start.
Set up the connection
1 Create a Connection
On the Data page, click New Connection and choose BigQuery as the type. Enter the credentials you gathered, then save.
- Project — your GCP project id
- Service Account JSON — the service-account key JSON
2 Create a Dataset
Back on the Data page, click New, select source Connection, and pick the BigQuery connection you just created. A Data Set points at a specific table and carries its own refresh schedule.
3 Select a table
Pick the table Ridge reads from the project, referenced directly as dataset.table.
4 Schedule ingestion
Set an ingestion schedule with standard cron syntax, then save. Ridge reads the table from BigQuery and stores the results, ready for analysis.
Best practices
A few habits keep ingestion fast, secure, and predictable.
Supported features & limitations
- Reads any table your service account can access
- Tests the connection when you save it, so credential problems surface immediately
- Refreshes on the schedule you set, with no infrastructure to manage
- One project per connection — a connection reads tables in the project you configure; add another connection for another project.
- Full refresh only — no incremental loading; use
WHEREto limit the volume ingested on each run.
Troubleshooting
Most connection issues fall into four buckets. Expand the one that matches your error.
Invalid credentials
"invalid serviceaccountcredentials", "could not parse PEM", "invalid_grant", 401, "unauthorized"
Your service-account key is bad or expired. Re-download the JSON key from Google Cloud and re-enter it.
Insufficient permissions
403, "permission denied", "does not have bigquery.…", "Permission bigquery.tables.get denied"
The service account lacks rights. Grant it BigQuery Data Viewer on the dataset (and Job User on the project).
Resource not found
404, "not found", "does not exist", "invalid table"
The project, dataset, or table is wrong. Check the project on the connection, and the dataset.table identifier on the Data Set.
Network unreachable
"could not resolve host", "timed out", "connection refused"
The endpoint is unreachable. Check your egress allowlist.