# Google BigQuery
BigQuery is a fully managed, serverless data warehouse that enables scalable analysis over petabytes of data.

omniload supports BigQuery as both a source and destination.

## URI format
The URI format for BigQuery is as follows:

```text
bigquery://<project-name>?credentials_path=/path/to/service/account.json&location=<location>
```

URI parameters:
- `project-name`: the name of the project in which the dataset resides
- `credentials_path`: optional, the path to the service account JSON file. If not provided, omniload will use [Application Default Credentials](https://googleapis.dev/python/google-api-core/latest/auth.html#overview)
- `credentials_base64`: optional, base64-encoded service account JSON credentials
- `location`: optional, the location of the dataset

### Authentication

omniload supports multiple authentication methods for BigQuery:

1. **Explicit credentials** (via `credentials_path` or `credentials_base64` in URI):
   ```text
   bigquery://my-project?credentials_path=/path/to/service-account.json
   ```

2. **Application Default Credentials** (recommended for local development and GCP environments):
   ```text
   bigquery://my-project
   ```
   
   When no credentials are provided in the URI, omniload will use the Google authentication library which automatically discovers credentials from:
   - The `GOOGLE_APPLICATION_CREDENTIALS` environment variable
   - User credentials set via `gcloud auth application-default login`
   - Service account credentials when running on Google Cloud (Compute Engine, App Engine, Cloud Run, etc.)

The same URI structure can be used both for sources and destinations. You can read more about SQLAlchemy's BigQuery dialect [here](https://github.com/googleapis/python-bigquery-sqlalchemy/#connection-string-parameters).

### Using GCS as a staging area

omniload can use GCS as a staging area for BigQuery. To do this, you need to set the `--staging-bucket` flag when you are running the command.

```bash
omniload ingest 
    --source-uri $SOURCE_URI
    --dest-uri $BIGQUERY_URI
    --source-table raw.input 
    --dest-table raw.output
    --staging-bucket "gs://your-bucket-name" # [!code focus]
```