About BigQuery

Google BigQuery is one of the remote sources that Coco Alemana supports natively. You can read data from existing tables, as well as save data to new tables entirely, without using the GCP Console. All of the actions within Coco Alemana also apply to BigQuery tables.

Setting up Google Credentials

You’ll need access to your GCP credentials, or a Google account with access to Google BigQuery.

We assume you have the appropriate permissions to:

1. Query BigQuery
2. List GCP Projects

Note

Your credentials are only stored on your device.

1. Open the External Accounts Window

To provide your credentials to Coco Alemana, open the External Accounts... pane, under the top-level Coco Alemana menu.

2. Add a new External Account

Press the “Add Account…” button, or the plus button on the bottom-left hand side of the window.

Select the “Google” option.

3. Connect Credentials

Provide your credentials through one of the many options available.

For long-term use, you should use “Service Account” key (JWT) credentials. This prevents you from having to re-login to Google periodically. Google enforces a maximum session duration with the “Sign in with Google” option. Please see more details on Service Accounts from Google.

Load a Table from BigQuery

Note

Be careful loading extremely large datasets from Google BigQuery. We execute queries on your behalf, and BigQuery’s pricing model can be expensive.

1. Open a new source

Once your credentials are configured, you’re able to load data from BigQuery. To start, you can create a new source via ⌘ N, and select “BigQuery”.

2. Select a Table

See your available databases and select a table you’d like to import. You can also search for a table in your database.

Modifying BigQuery Tables

You can modify BigQuery frames with the same actions as any other frame. The SQL used in Coco Alemana will translate into BigQuery SQL on your behalf. This means you can work with a massive table without downloading it.

Exporting Data

You export data to BigQuery just like any other frame. You can also export a BigQuery frame to a local file. This process will take slightly longer, as it requires downloading everything onto your device.