BigQuery connection
IP RESTRICTIONS
Make sure to allow traffic from one of the Paradime IPs in your firewall depending on the data location selected.
👉 See also: Paradime IP addresses.
Suggested permissions
This set of permissions will enable users in Paradime to read from and create tables and views when running dbt™️ from the Paradime terminal in you BigQuery project.
Add Development Connection
You will be prompted to add a Development connection during the onboarding, or you can add more connections by going to account settings > connections, select Development Environment and enter the required fields.
Using BigQuery OAuth
Check our Tutorial on how to setup BigQuery OAuth in your BIgQuery account. Once this connection is configured, each user will be redirected to BigQuery and asked to approved the required scopes.
pageConfigure BigQuery OAuthFields Details
Below are list of fields and example to create a connection.
🏢
Workspace level
fields are set by the the workspaceAdmin
and not configurable for by user👥
User level
fields are set by each user (Admin
/Developer
) when setting the Development connection.
Field | Description | Example | Level |
---|---|---|---|
Profile Name | The profile name set in your |
| 🏢 Workspace level |
Target | The target name used to identify the connection. See more here. |
| 🏢 Workspace level |
Dataset Location | The location of BigQuery datasets can be configured using the location configuration in a BigQuery profile. Location can be either a multi-regional location (e.g. |
| 🏢 Workspace level |
Project ID | The unique identifier of your BigQuery project. See more here. |
| 🏢 Workspace level |
Client ID | The Client ID generated when setting up the OAuth credentials. |
| 🏢 Workspace level |
Client Secret | The Client Secret generated when setting up the OAuth credentials. |
| 🏢 Workspace level |
Execution Project ID (Optional) | You can specify an Execution Project ID to bill for query execution, instead of the project where you materialize your resources. See more here. | (Optional) | 🏢 Workspace level |
Dataset | The default dataset used to build dbt™️ objects at runtime. |
| 👥 User level |
Threads | The number of threads used in this connection. See more here. |
| 👥 User level |
Using BigQuery Service Account JSON
Uploading a service account JSON key file is the quickly and accurately way to configure a connection to BigQuery and authenticate each user's development credentials.
To create a service account in BigQuery, follow the detailed steps in Google Cloud's Creating and managing service account keys.
Field Details
Below are list of fields and example to create a connection.
🏢
Workspace level
fields are set by the the workspaceAdmin
and not configurable for by user👥
User level
fields are set by each user (Admin
/Developer
) when setting the Development connection.
Field | Description | Example | Level |
---|---|---|---|
Profile Name | The profile name set in your |
| 🏢 Workspace level |
Target | The target name used to identify the connection. See more here. |
| 🏢 Workspace level |
Dataset Location | The location of BigQuery datasets can be configured using the location configuration in a BigQuery profile. Location can be either a multi-regional location (e.g. |
| 🏢 Workspace level |
Service AccountService Account JSON | The service account JSON file created for this service user. |
| 🏢 Workspace level |
Execution Project ID (Optional) | You can specify an Execution Project ID to bill for query execution, instead of the project where you materialize your resources. See more here. | (Optional) | 🏢 Workspace level |
Dataset | The default dataset used to build dbt™️ objects at runtime. |
| 👥 User level |
Threads | The number of threads used in this connection. See more here. |
| 👥 User level |
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