BigQuery
Google BigQuery is a fully managed, serverless data warehouse that enables scalable analysis over petabytes of data. As a development environment in Paradime, BigQuery enables dbt™ development from Paradime's Code IDE.
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:
The following permissions will enable users in Paradime to run dbt™ from Paradime in your BigQuery project:
BigQuery Data Editor
BigQuery User
Initial Setup Instructions
Click Settings in the top menu bar of the Paradime interface to access Account Settings
Click "Connections" in the left sidebar
Click "Add New" next to Code IDE Environment
Select "BigQuery"
Next, choose your preferred authentification method to proceed:
Using BigQuery OAuth
Follow our BigQuery OAuth setup guide to configure OAuth authentication. Each user will need to approve the required scopes when connecting.
Fields 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.
Profile Name
The profile name set in your dbt_project.yaml
. See more here.
dbt-bigquery
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. EU
, US
), or a regional location (e.g. europe-west2
). See more here.
US
Project ID
The unique identifier of your BigQuery project. See more here.
dbt-demo-project
Client ID
The Client ID generated when setting up the OAuth credentials.
xyz123.apps.googleusercontent.com
Client Secret
The Client Secret generated when setting up the OAuth credentials.
GOCSPX-hPfGJe7sd238772BLBA2Bi0ds
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) analytics-global-project
Dataset
The default dataset used to build dbt™️ objects at runtime.
dbt_john
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.
Profile Name
The profile name set in your dbt_project.yaml
. See more here.
dbt-bigquery
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. EU
, US
), or a regional location (e.g. europe-west2
). See more here.
US
Service AccountService Account JSON
The service account JSON file created for this service user.
service_account_user.json
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) analytics-global-project
Dataset
The default dataset used to build dbt™️ objects at runtime.
dbt_john
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