Connecting Looker To Bigquery

Connecting Looker to BigQuery

Creates a database connection in Looker to Google BigQuery. This instruction uses Application Default Credentials (ADC), which is the recommended and most secure method for Looker Core instances running in Google Cloud, as it avoids managing service account keys.

Prerequisites

• Looker CLI must be installed and authenticated (see installing-looker-cli and authenticating-looker-cli skills).
• Looker Core instance service account must have the necessary IAM roles on the BigQuery project.

Instructions

1. Identify the GCP Project and Datasets

Identify the following parameters from Step 1 (Discovery):

• GCP Project ID: The GCP project containing the BigQuery datasets (allows hyphens).
• Dataset ID: The BigQuery dataset you want to explore (must be alphanumeric/underscores only, no hyphens).

2. Pre-flight Check: Looker Service Account IAM Roles

Verify that the Looker Core service account has the necessary IAM roles on the target GCP project (BigQuery Data Viewer, BigQuery Job User, and Service Usage Consumer):

[!IMPORTANT] When running queries through the BigQuery connection from the Looker instance, Google Cloud requires the Looker service account to have permission to compute/use resources within the project where BigQuery is billed. Without the roles/serviceusage.serviceUsageConsumer role (which contains serviceusage.services.use), Looker cannot authenticate or dispatch query jobs to BigQuery, resulting in a 400 Bad Request error.

1. Run the IAM pre-flight check script, passing the Looker GCP project ID (where the Looker Core instance resides) and the BigQuery GCP project ID:

   ./skills/onboarding-preflight-check/scripts/preflight_check.sh \
     --mode iam \
     --looker-project {looker_gcp_project_id} \
     --bq-project {bigquery_gcp_project_id}
   

2. If the check fails because roles are missing, first obtain the Looker GCP project number (or copy the exact service account email from the preflight check error output):

   project_number=$(gcloud projects describe {looker_gcp_project_id} --format="value(projectNumber)")
   

   Then run the following commands to grant the required roles to the Looker service account:

   gcloud projects add-iam-policy-binding {bigquery_gcp_project_id} \
     --member="serviceAccount:service-${project_number}@gcp-sa-looker.iam.gserviceaccount.com" \
     --role="roles/bigquery.dataViewer"
   
   gcloud projects add-iam-policy-binding {bigquery_gcp_project_id} \
     --member="serviceAccount:service-${project_number}@gcp-sa-looker.iam.gserviceaccount.com" \
     --role="roles/bigquery.jobUser"
   
   gcloud projects add-iam-policy-binding {bigquery_gcp_project_id} \
     --member="serviceAccount:service-${project_number}@gcp-sa-looker.iam.gserviceaccount.com" \
     --role="roles/serviceusage.serviceUsageConsumer"
   

3. Create the Connection Payload File

To avoid CLI parsing errors with complex arguments, write the connection specifications directly to ./connection_config.json in your workspace.

[!IMPORTANT] For the BigQuery JDBC driver: - host must be set to your GCP Project ID (which supports hyphens). - database and schema must both be set to your Dataset ID (which is strictly alphanumeric/underscores only). Setting database to a project ID with hyphens will cause immediate query execution failures.

{
  "name": "{connection_name}",
  "dialect_name": "bigquery_standard_sql",
  "uses_application_default_credentials": true,
  "host": "{gcp_project_id}",
  "database": "{dataset_name}",
  "schema": "{dataset_name}"
}

4. Register the Connection in Looker

Execute the connection import CLI command, pointing to your payload file:

looker-cli connection import ./connection_config.json

5. Verify the Connection

Retrieve the connection details to ensure it was created correctly:

looker-cli connection cat {connection_name}