Connect to BigQuery

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Create a BigQuery Data Source

1. From the navigation pane, click Data > Data Sources.
2. Click Create a Data Source.
3. In the New Data Source window, from Select Data Store, select Google BigQuery.
4. Optional: Enter the unique identifier for your project in GCP Project ID.
5. Enter the Data Source Name.
6. Optional: Enter a Description to explain the purpose of the Data Source to others.
7. Click Next.
8. Copy your Private Key (JSON format). See creating a service account for instructions about creating a service account and downloading the JSON credentials file. You must copy the entire content of the file. The Domino secret store backed by HashiCorp Vault securely stores the credentials.
9. Click Test Credentials.
10. When your Data Source authenticates, click Next.
11. Enter the users and organizations who can view and use the Data Source in projects.
12. Click Finish Setup.

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Alternate way to connect to a Google BigQuery Data Source

1. Go to Google’s Service Accounts page. Select a previous project or create a new project. If you selected Create, the New Project page opens:
2. Create a Service account for your project.
3. Define the access that the Service account must have to BigQuery. See Google’s Access Control documentation for more information.
4. Confirm that your Service account has been created.
5. On the Service Accounts page, create a new key.
6. Download the JSON key and keep it in a safe place. You use this key later to programmatically authenticate to Google.
7. To enable the BigQuery API, click the Google APIs logo.
8. In the Library page, select the Big Query API.
9. If it is not enabled, click Enable.

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Activate your credentials from Domino

/home/ubuntu/google-cloud-sdk/bin/gcloud auth activate-service-account <service account name> --key-file <key file path>

/home/ubuntu/google-cloud-sdk/bin/gcloud auth activate-service-account big-query-example@example-big-query-170823.iam.gserviceaccount.com --key-file key.json

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Authenticate and query using Python

pip install --user gcloud oauth2client==1.4.12

from oauth2client.client import GoogleCredentials
from googleapiclient.discovery import build

# Grab the application's default credentials from the environment.
credentials = GoogleCredentials.get_application_default()

# Construct the service object for interacting with the BigQuery API.
bigquery_service = build('bigquery', 'v2', credentials=credentials)

query_request = bigquery_service.jobs()
query_data = {
    'query': (
    'SELECT TOP(corpus, 10) as title, '
    'COUNT(*) as unique_words '
    'FROM [publicdata:samples.shakespeare];')
}

query_response = query_request.query(
    projectId='example-big-query-170823', # Substitute your ProjectId
    body=query_data).execute()

print('Query Results:')
for row in query_response['rows']:
    print(' '.join(field['v'] for field in row['f']))

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Next steps

• After connecting to your Data Source, learn how to Use Data Sources.
• Share this Data Source with your collaborators.