Once your Looker (Google Cloud core) instance has been provisioned, it is listed on the Instances page of your Google Cloud project. Click the instance URL to access and authenticate in to the instance.
Once you have logged in to your Looker (Google Cloud core) instance, you can set up a database connection to your Looker (Google Cloud core) instance.
Set up a database connection
Looker (Google Cloud core) must be connected to a database to enable data exploration. See the list of supported dialects to learn which dialects are supported by Looker (Google Cloud core).
You can create a database connection within a Looker (Google Cloud core) instance if you have one of the following permissions:
- the Looker Admin role
- the
manage_project_connectionsLooker permission
You can follow the Set up Looker guide that appears dynamically within the Looker (Google Cloud core) instance to connect your database, or follow the steps listed on the Connecting Looker to your database documentation page and the dialect-specific documentation pages.
If your Looker (Google Cloud core) instance uses a private IP connection, you must set up a route or a private connection to connect it to any of the following types of databases:
- A database in a different network within Google Cloud
- A database that is hosted by another cloud service provider
- An on-premises database
Learn more about private networks and external services on the Private IP networking with Looker (Google Cloud core) documentation page.
Once a database connection is set up, you are ready to set up a LookML project.
Using Application Default Credentials to connect to a BigQuery database
Looker (Google Cloud core) instances can use Application Default Credentials (ADC) to authenticate when you're setting up a connection to a BigQuery Standard SQL database. When you use ADC, the connection will authenticate to the database using the credentials of the Looker (Google Cloud core) project's service account.
To use ADC with a BigQuery database, select Application Default Credentials in the Authentication field of the Connection Settings page of the Looker instance. To connect to a BigQuery database in a different project than your Looker (Google Cloud core) instance, some additional setup is required. See the Using Application Default Credentials with a BigQuery database in a different Google Cloud project section.
Service account impersonation
If you want to authenticate to the BigQuery database using a service account other than the Looker (Google Cloud core) project's service account, you can create a delegated request flow by entering another service account, or a comma-separated chain of service accounts, into the Impersonated Service Account field. The Looker (Google Cloud core) service account is automatically used as the first service account in the chain and does not need to be added to the field. The last service account in the chain (also known as the impersonated service account) is the one that authenticates with the database.
When using service account impersonation, do the following:
- Enable the Service Consumer Management API.
- Make sure that all service accounts in the chain, including the Looker (Google Cloud core) project's service account, have the appropriate IAM permissions.
- Make sure that the impersonated service account has the Service Usage Consumer role, the BigQuery Job User role, and the BigQuery Data Viewer role.
Using Application Default Credentials with a BigQuery database in a different Google Cloud project
The steps for using ADC for a BigQuery Standard SQL database that is outside the project that houses your Looker (Google Cloud core) instance are the same as those for setting up a connection inside the same project. However, prior to setting up the connection in your Looker (Google Cloud core) instance, your Looker (Google Cloud core) project's service account must have the following IAM roles:
- BigQuery Data Viewer role for the project that contains the BigQuery dataset.
- BigQuery Job User role and the Service Usage Consumer role on the billing project listed on the Connection Settings page.
- If your Looker (Google Cloud core) instance uses persistent derived tables with a BigQuery dataset, the service account must also have the BigQuery Data Editor role for the project that contains the BigQuery dataset.
If the Looker (Google Cloud core) service account doesn't already have IAM roles in the project that contains the BigQuery dataset, use the service account's email address when granting roles in that project. To find the service account's email address, go to the IAM page in the Google Cloud console and select the Include Google-provided role grants checkbox. The email will have the format service-<project number>@gcp-sa-looker.iam.gserviceaccount.com. Use that email to grant the proper roles to the service account.
Once the proper roles are granted, follow the steps to use ADC.
You can now use ADC with this BigQuery Standard SQL database. The project attached to the service account that is specified in the Connection Settings page will be used for billing and also act as the default project.
Supported dialects for Looker (Google Cloud core)
The following table shows the Looker (Google Cloud core) support for database dialects:
| Dialect | Supported? |
|---|---|
| Actian Avalanche | No |
| Amazon Athena | Yes |
| Amazon Aurora MySQL | Yes |
| Amazon Redshift | Yes |
| Apache Druid | No |
| Apache Druid 0.13+ | No |
| Apache Druid 0.18+ | Yes |
| Apache Hive 2.3+ | No |
| Apache Hive 3.1.2+ | Yes |
| Apache Spark 3+ | Yes |
| ClickHouse | Yes |
| Cloudera Impala 3.1+ | Yes |
| Cloudera Impala 3.1+ with Native Driver | No |
| Cloudera Impala with Native Driver | No |
| DataVirtuality | No |
| Databricks | Yes |
| Denodo 7 | No |
| Denodo 8 | Yes |
| Dremio | No |
| Dremio 11+ | Yes |
| Exasol | No |
| Firebolt | No |
| Google BigQuery Legacy SQL | No |
| Google BigQuery Standard SQL | Yes |
| Google Cloud PostgreSQL | Yes |
| Google Cloud SQL | Yes |
| Google Spanner | Yes |
| Greenplum | No |
| HyperSQL | Yes |
| IBM Netezza | Yes |
| MariaDB | Yes |
| Microsoft Azure PostgreSQL | Yes |
| Microsoft Azure SQL Database | Yes |
| Microsoft Azure Synapse Analytics | Yes |
| Microsoft SQL Server 2008+ | No |
| Microsoft SQL Server 2012+ | No |
| Microsoft SQL Server 2016 | No |
| Microsoft SQL Server 2017+ | Yes |
| MongoBI | No |
| MySQL | Yes |
| MySQL 8.0.12+ | Yes |
| Oracle | Yes |
| Oracle ADWC | No |
| PostgreSQL 9.5+ | Yes |
| PostgreSQL pre-9.5 | No |
| PrestoDB | Yes |
| PrestoSQL | Yes |
| SAP HANA | No |
| SAP HANA 2+ | Yes |
| SingleStore | No |
| SingleStore 7+ | Yes |
| Snowflake | Yes |
| Teradata | No |
| Trino | Yes |
| Vector | No |
| Vertica | Yes |
Database configuration instructions
Instructions are available for these SQL dialects:
What's next
- Configure a Looker (Google Cloud core) instance
- Manage users within Looker (Google Cloud core)
- Administer a Looker (Google Cloud core) instance from the Google Cloud console
- Looker (Google Cloud core) admin settings
- Use the sample LookML project on a Looker (Google Cloud core) instance