subcategory |
---|
Security |
This resource allows you to manage users in Databricks Workspace, Databricks Account Console or Azure Databricks Account Console. You can also associate Databricks users to databricks_group. Upon user creation the user will receive a welcome email. You can also get information about caller identity using databricks_current_user data source.
-> Note To assign account level users to workspace use databricks_mws_permission_assignment.
-> Note Entitlements, like, allow_cluster_create
, allow_instance_pool_create
, databricks_sql_access
, workspace_access
applicable only for workspace-level users. Use databricks_entitlements resource to assign entitlements inside a workspace to account-level users.
To create users in the Databricks account, the provider must be configured with host = "https://accounts.cloud.databricks.com"
on AWS deployments or host = "https://accounts.azuredatabricks.net"
and authenticate using AAD tokens on Azure deployments.
The default behavior when deleting a databricks_user
resource depends on whether the provider is configured at the workspace-level or account-level. When the provider is configured at the workspace-level, the user will be deleted from the workspace. When the provider is configured at the account-level, the user will be deactivated but not deleted. When the provider is configured at the account level, to delete the user from the account when the resource is deleted, set disable_as_user_deletion = false
. Conversely, when the provider is configured at the account-level, to deactivate the user when the resource is deleted, set disable_as_user_deletion = true
.
Creating regular user:
resource "databricks_user" "me" {
user_name = "[email protected]"
}
Creating user with administrative permissions - referencing special admins
databricks_group in databricks_group_member resource:
data "databricks_group" "admins" {
display_name = "admins"
}
resource "databricks_user" "me" {
user_name = "[email protected]"
}
resource "databricks_group_member" "i-am-admin" {
group_id = data.databricks_group.admins.id
member_id = databricks_user.me.id
}
Creating user with cluster create permissions:
resource "databricks_user" "me" {
user_name = "[email protected]"
display_name = "Example user"
allow_cluster_create = true
}
Creating user in AWS Databricks account:
// initialize provider at account-level
provider "databricks" {
alias = "mws"
host = "https://accounts.cloud.databricks.com"
account_id = "00000000-0000-0000-0000-000000000000"
client_id = var.client_id
client_secret = var.client_secret
}
resource "databricks_user" "account_user" {
provider = databricks.mws
user_name = "[email protected]"
display_name = "Example user"
}
Creating user in Azure Databricks account:
// initialize provider at Azure account-level
provider "databricks" {
alias = "azure_account"
host = "https://accounts.azuredatabricks.net"
account_id = "00000000-0000-0000-0000-000000000000"
auth_type = "azure-cli"
}
resource "databricks_user" "account_user" {
provider = databricks.azure_account
user_name = "[email protected]"
display_name = "Example user"
}
The following arguments are available:
user_name
- (Required) This is the username of the given user and will be their form of access and identity. Provided username will be converted to lower case if it contains upper case characters.display_name
- (Optional) This is an alias for the username that can be the full name of the user.external_id
- (Optional) ID of the user in an external identity provider.allow_cluster_create
- (Optional) Allow the user to have cluster create privileges. Defaults to false. More fine grained permissions could be assigned with databricks_permissions andcluster_id
argument. Everyone withoutallow_cluster_create
argument set, but with permission to use Cluster Policy would be able to create clusters, but within boundaries of that specific policy.allow_instance_pool_create
- (Optional) Allow the user to have instance pool create privileges. Defaults to false. More fine grained permissions could be assigned with databricks_permissions and instance_pool_id argument.databricks_sql_access
- (Optional) This is a field to allow the group to have access to Databricks SQL feature in User Interface and through databricks_sql_endpoint.active
- (Optional) Either user is active or not. True by default, but can be set to false in case of user deactivation with preserving user assets.force
- (Optional) Ignorecannot create user: User with username X already exists
errors and implicitly import the specific user into Terraform state, enforcing entitlements defined in the instance of resource. This functionality is experimental and is designed to simplify corner cases, like Azure Active Directory synchronisation.force_delete_repos
- (Optional) This flag determines whether the user's repo directory is deleted when the user is deleted. It will have no impact when in the accounts SCIM API. False by default.force_delete_home_dir
- (Optional) This flag determines whether the user's home directory is deleted when the user is deleted. It will have not impact when in the accounts SCIM API. False by default.disable_as_user_deletion
- (Optional) Deactivate the user when deleting the resource, rather than deleting the user entirely. Defaults totrue
when the provider is configured at the account-level andfalse
when configured at the workspace-level. This flag is exclusive to force_delete_repos and force_delete_home_dir flags.
In addition to all arguments above, the following attributes are exported:
id
- Canonical unique identifier for the user.home
- Home folder of the user, e.g./Users/[email protected]
.repos
- Personal Repos location of the user, e.g./Repos/[email protected]
.acl_principal_id
- identifier for use in databricks_access_control_rule_set, e.g.users/[email protected]
.
The resource scim user can be imported using id:
terraform import databricks_user.me <user-id>
The following resources are often used in the same context:
- End to end workspace management guide.
- databricks_group to manage groups in Databricks Workspace or Account Console (for AWS deployments).
- databricks_group data to retrieve information about databricks_group members, entitlements and instance profiles.
- databricks_group_instance_profile to attach databricks_instance_profile (AWS) to databricks_group.
- databricks_group_member to attach users and groups as group members.
- databricks_instance_profile to manage AWS EC2 instance profiles that users can launch databricks_cluster and access data, like databricks_mount.
- databricks_user data to retrieve information about databricks_user.