Google BigQuery Dataset IAM
This page shows how to write Terraform for BigQuery Dataset IAM and write them securely.
The Dataset IAM in BigQuery can be configured in Terraform with the resource name
google_bigquery_dataset_iam. The following sections describe how to use the resource and its parameters.
Example Usage from GitHub
An example could not be found in GitHub.
The following arguments are supported:
dataset_id- (Required) The dataset ID.
member/members- (Required) Identities that will be granted the privilege in
role. Each entry can have one of the following values:
- allUsers: A special identifier that represents anyone who is on the internet; with or without a Google account.
- allAuthenticatedUsers: A special identifier that represents anyone who is authenticated with a Google account or a service account.
- user:[emailid]: An email address that represents a specific Google account. For example, firstname.lastname@example.org or email@example.com.
- serviceAccount:[emailid]: An email address that represents a service account. For example, firstname.lastname@example.org.
- group:[emailid]: An email address that represents a Google group. For example, email@example.com.
- domain:[domain]: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
role- (Required) The role that should be applied. Only one
google_bigquery_dataset_iam_bindingcan be used per role. Note that custom roles must be of the format
policy_data- (Required only by
google_bigquery_dataset_iam_policy) The policy data generated by a
project- (Optional) The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
In addition to the arguments listed above, the following computed attributes are exported:
etag- (Computed) The etag of the dataset's IAM policy.
Explanation in Terraform Registry
Three different resources help you manage your IAM policy for BigQuery dataset. Each of these resources serves a different use case:
google_bigquery_dataset_iam_policy: Authoritative. Sets the IAM policy for the dataset and replaces any existing policy already attached.
google_bigquery_dataset_iam_binding: Authoritative for a given role. Updates the IAM policy to grant a role to a list of members. Other roles within the IAM policy for the dataset are preserved.
google_bigquery_dataset_iam_member: Non-authoritative. Updates the IAM policy to grant a role to a new member. Other members for the role for the dataset are preserved. These resources are intended to convert the permissions system for BigQuery datasets to the standard IAM interface. For advanced usages, including creating authorized views, please use either
Note: These resources cannot be used with
google_bigquery_dataset_accessresources or the
google_bigquery_datasetor they will fight over what the policy should be.
Note: Using any of these resources will remove any authorized view permissions from the dataset. To assign and preserve authorized view permissions use the
Note: Legacy BigQuery roles
READERcannot be used with any of these IAM resources. Instead use the full role form of:
google_bigquery_dataset_iam_policycannot be used in conjunction with
google_bigquery_dataset_iam_memberor they will fight over what your policy should be.
google_bigquery_dataset_iam_bindingresources can be used in conjunction with
google_bigquery_dataset_iam_memberresources only if they do not grant privilege to the same role.
Tips: Best Practices for The Other Google BigQuery Resources
In addition to the google_bigquery_dataset, Google BigQuery has the other resources that should be configured for security reasons. Please check some examples of those resources and precautions.
Ensure your BigQuery dataset blocks unwanted access
It is better to block unwanted access from users outside the organization.