Google BigQuery Dataset IAM

google_bigquery_dataset_iam (Terraform)

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.

Parameters

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, alice@gmail.com or joe@example.com.
  • serviceAccount:[emailid]: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
  • group:[emailid]: An email address that represents a Google group. For example, admins@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_binding can be used per role. Note that custom roles must be of the format [projects|organizations]/[parent-name]/roles/[role-name].

• policy_data - (Required only by google_bigquery_dataset_iam_policy) The policy data generated by a google_iam_policy data source.

• 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 google_bigquery_dataset_access or the access field on google_bigquery_dataset.

  Note: These resources cannot be used with google_bigquery_dataset_access resources or the access field on google_bigquery_dataset or 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 google_bigquery_dataset_access instead.

  Note: Legacy BigQuery roles OWNER WRITER and READER cannot be used with any of these IAM resources. Instead use the full role form of: roles/bigquery.dataOwner roles/bigquery.dataEditor and roles/bigquery.dataViewer.

  Note: google_bigquery_dataset_iam_policy cannot be used in conjunction with google_bigquery_dataset_iam_binding and google_bigquery_dataset_iam_member or they will fight over what your policy should be.

  Note: google_bigquery_dataset_iam_binding resources can be used in conjunction with google_bigquery_dataset_iam_member resources 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.

google_bigquery_dataset

Ensure your BigQuery dataset blocks unwanted access

It is better to block unwanted access from users outside the organization.