# Google Cloud Bigquery Module

This module allows managing a single BigQuery dataset, including access configuration, tables and views.

<!-- BEGIN TOC -->
- [Simple dataset with access configuration](#simple-dataset-with-access-configuration)
- [IAM roles](#iam-roles)
- [Authorized Views, Datasets, and Routines](#authorized-views-datasets-and-routines)
- [Dataset options](#dataset-options)
- [Tables, views and routines](#tables-views-and-routines)
- [Tag bindings](#tag-bindings)
- [TODO](#todo)
- [Variables](#variables)
- [Outputs](#outputs)
<!-- END TOC -->

## Simple dataset with access configuration

Access configuration defaults to using the separate `google_bigquery_dataset_access` resource, so as to leave the default dataset access rules untouched.

You can choose to manage the `google_bigquery_dataset` access rules instead via the `dataset_access` variable, but be sure to always have at least one `OWNER` access and to avoid duplicating accesses, or `terraform apply` will fail.

The access variables are split into `access` and `access_identities` variables, so that dynamic values can be passed in for identities (eg a service account email generated by a different module or resource).

```hcl
module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  access = {
    reader-group   = { role = "READER", type = "group" }
    owner          = { role = "OWNER", type = "user" }
    project_owners = { role = "OWNER", type = "special_group" }
    view_1         = { role = "READER", type = "view" }
  }
  access_identities = {
    reader-group   = "playground-test@ludomagno.net"
    owner          = "ludo@ludomagno.net"
    project_owners = "projectOwners"
    view_1         = "my-project|my_dataset|my-table"
  }
}
# tftest modules=1 resources=5 inventory=simple.yaml
```

## IAM roles

Access configuration can also be specified via IAM instead of basic roles via the `iam` variable. When using IAM, basic roles cannot be used via the `access` family variables.

```hcl
module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  iam = {
    "roles/bigquery.dataOwner" = ["user:user1@example.org"]
  }
  iam_bindings = {
    reader_user = {
      role    = "roles/bigquery.dataViewer"
      members = ["user:user2@example.org"]
    }
  }
}
# tftest modules=1 resources=3 inventory=iam.yaml
```

## Authorized Views, Datasets, and Routines

You can specify authorized [views](https://cloud.google.com/bigquery/docs/authorized-views), [datasets](https://cloud.google.com/bigquery/docs/authorized-datasets?hl=en), and [routines](https://cloud.google.com/bigquery/docs/authorized-routines) via the `authorized_views`, `authorized_datasets` and `authorized_routines` variables, respectively.

```hcl
// Create private BigQuery dataset that will not be publicly accessible, except via the authorized BigQuery resources
module "bigquery-dataset-private" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "private_project"
  id         = "private_dataset"
  authorized_views = [
    {
      project_id = "auth_view_project"
      dataset_id = "auth_view_dataset"
      table_id   = "auth_view"
    }
  ]
  authorized_datasets = [
    {
      project_id = "auth_dataset_project"
      dataset_id = "auth_dataset"
    }
  ]
  authorized_routines = [
    {
      project_id = "auth_routine_project"
      dataset_id = "auth_routine_dataset"
      routine_id = "auth_routine"
    }
  ]
}

// Create authorized view in a public dataset
module "bigquery-authorized-views-dataset-public" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "auth_view_project"
  id         = "auth_view_dataset"
  views = {
    auth_view = {
      friendly_name       = "Public"
      labels              = {}
      query               = "SELECT * FROM `private_project.private_dataset.private_table`"
      use_legacy_sql      = false
      deletion_protection = true
    }
  }
}

// Create public authorized dataset
module "bigquery-authorized-dataset-public" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "auth_dataset_project"
  id         = "auth_dataset"
}

// Create public authorized routine
module "bigquery-authorized-authorized-routine-dataset-public" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "auth_routine_project"
  id         = "auth_routine_dataset"
}

resource "google_bigquery_routine" "public-routine" {
  project         = "private_project"
  dataset_id      = module.bigquery-authorized-authorized-routine-dataset-public.dataset_id
  routine_id      = "auth_routine"
  routine_type    = "TABLE_VALUED_FUNCTION"
  language        = "SQL"
  definition_body = <<-EOS
    SELECT 1 + value AS value
  EOS
  arguments {
    name          = "value"
    argument_kind = "FIXED_TYPE"
    data_type     = jsonencode({ "typeKind" = "INT64" })
  }
  return_table_type = jsonencode({ "columns" = [
    { "name" = "value", "type" = { "typeKind" = "INT64" } },
  ] })
}
# tftest modules=4 resources=9 inventory=authorized_resources.yaml
```

Authorized views can be specified both using the standard `access` options and the `authorized_views` blocks. The example configuration below uses both blocks, and will create a dataset with three authorized views `view_id_1`, `view_id_2`, and `view_id_3`.

```hcl
module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  authorized_views = [
    {
      project_id = "view_project"
      dataset_id = "view_dataset"
      table_id   = "view_id_1"
    },
    {
      project_id = "view_project"
      dataset_id = "view_dataset"
      table_id   = "view_id_2"
    }
  ]
  access = {
    view_2 = { role = "READER", type = "view" }
    view_3 = { role = "READER", type = "view" }
  }
  access_identities = {
    view_2 = "view_project|view_dataset|view_id_2"
    view_3 = "view_project|view_dataset|view_id_3"
  }
}
# tftest modules=1 resources=4 inventory=authorized_resources_views.yaml
```

## Dataset options

Dataset options are set via the `options` variable. all options must be specified, but a `null` value can be set to options that need to use defaults.

```hcl
module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  options = {
    default_table_expiration_ms     = 3600000
    default_partition_expiration_ms = null
    delete_contents_on_destroy      = false
    max_time_travel_hours           = 168
  }
}
# tftest modules=1 resources=1 inventory=options.yaml
```

## Tables, views and routines

Tables are created via the `tables` variable. Support for external tables will be added in a future release.

```hcl
locals {
  countries_schema = jsonencode([
    { name = "country", type = "STRING" },
    { name = "population", type = "INT64" },
  ])
}

module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  tables = {
    countries = {
      friendly_name       = "Countries"
      schema              = local.countries_schema
      deletion_protection = true
    }
  }
}
# tftest modules=1 resources=2 inventory=tables.yaml
```

If partitioning is needed, populate the `partitioning` variable using either the `time` or `range` attribute.

```hcl
locals {
  countries_schema = jsonencode([
    { name = "country", type = "STRING" },
    { name = "population", type = "INT64" },
  ])
}

module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  tables = {
    table_a = {
      deletion_protection = true
      friendly_name       = "Table a"
      schema              = local.countries_schema
      partitioning = {
        time = { type = "DAY", expiration_ms = null }
      }
    }
  }
}
# tftest modules=1 resources=2 inventory=partitioning.yaml
```

To create views use the `views` variable. If you're querying a table created by the same module `terraform apply` will initially fail and eventually succeed once the underlying table has been created. You can probably also use the module's output in the view's query to create a dependency on the table.

```hcl
locals {
  countries_schema = jsonencode([
    { name = "country", type = "STRING" },
    { name = "population", type = "INT64" },
  ])
  population_schema = [
    {
      name        = "total",
      type        = "INT64",
      description = "Total population"
    }
  ]
}

module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  tables = {
    countries = {
      friendly_name       = "Countries"
      schema              = local.countries_schema
      deletion_protection = true
    }
  }
  views = {
    population = {
      friendly_name       = "Population"
      query               = "SELECT SUM(population) AS total FROM my_dataset.countries"
      schema              = local.population_schema
      use_legacy_sql      = false
      deletion_protection = true
    }
  }
}
# tftest modules=1 resources=3 inventory=views.yaml
```

To create routines use the `routines` variable.

```hcl
module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  routines = {
    custom_masking_routine = {
      routine_type         = "SCALAR_FUNCTION"
      language             = "SQL"
      data_governance_type = "DATA_MASKING"
      definition_body      = "SAFE.REGEXP_REPLACE(ssn, '[0-9]', 'X')"
      return_type          = "{\"typeKind\" :  \"STRING\"}"
      arguments = {
        ssn = {
          data_type = "{\"typeKind\" :  \"STRING\"}"
        }
      }
    }
  }
}
# tftest modules=1 resources=2 inventory=routines.yaml
```

## Tag bindings

Refer to the [Creating and managing tags](https://cloud.google.com/resource-manager/docs/tags/tags-creating-and-managing) documentation for details on usage.

```hcl
module "org" {
  source          = "./fabric/modules/organization"
  organization_id = var.organization_id
  tags = {
    environment = {
      description = "Environment specification."
      values = {
        dev     = {}
        prod    = {}
        sandbox = {}
      }
    }
  }
}

module "bigquery-dataset" {
  source     = "./fabric/modules/bigquery-dataset"
  project_id = "my-project"
  id         = "my_dataset"
  tag_bindings = {
    env-sandbox = module.org.tag_values["environment/sandbox"].id
  }
}
# tftest modules=2 resources=6
```

## TODO

- [ ] check for dynamic values in tables and views
- [ ] add support for external tables
<!-- BEGIN TFDOC -->
## Variables

| name | description | type | required | default |
|---|---|:---:|:---:|:---:|
| [id](variables.tf#L115) | Dataset id. | <code>string</code> | ✓ |  |
| [project_id](variables.tf#L179) | Id of the project where datasets will be created. | <code>string</code> | ✓ |  |
| [access](variables.tf#L17) | Map of access rules with role and identity type. Keys are arbitrary and must match those in the `access_identities` variable, types are `domain`, `group`, `special_group`, `user`, `view`. | <code>map&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#123;&#125;</code> |
| [access_identities](variables.tf#L33) | Map of access identities used for basic access roles. View identities have the format 'project_id\|dataset_id\|table_id'. | <code>map&#40;string&#41;</code> |  | <code>&#123;&#125;</code> |
| [authorized_datasets](variables.tf#L39) | An array of datasets to be authorized on the dataset. | <code>list&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#91;&#93;</code> |
| [authorized_routines](variables.tf#L48) | An array of routines to be authorized on the dataset. | <code>list&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#91;&#93;</code> |
| [authorized_views](variables.tf#L58) | An array of views to be authorized on the dataset. | <code>list&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#91;&#93;</code> |
| [context](variables.tf#L68) | Context-specific interpolations. | <code>object&#40;&#123;&#8230;&#125;&#41;</code> |  | <code>&#123;&#125;</code> |
| [dataset_access](variables.tf#L87) | Set access in the dataset resource instead of using separate resources. | <code>bool</code> |  | <code>false</code> |
| [description](variables.tf#L93) | Optional description. | <code>string</code> |  | <code>&#34;Terraform managed.&#34;</code> |
| [encryption_key](variables.tf#L99) | Self link of the KMS key that will be used to protect destination table. | <code>string</code> |  | <code>null</code> |
| [friendly_name](variables.tf#L105) | Dataset friendly name. | <code>string</code> |  | <code>null</code> |
| [iam](variables-iam.tf#L17) | IAM bindings in {ROLE => [MEMBERS]} format. Mutually exclusive with the access_* variables used for basic roles. | <code>map&#40;list&#40;string&#41;&#41;</code> |  | <code>&#123;&#125;</code> |
| [iam_bindings](variables-iam.tf#L23) | Authoritative IAM bindings in {KEY => {role = ROLE, members = [], condition = {}}}. Keys are arbitrary. | <code>map&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#123;&#125;</code> |
| [iam_bindings_additive](variables-iam.tf#L38) | Individual additive IAM bindings. Keys are arbitrary. | <code>map&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#123;&#125;</code> |
| [iam_by_principals](variables-iam.tf#L53) | Authoritative IAM binding in {PRINCIPAL => [ROLES]} format. Principals need to be statically defined to avoid errors. Merged internally with the `iam` variable. | <code>map&#40;list&#40;string&#41;&#41;</code> |  | <code>&#123;&#125;</code> |
| [labels](variables.tf#L120) | Dataset labels. | <code>map&#40;string&#41;</code> |  | <code>&#123;&#125;</code> |
| [location](variables.tf#L126) | Dataset location. | <code>string</code> |  | <code>&#34;EU&#34;</code> |
| [materialized_views](variables.tf#L132) | Materialized views definitions. | <code>map&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#123;&#125;</code> |
| [options](variables.tf#L165) | Dataset options. | <code>object&#40;&#123;&#8230;&#125;&#41;</code> |  | <code>&#123;&#125;</code> |
| [routines](variables.tf#L184) | Routine definitions. | <code>map&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#123;&#125;</code> |
| [tables](variables.tf#L223) | Table definitions. Options and partitioning default to null. Partitioning can only use `range` or `time`, set the unused one to null. | <code>map&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#123;&#125;</code> |
| [tag_bindings](variables.tf#L308) | Tag bindings for this dataset, in key => tag value id format. | <code>map&#40;string&#41;</code> |  | <code>&#123;&#125;</code> |
| [views](variables.tf#L315) | View definitions. | <code>map&#40;object&#40;&#123;&#8230;&#125;&#41;&#41;</code> |  | <code>&#123;&#125;</code> |

## Outputs

| name | description | sensitive |
|---|---|:---:|
| [dataset](outputs.tf#L17) | Dataset resource. |  |
| [dataset_id](outputs.tf#L22) | Dataset id. |  |
| [id](outputs.tf#L37) | Fully qualified dataset id. |  |
| [materialized_view_ids](outputs.tf#L52) | Map of fully qualified materialized view ids keyed by view ids. |  |
| [materialized_views](outputs.tf#L57) | Materialized view resources. |  |
| [routine_ids](outputs.tf#L62) | Map of fully qualified routine ids keyed by routine ids. |  |
| [routines](outputs.tf#L67) | Routine resources. |  |
| [self_link](outputs.tf#L72) | Dataset self link. |  |
| [table_ids](outputs.tf#L87) | Map of fully qualified table ids keyed by table ids. |  |
| [tables](outputs.tf#L92) | Table resources. |  |
| [view_ids](outputs.tf#L97) | Map of fully qualified view ids keyed by view ids. |  |
| [views](outputs.tf#L102) | View resources. |  |
<!-- END TFDOC -->
