BigQuery: Logical Models

Introduction

Supported from

Logical Models are supported from v2.26.0.

Logical Models are a GraphQL representation of database data. They provide an abstraction over the underlying database.

Logical Models are a new approach from Hasura and are currently used by the Native Queries feature to automatically create a GraphQL API for a native database query.

You can find examples of how to use Logical Models in the Native Queries documentation. For a more detailed explanation of Logical Models themselves, read on.

Tracking a Logical Model

Console

You can create a Logical Model from the "Data" tab of the Console, by clicking on Native Queries in the sidebar, then Add Logical Model:

CLI

You can create a logical model by adding it to the appropriate database definition in the metadata > databases > databases.yaml file:

  logical_models:
    - name: "<name>"
      fields:
        "<field name>":
          type: "<BigQuery field type>"
          nullable: false | true
          description: "<optional field description>"
        ...

API

You create a logical model through the metadata API:

POST /v1/metadata HTTP/1.1
Content-Type: application/json
X-Hasura-Role: admin

{
  "type": "bigquery_track_logical_model",
  "args": {
    "source": "default",
    "name": "<name>",
    "fields": [
      {
        "name": "<field name>",
        "type": "<BigQuery field type>",
        "nullable": false | true,
        "description": "<optional field description>"
      },
      ...
    ]
  }
}

The type of each field can be either a BigQuery data type or references to other Logical Models, and each field can be marked as nullable or not, see LogicalModelType.

Console

For example, we could track a representation of an article with excerpts as follows, by defining the fields we want to be able to return:

CLI

Add the following to the default database definition in the metadata > databases > databases.yaml file:

logical_models:
  - name: article
    fields:
      id:
        type: integer
        nullable: false
      title:
        type: text
        nullable: false
      contents:
        type: text
        nullable: false
      published_date:
        type: date
        nullable: true
      is_published:
        type: boolean
        nullable: false

API

POST /v1/metadata HTTP/1.1
Content-Type: application/json
X-Hasura-Role: admin

{
  "type": "bigquery_track_logical_model",
  "args": {
    "source": "default",
    "name": "article",
    "fields": [
      {
        "name": "id",
        "type":
          {
            "scalar": "integer"
          }
      },
      {
        "name": "title",
        "type":
          {
            "scalar": "text"
          }
      },
      {
        "name": "contents",
        "type":
          {
            "scalar": "text"
          }
      },
      {
        "name": "published_date",
        "type":
          {
            "scalar": "date",
            "nullable": true
          },
      },
      {
        "name": "is_published",
        "type":
          {
            "scalar": "boolean"
          }
      }
    ]
  }
}

Untracking a Logical Model

Console

To untrack a Logical Model, click Remove next to the Logical Model:

CLI

You can remove a Logical Model by removing it from the metadata > databases > databases.yaml file.

API

You can remove a Logical Model the same way:

POST /v1/metadata HTTP/1.1
Content-Type: application/json
X-Hasura-Role: admin

{
  "type": "bigquery_untrack_logical_model",
  "args": {
    "source": "default",
    "name": "<name>"
  }
}

Removing a Logical Model

Note that you can only remove an unused Logical Model; if the model is attached to a Native Query, this operation will fail. You must remove the Native Query first.

To untrack the above article Logical Model, we would run the following:

Console

CLI

Remove the above metadata from the metadata > databases > databases.yaml file.

API

POST /v1/metadata HTTP/1.1
Content-Type: application/json
X-Hasura-Role: admin

{
  "type": "bigquery_untrack_logical_model",
  "args": {
    "source": "default",
    "name": "article"
  }
}

Referencing other Logical Models

Logical Model fields are allowed to refer to other Logical Models, even recursively, allowing nested data types.

To elaborate on the article example above, we can include authors in the data model:

API

POST /v1/metadata HTTP/1.1
Content-Type: application/json
X-Hasura-Role: admin

{
  "type": "bulk_atomic",
  "args":
  [
    {
      "type": "bigquery_track_logical_model",
      "args": {
        "source": "default",
        "name": "article",
        "fields": [
          {
            "name": "id",
            "type":
              {
                "scalar": "integer"
              }
          },
          {
            "name": "title",
            "type":
              {
                "scalar": "text"
              }
          },
          {
            "name": "contents",
            "type":
              {
                "scalar": "text"
              }
          },
          {
            "name": "author_id",
            "type":
              {
                "scalar": "integer"
              }
          },
          {
            "name": "author",
            "type":
              {
                "logical_model": "author",
              },
          }
        ]
      }
    },
    {
      "type": "bigquery_track_logical_model",
      "args": {
        "source": "default",
        "name": "author",
        "fields": [
          {
            "name": "id",
            "type":
              {
                "scalar": "integer"
              }
          },
          {
            "name": "name",
            "type":
              {
                "scalar": "text"
              }
          },
          {
            "name": "articles",
            "type":
              {
                "array":
                  {
                    "logical_model": "article"
                  }
              }
          }
        ]
      }
    }
  ]
}

Wrap calls in bulk_atomic

Tracking the Logical Models one-by-one would fail, since article refers to author, which is not yet defined.

Tracking the Logical Models in one atomic operation postpones coherency checks until all models are tracked, which allows for mutual references.

Permissions

By default, a model has no permissions, and only the admin account will be able to use it. You can enable the model by adding permissions for a given role.

As Logical Models are currently only used for read-only purposes, you can only add select permissions.

The permissions consist of a list of columns that the role can access, and a filter that specifies which rows the role can receive.

Console

CLI

Columns must be specified, though you can use "*" to specify that you want to allow all columns.

The filter is the same boolean expression syntax as query filters. To allow all rows to be passed through to the response, you can specify an empty filter, {}.

Add the required permissions to the relevant logical model in metadata > databases > databases.yaml:

  logical_models:
    - name: "<name>"
      fields:
        ...
      select_permissions:
        - role: "<role name>"
          permission:
            columns: "*" | [
              "column 1",
              "column 2",
              ...
            ]
            filter: "<boolean expression>"
        - ...

API

Columns must be specified, though you can use "*" to specify that you want to allow all columns.

The filter is the same boolean expression syntax as query filters. To allow all rows to be passed through to the response, you can specify an empty filter, {}.

POST /v1/metadata HTTP/1.1
Content-Type: application/json
X-Hasura-Role: admin

{
  "type": "bigquery_create_logical_model_select_permission",
  "args": {
    "source": "default",
    "name": "<logical model name>",
    "role": "<role name>",
    "permission": {
      "columns": "*" | [
        "column 1",
        "column 2",
        ...
      ],
      "filter": <boolean expression>
    }
  }
}

For example, to allow access to the article Logical Model for the reader role, but only for published articles, we could use the following permission to limit the accessible rows to those where is_published is true, and then hide that column from the list (by specifying all other columns).

Console

CLI

Add the required permissions to the relevant logical model in metadata > databases > databases.yaml:

logical_models:
  - name: '<name>'
    fields: ...
    select_permissions:
      - role: reader
        permission:
          columns:
            - id
            - title
            - contents
            - date
          filter:
            is_published:
              _eq: true
      - ...

API

POST /v1/metadata HTTP/1.1
Content-Type: application/json
X-Hasura-Role: admin

{
  "type": "bigquery_create_logical_model_select_permission",
  "args": {
    "source": "default",
    "name": "article",
    "role": "reader",
    "permission": {
      "columns": [
        "id",
        "title",
        "contents",
        "date"
      ],
      "filter": {
        "is_published": {"_eq": true}
      }
    }
  }
}

You can also drop permissions:

Console

CLI

Remove the relevant permission from metadata > databases > databases.yaml.

API

POST /v1/metadata HTTP/1.1
Content-Type: application/json
X-Hasura-Role: admin

{
  "type": "bigquery_drop_logical_model_select_permission",
  "args": {
    "source": "default",
    "name": "<logical model name>",
    "role": "<role name>"
  }
}