# Data modeling with JavaScript

<InfoBox>

This functionality only works with data models written in JavaScript, not YAML.

For similar functionality in YAML, see [Dynamic data models with Jinja and Python](/product/data-modeling/dynamic/jinja).

</InfoBox>

Cube allows data models to be created on-the-fly using a special
[`asyncModule()`][ref-async-module] function only available in the
[execution environment][ref-schema-env]. `asyncModule()` allows registering an
async function to be executed at the end of the data model compile phase so
additional definitions can be added. This is often useful in situations where
data model properties can be dynamically updated through an API, for example.

<WarningBox>

Each `asyncModule` call will be invoked only once per data model compilation.

</WarningBox>

[ref-schema-env]: /product/data-modeling/dynamic/schema-execution-environment
[ref-async-module]:
  /product/data-modeling/dynamic/schema-execution-environment#asyncmodule

When creating data models via `asyncModule()`, it is important to be aware of
the following differences compared to statically defined ones with `cube()`:

- The `sql` and `drill_members` properties for both dimensions and measures must
  be of type `() => string` and `() => string[]` accordingly

Cube supports importing JavaScript logic from other files in a data model, so it
is useful to declare utility functions for handling the above differences in a
separate file:


```javascript
// model/utils.js
export const convertStringPropToFunction = (propNames, dimensionDefinition) => {
  let newResult = { ...dimensionDefinition };
  propNames.forEach((propName) => {
    const propValue = newResult[propName];

    if (!propValue) {
      return;
    }

    newResult[propName] = () => propValue;
  });
  return newResult;
};

export const transformDimensions = (dimensions) => {
  return Object.keys(dimensions).reduce((result, dimensionName) => {
    const dimensionDefinition = dimensions[dimensionName];
    return {
      ...result,
      [dimensionName]: convertStringPropToFunction(
        ["sql"],
        dimensionDefinition
      ),
    };
  }, {});
};

export const transformMeasures = (measures) => {
  return Object.keys(measures).reduce((result, dimensionName) => {
    const dimensionDefinition = measures[dimensionName];
    return {
      ...result,
      [dimensionName]: convertStringPropToFunction(
        ["sql", "drill_members"],
        dimensionDefinition
      ),
    };
  }, {});
};
```

## Generation

In the following example, we retrieve a JSON object representing all our cubes
using `fetch()`, transform some of the properties to be functions that return a
string, and then finally use the [`cube()` global function][ref-globals] to
generate data models from that data:

[ref-globals]:
  /product/data-modeling/dynamic/schema-execution-environment#cube-js-globals-cube-and-others

```javascript
// model/cubes/DynamicDataModel.js
const fetch = require("node-fetch");
import {
  convertStringPropToFunction,
  transformDimensions,
  transformMeasures,
} from "./utils";

asyncModule(async () => {
  const dynamicCubes = await (
    await fetch("http://your-api-endpoint/dynamicCubes")
  ).json();

  console.log(dynamicCubes);
  // [
  //   {
  //      name: 'dynamic_cube_model',
  //      sql_table: 'my_table',
  //
  //      measures: {
  //        price: {
  //          sql: `price`,
  //          type: `number`,
  //        }
  //      },
  //
  //      dimensions: {
  //        color: {
  //          sql: `color`,
  //          type: `string`,
  //        },
  //      },
  //   },
  // ]

  dynamicCubes.forEach((dynamicCube) => {
    const dimensions = transformDimensions(dynamicCube.dimensions);
    const measures = transformMeasures(dynamicCube.measures);

    cube(dynamicCube.name, {
      sql: dynamicCube.sql,
      dimensions,
      measures,
      pre_aggregations: {
        main: {
          // ...
        },
      },
    });
  });
});
```

## Usage with `schema_version`

It is also useful to be able to recompile the data model when there are changes
in the underlying input data. For this purpose, the [`schema_version`
][link-config-schema-version] value in the `cube.js` configuration options can
be specified as an asynchronous function:

```javascript
// cube.js
module.exports = {
  schemaVersion: async ({ securityContext }) => {
    const schemaVersions = await (
      await fetch("http://your-api-endpoint/schema_version")
    ).json();

    return schemaVersions[securityContext.tenantId];
  },
};
```

[link-config-schema-version]: /product/configuration/reference/config#schema_version

## Usage with COMPILE_CONTEXT

The `COMPILE_CONTEXT` global object can also be used in conjunction with async
data model creation to allow for multi-tenant deployments of Cube.

In an example scenario where all tenants share the same cube, but see different
dimensions and measures, you could do the following:

```javascript
// model/cubes/DynamicDataModel.js
const fetch = require("node-fetch");
import {
  convertStringPropToFunction,
  transformDimensions,
  transformMeasures,
} from "./utils";

asyncModule(async () => {
  const {
    securityContext: { tenantId },
  } = COMPILE_CONTEXT;

  const dynamicCubes = await (
    await fetch(`http://your-api-endpoint/dynamicCubes`)
  ).json();

  const allowedDimensions = await (
    await fetch(`http://your-api-endpoint/dynamicDimensions/${tenantId}`)
  ).json();

  const allowedMeasures = await (
    await fetch(`http://your-api-endpoint/dynamicMeasures/${tenantId}`)
  ).json();

  dynamicCubes.forEach((dynamicCube) => {
    const dimensions = transformDimensions(allowedDimensions);
    const measures = transformMeasures(allowedMeasures);

    cube(dynamicCube.name, {
      sql: dynamicCube.sql,
      title: `${dynamicCube.title}-${tenantId}`,
      dimensions,
      measures,
      pre_aggregations: {
        main: {
          // ...
        },
      },
    });
  });
});
```

## Usage with data_source

When using multiple databases, you'll need to ensure you set the
[`data_source`][ref-schema-datasource] property for any asynchronously-created
data models, as well as ensuring the corresponding database drivers are set up with
[`driverFactory()`][ref-config-driverfactory] in your [`cube.js` configuration
file][ref-config].

[ref-schema-datasource]: /product/data-modeling/reference/cube#data_source
[ref-config-driverfactory]: /product/configuration/reference/config#driverfactory
[ref-config]: /product/configuration/reference/config

For an example scenario where data models may use either MySQL or Postgres
databases, you could do the following:

```javascript
// model/cubes/DynamicDataModel.js
const fetch = require("node-fetch");
import {
  convertStringPropToFunction,
  transformDimensions,
  transformMeasures,
} from "./utils";

asyncModule(async () => {
  const dynamicCubes = await (
    await fetch("http://your-api-endpoint/dynamicCubes")
  ).json();

  dynamicCubes.forEach((dynamicCube) => {
    const dimensions = transformDimensions(dynamicCube.dimensions);
    const measures = transformMeasures(dynamicCube.measures);

    cube(dynamicCube.name, {
      data_source: dynamicCube.data_source,
      sql: dynamicCube.sql,
      dimensions,
      measures,
      pre_aggregations: {
        main: {
          // ...
        },
      },
    });
  });
});
```

```javascript
// cube.js
const MySQLDriver = require("@cubejs-backend/mysql-driver");
const PostgresDriver = require("@cubejs-backend/postgres-driver");

module.exports = {
  driverFactory: ({ dataSource }) => {
    if (dataSource === "mysql") {
      return new MySQLDriver({ database: dataSource });
    }

    return new PostgresDriver({ database: dataSource });
  },
};
```
