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Adding new MF command #5930

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Aug 14, 2024
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Adding new MF command #5930

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adding new MF command
runleonarun Aug 14, 2024
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removing space
runleonarun Aug 14, 2024
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Update website/docs/docs/build/metricflow-commands.md
runleonarun Aug 14, 2024
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Update metricflow-commands.md
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11 changes: 4 additions & 7 deletions website/docs/docs/build/metricflow-commands.md
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Expand Up @@ -26,13 +26,13 @@ Using MetricFlow with dbt Cloud means you won't need to manage versioning &mdash

- MetricFlow [commands](#metricflow-commands) are embedded in the dbt Cloud CLI. This means you can immediately run them once you install the dbt Cloud CLI and don't need to install MetricFlow separately.
- You don't need to manage versioning — your dbt Cloud account will automatically manage the versioning for you.

</TabItem>

<TabItem value="cloud ide" label="dbt Cloud IDE">

:::info
You can create metrics using MetricFlow in the dbt Cloud IDE. However, support for running MetricFlow commands in the IDE will be available soon.
You can create metrics using MetricFlow in the dbt Cloud IDE and [run `dbt sl validate`](/docs/build/validation#validations-command). Support for running more MetricFlow commands in the IDE will be available soon.
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:::

</TabItem>
Expand Down Expand Up @@ -78,10 +78,9 @@ You can use the `dbt sl` prefix before the command name to execute them in the d
- [`query`](#query) &mdash; Query metrics, saved queries, and dimensions you want to see in the command line interface. Refer to [query examples](#query-examples) to help you get started.
- [`export`](#export) &mdash; Runs exports for a singular saved query for testing and generating exports in your development environment. You can also use the `--select` flag to specify particular exports from a saved query.
- [`export-all`](#export-all) &mdash; Runs exports for multiple saved queries at once, saving time and effort.

- [`validate-configs`](#validate-configs) &mdash; Validates semantic model configurations.
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<!--below commands aren't supported in dbt cloud yet
- [`validate-configs`](#validate-configs) &mdash; Validates semantic model configurations.
- [`health-checks`](#health-checks) &mdash; Performs data platform health check.
- [`tutorial`](#tutorial) &mdash; Dedicated MetricFlow tutorial to help get you started.
-->
Expand Down Expand Up @@ -222,10 +221,8 @@ The list of available saved queries:

The following command performs validations against the defined semantic model configurations.

Note, in dbt Cloud you don't need to validate the Semantic Layer config separately. Running a dbt command (such as `dbt parse`, `dbt build`, `dbt compile`, `dbt run`) automatically checks it.

```bash

dbt sl validate-configs # dbt Cloud users
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mf validate-configs # In dbt Core

Options:
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5 changes: 2 additions & 3 deletions website/docs/docs/build/validation.md
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Expand Up @@ -14,11 +14,10 @@ The code that handles validation [can be found here](https://github.com/dbt-labs

## Validations command

You can run validations against the defined semantic model configurations from the command line with the following [MetricFlow commands](/docs/build/metricflow-commands):

Note, in dbt Cloud you don't need to validate the Semantic Layer config separately. Running a dbt command (such as `dbt parse`, `dbt build`, `dbt compile`, or `dbt run`) automatically checks it.
You can run validations from dbt Cloud or the command line with the following [MetricFlow commands](/docs/build/metricflow-commands). In dbt Cloud, you need developer credentials to run `dbt sl validate-configs` in the IDE or CLI, and deployment credentials to run it in CI.

```bash
dbt sl validate-configs # dbt Cloud users
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mf validate-configs # dbt Core users
```

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