Propagate the measure label when using create_metric option

[aliceliu]

Resolves #10538

Problem

When using create_metric on a measure, the label of the measure is not propagated to the metric

Solution

Set metric label to be measure label if it exists

Checklist

• I have read the contributing guide and understand what's expected of me.
• I have run this code in development, and it appears to resolve the stated issue.
• This PR includes tests, or tests are not required or relevant for this PR.
• This PR has no interface changes (e.g., macros, CLI, logs, JSON artifacts, config files, adapter interface, etc.) or this PR has already received feedback and approval from Product or DX.
• This PR includes type annotations for new and modified functions.

[github-actions]

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[aliceliu]

• Propagate the measure label when using create_metric option #10536 👈
• main

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 88.84%. Comparing base (21a4633) to head (e867392).
Report is 2 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main   #10536   +/-   ##
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  Coverage   88.84%   88.84%           
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  Files         180      180           
  Lines       22717    22720    +3     
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+ Hits        20182    20186    +4     
+ Misses       2535     2534    -1     

Flag	Coverage Δ
integration	86.07% <ø> (+<0.01%)	⬆️
unit	62.35% <ø> (+0.03%)	⬆️

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Components	Coverage Δ
Unit Tests	62.35% <ø> (+0.03%)	⬆️
Integration Tests	86.07% <ø> (+<0.01%)	⬆️

[QMalcolm]

This looks good to me. It would probably be worthwhile to add a test which checks the state of the created metric when the related measure does not have a label set, however this is not blocking.

Context

When _create_metric, which creates a metric from a measure, was written, measures did not have labels. It seems that when label was added to the measure class, we did not think to add it here. That is an oversight, but I can see how that happened.

Implications

For metrics created from measures, in order to get the correct label, a full reparse will be necessary. This is because partial parsing only reparses an object is the input for the object has changed. Thus, without a full parsing, the relevant metrics will only get updated if the underlying semantic model is modified somehow.

TL;DR

Looks good. People will need to run dbt parse --no-partial-parse to ensure all existing measures with labels that create metrics properly propagate the label.

[aliceliu]

@QMalcolm thanks for the context! I updated the test. I don't have permission to merge so I'll leave the merging to you

[Vitor-Avila]

Hey @QMalcolm, @WilliamDee
I have a question about this issue. I've created a measure like below:

measures:
  - name: metric_measure
    description: This is a measure (originally)
    label: This is the label value
    expr: order_id
    agg: count_distinct
    create_metric: true

After running both dbt run and/or dbt parse --no-partial-parse, I see the metric declared in the manifest.json like this:

{
    ...
    "metric.vec_sales.metric_measure":
    {
        "name": "metric_measure",
        "resource_type": "metric",
        "package_name": "vec_sales",
        "path": "vehicle_sales.yml",
        "original_file_path": "models/vehicle_sales.yml",
        "unique_id": "metric.vec_sales.metric_measure",
        "fqn": ["vec_sales", "metric_measure"],
        "description": "This is a measure (originally)",
        "label": "metric_measure",
        ...
}

The label in the manifest.json is still incorrectly using the measure name. Should I submit a new ticket about this? Am I missing something?

(dbt-latest) ➜  vec_sales pip freeze | grep dbt
dbt-adapters==1.10.3
dbt-common==1.13.0
dbt-core==1.8.9
dbt-extractor==0.5.1
dbt-postgres==1.8.2
dbt-semantic-interfaces==0.5.1

[QMalcolm]

@Vitor-Avila howdy! Looks like this never got backported to 1.8.latest and thus never went into a 1.8.x minor release. I can check in with the team if that is something we want to do, it shouldn't be a major lift.

However, we also plan to release 1.9.0 very soon. It should be fixed in that version. If you want a sneak peak of that, try installing the latest release candidate via pip install dbt-core==1.9.0rc2 (which should resolve your issue)

[Vitor-Avila]

Thank you so much for the quick response, @QMalcolm! 🙏 I've just tested using 1.9.0rc2 and confirmed it works. Appreciate the assistance here.