feat(dbt sync): Support metric key remapping #311
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Vitor-Avila
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betodealmeida
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Aug 14, 2024
| meta = metric.get("meta", {}) | ||
| kwargs = meta.pop("superset", {}) | ||
| metric_meta = parse_metric_meta( | ||
| metric.get("meta", metric.get("config", {}).get("meta", {})), |
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I think we should move this logic to the parse_metric_meta, it would make it easier to understand. Here we'd simply do:
metric_meta = parse_metric_meta(metric)And the parse_metric_meta function would handle the retrieval of meta.
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that makes sense! let me get that done
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@betodealmeida I implemented a base MetricSchema (shared across OG/MF/etc) o that I can also use it as the type hint for this helper. This caused some additional updates to other files.
Vitor-Avila
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Aug 16, 2024
| """ | ||
| Parses the metric's meta information. | ||
| """ | ||
| kwargs = metric.get("meta", {}).pop("superset", {}) |
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Still need to use .get("meta", {}) here as logic to handle meta || config.meta for dbt Cloud will be added in a future PR
|
double thanks! |
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dbt introduced new restrictions to metric names with MetricFlow (for example, it's no longer possible to have
__in metric names). As a consequence, in order to upgrade to a supported version customers have to update all their metric names according to new rules. The metric mapping with Preset happens based on the metric name, so a re-name in dbt would result in new metrics in Preset, leaving old metrics out of sync.This PR introduces a way to map a dbt metric with a Preset metric with diverging names, to minimize the impact of this change.
This PR also improves the
metahandling in general for metrics (so that Preset-specific fields can be controlled through dbt) and also improves the handling for the metriclabel(it wasn't being pulled from MetricFlow metrics).