removing limitation bullet #4549
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removing `metric_time` limitation as this was resolved in dbt-labs/metricflow#825
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Jstein77
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Nov 29, 2023
| 1. You can only use the [`metric_time` dimension](/docs/build/dimensions#time) to check cumulative metrics. If you don't use `metric_time` in the query, the cumulative metric will return incorrect results because it won't perform the time spine join. This means you cannot reference time dimensions other than the `metric_time` in the query. | ||
| 2. If you use `metric_time` in your query filter but don't include "start_time" and "end_time," cumulative metrics will left-censor the input data. For example, if you query a cumulative metric with a 7-day window with the filter `{{ TimeDimension('metric_time') }} BETWEEN '2023-08-15' AND '2023-08-30' `, the values for `2023-08-15` to `2023-08-20` return missing or incomplete data. This is because we apply the `metric_time` filter to the aggregation input. To avoid this, you must use `start_time` and `end_time` in the query filter. | ||
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| - You can only use the [`metric_time` dimension](/docs/build/dimensions#time) to check cumulative metrics. If you don't use `metric_time` in the query, the cumulative metric will return incorrect results because it won't perform the time spine join. This means you cannot reference time dimensions other than the `metric_time` in the query. |
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You can only use the
metric_timedimension to check
I would re-phrase this too "You are required to use metric_time when querying cumulative metrics"
Jstein77
approved these changes
Nov 29, 2023
mirnawong1
commented
Nov 29, 2023
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thanks @Jstein77 ! folded i your feedback and will merge this now! |
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removing
metric_timelimitation as this was resolved in dbt-labs/metricflow#825What are you changing in this pull request and why?