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Switch to FULL OUTER JOIN
for derived & ratio metrics
#842
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e0cb00f
Switch to OUTER JOIN for derived metrics
courtneyholcomb fab0350
Changelog
courtneyholcomb 7aa4682
Update snapshots & test SQL
courtneyholcomb a14e415
Update SQL engine snapshots
courtneyholcomb 3e5e8c2
Update test case SQL
courtneyholcomb dbb8a2f
Use FULL OUTER JOIN for ratio metrics, too
courtneyholcomb b243aad
Update docstring for visit_combine_metrics_node
courtneyholcomb 4c4f440
Remove join_type param
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,6 @@ | ||
kind: Breaking Changes | ||
body: Use FULL OUTER JOIN to combine input metrics for derived metrics. This is a change from using INNER JOIN and may result in changes in output. | ||
time: 2023-11-02T18:28:15.181064-07:00 | ||
custom: | ||
Author: courtneyholcomb | ||
Issue: "842" |
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@tlento do you have context on why for
INNER JOIN
we add thisNULL
column comparison, but forFULL OUTER JOIN
we don't? Wondering if that's intentional or something I should fix!There was a problem hiding this comment.
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The NULL comparison is needed because NULL = NULL evaluates to NULL, which is false-y in SQL comparisons, but we have to include sets in the INNER JOIN where the dimension values on both sides are NULL. If a row doesn't match on an INNER JOIN it gets discarded, so we must handle that case in the join condition.
For FULL OUTER JOIN we can't do OR conditions (or inequalities) - a bunch of our engines don't support them. Everything has to be a strict intersection of equality checks. However, if you do a FULL OUTER JOIN and a comparison fails due to a NULL = NULL check, you still get the rows from both sides. They're just not matched to anything, so you effectively get one row per aggregated measure source. That's why we have all these MAX expressions, because that's the hack I put in to deduplicate those output rows.
I have to say I find all of this absurd, but that is where we are.
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Oooh, I actually wrote it down!
https://github.com/dbt-labs/metricflow/blob/main/metricflow/plan_conversion/dataflow_to_sql.py#L906
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Ah thank you!! Super helpful