IgnatiusPang commented on PR #25743:
URL: https://github.com/apache/datafusion/pull/25743#issuecomment-5835271135
```markdown
### 1. SQL Reproducer (Scalar vs Grouped Divergence)
```sql
-- Query 1: Scalar evaluation on single-row NaN returns 0.0
SELECT var_pop(val) AS v
FROM (VALUES ('NaN'::double)) AS t(val);
-- Query 2: Grouped evaluation on the EXACT SAME single-row NaN returns NaN
SELECT grp, var_pop(val) AS v
FROM (VALUES ('g1', 'NaN'::double)) AS t(grp, val)
GROUP BY grp;
```
**Current Result (unpatched DataFusion):**
```text
Query 1 (Scalar):
+-----+
| v |
+-----+
| 0.0 | <-- Inconsistent!
+-----+
Query 2 (Grouped):
+-----+-----+
| grp | v |
+-----+-----+
| g1 | NaN | <-- Inconsistent!
+-----+-----+
```
**Expected Result:**
Both scalar and grouped queries must return `NaN`. A population containing a
`NaN` has an undefined/NaN variance.
---
### 2. Root Cause
In `datafusion/functions-aggregate/src/variance.rs`:
```rust
// VarianceAccumulator::evaluate (Scalar):
match self.count {
0 => None,
1 => {
if self.stats_type == StatsType::Population {
Some(0.0) // <-- Hardcoded 0.0, ignores self.m2.is_nan()!
} else {
None
}
}
_ => ...
}
```
In contrast, `VarianceGroupsAccumulator::variance_values` evaluates `m2 /
count = NaN / 1.0 = NaN`.
### 3. Proposed Fix
Check `if self.m2.is_nan() { Some(f64::NAN) }` before returning `Some(0.0)`
for single-row datasets in `VarianceAccumulator` and
`DistinctVarianceAccumulator`.
```
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