wudidapaopao commented on code in PR #25536:
URL: https://github.com/apache/datafusion/pull/25536#discussion_r4065514376
##########
datafusion/expr/src/udaf.rs:
##########
@@ -311,6 +312,17 @@ impl AggregateUDF {
self.inner.simplify()
}
+ /// Returns this aggregate function's candidate decomposition, if any.
+ ///
+ /// See [`AggregateUDFImpl::decompose`] for more details.
+ pub fn decompose(
Review Comment:
Thanks, I considered using `simplify`. I think we should retain the AVG
accumulator and only decompose `AVG` when its generated `SUM` or `COUNT` can be
shared. If implemented in `simplify`, every AVG would be unconditionally
rewritten into `SUM/COUNT`.
On 20 million random non-null Int64 rows:
```
SELECT AVG(x) FROM t;
```
versus:
```
SELECT SUM(CAST(x AS DOUBLE))
/ CAST(COUNT(*) AS DOUBLE)
FROM t;
```
took `9.06` ms and `10.72` ms respectively, so decomposition was `18.29%`
slower.
With one reusable SUM:
```
SELECT SUM(CAST(x AS DOUBLE)), AVG(x) FROM t;
```
decomposition improved `11.72` ms to `10.79` ms (`7.95%`).
With three reusable SUMs:
```
SELECT
SUM(CAST(x AS DOUBLE)), AVG(x),
SUM(CAST(y AS DOUBLE)), AVG(y),
SUM(CAST(z AS DOUBLE)), AVG(z)
FROM t;
```
decomposition improved `32.91` ms to `27.85` ms (`15.38%`).
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