leung-ming commented on code in PR #1922:
URL: https://github.com/apache/datafusion-comet/pull/1922#discussion_r2165657752
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native/spark-expr/src/agg_funcs/sum_decimal.rs:
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@@ -375,11 +375,17 @@ impl GroupsAccumulator for SumDecimalGroupsAccumulator {
// are null, in this case we'll return null
// 2. if `is_empty` is false, but `null_state` is true, it means
there's an overflow. In
// non-ANSI mode Spark returns null.
+ let result = emit_to.take_needed(&mut self.sum);
+ result.iter().enumerate().for_each(|(i, &v)| {
Review Comment:
Partial aggregate.
Use the test as example:
Two numbers 42 and 9*9 are parted.
```rust
part_1.update(42) // ok, 42
part_2.update(9*9) // ok, 9*9
// gather exchange
final.merge(part_1); final.merge(part_2) // overflow without setting nulls
final.evaluate() // overflowed value returned, spark throw
```
BTW, some time 9*9 and 42 are not parted, in that case sum will work, but
avg will fail, I am not yet put it to test though.
```rust
avg.update(42) // ok, 42
avg.update(9*9) // new_sum overflow, sum is still 42 and count is 2 and null
bit is set
avg.evaluate() // the evaluate of avg without checking the null bit,
yielding 21
```
There maybe other issue in avg, to be fixed later with #1893
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