viirya commented on code in PR #261:
URL:
https://github.com/apache/arrow-datafusion-comet/pull/261#discussion_r1561793369
##########
core/src/execution/datafusion/expressions/avg.rs:
##########
@@ -176,9 +176,15 @@ impl Accumulator for AvgAccumulator {
}
fn evaluate(&mut self) -> Result<ScalarValue> {
- Ok(ScalarValue::Float64(
- self.sum.map(|f| f / self.count as f64),
- ))
+ if self.count == 0 {
+ // If all input are nulls, count will be 0 and we will get null
after the division.
+ // This is consistent with Spark Average implementation.
+ return Ok(ScalarValue::Float64(None));
+ } else {
+ Ok(ScalarValue::Float64(
+ self.sum.map(|f| f / self.count as f64),
+ ))
Review Comment:
Actually the `GroupsAccumulator` below has correctly implemented this
behavior. Only `AvgAccumulator` has this issue.
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