goutamadwant commented on code in PR #24767:
URL: https://github.com/apache/datafusion/pull/24767#discussion_r4002731423
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datafusion/spark/src/function/aggregate/collect.rs:
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@@ -180,27 +234,49 @@ impl<T: Accumulator> NullToEmptyListAccumulator<T> {
pub fn new(inner: T, list_type: DataType) -> Self {
Self { inner, list_type }
}
+
+ fn normalize_input(&self, value: &ArrayRef) -> Result<ArrayRef> {
+ let DataType::List(field) = &self.list_type else {
+ return internal_err!(
+ "collect_list/collect_set expected List return type, got {:?}",
+ self.list_type
+ );
+ };
+ if value.data_type() == field.data_type() {
+ Ok(Arc::clone(value))
+ } else {
+ Ok(cast(value.as_ref(), field.data_type())?)
+ }
+ }
}
impl<T: Accumulator> Accumulator for NullToEmptyListAccumulator<T> {
fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
- self.inner.update_batch(values)
+ let [value] = values else {
+ return self.inner.update_batch(values);
+ };
+ let value = self.normalize_input(value)?;
+ self.inner.update_batch(&[value])
Review Comment:
Retractions now use the same input normalization as updates. The regression
covers nested schema differences through update, retract, state, merge, and
evaluation for both aggregates.
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