jonathanc-n commented on code in PR #20460:
URL: https://github.com/apache/datafusion/pull/20460#discussion_r2839507105
##########
datafusion/functions-aggregate/src/count.rs:
##########
@@ -1038,4 +1212,82 @@ mod tests {
assert_eq!(merged.evaluate()?, ScalarValue::Int64(Some(3)));
Ok(())
}
+
+ #[test]
+ fn multi_column_accumulator_basic() -> Result<()> {
+ let mut acc = MultiColumnDistinctCountAccumulator::new(vec![
+ DataType::Int32,
+ DataType::Utf8,
+ ]);
+
+ // (1, a), (1, b), (1, a), (2, b), (3, b)
+ let col1 = Arc::new(Int32Array::from(vec![
+ Some(1),
+ Some(1),
+ Some(1),
+ Some(2),
+ Some(3),
+ ]));
+ let col2 = Arc::new(StringArray::from(vec![
+ Some("a"),
+ Some("b"),
+ Some("a"),
+ Some("b"),
+ Some("b"),
+ ])) as ArrayRef;
+
+ acc.update_batch(&[col1, col2])?;
+ // Expected (1, a), (1, b), (2, b), (3, b)
+ assert_eq!(acc.evaluate()?, ScalarValue::Int64(Some(4)));
+ Ok(())
+ }
+
+ #[test]
+ fn multi_column_accumulator_merge() -> Result<()> {
+ let mut acc1 = MultiColumnDistinctCountAccumulator::new(vec![
+ DataType::Int32,
+ DataType::Utf8,
+ ]);
+
+ // (1, a), (1, b)
+ let col1 = Arc::new(Int32Array::from(vec![Some(1), Some(1)]));
+ let col2 = Arc::new(StringArray::from(vec![Some("a"), Some("b")])) as
ArrayRef;
+
+ acc1.update_batch(&[col1, col2])?;
+
+ let mut acc2 = MultiColumnDistinctCountAccumulator::new(vec![
+ DataType::Int32,
+ DataType::Utf8,
+ ]);
+
+ // (1, a), (2, b), (3, b)
+ let col1 = Arc::new(Int32Array::from(vec![Some(1), Some(2), Some(3)]));
+ let col2 = Arc::new(StringArray::from(vec![Some("a"), Some("b"),
Some("b")]))
+ as ArrayRef;
+
+ acc2.update_batch(&[col1, col2])?;
+
+ let state_sv1 = acc1.state()?;
+ let state_sv2 = acc2.state()?;
+ let state_arr1: Vec<ArrayRef> = state_sv1
+ .into_iter()
+ .map(|sv| sv.to_array())
+ .collect::<Result<_>>()?;
+ let state_arr2: Vec<ArrayRef> = state_sv2
+ .into_iter()
+ .map(|sv| sv.to_array())
+ .collect::<Result<_>>()?;
+
+ let mut merged = MultiColumnDistinctCountAccumulator::new(vec![
+ DataType::Int32,
+ DataType::Utf8,
+ ]);
+ merged.merge_batch(&state_arr1)?;
+ merged.merge_batch(&state_arr2)?;
+
+ // Expected (1, a), (1, b), (1, a), (2, b), (3, b)
Review Comment:
this is not a correct comment, we only expect 4
##########
datafusion/functions-aggregate/src/count.rs:
##########
@@ -293,20 +293,37 @@ impl AggregateUDFImpl for Count {
fn state_fields(&self, args: StateFieldsArgs) -> Result<Vec<FieldRef>> {
if args.is_distinct {
- let dtype: DataType = match &args.input_fields[0].data_type() {
- DataType::Dictionary(_, values_type) =>
(**values_type).clone(),
- &dtype => dtype.clone(),
- };
+ if args.input_fields.len() > 1 {
+ Ok(args
+ .input_fields
+ .iter()
+ .map(|field| {
+ Arc::new(Field::new(
+ format_state_name(args.name, "count distinct"),
Review Comment:
same column names will look identical here. we should include original field
name or col index to differentiate
##########
datafusion/functions-aggregate/src/count.rs:
##########
@@ -841,6 +865,156 @@ impl Accumulator for DistinctCountAccumulator {
}
}
+#[derive(Debug)]
+struct MultiColumnDistinctCountAccumulator {
+ values: HashSet<Vec<ScalarValue>, RandomState>,
+ state_data_types: Vec<DataType>,
+}
+
+impl MultiColumnDistinctCountAccumulator {
+ fn new(state_data_types: Vec<DataType>) -> Self {
+ Self {
+ values: HashSet::default(),
+ state_data_types,
+ }
+ }
+
+ fn update(&mut self, values: &[ScalarValue]) -> Result<()> {
+ if !values.iter().any(|v| v.is_null()) {
+ self.values.insert(values.to_vec());
+ }
+ Ok(())
+ }
+
+ fn fixed_size(&self) -> usize {
+ std::mem::size_of_val(self)
Review Comment:
Lets import `use std::mem::size_of_val`
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