dqkqd commented on code in PR #18104:
URL: https://github.com/apache/datafusion/pull/18104#discussion_r2442732221
##########
datafusion/functions-nested/src/set_ops.rs:
##########
@@ -563,3 +555,54 @@ fn general_array_distinct<OffsetSize: OffsetSizeTrait>(
array.nulls().cloned(),
)?))
}
+
+#[cfg(test)]
+mod tests {
+ use rstest::*;
+ use std::sync::Arc;
+
+ use arrow::{
+ array::{Int32Array, ListArray},
+ buffer::OffsetBuffer,
+ datatypes::{DataType, Field},
+ };
+ use datafusion_common::{config::ConfigOptions, DataFusionError};
+ use datafusion_expr::{ColumnarValue, ScalarFunctionArgs};
+
+ use crate::set_ops::array_distinct_udf;
+
+ #[rstest(inner_nullable, case(true), case(false))]
+ #[test]
+ fn test_array_distinct_inner_nullability_result_type_match_return_type(
+ inner_nullable: bool,
+ ) -> Result<(), DataFusionError> {
+ let udf = array_distinct_udf();
+
+ let inner_field = Field::new_list_field(DataType::Int32,
inner_nullable);
+ let input_field = Field::new_list("input",
Arc::new(inner_field.clone()), true);
+
+ // [[1, 1, 2]]
+ let input_array = ListArray::new(
+ inner_field.into(),
+ OffsetBuffer::new(vec![0, 3].into()),
+ Arc::new(Int32Array::new(vec![1, 1, 2].into(), None)),
+ None,
+ );
+ let input_array = ColumnarValue::Array(Arc::new(input_array));
+
+ let result = udf.invoke_with_args(ScalarFunctionArgs {
+ args: vec![input_array],
+ arg_fields: vec![input_field.clone().into()],
+ number_rows: 1,
+ return_field: input_field.clone().into(),
+ config_options: Arc::new(ConfigOptions::default()),
+ })?;
+
+ assert_eq!(
+ result.data_type(),
+ udf.return_type(&[input_field.data_type().clone()])?
+ );
Review Comment:
`ScalarUdf::invoke_with_args` has a data type check in debug mode:
https://github.com/apache/datafusion/blob/b98cad616ad9c69df9a425fc7473b799ffc258ee/datafusion/expr/src/udf.rs#L241-L249
But I think it is better to have an explicit assertion in the test code.
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