Revert to a80fc77: feat(min_max): rename predicate to requires_logical_row_scan

Author: kosiew

datafusion/functions-aggregate-common/src/min_max.rs

@@ -439,7 +439,12 @@ macro_rules! min_max {
     }};
 }
 
-fn scalar_batch_extreme(values: &ArrayRef, ordering: Ordering) -> Result<ScalarValue> {
+/// Finds the min/max by scanning logical rows via `ScalarValue::try_from_array`.
+///
+/// This path is required for dictionary arrays because comparing
+/// `dictionary.values()` is not semantically correct: it can include
+/// unreferenced values and ignore null key positions.
+fn scalar_row_extreme(values: &ArrayRef, ordering: Ordering) -> Result<ScalarValue> {
     let mut index = 0;
     let mut extreme = loop {
         if index == values.len() {
@@ -475,7 +480,9 @@ fn dictionary_scalar_parts(value: &ScalarValue) -> (&ScalarValue, Option<&DataTy
     }
 }
 
-fn is_row_wise_batch_type(data_type: &DataType) -> bool {
+// Primitive, string, and binary types use specialized Arrow min/max kernels.
+// These remaining types fall back to scalar row-by-row logical comparison.
+fn requires_logical_row_scan(data_type: &DataType) -> bool {
     matches!(
         data_type,
         DataType::Struct(_)
@@ -823,8 +830,8 @@ pub fn min_batch(values: &ArrayRef) -> Result<ScalarValue> {
                 min_binary_view
             )
         }
-        data_type if is_row_wise_batch_type(data_type) => {
-            scalar_batch_extreme(values, Ordering::Greater)?
+        data_type if requires_logical_row_scan(data_type) => {
+            scalar_row_extreme(values, Ordering::Greater)?
         }
         _ => min_max_batch!(values, min),
     })
@@ -875,8 +882,8 @@ pub fn max_batch(values: &ArrayRef) -> Result<ScalarValue> {
             let value = value.map(|e| e.to_vec());
             ScalarValue::FixedSizeBinary(*size, value)
         }
-        data_type if is_row_wise_batch_type(data_type) => {
-            scalar_batch_extreme(values, Ordering::Less)?
+        data_type if requires_logical_row_scan(data_type) => {
+            scalar_row_extreme(values, Ordering::Less)?
         }
         _ => min_max_batch!(values, max),
     })