alamb commented on code in PR #5151:
URL: https://github.com/apache/arrow-datafusion/pull/5151#discussion_r1094909934
##########
datafusion/physical-expr/src/expressions/binary.rs:
##########
@@ -1565,6 +1660,61 @@ mod tests {
Ok(())
}
+ #[test]
+ fn plus_op_scalar() -> Result<()> {
+ let schema = Schema::new(vec![Field::new("a", DataType::Int32,
false)]);
+ let a = Int32Array::from(vec![1, 2, 3, 4, 5]);
+
+ apply_arithmetic_scalar(
+ Arc::new(schema),
+ vec![Arc::new(a)],
+ Operator::Plus,
+ ScalarValue::Int32(Some(1)),
+ Arc::new(Int32Array::from(vec![2, 3, 4, 5, 6])),
+ )?;
+
+ Ok(())
+ }
+
+ #[test]
+ fn plus_op_dict_scalar() -> Result<()> {
+ let schema = Schema::new(vec![Field::new(
+ "a",
+ DataType::Dictionary(Box::new(DataType::Int8),
Box::new(DataType::Int32)),
+ true,
+ )]);
+
+ let mut dict_builder = PrimitiveDictionaryBuilder::<Int8Type,
Int32Type>::new();
+
+ dict_builder.append(1)?;
+ dict_builder.append_null();
+ dict_builder.append(2)?;
+ dict_builder.append(5)?;
+
+ let a = dict_builder.finish();
+
+ let mut dict_builder = PrimitiveDictionaryBuilder::<Int8Type,
Int32Type>::new();
+
+ dict_builder.append(2)?;
Review Comment:
👍
##########
datafusion/physical-expr/src/expressions/binary.rs:
##########
@@ -904,6 +977,7 @@ impl BinaryExpr {
scalar: &ScalarValue,
) -> Result<Option<Result<ArrayRef>>> {
let bool_type = &DataType::Boolean;
+ let left_type = array.data_type();
Review Comment:
Is there any reason to pass in `left_type` to the
`binary_primitive_array_op_dyn_scalar!` (as it already gets `array` maybe it
could call `array.data_type()` directly when needed)?
Not that I see anything wrong with this, but I was curious
##########
datafusion/expr/src/type_coercion/binary.rs:
##########
@@ -439,6 +448,12 @@ fn both_numeric_or_null_and_numeric(lhs_type: &DataType,
rhs_type: &DataType) ->
match (lhs_type, rhs_type) {
(_, DataType::Null) => is_numeric(lhs_type),
(DataType::Null, _) => is_numeric(rhs_type),
+ (DataType::Dictionary(_, value_type), _) => {
+ is_numeric(value_type) && is_numeric(rhs_type)
+ }
+ (_, DataType::Dictionary(_, value_type)) => {
Review Comment:
I wonder if this need to handle the case when both lhs and rhs are
Dictionaries 🤔
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