kosiew commented on code in PR #15648:
URL: https://github.com/apache/datafusion/pull/15648#discussion_r2039261553
##########
datafusion/physical-expr/src/expressions/binary.rs:
##########
@@ -405,23 +411,19 @@ impl PhysicalExpr for BinaryExpr {
let result_type = self.data_type(input_schema)?;
- // Attempt to use special kernels if one input is scalar and the other
is an array
- let scalar_result = match (&lhs, &rhs) {
- (ColumnarValue::Array(array), ColumnarValue::Scalar(scalar)) => {
- // if left is array and right is literal(not NULL) - use
scalar operations
- if scalar.is_null() {
- None
- } else {
- self.evaluate_array_scalar(array, scalar.clone())?.map(|r|
{
- r.and_then(|a| to_result_type_array(&self.op, a,
&result_type))
- })
+ // If the left-hand side is an array and the right-hand side is a
non-null scalar, try the optimized kernel.
+ if let (ColumnarValue::Array(array), ColumnarValue::Scalar(ref
scalar)) =
+ (&lhs, &rhs)
+ {
+ if !scalar.is_null() {
+ if let Some(result_array) =
+ self.evaluate_array_scalar(array, scalar.clone())?
+ {
+ let final_array = result_array
+ .and_then(|a| to_result_type_array(&self.op, a,
&result_type));
+ return final_array.map(ColumnarValue::Array);
Review Comment:
a rewrite while trying to optimize this function.
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