pepijnve commented on code in PR #20097:
URL: https://github.com/apache/datafusion/pull/20097#discussion_r2754549607
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datafusion/physical-expr/src/expressions/case.rs:
##########
@@ -961,32 +962,40 @@ impl CaseBody {
let then_batch = filter_record_batch(batch, &when_filter)?;
let then_value = self.when_then_expr[0].1.evaluate(&then_batch)?;
- let else_selection = not(&when_value)?;
- let else_filter = create_filter(&else_selection, optimize_filter);
- let else_batch = filter_record_batch(batch, &else_filter)?;
-
- // keep `else_expr`'s data type and return type consistent
- let e = self.else_expr.as_ref().unwrap();
- let return_type = self.data_type(&batch.schema())?;
- let else_expr = try_cast(Arc::clone(e), &batch.schema(),
return_type.clone())
- .unwrap_or_else(|_| Arc::clone(e));
-
- let else_value = else_expr.evaluate(&else_batch)?;
-
- Ok(ColumnarValue::Array(match (then_value, else_value) {
- (ColumnarValue::Array(t), ColumnarValue::Array(e)) => {
- merge(&when_value, &t, &e)
- }
- (ColumnarValue::Scalar(t), ColumnarValue::Array(e)) => {
- merge(&when_value, &t.to_scalar()?, &e)
- }
- (ColumnarValue::Array(t), ColumnarValue::Scalar(e)) => {
- merge(&when_value, &t, &e.to_scalar()?)
+ match &self.else_expr {
+ None => {
+ let then_array = then_value.to_array(when_value.true_count())?;
+ scatter(&when_value,
then_array.as_ref()).map(ColumnarValue::Array)
}
- (ColumnarValue::Scalar(t), ColumnarValue::Scalar(e)) => {
- merge(&when_value, &t.to_scalar()?, &e.to_scalar()?)
+ Some(else_expr) => {
+ let else_selection = not(&when_value)?;
+ let else_filter = create_filter(&else_selection,
optimize_filter);
+ let else_batch = filter_record_batch(batch, &else_filter)?;
+
+ // keep `else_expr`'s data type and return type consistent
+ let return_type = self.data_type(&batch.schema())?;
+ let else_expr =
+ try_cast(Arc::clone(else_expr), &batch.schema(),
return_type.clone())
+ .unwrap_or_else(|_| Arc::clone(else_expr));
Review Comment:
@alamb logged #1609 back then. Not sure how relevant this all still is today.
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