Jimexist commented on a change in pull request #303:
URL: https://github.com/apache/arrow-datafusion/pull/303#discussion_r630623061
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File path: datafusion/src/physical_plan/functions.rs
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@@ -1373,20 +1370,26 @@ impl PhysicalExpr for ScalarFunctionExpr {
}
fn evaluate(&self, batch: &RecordBatch) -> Result<ColumnarValue> {
- // evaluate the arguments
- let inputs = self
- .args
- .iter()
- .map(|e| e.evaluate(batch))
- .collect::<Result<Vec<_>>>()?;
+ // evaluate the arguments, if there are no arguments we'll instead
pass in a null array of
+ // batch size (as a convention)
+ let inputs = match self.args.len() {
+ 0 => vec![ColumnarValue::Array(Arc::new(NullArray::new(
Review comment:
@alamb @Dandandan and @jorgecarleitao thanks for the discussion.
I agree that both ways are similar and equally “hacky” but for lack of a
better solution they are okay. I'd slightly prefer null array because there's
no ScalarValue::USize and having to convert from/to UInt32 is a bit cumbersome.
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