[GitHub] [arrow-datafusion] jorgecarleitao commented on a change in pull request #303: add random SQL function

[GitBox]

jorgecarleitao commented on a change in pull request #303:
URL: https://github.com/apache/arrow-datafusion/pull/303#discussion_r630285020



##########
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:
       Note that `NullArray` is composed by zero buffers, zero childs, no 
validity and one datatype, so the cost to instantiate it is really small. The 
advantage over a `ScalarValue` is that the semantics of getting a length are 
preserved: use `array.len()` as any other array.
   
   I am not married with any; was just trying to think about this from a 
documentations' perspective:
   
   > We support zero-argument UDFs. They MUST be declared as accepting zero 
arguments and the function signature MUST be a single argument. DataFusion will 
pass an `Array` to it, from which you can retrieve its length via 
`Array::len()`. The function MUST return an array whose number of rows equals 
the length of the array.
   
   If we pass a scalar of any type, if the evaluation is distributed, I believe 
that we will have to serialize `Scalar -> Array` in Ballista.




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