thinkharderdev commented on code in PR #8578:
URL: https://github.com/apache/arrow-datafusion/pull/8578#discussion_r1506097216
##########
datafusion/expr/src/udf.rs:
##########
@@ -17,21 +17,32 @@
//! [`ScalarUDF`]: Scalar User Defined Functions
-use crate::{Expr, ReturnTypeFunction, ScalarFunctionImplementation, Signature};
+use crate::{
+ ColumnarValue, Expr, ReturnTypeFunction, ScalarFunctionImplementation,
Signature,
+};
use arrow::datatypes::DataType;
use datafusion_common::Result;
+use std::any::Any;
use std::fmt;
use std::fmt::Debug;
use std::fmt::Formatter;
use std::sync::Arc;
/// Logical representation of a Scalar User Defined Function.
///
-/// A scalar function produces a single row output for each row of input.
+/// A scalar function produces a single row output for each row of input. This
+/// struct contains the information DataFusion needs to plan and invoke
+/// functions you supply such name, type signature, return type, and actual
+/// implementation.
///
-/// This struct contains the information DataFusion needs to plan and invoke
-/// functions such name, type signature, return type, and actual
implementation.
///
+/// 1. For simple (less performant) use cases, use [`create_udf`] and
[`simple_udf.rs`].
Review Comment:
Using `create_udf` create an extra indirection. Under the hood it's creating
a
```
pub struct SimpleScalarUDF {
name: String,
signature: Signature,
return_type: DataType,
fun: ScalarFunctionImplementation,
}
impl ScalarUDFImpl for SimpleScalarUDF {
fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> {
(self.fun)(args)
}
}
```
so it adds an extra call for every batch processed through the UDF
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