SteveLauC commented on code in PR #8578:
URL: https://github.com/apache/arrow-datafusion/pull/8578#discussion_r1505483541
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datafusion/expr/src/udf.rs:
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@@ -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:
> less performant
Hi, is there anyone who would like to explain a bit about why `create_udf()`
is less performant than the UDFs created by `ScalarUDFImpl`?
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