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new 913d1c0a7c perf: Optimize signum scalar performance with fast path
(#19871)
913d1c0a7c is described below
commit 913d1c0a7c8bdd18b3a43f70abbbe283cf96aac8
Author: Kumar Ujjawal <[email protected]>
AuthorDate: Wed Jan 21 09:04:48 2026 +0530
perf: Optimize signum scalar performance with fast path (#19871)
## Which issue does this PR close?
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We generally require a GitHub issue to be filed for all bug fixes and
enhancements and this helps us generate change logs for our releases.
You can link an issue to this PR using the GitHub syntax. For example
`Closes #123` indicates that this PR will close issue #123.
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- Part of https://github.com/apache/datafusion-comet/issues/2986
## Rationale for this change
The signum function currently converts scalar inputs to arrays before
processing, even for single scalar values. This adds unnecessary
overhead from array allocation and conversion. Adding a scalar fast path
avoids this overhead and improves performance for constant folding and
scalar expression evaluation.
<!--
Why are you proposing this change? If this is already explained clearly
in the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand
your changes and offer better suggestions for fixes.
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## What changes are included in this PR?
- Added scalar fast path for `float32` and `float64`
| Type | Before | After | Speedup |
|------|--------|-------|---------|
| **signum_f64_scalar** | 266 ns | 54 ns | **4.9x** |
| **signum_f32_scalar** | 263 ns | 55 ns | **4.8x** |
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is sometimes worth providing a summary of the individual changes in this
PR.
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## Are these changes tested?
Yes
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2. Serve as another way to document the expected behavior of the code
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## Are there any user-facing changes?
No
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---------
Co-authored-by: Jeffrey Vo <[email protected]>
---
datafusion/functions/benches/signum.rs | 46 ++++++++++++++++++
datafusion/functions/src/math/signum.rs | 82 ++++++++++++++++++++-------------
2 files changed, 96 insertions(+), 32 deletions(-)
diff --git a/datafusion/functions/benches/signum.rs
b/datafusion/functions/benches/signum.rs
index 08a197a60e..b34e52d7f2 100644
--- a/datafusion/functions/benches/signum.rs
+++ b/datafusion/functions/benches/signum.rs
@@ -23,6 +23,7 @@ use arrow::{
util::bench_util::create_primitive_array,
};
use criterion::{Criterion, criterion_group, criterion_main};
+use datafusion_common::ScalarValue;
use datafusion_common::config::ConfigOptions;
use datafusion_expr::{ColumnarValue, ScalarFunctionArgs};
use datafusion_functions::math::signum;
@@ -88,6 +89,51 @@ fn criterion_benchmark(c: &mut Criterion) {
)
})
});
+
+ // Scalar benchmarks (the optimization we added)
+ let scalar_f32_args =
+ vec![ColumnarValue::Scalar(ScalarValue::Float32(Some(-42.5)))];
+ let scalar_f32_arg_fields =
+ vec![Field::new("a", DataType::Float32, false).into()];
+ let return_field_f32 = Field::new("f", DataType::Float32,
false).into();
+
+ c.bench_function(&format!("signum f32 scalar: {size}"), |b| {
+ b.iter(|| {
+ black_box(
+ signum
+ .invoke_with_args(ScalarFunctionArgs {
+ args: scalar_f32_args.clone(),
+ arg_fields: scalar_f32_arg_fields.clone(),
+ number_rows: 1,
+ return_field: Arc::clone(&return_field_f32),
+ config_options: Arc::clone(&config_options),
+ })
+ .unwrap(),
+ )
+ })
+ });
+
+ let scalar_f64_args =
+ vec![ColumnarValue::Scalar(ScalarValue::Float64(Some(-42.5)))];
+ let scalar_f64_arg_fields =
+ vec![Field::new("a", DataType::Float64, false).into()];
+ let return_field_f64 = Field::new("f", DataType::Float64,
false).into();
+
+ c.bench_function(&format!("signum f64 scalar: {size}"), |b| {
+ b.iter(|| {
+ black_box(
+ signum
+ .invoke_with_args(ScalarFunctionArgs {
+ args: scalar_f64_args.clone(),
+ arg_fields: scalar_f64_arg_fields.clone(),
+ number_rows: 1,
+ return_field: Arc::clone(&return_field_f64),
+ config_options: Arc::clone(&config_options),
+ })
+ .unwrap(),
+ )
+ })
+ });
}
}
diff --git a/datafusion/functions/src/math/signum.rs
b/datafusion/functions/src/math/signum.rs
index e217088c64..8a3769a12f 100644
--- a/datafusion/functions/src/math/signum.rs
+++ b/datafusion/functions/src/math/signum.rs
@@ -18,11 +18,12 @@
use std::any::Any;
use std::sync::Arc;
-use arrow::array::{ArrayRef, AsArray};
+use arrow::array::AsArray;
use arrow::datatypes::DataType::{Float32, Float64};
use arrow::datatypes::{DataType, Float32Type, Float64Type};
-use datafusion_common::{Result, exec_err};
+use datafusion_common::utils::take_function_args;
+use datafusion_common::{Result, ScalarValue, internal_err};
use datafusion_expr::sort_properties::{ExprProperties, SortProperties};
use datafusion_expr::{
ColumnarValue, Documentation, ScalarFunctionArgs, ScalarUDFImpl, Signature,
@@ -30,8 +31,6 @@ use datafusion_expr::{
};
use datafusion_macros::user_doc;
-use crate::utils::make_scalar_function;
-
#[user_doc(
doc_section(label = "Math Functions"),
description = r#"Returns the sign of a number.
@@ -98,7 +97,53 @@ impl ScalarUDFImpl for SignumFunc {
}
fn invoke_with_args(&self, args: ScalarFunctionArgs) ->
Result<ColumnarValue> {
- make_scalar_function(signum, vec![])(&args.args)
+ let return_type = args.return_type().clone();
+ let [arg] = take_function_args(self.name(), args.args)?;
+
+ match arg {
+ ColumnarValue::Scalar(scalar) => {
+ if scalar.is_null() {
+ return ColumnarValue::Scalar(ScalarValue::Null)
+ .cast_to(&return_type, None);
+ }
+
+ match scalar {
+ ScalarValue::Float64(Some(v)) => {
+ let result = if v == 0.0 { 0.0 } else { v.signum() };
+
Ok(ColumnarValue::Scalar(ScalarValue::Float64(Some(result))))
+ }
+ ScalarValue::Float32(Some(v)) => {
+ let result = if v == 0.0 { 0.0 } else { v.signum() };
+
Ok(ColumnarValue::Scalar(ScalarValue::Float32(Some(result))))
+ }
+ _ => {
+ internal_err!(
+ "Unexpected scalar type for signum: {:?}",
+ scalar.data_type()
+ )
+ }
+ }
+ }
+ ColumnarValue::Array(array) => match array.data_type() {
+ Float64 => Ok(ColumnarValue::Array(Arc::new(
+ array.as_primitive::<Float64Type>().unary::<_,
Float64Type>(
+ |x: f64| {
+ if x == 0.0 { 0.0 } else { x.signum() }
+ },
+ ),
+ ))),
+ Float32 => Ok(ColumnarValue::Array(Arc::new(
+ array.as_primitive::<Float32Type>().unary::<_,
Float32Type>(
+ |x: f32| {
+ if x == 0.0 { 0.0 } else { x.signum() }
+ },
+ ),
+ ))),
+ other => {
+ internal_err!("Unsupported data type {other:?} for
function signum")
+ }
+ },
+ }
}
fn documentation(&self) -> Option<&Documentation> {
@@ -106,33 +151,6 @@ impl ScalarUDFImpl for SignumFunc {
}
}
-/// signum SQL function
-fn signum(args: &[ArrayRef]) -> Result<ArrayRef> {
- match args[0].data_type() {
- Float64 => Ok(Arc::new(
- args[0]
- .as_primitive::<Float64Type>()
- .unary::<_, Float64Type>(
- |x: f64| {
- if x == 0_f64 { 0_f64 } else { x.signum() }
- },
- ),
- ) as ArrayRef),
-
- Float32 => Ok(Arc::new(
- args[0]
- .as_primitive::<Float32Type>()
- .unary::<_, Float32Type>(
- |x: f32| {
- if x == 0_f32 { 0_f32 } else { x.signum() }
- },
- ),
- ) as ArrayRef),
-
- other => exec_err!("Unsupported data type {other:?} for function
signum"),
- }
-}
-
#[cfg(test)]
mod test {
use std::sync::Arc;
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