datafusion_functions/math/
nans.rsuse arrow::datatypes::{DataType, Float32Type, Float64Type};
use datafusion_common::{exec_err, Result};
use datafusion_expr::{ColumnarValue, TypeSignature};
use arrow::array::{ArrayRef, AsArray, BooleanArray};
use datafusion_expr::scalar_doc_sections::DOC_SECTION_MATH;
use datafusion_expr::{Documentation, ScalarUDFImpl, Signature, Volatility};
use std::any::Any;
use std::sync::{Arc, OnceLock};
#[derive(Debug)]
pub struct IsNanFunc {
signature: Signature,
}
impl Default for IsNanFunc {
fn default() -> Self {
Self::new()
}
}
impl IsNanFunc {
pub fn new() -> Self {
use DataType::*;
Self {
signature: Signature::one_of(
vec![
TypeSignature::Exact(vec![Float32]),
TypeSignature::Exact(vec![Float64]),
],
Volatility::Immutable,
),
}
}
}
impl ScalarUDFImpl for IsNanFunc {
fn as_any(&self) -> &dyn Any {
self
}
fn name(&self) -> &str {
"isnan"
}
fn signature(&self) -> &Signature {
&self.signature
}
fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
Ok(DataType::Boolean)
}
fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> {
let args = ColumnarValue::values_to_arrays(args)?;
let arr: ArrayRef = match args[0].data_type() {
DataType::Float64 => Arc::new(BooleanArray::from_unary(
args[0].as_primitive::<Float64Type>(),
f64::is_nan,
)) as ArrayRef,
DataType::Float32 => Arc::new(BooleanArray::from_unary(
args[0].as_primitive::<Float32Type>(),
f32::is_nan,
)) as ArrayRef,
other => {
return exec_err!(
"Unsupported data type {other:?} for function {}",
self.name()
)
}
};
Ok(ColumnarValue::Array(arr))
}
fn documentation(&self) -> Option<&Documentation> {
Some(get_isnan_doc())
}
}
static DOCUMENTATION: OnceLock<Documentation> = OnceLock::new();
fn get_isnan_doc() -> &'static Documentation {
DOCUMENTATION.get_or_init(|| {
Documentation::builder()
.with_doc_section(DOC_SECTION_MATH)
.with_description(
"Returns true if a given number is +NaN or -NaN otherwise returns false.",
)
.with_syntax_example("isnan(numeric_expression)")
.with_standard_argument("numeric_expression", Some("Numeric"))
.build()
.unwrap()
})
}