datafusion_functions/math/
random.rsuse std::any::Any;
use std::sync::Arc;
use arrow::array::Float64Array;
use arrow::datatypes::DataType;
use arrow::datatypes::DataType::Float64;
use rand::{thread_rng, Rng};
use datafusion_common::{internal_err, Result};
use datafusion_expr::ColumnarValue;
use datafusion_expr::{Documentation, ScalarUDFImpl, Signature, Volatility};
use datafusion_macros::user_doc;
#[user_doc(
doc_section(label = "Math Functions"),
description = r#"Returns a random float value in the range [0, 1).
The random seed is unique to each row."#,
syntax_example = "random()"
)]
#[derive(Debug)]
pub struct RandomFunc {
signature: Signature,
}
impl Default for RandomFunc {
fn default() -> Self {
RandomFunc::new()
}
}
impl RandomFunc {
pub fn new() -> Self {
Self {
signature: Signature::nullary(Volatility::Volatile),
}
}
}
impl ScalarUDFImpl for RandomFunc {
fn as_any(&self) -> &dyn Any {
self
}
fn name(&self) -> &str {
"random"
}
fn signature(&self) -> &Signature {
&self.signature
}
fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
Ok(Float64)
}
fn invoke_batch(
&self,
args: &[ColumnarValue],
num_rows: usize,
) -> Result<ColumnarValue> {
if !args.is_empty() {
return internal_err!("{} function does not accept arguments", self.name());
}
let mut rng = thread_rng();
let mut values = vec![0.0; num_rows];
rng.fill(&mut values[..]);
let array = Float64Array::from(values);
Ok(ColumnarValue::Array(Arc::new(array)))
}
fn documentation(&self) -> Option<&Documentation> {
self.doc()
}
}