datafusion-functions 38.0.0

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// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.

use arrow::array::{ArrayRef, Int64Array};
use std::any::Any;
use std::sync::Arc;

use arrow::datatypes::DataType;
use arrow::datatypes::DataType::Int64;

use crate::utils::make_scalar_function;
use datafusion_common::{exec_err, DataFusionError, Result};
use datafusion_expr::{ColumnarValue, ScalarUDFImpl, Signature, Volatility};

#[derive(Debug)]
pub struct FactorialFunc {
    signature: Signature,
}

impl Default for FactorialFunc {
    fn default() -> Self {
        FactorialFunc::new()
    }
}

impl FactorialFunc {
    pub fn new() -> Self {
        Self {
            signature: Signature::uniform(1, vec![Int64], Volatility::Immutable),
        }
    }
}

impl ScalarUDFImpl for FactorialFunc {
    fn as_any(&self) -> &dyn Any {
        self
    }

    fn name(&self) -> &str {
        "factorial"
    }

    fn signature(&self) -> &Signature {
        &self.signature
    }

    fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
        Ok(Int64)
    }

    fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> {
        make_scalar_function(factorial, vec![])(args)
    }
}

macro_rules! make_function_scalar_inputs {
    ($ARG: expr, $NAME:expr, $ARRAY_TYPE:ident, $FUNC: block) => {{
        let arg = downcast_arg!($ARG, $NAME, $ARRAY_TYPE);

        arg.iter()
            .map(|a| match a {
                Some(a) => Some($FUNC(a)),
                _ => None,
            })
            .collect::<$ARRAY_TYPE>()
    }};
}

/// Factorial SQL function
fn factorial(args: &[ArrayRef]) -> Result<ArrayRef> {
    match args[0].data_type() {
        DataType::Int64 => Ok(Arc::new(make_function_scalar_inputs!(
            &args[0],
            "value",
            Int64Array,
            { |value: i64| { (1..=value).product() } }
        )) as ArrayRef),
        other => exec_err!("Unsupported data type {other:?} for function factorial."),
    }
}

#[cfg(test)]
mod test {

    use datafusion_common::cast::as_int64_array;

    use super::*;

    #[test]
    fn test_factorial_i64() {
        let args: Vec<ArrayRef> = vec![
            Arc::new(Int64Array::from(vec![0, 1, 2, 4])), // input
        ];

        let result = factorial(&args).expect("failed to initialize function factorial");
        let ints =
            as_int64_array(&result).expect("failed to initialize function factorial");

        let expected = Int64Array::from(vec![1, 1, 2, 24]);

        assert_eq!(ints, &expected);
    }
}