datafusion-comet-spark-expr 0.10.0

// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements.  See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership.  The ASF licenses this file
// 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::*, datatypes::DataType};
use datafusion::common::{exec_err, internal_datafusion_err, internal_err, Result};
use datafusion::logical_expr::{ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility};
use datafusion::{error::DataFusionError, logical_expr::ColumnarValue};
use std::any::Any;
use std::sync::Arc;

#[derive(Debug)]
pub struct SparkBitwiseCount {
    signature: Signature,
    aliases: Vec<String>,
}

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

impl SparkBitwiseCount {
    pub fn new() -> Self {
        Self {
            signature: Signature::user_defined(Volatility::Immutable),
            aliases: vec![],
        }
    }
}

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

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

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

    fn return_type(&self, _: &[DataType]) -> Result<DataType> {
        Ok(DataType::Int32)
    }

    fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> {
        let args: [ColumnarValue; 1] = args
            .args
            .try_into()
            .map_err(|_| internal_datafusion_err!("bit_count expects exactly one argument"))?;
        spark_bit_count(args)
    }

    fn aliases(&self) -> &[String] {
        &self.aliases
    }
}

macro_rules! compute_op {
    ($OPERAND:expr, $DT:ident) => {{
        let operand = $OPERAND.as_any().downcast_ref::<$DT>().ok_or_else(|| {
            DataFusionError::Execution(format!(
                "compute_op failed to downcast array to: {:?}",
                stringify!($DT)
            ))
        })?;

        let result: Int32Array = operand
            .iter()
            .map(|x| x.map(|y| bit_count(y.into())))
            .collect();

        Ok(Arc::new(result))
    }};
}

pub fn spark_bit_count(args: [ColumnarValue; 1]) -> Result<ColumnarValue> {
    match args {
        [ColumnarValue::Array(array)] => {
            let result: Result<ArrayRef> = match array.data_type() {
                DataType::Int8 | DataType::Boolean => compute_op!(array, Int8Array),
                DataType::Int16 => compute_op!(array, Int16Array),
                DataType::Int32 => compute_op!(array, Int32Array),
                DataType::Int64 => compute_op!(array, Int64Array),
                _ => exec_err!("bit_count can't be evaluated because the expression's type is {:?}, not signed int", array.data_type()),
            };
            result.map(ColumnarValue::Array)
        }
        [ColumnarValue::Scalar(_)] => internal_err!("shouldn't go to bitwise count scalar path"),
    }
}

// Here’s the equivalent Rust implementation of the bitCount function (similar to Apache Spark's bitCount for LongType)
fn bit_count(i: i64) -> i32 {
    let mut u = i as u64;
    u = u - ((u >> 1) & 0x5555555555555555);
    u = (u & 0x3333333333333333) + ((u >> 2) & 0x3333333333333333);
    u = (u + (u >> 4)) & 0x0f0f0f0f0f0f0f0f;
    u = u + (u >> 8);
    u = u + (u >> 16);
    u = u + (u >> 32);
    (u as i32) & 0x7f
}

#[cfg(test)]
mod tests {
    use datafusion::common::{cast::as_int32_array, Result};

    use super::*;

    #[test]
    fn bitwise_count_op() -> Result<()> {
        let args = ColumnarValue::Array(Arc::new(Int32Array::from(vec![
            Some(1),
            None,
            Some(12345),
            Some(89),
            Some(-3456),
        ])));
        let expected = &Int32Array::from(vec![Some(1), None, Some(6), Some(4), Some(54)]);

        let ColumnarValue::Array(result) = spark_bit_count([args])? else {
            unreachable!()
        };

        let result = as_int32_array(&result).expect("failed to downcast to In32Array");
        assert_eq!(result, expected);

        Ok(())
    }
}