// 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.

//! Defines physical expressions that can evaluated at runtime during query execution

use std::any::Any;
use std::convert::TryFrom;
use std::sync::Arc;

use crate::{AggregateExpr, PhysicalExpr};
use arrow::datatypes::DataType;
use arrow::{
    array::{
        ArrayRef, Int16Array, Int32Array, Int64Array, Int8Array, UInt16Array,
        UInt32Array, UInt64Array, UInt8Array,
    },
    datatypes::Field,
};
use datafusion_common::{downcast_value, DataFusionError, Result, ScalarValue};
use datafusion_expr::Accumulator;

use crate::aggregate::row_accumulator::{
    is_row_accumulator_support_dtype, RowAccumulator,
};
use crate::aggregate::utils::down_cast_any_ref;
use crate::expressions::format_state_name;
use arrow::array::Array;
use arrow::array::PrimitiveArray;
use arrow::datatypes::ArrowNativeTypeOp;
use arrow::datatypes::ArrowNumericType;
use datafusion_row::accessor::RowAccessor;
use std::ops::BitAnd as BitAndImplementation;
use std::ops::BitOr as BitOrImplementation;
use std::ops::BitXor as BitXorImplementation;

// TODO: remove this macro rules after implementation in arrow-rs
// https://github.com/apache/arrow-rs/pull/4210
macro_rules! bit_operation {
    ($NAME:ident, $OP:ident, $NATIVE:ident, $DEFAULT:expr, $DOC:expr) => {
        #[doc = $DOC]
        ///
        /// Returns `None` if the array is empty or only contains null values.
        fn $NAME<T>(array: &PrimitiveArray<T>) -> Option<T::Native>
        where
            T: ArrowNumericType,
            T::Native: $NATIVE<Output = T::Native> + ArrowNativeTypeOp,
        {
            let default;
            if $DEFAULT == -1 {
                default = T::Native::ONE.neg_wrapping();
            } else {
                default = T::default_value();
            }

            let null_count = array.null_count();

            if null_count == array.len() {
                return None;
            }

            let data: &[T::Native] = array.values();

            match array.nulls() {
                None => {
                    let result = data
                        .iter()
                        .fold(default, |accumulator, value| accumulator.$OP(*value));

                    Some(result)
                }
                Some(nulls) => {
                    let mut result = default;
                    let data_chunks = data.chunks_exact(64);
                    let remainder = data_chunks.remainder();

                    let bit_chunks = nulls.inner().bit_chunks();
                    data_chunks
                        .zip(bit_chunks.iter())
                        .for_each(|(chunk, mask)| {
                            // index_mask has value 1 << i in the loop
                            let mut index_mask = 1;
                            chunk.iter().for_each(|value| {
                                if (mask & index_mask) != 0 {
                                    result = result.$OP(*value);
                                }
                                index_mask <<= 1;
                            });
                        });

                    let remainder_bits = bit_chunks.remainder_bits();

                    remainder.iter().enumerate().for_each(|(i, value)| {
                        if remainder_bits & (1 << i) != 0 {
                            result = result.$OP(*value);
                        }
                    });

                    Some(result)
                }
            }
        }
    };
}

bit_operation!(
    bit_and,
    bitand,
    BitAndImplementation,
    -1,
    "Returns the bitwise and of all non-null input values."
);
bit_operation!(
    bit_or,
    bitor,
    BitOrImplementation,
    0,
    "Returns the bitwise or of all non-null input values."
);
bit_operation!(
    bit_xor,
    bitxor,
    BitXorImplementation,
    0,
    "Returns the bitwise xor of all non-null input values."
);

// returns the new value after bit_and/bit_or/bit_xor with the new values, taking nullability into account
macro_rules! typed_bit_and_or_xor_batch {
    ($VALUES:expr, $ARRAYTYPE:ident, $SCALAR:ident, $OP:ident) => {{
        let array = downcast_value!($VALUES, $ARRAYTYPE);
        let delta = $OP(array);
        Ok(ScalarValue::$SCALAR(delta))
    }};
}

// bit_and/bit_or/bit_xor the array and returns a ScalarValue of its corresponding type.
macro_rules! bit_and_or_xor_batch {
    ($VALUES:expr, $OP:ident) => {{
        match $VALUES.data_type() {
            DataType::Int64 => {
                typed_bit_and_or_xor_batch!($VALUES, Int64Array, Int64, $OP)
            }
            DataType::Int32 => {
                typed_bit_and_or_xor_batch!($VALUES, Int32Array, Int32, $OP)
            }
            DataType::Int16 => {
                typed_bit_and_or_xor_batch!($VALUES, Int16Array, Int16, $OP)
            }
            DataType::Int8 => {
                typed_bit_and_or_xor_batch!($VALUES, Int8Array, Int8, $OP)
            }
            DataType::UInt64 => {
                typed_bit_and_or_xor_batch!($VALUES, UInt64Array, UInt64, $OP)
            }
            DataType::UInt32 => {
                typed_bit_and_or_xor_batch!($VALUES, UInt32Array, UInt32, $OP)
            }
            DataType::UInt16 => {
                typed_bit_and_or_xor_batch!($VALUES, UInt16Array, UInt16, $OP)
            }
            DataType::UInt8 => {
                typed_bit_and_or_xor_batch!($VALUES, UInt8Array, UInt8, $OP)
            }
            e => {
                return Err(DataFusionError::Internal(format!(
                    "Bit and/Bit or/Bit xor is not expected to receive the type {e:?}"
                )));
            }
        }
    }};
}

/// dynamically-typed bit_and(array) -> ScalarValue
fn bit_and_batch(values: &ArrayRef) -> Result<ScalarValue> {
    bit_and_or_xor_batch!(values, bit_and)
}

/// dynamically-typed bit_or(array) -> ScalarValue
fn bit_or_batch(values: &ArrayRef) -> Result<ScalarValue> {
    bit_and_or_xor_batch!(values, bit_or)
}

/// dynamically-typed bit_xor(array) -> ScalarValue
fn bit_xor_batch(values: &ArrayRef) -> Result<ScalarValue> {
    bit_and_or_xor_batch!(values, bit_xor)
}

// bit_and/bit_or/bit_xor of two scalar values.
macro_rules! typed_bit_and_or_xor_v2 {
    ($INDEX:ident, $ACC:ident, $SCALAR:expr, $TYPE:ident, $OP:ident) => {{
        paste::item! {
            match $SCALAR {
                None => {}
                Some(v) => $ACC.[<$OP _ $TYPE>]($INDEX, *v as $TYPE)
            }
        }
    }};
}

macro_rules! bit_and_or_xor_v2 {
    ($INDEX:ident, $ACC:ident, $SCALAR:expr, $OP:ident) => {{
        Ok(match $SCALAR {
            ScalarValue::UInt64(rhs) => {
                typed_bit_and_or_xor_v2!($INDEX, $ACC, rhs, u64, $OP)
            }
            ScalarValue::UInt32(rhs) => {
                typed_bit_and_or_xor_v2!($INDEX, $ACC, rhs, u32, $OP)
            }
            ScalarValue::UInt16(rhs) => {
                typed_bit_and_or_xor_v2!($INDEX, $ACC, rhs, u16, $OP)
            }
            ScalarValue::UInt8(rhs) => {
                typed_bit_and_or_xor_v2!($INDEX, $ACC, rhs, u8, $OP)
            }
            ScalarValue::Int64(rhs) => {
                typed_bit_and_or_xor_v2!($INDEX, $ACC, rhs, i64, $OP)
            }
            ScalarValue::Int32(rhs) => {
                typed_bit_and_or_xor_v2!($INDEX, $ACC, rhs, i32, $OP)
            }
            ScalarValue::Int16(rhs) => {
                typed_bit_and_or_xor_v2!($INDEX, $ACC, rhs, i16, $OP)
            }
            ScalarValue::Int8(rhs) => {
                typed_bit_and_or_xor_v2!($INDEX, $ACC, rhs, i8, $OP)
            }
            ScalarValue::Null => {
                // do nothing
            }
            e => {
                return Err(DataFusionError::Internal(format!(
                    "BIT AND/BIT OR/BIT XOR is not expected to receive scalars of incompatible types {:?}",
                    e
                )))
            }
        })
    }};
}

pub fn bit_and_row(
    index: usize,
    accessor: &mut RowAccessor,
    s: &ScalarValue,
) -> Result<()> {
    bit_and_or_xor_v2!(index, accessor, s, bitand)
}

pub fn bit_or_row(
    index: usize,
    accessor: &mut RowAccessor,
    s: &ScalarValue,
) -> Result<()> {
    bit_and_or_xor_v2!(index, accessor, s, bitor)
}

pub fn bit_xor_row(
    index: usize,
    accessor: &mut RowAccessor,
    s: &ScalarValue,
) -> Result<()> {
    bit_and_or_xor_v2!(index, accessor, s, bitxor)
}

/// BIT_AND aggregate expression
#[derive(Debug, Clone)]
pub struct BitAnd {
    name: String,
    pub data_type: DataType,
    expr: Arc<dyn PhysicalExpr>,
    nullable: bool,
}

impl BitAnd {
    /// Create a new BIT_AND aggregate function
    pub fn new(
        expr: Arc<dyn PhysicalExpr>,
        name: impl Into<String>,
        data_type: DataType,
    ) -> Self {
        Self {
            name: name.into(),
            expr,
            data_type,
            nullable: true,
        }
    }
}

impl AggregateExpr for BitAnd {
    /// Return a reference to Any that can be used for downcasting
    fn as_any(&self) -> &dyn Any {
        self
    }

    fn field(&self) -> Result<Field> {
        Ok(Field::new(
            &self.name,
            self.data_type.clone(),
            self.nullable,
        ))
    }

    fn create_accumulator(&self) -> Result<Box<dyn Accumulator>> {
        Ok(Box::new(BitAndAccumulator::try_new(&self.data_type)?))
    }

    fn state_fields(&self) -> Result<Vec<Field>> {
        Ok(vec![Field::new(
            format_state_name(&self.name, "bit_and"),
            self.data_type.clone(),
            self.nullable,
        )])
    }

    fn expressions(&self) -> Vec<Arc<dyn PhysicalExpr>> {
        vec![self.expr.clone()]
    }

    fn name(&self) -> &str {
        &self.name
    }

    fn row_accumulator_supported(&self) -> bool {
        is_row_accumulator_support_dtype(&self.data_type)
    }

    fn create_row_accumulator(
        &self,
        start_index: usize,
    ) -> Result<Box<dyn RowAccumulator>> {
        Ok(Box::new(BitAndRowAccumulator::new(
            start_index,
            self.data_type.clone(),
        )))
    }

    fn reverse_expr(&self) -> Option<Arc<dyn AggregateExpr>> {
        Some(Arc::new(self.clone()))
    }
}

impl PartialEq<dyn Any> for BitAnd {
    fn eq(&self, other: &dyn Any) -> bool {
        down_cast_any_ref(other)
            .downcast_ref::<Self>()
            .map(|x| {
                self.name == x.name
                    && self.data_type == x.data_type
                    && self.nullable == x.nullable
                    && self.expr.eq(&x.expr)
            })
            .unwrap_or(false)
    }
}

#[derive(Debug)]
struct BitAndAccumulator {
    bit_and: ScalarValue,
}

impl BitAndAccumulator {
    /// new bit_and accumulator
    pub fn try_new(data_type: &DataType) -> Result<Self> {
        Ok(Self {
            bit_and: ScalarValue::try_from(data_type)?,
        })
    }
}

impl Accumulator for BitAndAccumulator {
    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
        let values = &values[0];
        let delta = &bit_and_batch(values)?;
        self.bit_and = self.bit_and.bitand(delta)?;
        Ok(())
    }

    fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
        self.update_batch(states)
    }

    fn state(&self) -> Result<Vec<ScalarValue>> {
        Ok(vec![self.bit_and.clone()])
    }

    fn evaluate(&self) -> Result<ScalarValue> {
        Ok(self.bit_and.clone())
    }

    fn size(&self) -> usize {
        std::mem::size_of_val(self) - std::mem::size_of_val(&self.bit_and)
            + self.bit_and.size()
    }
}

#[derive(Debug)]
struct BitAndRowAccumulator {
    index: usize,
    datatype: DataType,
}

impl BitAndRowAccumulator {
    pub fn new(index: usize, datatype: DataType) -> Self {
        Self { index, datatype }
    }
}

impl RowAccumulator for BitAndRowAccumulator {
    fn update_batch(
        &mut self,
        values: &[ArrayRef],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        let values = &values[0];
        let delta = &bit_and_batch(values)?;
        bit_and_row(self.index, accessor, delta)
    }

    fn update_scalar_values(
        &mut self,
        values: &[ScalarValue],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        let value = &values[0];
        bit_and_row(self.index, accessor, value)
    }

    fn update_scalar(
        &mut self,
        value: &ScalarValue,
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        bit_and_row(self.index, accessor, value)
    }

    fn merge_batch(
        &mut self,
        states: &[ArrayRef],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        self.update_batch(states, accessor)
    }

    fn evaluate(&self, accessor: &RowAccessor) -> Result<ScalarValue> {
        Ok(accessor.get_as_scalar(&self.datatype, self.index))
    }

    #[inline(always)]
    fn state_index(&self) -> usize {
        self.index
    }
}

/// BIT_OR aggregate expression
#[derive(Debug, Clone)]
pub struct BitOr {
    name: String,
    pub data_type: DataType,
    expr: Arc<dyn PhysicalExpr>,
    nullable: bool,
}

impl BitOr {
    /// Create a new BIT_OR aggregate function
    pub fn new(
        expr: Arc<dyn PhysicalExpr>,
        name: impl Into<String>,
        data_type: DataType,
    ) -> Self {
        Self {
            name: name.into(),
            expr,
            data_type,
            nullable: true,
        }
    }
}

impl AggregateExpr for BitOr {
    /// Return a reference to Any that can be used for downcasting
    fn as_any(&self) -> &dyn Any {
        self
    }

    fn field(&self) -> Result<Field> {
        Ok(Field::new(
            &self.name,
            self.data_type.clone(),
            self.nullable,
        ))
    }

    fn create_accumulator(&self) -> Result<Box<dyn Accumulator>> {
        Ok(Box::new(BitOrAccumulator::try_new(&self.data_type)?))
    }

    fn state_fields(&self) -> Result<Vec<Field>> {
        Ok(vec![Field::new(
            format_state_name(&self.name, "bit_or"),
            self.data_type.clone(),
            self.nullable,
        )])
    }

    fn expressions(&self) -> Vec<Arc<dyn PhysicalExpr>> {
        vec![self.expr.clone()]
    }

    fn name(&self) -> &str {
        &self.name
    }

    fn row_accumulator_supported(&self) -> bool {
        is_row_accumulator_support_dtype(&self.data_type)
    }

    fn create_row_accumulator(
        &self,
        start_index: usize,
    ) -> Result<Box<dyn RowAccumulator>> {
        Ok(Box::new(BitOrRowAccumulator::new(
            start_index,
            self.data_type.clone(),
        )))
    }

    fn reverse_expr(&self) -> Option<Arc<dyn AggregateExpr>> {
        Some(Arc::new(self.clone()))
    }
}

impl PartialEq<dyn Any> for BitOr {
    fn eq(&self, other: &dyn Any) -> bool {
        down_cast_any_ref(other)
            .downcast_ref::<Self>()
            .map(|x| {
                self.name == x.name
                    && self.data_type == x.data_type
                    && self.nullable == x.nullable
                    && self.expr.eq(&x.expr)
            })
            .unwrap_or(false)
    }
}

#[derive(Debug)]
struct BitOrAccumulator {
    bit_or: ScalarValue,
}

impl BitOrAccumulator {
    /// new bit_or accumulator
    pub fn try_new(data_type: &DataType) -> Result<Self> {
        Ok(Self {
            bit_or: ScalarValue::try_from(data_type)?,
        })
    }
}

impl Accumulator for BitOrAccumulator {
    fn state(&self) -> Result<Vec<ScalarValue>> {
        Ok(vec![self.bit_or.clone()])
    }

    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
        let values = &values[0];
        let delta = &bit_or_batch(values)?;
        self.bit_or = self.bit_or.bitor(delta)?;
        Ok(())
    }

    fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
        self.update_batch(states)
    }

    fn evaluate(&self) -> Result<ScalarValue> {
        Ok(self.bit_or.clone())
    }

    fn size(&self) -> usize {
        std::mem::size_of_val(self) - std::mem::size_of_val(&self.bit_or)
            + self.bit_or.size()
    }
}

#[derive(Debug)]
struct BitOrRowAccumulator {
    index: usize,
    datatype: DataType,
}

impl BitOrRowAccumulator {
    pub fn new(index: usize, datatype: DataType) -> Self {
        Self { index, datatype }
    }
}

impl RowAccumulator for BitOrRowAccumulator {
    fn update_batch(
        &mut self,
        values: &[ArrayRef],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        let values = &values[0];
        let delta = &bit_or_batch(values)?;
        bit_or_row(self.index, accessor, delta)?;
        Ok(())
    }

    fn update_scalar_values(
        &mut self,
        values: &[ScalarValue],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        let value = &values[0];
        bit_or_row(self.index, accessor, value)
    }

    fn update_scalar(
        &mut self,
        value: &ScalarValue,
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        bit_or_row(self.index, accessor, value)
    }

    fn merge_batch(
        &mut self,
        states: &[ArrayRef],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        self.update_batch(states, accessor)
    }

    fn evaluate(&self, accessor: &RowAccessor) -> Result<ScalarValue> {
        Ok(accessor.get_as_scalar(&self.datatype, self.index))
    }

    #[inline(always)]
    fn state_index(&self) -> usize {
        self.index
    }
}

/// BIT_XOR aggregate expression
#[derive(Debug, Clone)]
pub struct BitXor {
    name: String,
    pub data_type: DataType,
    expr: Arc<dyn PhysicalExpr>,
    nullable: bool,
}

impl BitXor {
    /// Create a new BIT_XOR aggregate function
    pub fn new(
        expr: Arc<dyn PhysicalExpr>,
        name: impl Into<String>,
        data_type: DataType,
    ) -> Self {
        Self {
            name: name.into(),
            expr,
            data_type,
            nullable: true,
        }
    }
}

impl AggregateExpr for BitXor {
    /// Return a reference to Any that can be used for downcasting
    fn as_any(&self) -> &dyn Any {
        self
    }

    fn field(&self) -> Result<Field> {
        Ok(Field::new(
            &self.name,
            self.data_type.clone(),
            self.nullable,
        ))
    }

    fn create_accumulator(&self) -> Result<Box<dyn Accumulator>> {
        Ok(Box::new(BitXorAccumulator::try_new(&self.data_type)?))
    }

    fn state_fields(&self) -> Result<Vec<Field>> {
        Ok(vec![Field::new(
            format_state_name(&self.name, "bit_xor"),
            self.data_type.clone(),
            self.nullable,
        )])
    }

    fn expressions(&self) -> Vec<Arc<dyn PhysicalExpr>> {
        vec![self.expr.clone()]
    }

    fn name(&self) -> &str {
        &self.name
    }

    fn row_accumulator_supported(&self) -> bool {
        is_row_accumulator_support_dtype(&self.data_type)
    }

    fn create_row_accumulator(
        &self,
        start_index: usize,
    ) -> Result<Box<dyn RowAccumulator>> {
        Ok(Box::new(BitXorRowAccumulator::new(
            start_index,
            self.data_type.clone(),
        )))
    }

    fn reverse_expr(&self) -> Option<Arc<dyn AggregateExpr>> {
        Some(Arc::new(self.clone()))
    }
}

impl PartialEq<dyn Any> for BitXor {
    fn eq(&self, other: &dyn Any) -> bool {
        down_cast_any_ref(other)
            .downcast_ref::<Self>()
            .map(|x| {
                self.name == x.name
                    && self.data_type == x.data_type
                    && self.nullable == x.nullable
                    && self.expr.eq(&x.expr)
            })
            .unwrap_or(false)
    }
}

#[derive(Debug)]
struct BitXorAccumulator {
    bit_xor: ScalarValue,
}

impl BitXorAccumulator {
    /// new bit_xor accumulator
    pub fn try_new(data_type: &DataType) -> Result<Self> {
        Ok(Self {
            bit_xor: ScalarValue::try_from(data_type)?,
        })
    }
}

impl Accumulator for BitXorAccumulator {
    fn state(&self) -> Result<Vec<ScalarValue>> {
        Ok(vec![self.bit_xor.clone()])
    }

    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
        let values = &values[0];
        let delta = &bit_xor_batch(values)?;
        self.bit_xor = self.bit_xor.bitxor(delta)?;
        Ok(())
    }

    fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
        self.update_batch(states)
    }

    fn evaluate(&self) -> Result<ScalarValue> {
        Ok(self.bit_xor.clone())
    }

    fn size(&self) -> usize {
        std::mem::size_of_val(self) - std::mem::size_of_val(&self.bit_xor)
            + self.bit_xor.size()
    }
}

#[derive(Debug)]
struct BitXorRowAccumulator {
    index: usize,
    datatype: DataType,
}

impl BitXorRowAccumulator {
    pub fn new(index: usize, datatype: DataType) -> Self {
        Self { index, datatype }
    }
}

impl RowAccumulator for BitXorRowAccumulator {
    fn update_batch(
        &mut self,
        values: &[ArrayRef],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        let values = &values[0];
        let delta = &bit_xor_batch(values)?;
        bit_xor_row(self.index, accessor, delta)?;
        Ok(())
    }

    fn update_scalar_values(
        &mut self,
        values: &[ScalarValue],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        let value = &values[0];
        bit_xor_row(self.index, accessor, value)
    }

    fn update_scalar(
        &mut self,
        value: &ScalarValue,
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        bit_xor_row(self.index, accessor, value)
    }

    fn merge_batch(
        &mut self,
        states: &[ArrayRef],
        accessor: &mut RowAccessor,
    ) -> Result<()> {
        self.update_batch(states, accessor)
    }

    fn evaluate(&self, accessor: &RowAccessor) -> Result<ScalarValue> {
        Ok(accessor.get_as_scalar(&self.datatype, self.index))
    }

    #[inline(always)]
    fn state_index(&self) -> usize {
        self.index
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::expressions::col;
    use crate::expressions::tests::aggregate;
    use crate::generic_test_op;
    use arrow::datatypes::*;
    use arrow::record_batch::RecordBatch;
    use datafusion_common::Result;

    #[test]
    fn bit_and_i32() -> Result<()> {
        let a: ArrayRef = Arc::new(Int32Array::from(vec![4, 7, 15]));
        generic_test_op!(a, DataType::Int32, BitAnd, ScalarValue::from(4i32))
    }

    #[test]
    fn bit_and_i32_with_nulls() -> Result<()> {
        let a: ArrayRef =
            Arc::new(Int32Array::from(vec![Some(1), None, Some(3), Some(5)]));
        generic_test_op!(a, DataType::Int32, BitAnd, ScalarValue::from(1i32))
    }

    #[test]
    fn bit_and_i32_all_nulls() -> Result<()> {
        let a: ArrayRef = Arc::new(Int32Array::from(vec![None, None]));
        generic_test_op!(a, DataType::Int32, BitAnd, ScalarValue::Int32(None))
    }

    #[test]
    fn bit_and_u32() -> Result<()> {
        let a: ArrayRef = Arc::new(UInt32Array::from(vec![4_u32, 7_u32, 15_u32]));
        generic_test_op!(a, DataType::UInt32, BitAnd, ScalarValue::from(4u32))
    }

    #[test]
    fn bit_or_i32() -> Result<()> {
        let a: ArrayRef = Arc::new(Int32Array::from(vec![4, 7, 15]));
        generic_test_op!(a, DataType::Int32, BitOr, ScalarValue::from(15i32))
    }

    #[test]
    fn bit_or_i32_with_nulls() -> Result<()> {
        let a: ArrayRef =
            Arc::new(Int32Array::from(vec![Some(1), None, Some(3), Some(5)]));
        generic_test_op!(a, DataType::Int32, BitOr, ScalarValue::from(7i32))
    }

    #[test]
    fn bit_or_i32_all_nulls() -> Result<()> {
        let a: ArrayRef = Arc::new(Int32Array::from(vec![None, None]));
        generic_test_op!(a, DataType::Int32, BitOr, ScalarValue::Int32(None))
    }

    #[test]
    fn bit_or_u32() -> Result<()> {
        let a: ArrayRef = Arc::new(UInt32Array::from(vec![4_u32, 7_u32, 15_u32]));
        generic_test_op!(a, DataType::UInt32, BitOr, ScalarValue::from(15u32))
    }

    #[test]
    fn bit_xor_i32() -> Result<()> {
        let a: ArrayRef = Arc::new(Int32Array::from(vec![4, 7, 15]));
        generic_test_op!(a, DataType::Int32, BitXor, ScalarValue::from(12i32))
    }

    #[test]
    fn bit_xor_i32_with_nulls() -> Result<()> {
        let a: ArrayRef =
            Arc::new(Int32Array::from(vec![Some(1), None, Some(3), Some(5)]));
        generic_test_op!(a, DataType::Int32, BitXor, ScalarValue::from(7i32))
    }

    #[test]
    fn bit_xor_i32_all_nulls() -> Result<()> {
        let a: ArrayRef = Arc::new(Int32Array::from(vec![None, None]));
        generic_test_op!(a, DataType::Int32, BitXor, ScalarValue::Int32(None))
    }

    #[test]
    fn bit_xor_u32() -> Result<()> {
        let a: ArrayRef = Arc::new(UInt32Array::from(vec![4_u32, 7_u32, 15_u32]));
        generic_test_op!(a, DataType::UInt32, BitXor, ScalarValue::from(12u32))
    }
}