16935267080

Committed 13 Aug 2025 11:00AM UTC coverage: 24.312% (-63.3%) from 87.658%

Build # 16935267080

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Pull #4226

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Merge 81b48c7fb into baa6ea202

Pull Request Pull Request #4226: Support converting TimestampTZ to and from duckdb

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/vortex-array/src/compute/numeric.rs

// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright the Vortex contributors

use std::any::Any;
use std::sync::LazyLock;

use arcref::ArcRef;
use vortex_dtype::DType;
use vortex_error::{VortexError, VortexResult, vortex_bail, vortex_err};
use vortex_scalar::{NumericOperator, Scalar};

use crate::arrays::ConstantArray;
use crate::arrow::{Datum, from_arrow_array_with_len};
use crate::compute::{ComputeFn, ComputeFnVTable, InvocationArgs, Kernel, Options, Output};
use crate::vtable::VTable;
use crate::{Array, ArrayRef, IntoArray};

static NUMERIC_FN: LazyLock<ComputeFn> = LazyLock::new(|| {
    let compute = ComputeFn::new("numeric".into(), ArcRef::new_ref(&Numeric));
    for kernel in inventory::iter::<NumericKernelRef> {
        compute.register_kernel(kernel.0.clone());
    }
    compute
});

/// Point-wise add two numeric arrays.
///
/// Errs at runtime if the sum would overflow or underflow.
///
/// The result is null at any index that either input is null.
pub fn add(lhs: &dyn Array, rhs: &dyn Array) -> VortexResult<ArrayRef> {
    numeric(lhs, rhs, NumericOperator::Add)
}

/// Point-wise add a scalar value to this array on the right-hand-side.
pub fn add_scalar(lhs: &dyn Array, rhs: Scalar) -> VortexResult<ArrayRef> {
    numeric(
        lhs,
        &ConstantArray::new(rhs, lhs.len()).into_array(),
        NumericOperator::Add,
    )
}

/// Point-wise subtract two numeric arrays.
pub fn sub(lhs: &dyn Array, rhs: &dyn Array) -> VortexResult<ArrayRef> {
    numeric(lhs, rhs, NumericOperator::Sub)
}

/// Point-wise subtract a scalar value from this array on the right-hand-side.
pub fn sub_scalar(lhs: &dyn Array, rhs: Scalar) -> VortexResult<ArrayRef> {
    numeric(
        lhs,
        &ConstantArray::new(rhs, lhs.len()).into_array(),
        NumericOperator::Sub,
    )
}

/// Point-wise multiply two numeric arrays.
pub fn mul(lhs: &dyn Array, rhs: &dyn Array) -> VortexResult<ArrayRef> {
    numeric(lhs, rhs, NumericOperator::Mul)
}

/// Point-wise multiply a scalar value into this array on the right-hand-side.
pub fn mul_scalar(lhs: &dyn Array, rhs: Scalar) -> VortexResult<ArrayRef> {
    numeric(
        lhs,
        &ConstantArray::new(rhs, lhs.len()).into_array(),
        NumericOperator::Mul,
    )
}

/// Point-wise divide two numeric arrays.
pub fn div(lhs: &dyn Array, rhs: &dyn Array) -> VortexResult<ArrayRef> {
    numeric(lhs, rhs, NumericOperator::Div)
}

/// Point-wise divide a scalar value into this array on the right-hand-side.
pub fn div_scalar(lhs: &dyn Array, rhs: Scalar) -> VortexResult<ArrayRef> {
    numeric(
        lhs,
        &ConstantArray::new(rhs, lhs.len()).into_array(),
        NumericOperator::Mul,
    )
}

/// Point-wise numeric operation between two arrays of the same type and length.
pub fn numeric(lhs: &dyn Array, rhs: &dyn Array, op: NumericOperator) -> VortexResult<ArrayRef> {
    NUMERIC_FN
        .invoke(&InvocationArgs {
            inputs: &[lhs.into(), rhs.into()],
            options: &op,
        })?
        .unwrap_array()
}

pub struct NumericKernelRef(ArcRef<dyn Kernel>);
inventory::collect!(NumericKernelRef);

pub trait NumericKernel: VTable {
    fn numeric(
        &self,
        array: &Self::Array,
        other: &dyn Array,
        op: NumericOperator,
    ) -> VortexResult<Option<ArrayRef>>;
}

#[derive(Debug)]
pub struct NumericKernelAdapter<V: VTable>(pub V);

impl<V: VTable + NumericKernel> NumericKernelAdapter<V> {
    pub const fn lift(&'static self) -> NumericKernelRef {
        NumericKernelRef(ArcRef::new_ref(self))
    }
}

impl<V: VTable + NumericKernel> Kernel for NumericKernelAdapter<V> {
    fn invoke(&self, args: &InvocationArgs) -> VortexResult<Option<Output>> {
        let inputs = NumericArgs::try_from(args)?;
        let Some(lhs) = inputs.lhs.as_opt::<V>() else {
            return Ok(None);
        };
        Ok(V::numeric(&self.0, lhs, inputs.rhs, inputs.operator)?.map(|array| array.into()))
    }
}

struct Numeric;

impl ComputeFnVTable for Numeric {
    fn invoke(
        &self,
        args: &InvocationArgs,
        kernels: &[ArcRef<dyn Kernel>],
    ) -> VortexResult<Output> {
        let NumericArgs { lhs, rhs, operator } = NumericArgs::try_from(args)?;

        // Check if LHS supports the operation directly.
        for kernel in kernels {
            if let Some(output) = kernel.invoke(args)? {
                return Ok(output);
            }
        }
        if let Some(output) = lhs.invoke(&NUMERIC_FN, args)? {
            return Ok(output);
        }

        // Check if RHS supports the operation directly.
        let inverted_args = InvocationArgs {
            inputs: &[rhs.into(), lhs.into()],
            options: &operator.swap(),
        };
        for kernel in kernels {
            if let Some(output) = kernel.invoke(&inverted_args)? {
                return Ok(output);
            }
        }
        if let Some(output) = rhs.invoke(&NUMERIC_FN, &inverted_args)? {
            return Ok(output);
        }

        log::debug!(
            "No numeric implementation found for LHS {}, RHS {}, and operator {:?}",
            lhs.encoding_id(),
            rhs.encoding_id(),
            operator,
        );

        // If neither side implements the trait, then we delegate to Arrow compute.
        Ok(arrow_numeric(lhs, rhs, operator)?.into())
    }

    fn return_dtype(&self, args: &InvocationArgs) -> VortexResult<DType> {
        let NumericArgs { lhs, rhs, .. } = NumericArgs::try_from(args)?;
        if !matches!(
            (lhs.dtype(), rhs.dtype()),
            (DType::Primitive(..), DType::Primitive(..)) | (DType::Decimal(..), DType::Decimal(..))
        ) || !lhs.dtype().eq_ignore_nullability(rhs.dtype())
        {
            vortex_bail!(
                "Numeric operations are only supported on two arrays sharing the same numeric type: {} {}",
                lhs.dtype(),
                rhs.dtype()
            )
        }
        Ok(lhs.dtype().union_nullability(rhs.dtype().nullability()))
    }

    fn return_len(&self, args: &InvocationArgs) -> VortexResult<usize> {
        let NumericArgs { lhs, rhs, .. } = NumericArgs::try_from(args)?;
        if lhs.len() != rhs.len() {
            vortex_bail!(
                "Numeric operations aren't supported on arrays of different lengths {} {}",
                lhs.len(),
                rhs.len()
            )
        }
        Ok(lhs.len())
    }

    fn is_elementwise(&self) -> bool {
        true
    }
}

struct NumericArgs<'a> {
    lhs: &'a dyn Array,
    rhs: &'a dyn Array,
    operator: NumericOperator,
}

impl<'a> TryFrom<&InvocationArgs<'a>> for NumericArgs<'a> {
    type Error = VortexError;

    fn try_from(args: &InvocationArgs<'a>) -> VortexResult<Self> {
        if args.inputs.len() != 2 {
            vortex_bail!("Numeric operations require exactly 2 inputs");
        }
        let lhs = args.inputs[0]
            .array()
            .ok_or_else(|| vortex_err!("LHS is not an array"))?;
        let rhs = args.inputs[1]
            .array()
            .ok_or_else(|| vortex_err!("RHS is not an array"))?;
        let operator = *args
            .options
            .as_any()
            .downcast_ref::<NumericOperator>()
            .ok_or_else(|| vortex_err!("Operator is not a numeric operator"))?;
        Ok(Self { lhs, rhs, operator })
    }
}

impl Options for NumericOperator {
    fn as_any(&self) -> &dyn Any {
        self
    }
}

/// Implementation of `BinaryNumericFn` using the Arrow crate.
///
/// Note that other encodings should handle a constant RHS value, so we can assume here that
/// the RHS is not constant and expand to a full array.
fn arrow_numeric(
    lhs: &dyn Array,
    rhs: &dyn Array,
    operator: NumericOperator,
) -> VortexResult<ArrayRef> {
    let nullable = lhs.dtype().is_nullable() || rhs.dtype().is_nullable();
    let len = lhs.len();

    let left = Datum::try_new(lhs)?;
    let right = Datum::try_new(rhs)?;

    let array = match operator {
        NumericOperator::Add => arrow_arith::numeric::add(&left, &right)?,
        NumericOperator::Sub => arrow_arith::numeric::sub(&left, &right)?,
        NumericOperator::RSub => arrow_arith::numeric::sub(&right, &left)?,
        NumericOperator::Mul => arrow_arith::numeric::mul(&left, &right)?,
        NumericOperator::Div => arrow_arith::numeric::div(&left, &right)?,
        NumericOperator::RDiv => arrow_arith::numeric::div(&right, &left)?,
    };

    from_arrow_array_with_len(array.as_ref(), len, nullable)
}

#[cfg(test)]
mod test {
    use vortex_buffer::buffer;
    use vortex_scalar::Scalar;

    use crate::IntoArray;
    use crate::arrays::PrimitiveArray;
    use crate::canonical::ToCanonical;
    use crate::compute::sub_scalar;

    #[test]
    fn test_scalar_subtract_unsigned() {
        let values = buffer![1u16, 2, 3].into_array();
        let results = sub_scalar(&values, 1u16.into())
            .unwrap()
            .to_primitive()
            .unwrap()
            .as_slice::<u16>()
            .to_vec();
        assert_eq!(results, &[0u16, 1, 2]);
    }

    #[test]
    fn test_scalar_subtract_signed() {
        let values = buffer![1i64, 2, 3].into_array();
        let results = sub_scalar(&values, (-1i64).into())
            .unwrap()
            .to_primitive()
            .unwrap()
            .as_slice::<i64>()
            .to_vec();
        assert_eq!(results, &[2i64, 3, 4]);
    }

    #[test]
    fn test_scalar_subtract_nullable() {
        let values = PrimitiveArray::from_option_iter([Some(1u16), Some(2), None, Some(3)]);
        let result = sub_scalar(values.as_ref(), Some(1u16).into())
            .unwrap()
            .to_primitive()
            .unwrap();

        let actual = (0..result.len())
            .map(|index| result.scalar_at(index).unwrap())
            .collect::<Vec<_>>();
        assert_eq!(
            actual,
            vec![
                Scalar::from(Some(0u16)),
                Scalar::from(Some(1u16)),
                Scalar::from(None::<u16>),
                Scalar::from(Some(2u16))
            ]
        );
    }

    #[test]
    fn test_scalar_subtract_float() {
        let values = buffer![1.0f64, 2.0, 3.0].into_array();
        let to_subtract = -1f64;
        let results = sub_scalar(&values, to_subtract.into())
            .unwrap()
            .to_primitive()
            .unwrap()
            .as_slice::<f64>()
            .to_vec();
        assert_eq!(results, &[2.0f64, 3.0, 4.0]);
    }

    #[test]
    fn test_scalar_subtract_float_underflow_is_ok() {
        let values = buffer![f32::MIN, 2.0, 3.0].into_array();
        let _results = sub_scalar(&values, 1.0f32.into()).unwrap();
        let _results = sub_scalar(&values, f32::MAX.into()).unwrap();
    }

    #[test]
    fn test_scalar_subtract_type_mismatch_fails() {
        let values = buffer![1u64, 2, 3].into_array();
        // Subtracting incompatible dtypes should fail
        let _results =
            sub_scalar(&values, 1.5f64.into()).expect_err("Expected type mismatch error");
    }
}

1	// SPDX-License-Identifier: Apache-2.0
2	// SPDX-FileCopyrightText: Copyright the Vortex contributors
3
4	use std::any::Any;
5	use std::sync::LazyLock;
6
7	use arcref::ArcRef;
8	use vortex_dtype::DType;
9	use vortex_error::{VortexError, VortexResult, vortex_bail, vortex_err};
10	use vortex_scalar::{NumericOperator, Scalar};
11
12	use crate::arrays::ConstantArray;
13	use crate::arrow::{Datum, from_arrow_array_with_len};
14	use crate::compute::{ComputeFn, ComputeFnVTable, InvocationArgs, Kernel, Options, Output};
15	use crate::vtable::VTable;
16	use crate::{Array, ArrayRef, IntoArray};
17
UNCOV 18	static NUMERIC_FN: LazyLock<ComputeFn> = LazyLock::new(\|\| {	×
UNCOV 19	let compute = ComputeFn::new("numeric".into(), ArcRef::new_ref(&Numeric));	×
UNCOV 20	for kernel in inventory::iter::<NumericKernelRef> {	×
UNCOV 21	compute.register_kernel(kernel.0.clone());	×
UNCOV 22	}	×
UNCOV 23	compute	×
UNCOV 24	});	×
25
26	/// Point-wise add two numeric arrays.
27	///
28	/// Errs at runtime if the sum would overflow or underflow.
29	///
30	/// The result is null at any index that either input is null.
31	pub fn add(lhs: &dyn Array, rhs: &dyn Array) -> VortexResult<ArrayRef> {	×
32	numeric(lhs, rhs, NumericOperator::Add)	×
33	}	×
34
35	/// Point-wise add a scalar value to this array on the right-hand-side.
UNCOV 36	pub fn add_scalar(lhs: &dyn Array, rhs: Scalar) -> VortexResult<ArrayRef> {	×
UNCOV 37	numeric(	×
UNCOV 38	lhs,	×
UNCOV 39	&ConstantArray::new(rhs, lhs.len()).into_array(),	×
UNCOV 40	NumericOperator::Add,	×
41	)
UNCOV 42	}	×
43
44	/// Point-wise subtract two numeric arrays.
45	pub fn sub(lhs: &dyn Array, rhs: &dyn Array) -> VortexResult<ArrayRef> {	×
46	numeric(lhs, rhs, NumericOperator::Sub)	×
47	}	×
48
49	/// Point-wise subtract a scalar value from this array on the right-hand-side.
UNCOV 50	pub fn sub_scalar(lhs: &dyn Array, rhs: Scalar) -> VortexResult<ArrayRef> {	×
UNCOV 51	numeric(	×
UNCOV 52	lhs,	×
UNCOV 53	&ConstantArray::new(rhs, lhs.len()).into_array(),	×
UNCOV 54	NumericOperator::Sub,	×
55	)
UNCOV 56	}	×
57
58	/// Point-wise multiply two numeric arrays.
59	pub fn mul(lhs: &dyn Array, rhs: &dyn Array) -> VortexResult<ArrayRef> {	×
60	numeric(lhs, rhs, NumericOperator::Mul)	×
61	}	×
62
63	/// Point-wise multiply a scalar value into this array on the right-hand-side.
64	pub fn mul_scalar(lhs: &dyn Array, rhs: Scalar) -> VortexResult<ArrayRef> {	×
65	numeric(	×
66	lhs,	×
67	&ConstantArray::new(rhs, lhs.len()).into_array(),	×
68	NumericOperator::Mul,	×
69	)
70	}	×
71
72	/// Point-wise divide two numeric arrays.
73	pub fn div(lhs: &dyn Array, rhs: &dyn Array) -> VortexResult<ArrayRef> {	×
74	numeric(lhs, rhs, NumericOperator::Div)	×
75	}	×
76
77	/// Point-wise divide a scalar value into this array on the right-hand-side.
78	pub fn div_scalar(lhs: &dyn Array, rhs: Scalar) -> VortexResult<ArrayRef> {	×
79	numeric(	×
80	lhs,	×
81	&ConstantArray::new(rhs, lhs.len()).into_array(),	×
82	NumericOperator::Mul,	×
83	)
84	}	×
85
86	/// Point-wise numeric operation between two arrays of the same type and length.
UNCOV 87	pub fn numeric(lhs: &dyn Array, rhs: &dyn Array, op: NumericOperator) -> VortexResult<ArrayRef> {	×
UNCOV 88	NUMERIC_FN	×
UNCOV 89	.invoke(&InvocationArgs {	×
UNCOV 90	inputs: &[lhs.into(), rhs.into()],	×
UNCOV 91	options: &op,	×
UNCOV 92	})?	×
UNCOV 93	.unwrap_array()	×
UNCOV 94	}	×
95
96	pub struct NumericKernelRef(ArcRef<dyn Kernel>);
97	inventory::collect!(NumericKernelRef);
98
99	pub trait NumericKernel: VTable {
100	fn numeric(
101	&self,
102	array: &Self::Array,
103	other: &dyn Array,
104	op: NumericOperator,
105	) -> VortexResult<Option<ArrayRef>>;
106	}
107
108	#[derive(Debug)]
109	pub struct NumericKernelAdapter<V: VTable>(pub V);
110
111	impl<V: VTable + NumericKernel> NumericKernelAdapter<V> {
112	pub const fn lift(&'static self) -> NumericKernelRef {	×
113	NumericKernelRef(ArcRef::new_ref(self))	×
114	}	×
115	}
116
117	impl<V: VTable + NumericKernel> Kernel for NumericKernelAdapter<V> {
UNCOV 118	fn invoke(&self, args: &InvocationArgs) -> VortexResult<Option<Output>> {	×
UNCOV 119	let inputs = NumericArgs::try_from(args)?;	×
UNCOV 120	let Some(lhs) = inputs.lhs.as_opt::<V>() else {	×
UNCOV 121	return Ok(None);	×
122	};
UNCOV 123	Ok(V::numeric(&self.0, lhs, inputs.rhs, inputs.operator)?.map(\|array\| array.into()))	×
UNCOV 124	}	×
125	}
126
127	struct Numeric;
128
129	impl ComputeFnVTable for Numeric {
UNCOV 130	fn invoke(	×
UNCOV 131	&self,	×
UNCOV 132	args: &InvocationArgs,	×
UNCOV 133	kernels: &[ArcRef<dyn Kernel>],	×
UNCOV 134	) -> VortexResult<Output> {	×
UNCOV 135	let NumericArgs { lhs, rhs, operator } = NumericArgs::try_from(args)?;	×
136
137	// Check if LHS supports the operation directly.
UNCOV 138	for kernel in kernels {	×
UNCOV 139	if let Some(output) = kernel.invoke(args)? {	×
UNCOV 140	return Ok(output);	×
UNCOV 141	}	×
142	}
UNCOV 143	if let Some(output) = lhs.invoke(&NUMERIC_FN, args)? {	×
UNCOV 144	return Ok(output);	×
UNCOV 145	}	×
146
147	// Check if RHS supports the operation directly.
UNCOV 148	let inverted_args = InvocationArgs {	×
UNCOV 149	inputs: &[rhs.into(), lhs.into()],	×
UNCOV 150	options: &operator.swap(),	×
UNCOV 151	};	×
UNCOV 152	for kernel in kernels {	×
UNCOV 153	if let Some(output) = kernel.invoke(&inverted_args)? {	×
UNCOV 154	return Ok(output);	×
UNCOV 155	}	×
156	}
UNCOV 157	if let Some(output) = rhs.invoke(&NUMERIC_FN, &inverted_args)? {	×
UNCOV 158	return Ok(output);	×
UNCOV 159	}	×
160
UNCOV 161	log::debug!(	×
162	"No numeric implementation found for LHS {}, RHS {}, and operator {:?}",	×
163	lhs.encoding_id(),	×
164	rhs.encoding_id(),	×
165	operator,
166	);
167
168	// If neither side implements the trait, then we delegate to Arrow compute.
UNCOV 169	Ok(arrow_numeric(lhs, rhs, operator)?.into())	×
UNCOV 170	}	×
171
UNCOV 172	fn return_dtype(&self, args: &InvocationArgs) -> VortexResult<DType> {	×
UNCOV 173	let NumericArgs { lhs, rhs, .. } = NumericArgs::try_from(args)?;	×
174	if !matches!(	×
UNCOV 175	(lhs.dtype(), rhs.dtype()),	×
176	(DType::Primitive(..), DType::Primitive(..)) \| (DType::Decimal(..), DType::Decimal(..))
UNCOV 177	) \|\| !lhs.dtype().eq_ignore_nullability(rhs.dtype())	×
178	{
UNCOV 179	vortex_bail!(	×
UNCOV 180	"Numeric operations are only supported on two arrays sharing the same numeric type: {} {}",	×
UNCOV 181	lhs.dtype(),	×
UNCOV 182	rhs.dtype()	×
183	)
UNCOV 184	}	×
UNCOV 185	Ok(lhs.dtype().union_nullability(rhs.dtype().nullability()))	×
UNCOV 186	}	×
187
UNCOV 188	fn return_len(&self, args: &InvocationArgs) -> VortexResult<usize> {	×
UNCOV 189	let NumericArgs { lhs, rhs, .. } = NumericArgs::try_from(args)?;	×
UNCOV 190	if lhs.len() != rhs.len() {	×
191	vortex_bail!(	×
192	"Numeric operations aren't supported on arrays of different lengths {} {}",	×
193	lhs.len(),	×
194	rhs.len()	×
195	)
UNCOV 196	}	×
UNCOV 197	Ok(lhs.len())	×
UNCOV 198	}	×
199
UNCOV 200	fn is_elementwise(&self) -> bool {	×
UNCOV 201	true	×
UNCOV 202	}	×
203	}
204
205	struct NumericArgs<'a> {
206	lhs: &'a dyn Array,
207	rhs: &'a dyn Array,
208	operator: NumericOperator,
209	}
210
211	impl<'a> TryFrom<&InvocationArgs<'a>> for NumericArgs<'a> {
212	type Error = VortexError;
213
UNCOV 214	fn try_from(args: &InvocationArgs<'a>) -> VortexResult<Self> {	×
UNCOV 215	if args.inputs.len() != 2 {	×
216	vortex_bail!("Numeric operations require exactly 2 inputs");	×
UNCOV 217	}	×
UNCOV 218	let lhs = args.inputs[0]	×
UNCOV 219	.array()	×
UNCOV 220	.ok_or_else(\|\| vortex_err!("LHS is not an array"))?;	×
UNCOV 221	let rhs = args.inputs[1]	×
UNCOV 222	.array()	×
UNCOV 223	.ok_or_else(\|\| vortex_err!("RHS is not an array"))?;	×
UNCOV 224	let operator = *args	×
UNCOV 225	.options	×
UNCOV 226	.as_any()	×
UNCOV 227	.downcast_ref::<NumericOperator>()	×
UNCOV 228	.ok_or_else(\|\| vortex_err!("Operator is not a numeric operator"))?;	×
UNCOV 229	Ok(Self { lhs, rhs, operator })	×
UNCOV 230	}	×
231	}
232
233	impl Options for NumericOperator {
UNCOV 234	fn as_any(&self) -> &dyn Any {	×
UNCOV 235	self	×
UNCOV 236	}	×
237	}
238
239	/// Implementation of `BinaryNumericFn` using the Arrow crate.
240	///
241	/// Note that other encodings should handle a constant RHS value, so we can assume here that
242	/// the RHS is not constant and expand to a full array.
UNCOV 243	fn arrow_numeric(	×
UNCOV 244	lhs: &dyn Array,	×
UNCOV 245	rhs: &dyn Array,	×
UNCOV 246	operator: NumericOperator,	×
UNCOV 247	) -> VortexResult<ArrayRef> {	×
UNCOV 248	let nullable = lhs.dtype().is_nullable() \|\| rhs.dtype().is_nullable();	×
UNCOV 249	let len = lhs.len();	×
250
UNCOV 251	let left = Datum::try_new(lhs)?;	×
UNCOV 252	let right = Datum::try_new(rhs)?;	×
253
UNCOV 254	let array = match operator {	×
UNCOV 255	NumericOperator::Add => arrow_arith::numeric::add(&left, &right)?,	×
UNCOV 256	NumericOperator::Sub => arrow_arith::numeric::sub(&left, &right)?,	×
UNCOV 257	NumericOperator::RSub => arrow_arith::numeric::sub(&right, &left)?,	×
UNCOV 258	NumericOperator::Mul => arrow_arith::numeric::mul(&left, &right)?,	×
UNCOV 259	NumericOperator::Div => arrow_arith::numeric::div(&left, &right)?,	×
UNCOV 260	NumericOperator::RDiv => arrow_arith::numeric::div(&right, &left)?,	×
261	};
262
UNCOV 263	from_arrow_array_with_len(array.as_ref(), len, nullable)	×
UNCOV 264	}	×
265
266	#[cfg(test)]
267	mod test {
268	use vortex_buffer::buffer;
269	use vortex_scalar::Scalar;
270
271	use crate::IntoArray;
272	use crate::arrays::PrimitiveArray;
273	use crate::canonical::ToCanonical;
274	use crate::compute::sub_scalar;
275
276	#[test]
277	fn test_scalar_subtract_unsigned() {
278	let values = buffer![1u16, 2, 3].into_array();
279	let results = sub_scalar(&values, 1u16.into())
280	.unwrap()
281	.to_primitive()
282	.unwrap()
283	.as_slice::<u16>()
284	.to_vec();
285	assert_eq!(results, &[0u16, 1, 2]);
286	}
287
288	#[test]
289	fn test_scalar_subtract_signed() {
290	let values = buffer![1i64, 2, 3].into_array();
291	let results = sub_scalar(&values, (-1i64).into())
292	.unwrap()
293	.to_primitive()
294	.unwrap()
295	.as_slice::<i64>()
296	.to_vec();
297	assert_eq!(results, &[2i64, 3, 4]);
298	}
299
300	#[test]
301	fn test_scalar_subtract_nullable() {
302	let values = PrimitiveArray::from_option_iter([Some(1u16), Some(2), None, Some(3)]);
303	let result = sub_scalar(values.as_ref(), Some(1u16).into())
304	.unwrap()
305	.to_primitive()
306	.unwrap();
307
308	let actual = (0..result.len())
309	.map(\|index\| result.scalar_at(index).unwrap())
310	.collect::<Vec<_>>();
311	assert_eq!(
312	actual,
313	vec![
314	Scalar::from(Some(0u16)),
315	Scalar::from(Some(1u16)),
316	Scalar::from(None::<u16>),
317	Scalar::from(Some(2u16))
318	]
319	);
320	}
321
322	#[test]
323	fn test_scalar_subtract_float() {
324	let values = buffer![1.0f64, 2.0, 3.0].into_array();
325	let to_subtract = -1f64;
326	let results = sub_scalar(&values, to_subtract.into())
327	.unwrap()
328	.to_primitive()
329	.unwrap()
330	.as_slice::<f64>()
331	.to_vec();
332	assert_eq!(results, &[2.0f64, 3.0, 4.0]);
333	}
334
335	#[test]
336	fn test_scalar_subtract_float_underflow_is_ok() {
337	let values = buffer![f32::MIN, 2.0, 3.0].into_array();
338	let _results = sub_scalar(&values, 1.0f32.into()).unwrap();
339	let _results = sub_scalar(&values, f32::MAX.into()).unwrap();
340	}
341
342	#[test]
343	fn test_scalar_subtract_type_mismatch_fails() {
344	let values = buffer![1u64, 2, 3].into_array();
345	// Subtracting incompatible dtypes should fail
346	let _results =
347	sub_scalar(&values, 1.5f64.into()).expect_err("Expected type mismatch error");
348	}
349	}

vortex-data / vortex / 16935267080

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