vortex_array/compute/
numeric.rs

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

vortex_array/compute/
numeric.rs
