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// 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 basic arithmetic kernels for `PrimitiveArrays`.
//!
//! These kernels can leverage SIMD if available on your system. Currently no runtime
//! detection is provided, you should enable the specific SIMD intrinsics using
//! `RUSTFLAGS="-C target-feature=+avx2"` for example. See the documentation
//! [here](https://doc.rust-lang.org/stable/core/arch/) for more information.
use crate::arity::*;
use arrow_array::types::*;
use arrow_array::*;
use arrow_buffer::i256;
use arrow_buffer::ArrowNativeType;
use arrow_schema::*;
use std::cmp::min;
use std::sync::Arc;
/// Returns the precision and scale of the result of a multiplication of two decimal types,
/// and the divisor for fixed point multiplication.
fn get_fixed_point_info(
left: (u8, i8),
right: (u8, i8),
required_scale: i8,
) -> Result<(u8, i8, i256), ArrowError> {
let product_scale = left.1 + right.1;
let precision = min(left.0 + right.0 + 1, DECIMAL128_MAX_PRECISION);
if required_scale > product_scale {
return Err(ArrowError::ComputeError(format!(
"Required scale {} is greater than product scale {}",
required_scale, product_scale
)));
}
let divisor = i256::from_i128(10).pow_wrapping((product_scale - required_scale) as u32);
Ok((precision, product_scale, divisor))
}
/// Perform `left * right` operation on two decimal arrays. If either left or right value is
/// null then the result is also null.
///
/// This performs decimal multiplication which allows precision loss if an exact representation
/// is not possible for the result, according to the required scale. In the case, the result
/// will be rounded to the required scale.
///
/// If the required scale is greater than the product scale, an error is returned.
///
/// This doesn't detect overflow. Once overflowing, the result will wrap around.
///
/// It is implemented for compatibility with precision loss `multiply` function provided by
/// other data processing engines. For multiplication with precision loss detection, use
/// `multiply_dyn` or `multiply_dyn_checked` instead.
pub fn multiply_fixed_point_dyn(
left: &dyn Array,
right: &dyn Array,
required_scale: i8,
) -> Result<ArrayRef, ArrowError> {
match (left.data_type(), right.data_type()) {
(DataType::Decimal128(_, _), DataType::Decimal128(_, _)) => {
let left = left.as_any().downcast_ref::<Decimal128Array>().unwrap();
let right = right.as_any().downcast_ref::<Decimal128Array>().unwrap();
multiply_fixed_point(left, right, required_scale).map(|a| Arc::new(a) as ArrayRef)
}
(_, _) => Err(ArrowError::CastError(format!(
"Unsupported data type {}, {}",
left.data_type(),
right.data_type()
))),
}
}
/// Perform `left * right` operation on two decimal arrays. If either left or right value is
/// null then the result is also null.
///
/// This performs decimal multiplication which allows precision loss if an exact representation
/// is not possible for the result, according to the required scale. In the case, the result
/// will be rounded to the required scale.
///
/// If the required scale is greater than the product scale, an error is returned.
///
/// It is implemented for compatibility with precision loss `multiply` function provided by
/// other data processing engines. For multiplication with precision loss detection, use
/// `multiply` or `multiply_checked` instead.
pub fn multiply_fixed_point_checked(
left: &PrimitiveArray<Decimal128Type>,
right: &PrimitiveArray<Decimal128Type>,
required_scale: i8,
) -> Result<PrimitiveArray<Decimal128Type>, ArrowError> {
let (precision, product_scale, divisor) = get_fixed_point_info(
(left.precision(), left.scale()),
(right.precision(), right.scale()),
required_scale,
)?;
if required_scale == product_scale {
return try_binary::<_, _, _, Decimal128Type>(left, right, |a, b| a.mul_checked(b))?
.with_precision_and_scale(precision, required_scale);
}
try_binary::<_, _, _, Decimal128Type>(left, right, |a, b| {
let a = i256::from_i128(a);
let b = i256::from_i128(b);
let mut mul = a.wrapping_mul(b);
mul = divide_and_round::<Decimal256Type>(mul, divisor);
mul.to_i128().ok_or_else(|| {
ArrowError::ArithmeticOverflow(format!("Overflow happened on: {:?} * {:?}", a, b))
})
})
.and_then(|a| a.with_precision_and_scale(precision, required_scale))
}
/// Perform `left * right` operation on two decimal arrays. If either left or right value is
/// null then the result is also null.
///
/// This performs decimal multiplication which allows precision loss if an exact representation
/// is not possible for the result, according to the required scale. In the case, the result
/// will be rounded to the required scale.
///
/// If the required scale is greater than the product scale, an error is returned.
///
/// This doesn't detect overflow. Once overflowing, the result will wrap around.
/// For an overflow-checking variant, use `multiply_fixed_point_checked` instead.
///
/// It is implemented for compatibility with precision loss `multiply` function provided by
/// other data processing engines. For multiplication with precision loss detection, use
/// `multiply` or `multiply_checked` instead.
pub fn multiply_fixed_point(
left: &PrimitiveArray<Decimal128Type>,
right: &PrimitiveArray<Decimal128Type>,
required_scale: i8,
) -> Result<PrimitiveArray<Decimal128Type>, ArrowError> {
let (precision, product_scale, divisor) = get_fixed_point_info(
(left.precision(), left.scale()),
(right.precision(), right.scale()),
required_scale,
)?;
if required_scale == product_scale {
return binary(left, right, |a, b| a.mul_wrapping(b))?
.with_precision_and_scale(precision, required_scale);
}
binary::<_, _, _, Decimal128Type>(left, right, |a, b| {
let a = i256::from_i128(a);
let b = i256::from_i128(b);
let mut mul = a.wrapping_mul(b);
mul = divide_and_round::<Decimal256Type>(mul, divisor);
mul.as_i128()
})
.and_then(|a| a.with_precision_and_scale(precision, required_scale))
}
/// Divide a decimal native value by given divisor and round the result.
fn divide_and_round<I>(input: I::Native, div: I::Native) -> I::Native
where
I: DecimalType,
I::Native: ArrowNativeTypeOp,
{
let d = input.div_wrapping(div);
let r = input.mod_wrapping(div);
let half = div.div_wrapping(I::Native::from_usize(2).unwrap());
let half_neg = half.neg_wrapping();
// Round result
match input >= I::Native::ZERO {
true if r >= half => d.add_wrapping(I::Native::ONE),
false if r <= half_neg => d.sub_wrapping(I::Native::ONE),
_ => d,
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::numeric::mul;
#[test]
fn test_decimal_multiply_allow_precision_loss() {
// Overflow happening as i128 cannot hold multiplying result.
// [123456789]
let a = Decimal128Array::from(vec![123456789000000000000000000])
.with_precision_and_scale(38, 18)
.unwrap();
// [10]
let b = Decimal128Array::from(vec![10000000000000000000])
.with_precision_and_scale(38, 18)
.unwrap();
let err = mul(&a, &b).unwrap_err();
assert!(err
.to_string()
.contains("Overflow happened on: 123456789000000000000000000 * 10000000000000000000"));
// Allow precision loss.
let result = multiply_fixed_point_checked(&a, &b, 28).unwrap();
// [1234567890]
let expected = Decimal128Array::from(vec![12345678900000000000000000000000000000])
.with_precision_and_scale(38, 28)
.unwrap();
assert_eq!(&expected, &result);
assert_eq!(
result.value_as_string(0),
"1234567890.0000000000000000000000000000"
);
// Rounding case
// [0.000000000000000001, 123456789.555555555555555555, 1.555555555555555555]
let a = Decimal128Array::from(vec![1, 123456789555555555555555555, 1555555555555555555])
.with_precision_and_scale(38, 18)
.unwrap();
// [1.555555555555555555, 11.222222222222222222, 0.000000000000000001]
let b = Decimal128Array::from(vec![1555555555555555555, 11222222222222222222, 1])
.with_precision_and_scale(38, 18)
.unwrap();
let result = multiply_fixed_point_checked(&a, &b, 28).unwrap();
// [
// 0.0000000000000000015555555556,
// 1385459527.2345679012071330528765432099,
// 0.0000000000000000015555555556
// ]
let expected = Decimal128Array::from(vec![
15555555556,
13854595272345679012071330528765432099,
15555555556,
])
.with_precision_and_scale(38, 28)
.unwrap();
assert_eq!(&expected, &result);
// Rounded the value "1385459527.234567901207133052876543209876543210".
assert_eq!(
result.value_as_string(1),
"1385459527.2345679012071330528765432099"
);
assert_eq!(result.value_as_string(0), "0.0000000000000000015555555556");
assert_eq!(result.value_as_string(2), "0.0000000000000000015555555556");
let a = Decimal128Array::from(vec![1230])
.with_precision_and_scale(4, 2)
.unwrap();
let b = Decimal128Array::from(vec![1000])
.with_precision_and_scale(4, 2)
.unwrap();
// Required scale is same as the product of the input scales. Behavior is same as multiply.
let result = multiply_fixed_point_checked(&a, &b, 4).unwrap();
assert_eq!(result.precision(), 9);
assert_eq!(result.scale(), 4);
let expected = mul(&a, &b).unwrap();
assert_eq!(expected.as_ref(), &result);
// Required scale cannot be larger than the product of the input scales.
let result = multiply_fixed_point_checked(&a, &b, 5).unwrap_err();
assert!(result
.to_string()
.contains("Required scale 5 is greater than product scale 4"));
}
#[test]
fn test_decimal_multiply_allow_precision_loss_overflow() {
// [99999999999123456789]
let a = Decimal128Array::from(vec![99999999999123456789000000000000000000])
.with_precision_and_scale(38, 18)
.unwrap();
// [9999999999910]
let b = Decimal128Array::from(vec![9999999999910000000000000000000])
.with_precision_and_scale(38, 18)
.unwrap();
let err = multiply_fixed_point_checked(&a, &b, 28).unwrap_err();
assert!(err.to_string().contains(
"Overflow happened on: 99999999999123456789000000000000000000 * 9999999999910000000000000000000"
));
let result = multiply_fixed_point(&a, &b, 28).unwrap();
let expected = Decimal128Array::from(vec![62946009661555981610246871926660136960])
.with_precision_and_scale(38, 28)
.unwrap();
assert_eq!(&expected, &result);
}
#[test]
fn test_decimal_multiply_fixed_point() {
// [123456789]
let a = Decimal128Array::from(vec![123456789000000000000000000])
.with_precision_and_scale(38, 18)
.unwrap();
// [10]
let b = Decimal128Array::from(vec![10000000000000000000])
.with_precision_and_scale(38, 18)
.unwrap();
// `multiply` overflows on this case.
let err = mul(&a, &b).unwrap_err();
assert_eq!(err.to_string(), "Arithmetic overflow: Overflow happened on: 123456789000000000000000000 * 10000000000000000000");
// Avoid overflow by reducing the scale.
let result = multiply_fixed_point(&a, &b, 28).unwrap();
// [1234567890]
let expected = Decimal128Array::from(vec![12345678900000000000000000000000000000])
.with_precision_and_scale(38, 28)
.unwrap();
assert_eq!(&expected, &result);
assert_eq!(
result.value_as_string(0),
"1234567890.0000000000000000000000000000"
);
}
}