1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
use std::ops::Add;

use multiversion::multiversion;

use crate::bitmap::utils::{BitChunkIterExact, BitChunksExact};
use crate::datatypes::{DataType, IntervalUnit};
use crate::error::{ArrowError, Result};
use crate::scalar::*;
use crate::types::simd::*;
use crate::types::NativeType;
use crate::{
    array::{Array, PrimitiveArray},
    bitmap::Bitmap,
};

/// Object that can reduce itself to a number. This is used in the context of SIMD to reduce
/// a MD (e.g. `[f32; 16]`) into a single number (`f32`).
pub trait Sum<T> {
    fn simd_sum(self) -> T;
}

#[multiversion]
#[clone(target = "x86_64+avx")]
fn nonnull_sum<T>(values: &[T]) -> T
where
    T: NativeType + Simd,
    T::Simd: Add<Output = T::Simd> + Sum<T>,
{
    let mut chunks = values.chunks_exact(T::Simd::LANES);

    let sum = chunks.by_ref().fold(T::Simd::default(), |acc, chunk| {
        acc + T::Simd::from_chunk(chunk)
    });

    let remainder = T::Simd::from_incomplete_chunk(chunks.remainder(), T::default());
    let reduced = sum + remainder;

    reduced.simd_sum()
}

/// # Panics
/// iff `values.len() != bitmap.len()` or the operation overflows.
#[multiversion]
#[clone(target = "x86_64+avx")]
fn null_sum_impl<T, I>(values: &[T], mut validity_masks: I) -> T
where
    T: NativeType + Simd,
    T::Simd: Add<Output = T::Simd> + Sum<T>,
    I: BitChunkIterExact<<<T as Simd>::Simd as NativeSimd>::Chunk>,
{
    let mut chunks = values.chunks_exact(T::Simd::LANES);

    let sum = chunks.by_ref().zip(validity_masks.by_ref()).fold(
        T::Simd::default(),
        |acc, (chunk, validity_chunk)| {
            let chunk = T::Simd::from_chunk(chunk);
            let mask = <T::Simd as NativeSimd>::Mask::from_chunk(validity_chunk);
            let selected = chunk.select(mask, T::Simd::default());
            acc + selected
        },
    );

    let remainder = T::Simd::from_incomplete_chunk(chunks.remainder(), T::default());
    let mask = <T::Simd as NativeSimd>::Mask::from_chunk(validity_masks.remainder());
    let remainder = remainder.select(mask, T::Simd::default());
    let reduced = sum + remainder;

    reduced.simd_sum()
}

/// # Panics
/// iff `values.len() != bitmap.len()` or the operation overflows.
fn null_sum<T>(values: &[T], bitmap: &Bitmap) -> T
where
    T: NativeType + Simd,
    T::Simd: Add<Output = T::Simd> + Sum<T>,
{
    let (slice, offset, length) = bitmap.as_slice();
    if offset == 0 {
        let validity_masks = BitChunksExact::<<T::Simd as NativeSimd>::Chunk>::new(slice, length);
        null_sum_impl(values, validity_masks)
    } else {
        let validity_masks = bitmap.chunks::<<T::Simd as NativeSimd>::Chunk>();
        null_sum_impl(values, validity_masks)
    }
}

/// Returns the sum of values in the array.
///
/// Returns `None` if the array is empty or only contains null values.
pub fn sum_primitive<T>(array: &PrimitiveArray<T>) -> Option<T>
where
    T: NativeType + Simd,
    T::Simd: Add<Output = T::Simd> + Sum<T>,
{
    let null_count = array.null_count();

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

    match array.validity() {
        None => Some(nonnull_sum(array.values())),
        Some(bitmap) => Some(null_sum(array.values(), bitmap)),
    }
}

macro_rules! dyn_sum {
    ($ty:ty, $array:expr) => {{
        let array = $array
            .as_any()
            .downcast_ref::<PrimitiveArray<$ty>>()
            .unwrap();
        Box::new(PrimitiveScalar::<$ty>::new(
            $array.data_type().clone(),
            sum_primitive::<$ty>(array),
        ))
    }};
}

pub fn can_sum(data_type: &DataType) -> bool {
    use DataType::*;
    matches!(
        data_type,
        Int8 | Int16
            | Date32
            | Time32(_)
            | Interval(IntervalUnit::YearMonth)
            | Int64
            | Date64
            | Time64(_)
            | Timestamp(_, _)
            | Duration(_)
            | UInt8
            | UInt16
            | UInt32
            | UInt64
            | Float32
            | Float64
    )
}

/// Returns the sum of all elements in `array` as a [`Scalar`] of the same physical
/// and logical types as `array`.
/// # Error
/// Errors iff the operation is not supported.
pub fn sum(array: &dyn Array) -> Result<Box<dyn Scalar>> {
    Ok(match array.data_type() {
        DataType::Int8 => dyn_sum!(i8, array),
        DataType::Int16 => dyn_sum!(i16, array),
        DataType::Int32
        | DataType::Date32
        | DataType::Time32(_)
        | DataType::Interval(IntervalUnit::YearMonth) => {
            dyn_sum!(i32, array)
        }
        DataType::Int64
        | DataType::Date64
        | DataType::Time64(_)
        | DataType::Timestamp(_, _)
        | DataType::Duration(_) => dyn_sum!(i64, array),
        DataType::UInt8 => dyn_sum!(u8, array),
        DataType::UInt16 => dyn_sum!(u16, array),
        DataType::UInt32 => dyn_sum!(u32, array),
        DataType::UInt64 => dyn_sum!(u64, array),
        DataType::Float16 => unreachable!(),
        DataType::Float32 => dyn_sum!(f32, array),
        DataType::Float64 => dyn_sum!(f64, array),
        _ => {
            return Err(ArrowError::InvalidArgumentError(format!(
                "The `sum` operator does not support type `{}`",
                array.data_type(),
            )))
        }
    })
}

#[cfg(test)]
mod tests {
    use super::super::super::arithmetics;
    use super::*;
    use crate::array::*;

    #[test]
    fn test_primitive_array_sum() {
        let a = Int32Array::from_slice(&[1, 2, 3, 4, 5]);
        assert_eq!(
            &PrimitiveScalar::<i32>::from(Some(15)) as &dyn Scalar,
            sum(&a).unwrap().as_ref()
        );

        let a = a.to(DataType::Date32);
        assert_eq!(
            &PrimitiveScalar::<i32>::from(Some(15)).to(DataType::Date32) as &dyn Scalar,
            sum(&a).unwrap().as_ref()
        );
    }

    #[test]
    fn test_primitive_array_float_sum() {
        let a = Float64Array::from_slice(&[1.1f64, 2.2, 3.3, 4.4, 5.5]);
        assert!((16.5 - sum_primitive(&a).unwrap()).abs() < f64::EPSILON);
    }

    #[test]
    fn test_primitive_array_sum_with_nulls() {
        let a = Int32Array::from(&[None, Some(2), Some(3), None, Some(5)]);
        assert_eq!(10, sum_primitive(&a).unwrap());
    }

    #[test]
    fn test_primitive_array_sum_all_nulls() {
        let a = Int32Array::from(&[None, None, None]);
        assert_eq!(None, sum_primitive(&a));
    }

    #[test]
    fn test_primitive_array_sum_large_64() {
        let a: Int64Array = (1..=100)
            .map(|i| if i % 3 == 0 { Some(i) } else { None })
            .collect();
        let b: Int64Array = (1..=100)
            .map(|i| if i % 3 == 0 { Some(0) } else { Some(i) })
            .collect();
        // create an array that actually has non-zero values at the invalid indices
        let c = arithmetics::basic::add::add(&a, &b).unwrap();
        assert_eq!(
            Some((1..=100).filter(|i| i % 3 == 0).sum()),
            sum_primitive(&c)
        );
    }
}