#[macro_use]
extern crate criterion;
use criterion::Criterion;
use rand::Rng;
use std::sync::Arc;
extern crate arrow;
use arrow::util::bench_util::*;
use arrow::{array::*, datatypes::Float32Type};
use arrow::{compute::kernels::arithmetic::*, util::test_util::seedable_rng};
fn create_array(size: usize, with_nulls: bool) -> ArrayRef {
let null_density = if with_nulls { 0.5 } else { 0.0 };
let array = create_primitive_array::<Float32Type>(size, null_density);
Arc::new(array)
}
fn bench_add(arr_a: &ArrayRef, arr_b: &ArrayRef) {
let arr_a = arr_a.as_any().downcast_ref::<Float32Array>().unwrap();
let arr_b = arr_b.as_any().downcast_ref::<Float32Array>().unwrap();
criterion::black_box(add(arr_a, arr_b).unwrap());
}
fn bench_subtract(arr_a: &ArrayRef, arr_b: &ArrayRef) {
let arr_a = arr_a.as_any().downcast_ref::<Float32Array>().unwrap();
let arr_b = arr_b.as_any().downcast_ref::<Float32Array>().unwrap();
criterion::black_box(subtract(arr_a, arr_b).unwrap());
}
fn bench_multiply(arr_a: &ArrayRef, arr_b: &ArrayRef) {
let arr_a = arr_a.as_any().downcast_ref::<Float32Array>().unwrap();
let arr_b = arr_b.as_any().downcast_ref::<Float32Array>().unwrap();
criterion::black_box(multiply(arr_a, arr_b).unwrap());
}
fn bench_divide(arr_a: &ArrayRef, arr_b: &ArrayRef) {
let arr_a = arr_a.as_any().downcast_ref::<Float32Array>().unwrap();
let arr_b = arr_b.as_any().downcast_ref::<Float32Array>().unwrap();
criterion::black_box(divide(arr_a, arr_b).unwrap());
}
fn bench_divide_unchecked(arr_a: &ArrayRef, arr_b: &ArrayRef) {
let arr_a = arr_a.as_any().downcast_ref::<Float32Array>().unwrap();
let arr_b = arr_b.as_any().downcast_ref::<Float32Array>().unwrap();
criterion::black_box(divide_unchecked(arr_a, arr_b).unwrap());
}
fn bench_divide_scalar(array: &ArrayRef, divisor: f32) {
let array = array.as_any().downcast_ref::<Float32Array>().unwrap();
criterion::black_box(divide_scalar(array, divisor).unwrap());
}
fn bench_modulo(arr_a: &ArrayRef, arr_b: &ArrayRef) {
let arr_a = arr_a.as_any().downcast_ref::<Float32Array>().unwrap();
let arr_b = arr_b.as_any().downcast_ref::<Float32Array>().unwrap();
criterion::black_box(modulus(arr_a, arr_b).unwrap());
}
fn bench_modulo_scalar(array: &ArrayRef, divisor: f32) {
let array = array.as_any().downcast_ref::<Float32Array>().unwrap();
criterion::black_box(modulus_scalar(array, divisor).unwrap());
}
fn add_benchmark(c: &mut Criterion) {
const BATCH_SIZE: usize = 64 * 1024;
let arr_a = create_array(BATCH_SIZE, false);
let arr_b = create_array(BATCH_SIZE, false);
let scalar = seedable_rng().gen();
c.bench_function("add", |b| b.iter(|| bench_add(&arr_a, &arr_b)));
c.bench_function("subtract", |b| b.iter(|| bench_subtract(&arr_a, &arr_b)));
c.bench_function("multiply", |b| b.iter(|| bench_multiply(&arr_a, &arr_b)));
c.bench_function("divide", |b| b.iter(|| bench_divide(&arr_a, &arr_b)));
c.bench_function("divide_unchecked", |b| {
b.iter(|| bench_divide_unchecked(&arr_a, &arr_b))
});
c.bench_function("divide_scalar", |b| {
b.iter(|| bench_divide_scalar(&arr_a, scalar))
});
c.bench_function("modulo", |b| b.iter(|| bench_modulo(&arr_a, &arr_b)));
c.bench_function("modulo_scalar", |b| {
b.iter(|| bench_modulo_scalar(&arr_a, scalar))
});
let arr_a_nulls = create_array(BATCH_SIZE, true);
let arr_b_nulls = create_array(BATCH_SIZE, true);
c.bench_function("add_nulls", |b| {
b.iter(|| bench_add(&arr_a_nulls, &arr_b_nulls))
});
c.bench_function("divide_nulls", |b| {
b.iter(|| bench_divide(&arr_a_nulls, &arr_b_nulls))
});
c.bench_function("divide_nulls_unchecked", |b| {
b.iter(|| bench_divide_unchecked(&arr_a_nulls, &arr_b_nulls))
});
c.bench_function("divide_scalar_nulls", |b| {
b.iter(|| bench_divide_scalar(&arr_a_nulls, scalar))
});
c.bench_function("modulo_nulls", |b| {
b.iter(|| bench_modulo(&arr_a_nulls, &arr_b_nulls))
});
c.bench_function("modulo_scalar_nulls", |b| {
b.iter(|| bench_modulo_scalar(&arr_a_nulls, scalar))
});
}
criterion_group!(benches, add_benchmark);
criterion_main!(benches);