jhorstmann commented on code in PR #5096:
URL: https://github.com/apache/arrow-rs/pull/5096#discussion_r1398273524
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arrow/benches/aggregate_kernels.rs:
##########
@@ -17,50 +17,55 @@
#[macro_use]
extern crate criterion;
-use criterion::Criterion;
+use criterion::{Criterion, Throughput};
+use rand::distributions::{Distribution, Standard};
extern crate arrow;
use arrow::compute::kernels::aggregate::*;
use arrow::util::bench_util::*;
use arrow::{array::*, datatypes::Float32Type};
+use arrow_array::types::{Float64Type, Int16Type, Int32Type, Int64Type,
Int8Type};
-fn bench_sum(arr_a: &Float32Array) {
- criterion::black_box(sum(arr_a).unwrap());
-}
-
-fn bench_min(arr_a: &Float32Array) {
- criterion::black_box(min(arr_a).unwrap());
-}
-
-fn bench_max(arr_a: &Float32Array) {
- criterion::black_box(max(arr_a).unwrap());
-}
+const BATCH_SIZE: usize = 64 * 1024;
-fn bench_min_string(arr_a: &StringArray) {
- criterion::black_box(min_string(arr_a).unwrap());
+fn primitive_benchmark<T: ArrowNumericType>(c: &mut Criterion, name: &str)
+where
+ Standard: Distribution<T::Native>,
+{
+ let nonnull_array = create_primitive_array::<T>(BATCH_SIZE, 0.0);
+ let nullable_array = create_primitive_array::<T>(BATCH_SIZE, 0.5);
+ c.benchmark_group(name)
+ .throughput(Throughput::Bytes(
+ (std::mem::size_of::<T::Native>() * BATCH_SIZE) as u64,
+ ))
+ .bench_function("sum nonnull", |b| b.iter(|| sum(&nonnull_array)))
Review Comment:
It is indeed always wrapping, scalar version goes through
`ArrowNativeTypeOp::add_wrapping` and I guess the simd version wraps by
default. There seems to be a separate `sum_checked` kernels, I'm not sure yet
whether that could be vectorized.
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