influxdb/cache_system/benches/addressable_heap.rs

382 lines
10 KiB
Rust

use std::mem::size_of;
use cache_system::addressable_heap::AddressableHeap;
use criterion::{
criterion_group, criterion_main, measurement::WallTime, AxisScale, BatchSize, BenchmarkGroup,
BenchmarkId, Criterion, PlotConfiguration, SamplingMode,
};
use rand::{prelude::SliceRandom, thread_rng, Rng};
/// Payload (`V`) for testing.
///
/// This is a 64bit-wide object which is enough to store a [`Box`] or a [`usize`].
#[derive(Debug, Clone, Default)]
struct Payload([u8; 8]);
const _: () = assert!(size_of::<Payload>() == 8);
const _: () = assert!(size_of::<Payload>() >= size_of::<Box<Vec<u32>>>());
const _: () = assert!(size_of::<Payload>() >= size_of::<usize>());
type TestHeap = AddressableHeap<u64, Payload, u64>;
const TEST_SIZES: &[usize] = &[0, 1, 10, 100, 1_000, 10_000];
#[derive(Debug, Clone)]
struct Entry {
k: u64,
o: u64,
}
impl Entry {
fn new_random<R>(rng: &mut R) -> Self
where
R: Rng,
{
Self {
k: rng.gen(),
o: rng.gen(),
}
}
fn new_random_n<R>(rng: &mut R, n: usize) -> Vec<Self>
where
R: Rng,
{
(0..n).map(|_| Self::new_random(rng)).collect()
}
}
fn create_filled_heap<R>(rng: &mut R, n: usize) -> (TestHeap, Vec<Entry>)
where
R: Rng,
{
let mut heap = TestHeap::default();
let mut entries = Vec::with_capacity(n);
for _ in 0..n {
let entry = Entry::new_random(rng);
heap.insert(entry.k, Payload::default(), entry.o);
entries.push(entry);
}
(heap, entries)
}
fn setup_group(g: &mut BenchmarkGroup<'_, WallTime>) {
g.plot_config(PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
g.sampling_mode(SamplingMode::Flat);
}
fn bench_insert_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("insert_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| (TestHeap::default(), Entry::new_random_n(&mut rng, *n)),
|(mut heap, entries)| {
for entry in &entries {
heap.insert(entry.k, Payload::default(), entry.o);
}
// let criterion handle the drop
(heap, entries)
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_peek_after_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("peek_after_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| create_filled_heap(&mut rng, *n).0,
|heap| {
heap.peek();
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_get_existing_after_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("get_existing_after_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
if *n == 0 {
continue;
}
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| {
let (heap, entries) = create_filled_heap(&mut rng, *n);
let entry = entries.choose(&mut rng).unwrap().clone();
(heap, entry)
},
|(heap, entry)| {
heap.get(&entry.k);
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_get_new_after_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("get_new_after_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| {
let (heap, _entries) = create_filled_heap(&mut rng, *n);
let entry = Entry::new_random(&mut rng);
(heap, entry)
},
|(heap, entry)| {
heap.get(&entry.k);
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_pop_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("pop_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| create_filled_heap(&mut rng, *n).0,
|mut heap| {
for _ in 0..*n {
heap.pop();
}
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_remove_existing_after_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("remove_existing_after_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
if *n == 0 {
continue;
}
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| {
let (heap, entries) = create_filled_heap(&mut rng, *n);
let entry = entries.choose(&mut rng).unwrap().clone();
(heap, entry)
},
|(mut heap, entry)| {
heap.remove(&entry.k);
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_remove_new_after_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("remove_new_after_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| {
let (heap, _entries) = create_filled_heap(&mut rng, *n);
let entry = Entry::new_random(&mut rng);
(heap, entry)
},
|(mut heap, entry)| {
heap.remove(&entry.k);
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_replace_after_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("replace_after_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
if *n == 0 {
continue;
}
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| {
let (heap, entries) = create_filled_heap(&mut rng, *n);
let entry = entries.choose(&mut rng).unwrap().clone();
let entry = Entry {
k: entry.k,
o: Entry::new_random(&mut rng).o,
};
(heap, entry)
},
|(mut heap, entry)| {
heap.insert(entry.k, Payload::default(), entry.o);
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_update_order_existing_after_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("update_order_existing_after_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
if *n == 0 {
continue;
}
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| {
let (heap, entries) = create_filled_heap(&mut rng, *n);
let entry = entries.choose(&mut rng).unwrap().clone();
let entry = Entry {
k: entry.k,
o: Entry::new_random(&mut rng).o,
};
(heap, entry)
},
|(mut heap, entry)| {
heap.update_order(&entry.k, entry.o);
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
fn bench_update_order_new_after_n_elements(c: &mut Criterion) {
let mut g = c.benchmark_group("update_order_new_after_n_elements");
setup_group(&mut g);
let mut rng = thread_rng();
for n in TEST_SIZES {
g.bench_with_input(BenchmarkId::from_parameter(n), &n, |b, &_n| {
b.iter_batched(
|| {
let (heap, _entries) = create_filled_heap(&mut rng, *n);
let entry = Entry::new_random(&mut rng);
(heap, entry)
},
|(mut heap, entry)| {
heap.update_order(&entry.k, entry.o);
// let criterion handle the drop
heap
},
BatchSize::LargeInput,
);
});
}
g.finish();
}
criterion_group! {
name = benches;
config = Criterion::default();
targets =
bench_insert_n_elements,
bench_peek_after_n_elements,
bench_get_existing_after_n_elements,
bench_get_new_after_n_elements,
bench_pop_n_elements,
bench_remove_existing_after_n_elements,
bench_remove_new_after_n_elements,
bench_replace_after_n_elements,
bench_update_order_existing_after_n_elements,
bench_update_order_new_after_n_elements,
}
criterion_main!(benches);