refactor: clarify benchmark
Edd Robinson
parent
f5fe270e43
commit
f86e0641fd
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@ -38,7 +38,7 @@ name = "database"
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harness = false
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[[bench]]
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name = "sum"
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name = "sum_fixed"
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harness = false
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[[bench]]
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@ -0,0 +1,269 @@
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use std::mem::size_of;
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use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
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use rand::prelude::*;
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use arrow::datatypes::*;
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use read_buffer::benchmarks::Fixed;
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use read_buffer::benchmarks::FixedNull;
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const ROWS: [usize; 5] = [10, 100, 1_000, 10_000, 60_000];
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const CHUNKS: [Chunks; 4] = [
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Chunks::All,
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Chunks::Even,
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Chunks::ManySmall,
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Chunks::RandomTenPercent,
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];
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const PHYSICAL_TYPES: [PhysicalType; 3] = [PhysicalType::I64, PhysicalType::I32, PhysicalType::I16];
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#[derive(Debug)]
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enum Chunks {
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All, // sum up the entire column
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Even, // sum up the even rows
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ManySmall, // sum up chunks of 10 values
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RandomTenPercent, // sum up random 10% of values
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}
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enum EncType {
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Fixed,
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FixedNull,
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}
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enum PhysicalType {
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I64,
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I32,
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I16,
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}
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fn encoding_sum(c: &mut Criterion) {
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benchmark_none_sum(
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c,
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"encoding_none_sum",
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EncType::Fixed,
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&ROWS,
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&CHUNKS,
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&PHYSICAL_TYPES,
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);
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benchmark_none_sum(
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c,
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"encoding_none_sum",
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EncType::FixedNull,
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&ROWS,
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&CHUNKS,
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&PHYSICAL_TYPES,
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);
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}
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fn benchmark_none_sum(
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c: &mut Criterion,
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benchmark_group_name: &str,
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enc_type: EncType,
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row_size: &[usize],
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chunks: &[Chunks],
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physical_type: &[PhysicalType],
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) {
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let mut group = c.benchmark_group(benchmark_group_name);
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for &num_rows in row_size {
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for chunk in chunks {
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for pt in physical_type {
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// Encoded incrementing values.
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let input: Vec<u32>;
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match chunk {
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Chunks::All => input = (0..num_rows as u32).collect(),
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Chunks::Even => input = gen_even_chunk(num_rows),
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Chunks::ManySmall => input = gen_many_small_chunk(num_rows),
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Chunks::RandomTenPercent => input = gen_random_10_percent(num_rows),
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}
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match pt {
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PhysicalType::I64 => {
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group
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.throughput(Throughput::Bytes((input.len() * size_of::<i64>()) as u64));
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match enc_type {
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EncType::Fixed => {
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let encoding = Fixed::<i64>::from(
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(0..num_rows as i64).collect::<Vec<i64>>().as_slice(),
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);
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group.bench_with_input(
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BenchmarkId::from_parameter(format!(
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"{:?}_{:?}_i64",
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num_rows, chunk
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)),
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&input,
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|b, input| {
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b.iter(|| {
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// do work
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let _ = encoding.sum::<i64>(&input);
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});
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},
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);
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}
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EncType::FixedNull => {
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let encoding = FixedNull::<Int64Type>::from(
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(0..num_rows as i64).collect::<Vec<i64>>().as_slice(),
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);
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group.bench_with_input(
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BenchmarkId::from_parameter(format!(
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"{:?}_{:?}_i64",
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num_rows, chunk
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)),
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&input,
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|b, input| {
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b.iter(|| {
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// do work
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let _ = encoding.sum(&input);
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});
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},
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);
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}
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}
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}
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PhysicalType::I32 => {
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group
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.throughput(Throughput::Bytes((input.len() * size_of::<i64>()) as u64));
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match enc_type {
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EncType::Fixed => {
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let encoding = Fixed::<i32>::from(
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(0..num_rows as i32).collect::<Vec<i32>>().as_slice(),
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);
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group.bench_with_input(
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BenchmarkId::from_parameter(format!(
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"{:?}_{:?}_i32",
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num_rows, chunk
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)),
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&input,
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|b, input| {
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b.iter(|| {
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// do work
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let _ = encoding.sum::<i32>(&input);
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});
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},
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);
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}
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EncType::FixedNull => {
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let encoding = FixedNull::<Int32Type>::from(
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(0..num_rows as i32).collect::<Vec<i32>>().as_slice(),
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);
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group.bench_with_input(
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BenchmarkId::from_parameter(format!(
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"{:?}_{:?}_i32",
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num_rows, chunk
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)),
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&input,
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|b, input| {
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b.iter(|| {
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// do work
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let _ = encoding.sum(&input);
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});
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},
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);
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}
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}
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}
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PhysicalType::I16 => {
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group
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.throughput(Throughput::Bytes((input.len() * size_of::<i64>()) as u64));
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match enc_type {
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EncType::Fixed => {
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let encoding = Fixed::<i16>::from(
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(0..num_rows as i16).collect::<Vec<i16>>().as_slice(),
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);
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group.bench_with_input(
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BenchmarkId::from_parameter(format!(
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"{:?}_{:?}_i16",
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num_rows, chunk
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)),
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&input,
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|b, input| {
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b.iter(|| {
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// do work
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let _ = encoding.sum::<i16>(&input);
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});
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},
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);
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}
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EncType::FixedNull => {
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let encoding = FixedNull::<Int16Type>::from(
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(0..num_rows as i16).collect::<Vec<i16>>().as_slice(),
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);
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group.bench_with_input(
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BenchmarkId::from_parameter(format!(
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"{:?}_{:?}_i16",
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num_rows, chunk
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)),
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&input,
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|b, input| {
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b.iter(|| {
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// do work
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let _ = encoding.sum(&input);
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});
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},
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);
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}
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}
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}
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}
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}
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}
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}
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group.finish();
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}
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// results in about 50% rows being requested.
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fn gen_even_chunk(rows: usize) -> Vec<u32> {
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(0..rows as u32).filter(|x| x % 2 == 0).collect()
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}
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// generate small sequences of 3 rows periodically. This leads to about 34% of
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// rows being requested.
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fn gen_many_small_chunk(rows: usize) -> Vec<u32> {
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let mut input = vec![];
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let mut emit_chunk = false;
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let mut chunk_size = 0;
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for i in 0..rows as u32 {
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if i % 9 == 0 {
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emit_chunk = true;
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}
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if emit_chunk {
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input.push(i);
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chunk_size += 1;
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}
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if chunk_size == 3 {
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chunk_size = 0;
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emit_chunk = false;
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}
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}
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input
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}
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// generate random 10% sequence.
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fn gen_random_10_percent(rows: usize) -> Vec<u32> {
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let mut rnd = thread_rng();
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let mut input = vec![];
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for i in 0..rows as u32 {
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if rnd.gen::<f64>() < 0.1 {
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input.push(i);
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}
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}
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input
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}
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criterion_group!(benches, encoding_sum,);
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criterion_main!(benches);
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