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Commitd6a6eb8

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Modify benchmarks to compare against stdlib functions
This commit refactors and expands the microbenchmarks in order toevaluate the performance hit of handling full unicode. It is expectedthat `unicode-segmentation`'s functions are slower since they considergraphemes, the question is just how much.- bump criterion dependency- rename benchmarks to remove unicode/grapheme relationship- move benchmarks into benchmark group- add scalar versions with stdlib "equivalents" (scalars)
1 parentbaab923 commitd6a6eb8

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6 files changed

+154
-184
lines changed

6 files changed

+154
-184
lines changed

‎Cargo.toml

Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -23,17 +23,16 @@ no_std = [] # This is a no-op, preserved for backward compatibility only.
2323

2424
[dev-dependencies]
2525
quickcheck ="0.7"
26-
criterion ="0.3"
26+
criterion ="0.5"
2727

2828
[[bench]]
29-
name ="graphemes"
29+
name ="chars"
3030
harness =false
3131

3232
[[bench]]
33-
name ="unicode_words"
33+
name ="words"
3434
harness =false
3535

3636
[[bench]]
3737
name ="word_bounds"
3838
harness =false
39-

‎benches/chars.rs

Lines changed: 60 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,60 @@
1+
//! Compares the performance of `UnicodeSegmentation::graphemes` with stdlib's UTF-8 scalar-based
2+
//! `std::str::chars`.
3+
//!
4+
//! It is expected that `std::str::chars` is faster than `UnicodeSegmentation::graphemes` since it
5+
//! does not consider the complexity of grapheme clusters. The question in this benchmark
6+
//! is how much slower full unicode handling is.
7+
8+
use criterion::{black_box, criterion_group, criterion_main,BenchmarkId,Criterion};
9+
use unicode_segmentation;
10+
11+
use std::fs;
12+
use unicode_segmentation::UnicodeSegmentation;
13+
14+
constFILES:&[&str] =&[
15+
"arabic",
16+
"english",
17+
"hindi",
18+
"japanese",
19+
"korean",
20+
"mandarin",
21+
"russian",
22+
"source_code",
23+
];
24+
25+
#[inline(always)]
26+
fngrapheme(text:&str){
27+
for cinUnicodeSegmentation::graphemes(black_box(&*text),true){
28+
black_box(c);
29+
}
30+
}
31+
32+
#[inline(always)]
33+
fnscalar(text:&str){
34+
for cinblack_box(&*text).chars(){
35+
black_box(c);
36+
}
37+
}
38+
39+
fnbench_all(c:&mutCriterion){
40+
letmut group = c.benchmark_group("chars");
41+
42+
for fileinFILES{
43+
group.bench_with_input(
44+
BenchmarkId::new("grapheme", file),
45+
&fs::read_to_string(format!("benches/texts/{}.txt", file)).unwrap(),
46+
|b, content| b.iter(||grapheme(content)),
47+
);
48+
}
49+
50+
for fileinFILES{
51+
group.bench_with_input(
52+
BenchmarkId::new("scalar", file),
53+
&fs::read_to_string(format!("benches/texts/{}.txt", file)).unwrap(),
54+
|b, content| b.iter(||scalar(content)),
55+
);
56+
}
57+
}
58+
59+
criterion_group!(benches, bench_all);
60+
criterion_main!(benches);

‎benches/graphemes.rs

Lines changed: 0 additions & 63 deletions
This file was deleted.

‎benches/unicode_words.rs

Lines changed: 0 additions & 61 deletions
This file was deleted.

‎benches/word_bounds.rs

Lines changed: 32 additions & 56 deletions
Original file line numberDiff line numberDiff line change
@@ -1,61 +1,37 @@
1-
use criterion::{black_box, criterion_group, criterion_main,Criterion};
1+
use criterion::{black_box, criterion_group, criterion_main,BenchmarkId,Criterion};
22

33
use std::fs;
44
use unicode_segmentation::UnicodeSegmentation;
55

6-
fnword_bounds(c:&mutCriterion,lang:&str,path:&str){
7-
let text = fs::read_to_string(path).unwrap();
8-
c.bench_function(&format!("word_bounds_{}", lang), |bench|{
9-
bench.iter(||{
10-
for win text.split_word_bounds(){
11-
black_box(w);
12-
}
13-
});
14-
});
15-
}
16-
17-
fnword_bounds_arabic(c:&mutCriterion){
18-
word_bounds(c,"arabic","benches/texts/arabic.txt");
19-
}
20-
21-
fnword_bounds_english(c:&mutCriterion){
22-
word_bounds(c,"english","benches/texts/english.txt");
23-
}
24-
25-
fnword_bounds_hindi(c:&mutCriterion){
26-
word_bounds(c,"hindi","benches/texts/hindi.txt");
27-
}
28-
29-
fnword_bounds_japanese(c:&mutCriterion){
30-
word_bounds(c,"japanese","benches/texts/japanese.txt");
31-
}
32-
33-
fnword_bounds_korean(c:&mutCriterion){
34-
word_bounds(c,"korean","benches/texts/korean.txt");
35-
}
36-
37-
fnword_bounds_mandarin(c:&mutCriterion){
38-
word_bounds(c,"mandarin","benches/texts/mandarin.txt");
39-
}
40-
41-
fnword_bounds_russian(c:&mutCriterion){
42-
word_bounds(c,"russian","benches/texts/russian.txt");
43-
}
44-
45-
fnword_bounds_source_code(c:&mutCriterion){
46-
word_bounds(c,"source_code","benches/texts/source_code.txt");
47-
}
48-
49-
criterion_group!(
50-
benches,
51-
word_bounds_arabic,
52-
word_bounds_english,
53-
word_bounds_hindi,
54-
word_bounds_japanese,
55-
word_bounds_korean,
56-
word_bounds_mandarin,
57-
word_bounds_russian,
58-
word_bounds_source_code,
59-
);
60-
6+
constFILES:&[&str] =&[
7+
"arabic",
8+
"english",
9+
"hindi",
10+
"japanese",
11+
"korean",
12+
"mandarin",
13+
"russian",
14+
"source_code",
15+
];
16+
17+
#[inline(always)]
18+
fngrapheme(text:&str){
19+
for win text.split_word_bounds(){
20+
black_box(w);
21+
}
22+
}
23+
24+
fnbench_all(c:&mutCriterion){
25+
letmut group = c.benchmark_group("word_bounds");
26+
27+
for fileinFILES{
28+
group.bench_with_input(
29+
BenchmarkId::new("grapheme", file),
30+
&fs::read_to_string(format!("benches/texts/{}.txt", file)).unwrap(),
31+
|b, content| b.iter(||grapheme(content)),
32+
);
33+
}
34+
}
35+
36+
criterion_group!(benches, bench_all);
6137
criterion_main!(benches);

‎benches/words.rs

Lines changed: 59 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,59 @@
1+
//! Compares the performance of `UnicodeSegmentation::unicode_words` with stdlib's UTF-8
2+
//! scalar-based `std::str::split_whitespace`.
3+
//!
4+
//! It is expected that `std::str::split_whitespace` is faster than
5+
//! `UnicodeSegmentation::unicode_words` since it does not consider the complexity of grapheme
6+
//! clusters. The question in this benchmark is how much slower full unicode handling is.
7+
8+
use criterion::{black_box, criterion_group, criterion_main,BenchmarkId,Criterion};
9+
10+
use std::fs;
11+
use unicode_segmentation::UnicodeSegmentation;
12+
13+
constFILES:&[&str] =&[
14+
"arabic",
15+
"english",
16+
"hindi",
17+
"japanese",
18+
"korean",
19+
"mandarin",
20+
"russian",
21+
"source_code",
22+
];
23+
24+
#[inline(always)]
25+
fngrapheme(text:&str){
26+
for win text.unicode_words(){
27+
black_box(w);
28+
}
29+
}
30+
31+
#[inline(always)]
32+
fnscalar(text:&str){
33+
for win text.split_whitespace(){
34+
black_box(w);
35+
}
36+
}
37+
38+
fnbench_all(c:&mutCriterion){
39+
letmut group = c.benchmark_group("words");
40+
41+
for fileinFILES{
42+
group.bench_with_input(
43+
BenchmarkId::new("grapheme", file),
44+
&fs::read_to_string(format!("benches/texts/{}.txt", file)).unwrap(),
45+
|b, content| b.iter(||grapheme(content)),
46+
);
47+
}
48+
49+
for fileinFILES{
50+
group.bench_with_input(
51+
BenchmarkId::new("scalar", file),
52+
&fs::read_to_string(format!("benches/texts/{}.txt", file)).unwrap(),
53+
|b, content| b.iter(||scalar(content)),
54+
);
55+
}
56+
}
57+
58+
criterion_group!(benches, bench_all);
59+
criterion_main!(benches);

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