我写了一个计算字数的程序。
这是程序
use std::collections::HashMap;
use std::io;
use std::io::prelude::*;
#[derive(Debug)]
struct Entry {
word: String,
count: u32,
}
static SEPARATORS: &'static [char] = &[
' ', ',', '.', '!', '?', '\'', '"', '\n', '(', ')', '#', '{', '}', '[', ']', '-', ';', ':',
];
fn main() {
if let Err(err) = try_main() {
if err.kind() == std::io::ErrorKind::BrokenPipe {
return;
}
// Ignore any error that may occur while writing to stderr.
let _ = writeln!(std::io::stderr(), "{}", err);
}
}
fn try_main() -> Result<(), std::io::Error> {
let mut words: HashMap<String, u32> = HashMap::new();
let stdin = io::stdin();
for result in stdin.lock().lines() {
let line = result?;
line_processor(line, &mut words)
}
output(&mut words)?;
Ok(())
}
fn line_processor(line: String, words: &mut HashMap<String, u32>) {
let mut word = String::new();
for c in line.chars() {
if SEPARATORS.contains(&c) {
add_word(word, words);
word = String::new();
} else {
word.push_str(&c.to_string());
}
}
}
fn add_word(word: String, words: &mut HashMap<String, u32>) {
if word.len() > 0 {
if words.contains_key::<str>(&word) {
words.insert(word.to_string(), words.get(&word).unwrap() + 1);
} else {
words.insert(word.to_string(), 1);
}
// println!("word >{}<", word.to_string())
}
}
fn output(words: &mut HashMap<String, u32>) -> Result<(), std::io::Error> {
let mut stack = Vec::<Entry>::new();
for (k, v) in words {
stack.push(Entry {
word: k.to_string(),
count: *v,
});
}
stack.sort_by(|a, b| b.count.cmp(&a.count));
stack.reverse();
let stdout = io::stdout();
let mut stdout = stdout.lock();
while let Some(entry) = stack.pop() {
writeln!(stdout, "{}\t{}", entry.count, entry.word)?;
}
Ok(())
}
它将任意文本文件作为输入并计算单词数以产生一些输出,例如:
15 the
14 in
11 are
10 and
10 of
9 species
9 bats
8 horseshoe
8 is
6 or
6 as
5 which
5 their
我这样编译它:
cargo build --release
我这样运行:
cat wiki-sample.txt | ./target/release/wordstats | head -n 50
我使用的 wiki-sample.txt 文件是here https://www.dropbox.com/s/3p3cwhk04va2o8g/wiki-sample.txt?dl=1
我将执行时间与 python (3.8) 版本进行了比较:
import sys
from collections import defaultdict
# import unidecode
seps = set(
[
" ",
",",
".",
"!",
"?",
"'",
'"',
"\n",
"(",
")",
"#",
"{",
"}",
"[",
"]",
"-",
";",
":",
]
)
def out(result):
for i in result:
print(f"{i[1]}\t{i[0]}")
if __name__ == "__main__":
c = defaultdict(int)
for line in sys.stdin:
words = line.split(" ")
for word in words:
clean_word = []
for char in word:
if char not in seps and char:
clean_word.append(char)
r = "".join(clean_word)
# r = unidecode.unidecode(r)
if r:
c[r] += 1
r = sorted(list(c.items()), key=lambda x: -x[1])
try:
out(r)
except BrokenPipeError as e:
pass
我这样运行它:
cat /tmp/t.txt | ./venv/bin/python3 src/main.py | head -n 100
- 平均计算时间为:rust -> 5',python3.8 -> 19'
- python 版本(我认为)优化较差(整行的分割需要额外的 O(n))
- 这是单线程进程,并且是一个非常简单的程序
- 大部分计算时间都在字循环处理中,输出几乎是即时的。
- 我还删除了删除重音的库代码,以更接近两种语言的标准库。
Question: Rust 的性能“仅”提高约 3-4 倍,这正常吗?
我还想知道我是否在这里遗漏了一些东西,因为我发现“仅”100Mb 数据的计算时间相当长。我不认为(天真地)有一些处理与较低的大 O 对此,我可能是错的。
我习惯于将一些 python 代码与 go、java 或 vlang 中的等效代码进行比较,并且这些工作台的速度通常会提高 20 倍到 100 倍。
也许cpython擅长这种处理,也许我错过了rust程序中的一些东西(我对rust很陌生)以使其更加高效。
我害怕在测试中错过一些重要的东西,但是对此有什么想法吗?
编辑:根据人们的建议,我现在有以下版本:
use std::collections::HashMap;
use std::io;
use std::io::prelude::*;
#[derive(Debug)]
struct Entry<'a> {
word: &'a str, // word: String,
count: u32,
}
static SEPARATORS: &'static [char] = &[
' ', ',', '.', '!', '?', '\'', '"', '\n', '(', ')', '#', '{', '}', '[', ']', '-', ';', ':',
];
fn main() {
if let Err(err) = try_main() {
if err.kind() == std::io::ErrorKind::BrokenPipe {
return;
}
// Ignore any error that may occur while writing to stderr.
let _ = writeln!(std::io::stderr(), "{}", err);
}
}
fn try_main() -> Result<(), std::io::Error> {
let mut words: HashMap<String, u32> = HashMap::new();
let stdin = io::stdin();
for result in stdin.lock().lines() {
let line = result?;
line_processor(line, &mut words)
}
output(&mut words)?;
Ok(())
}
fn line_processor(line: String, words: &mut HashMap<String, u32>) {
let mut l = line.as_str();
loop {
if let Some(pos) = l.find(|c: char| SEPARATORS.contains(&c)) {
let (head, tail) = l.split_at(pos);
add_word(head.to_owned(), words);
l = &tail[1..];
} else {
break;
}
}
}
fn add_word(word: String, words: &mut HashMap<String, u32>) {
if word.len() > 0 {
let count = words.entry(word).or_insert(0);
*count += 1;
}
}
fn output(words: &mut HashMap<String, u32>) -> Result<(), std::io::Error> {
let mut stack = Vec::<Entry>::new();
for (k, v) in words {
stack.push(Entry {
word: k.as_str(), // word: k.to_string(),
count: *v,
});
}
stack.sort_by(|a, b| a.count.cmp(&b.count));
let stdout = io::stdout();
let mut stdout = stdout.lock();
while let Some(entry) = stack.pop() {
writeln!(stdout, "{}\t{}", entry.count, entry.word)?;
}
Ok(())
}
现在在我的电脑上大约需要 2.6'。这比 python 版本要好得多,几乎快 10 倍,虽然更好,但仍然没有达到我的预期(这不是一个真正的问题)。可能还有一些我暂时没有想到的其他优化。