造轮子的快乐！一个极快的纯 C 异步日志库

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这是一个创建于 797 天前的主题，其中的信息可能已经有所发展或是发生改变。

项目地址: https://github.com/MuggleWei/haclog

十一放假之前，看了一下 Nanolog 的论文，感觉思路非常赞，可惜 Nanolog 并不跨平台，而且为了性能和吞吐量，其日志输出并不直接可读。既然已经有了大体思路，接下来当然是自己撸一个啦！而且因为我也比较多 C 的库需要使用，所以就撸一个纯 C 的版本~
长假当中就断断续续写了一些，这几天在家的时间没事也写几段，今天大致到了较为满意的程度. 下面是在 Mac M1 2021 和 ThinkPad X1C 2019 上的 benchmark 结果 (测试程序可以直接在工程目录中找到： haclog gbenchmark)，欢迎各位老板们使用和提意见

Mac M1 2021

Run on (8 X 24 MHz CPU s) CPU Caches: L1 Data 64 KiB L1 Instruction 128 KiB L2 Unified 4096 KiB (x8) Load Average: 8.88, 4.53, 2.84 ----------------------------------------------------------------------------------------------------------- Benchmark Time CPU Iterations ----------------------------------------------------------------------------------------------------------- ConstIterFixture/run/min_time:3.000/threads:1 66.3 ns 66.2 ns 60803739 ConstIterFixture/run/min_time:3.000/threads:2 34.0 ns 67.8 ns 58196532 ConstIterFixture/run/min_time:3.000/threads:4 24.7 ns 96.0 ns 46114032 ConstIterFixture/run/min_time:3.000/threads:7 30.0 ns 146 ns 25301248 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 120 ns 120 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 74.8 ns 74.8 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 65.9 ns 66.0 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 87.8 ns 87.8 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 79.8 ns 80.0 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1_mean 85.7 ns 85.7 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:1_median 79.8 ns 80.0 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:1_stddev 20.8 ns 20.7 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:1_cv 24.29 % 24.19 % 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:4 25.6 ns 102 ns 24000 ConstIterFixture/run/iterations:6000/repeats:5/threads:4 23.0 ns 91.8 ns 24000 ConstIterFixture/run/iterations:6000/repeats:5/threads:4 28.5 ns 114 ns 24000 ConstIterFixture/run/iterations:6000/repeats:5/threads:4 27.8 ns 111 ns 24000 ConstIterFixture/run/iterations:6000/repeats:5/threads:4 28.6 ns 114 ns 24000 ConstIterFixture/run/iterations:6000/repeats:5/threads:4_mean 26.7 ns 107 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:4_median 27.8 ns 111 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:4_stddev 2.42 ns 9.71 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:4_cv 9.05 % 9.09 % 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:8 16.7 ns 132 ns 48000 ConstIterFixture/run/iterations:6000/repeats:5/threads:8 17.5 ns 130 ns 48000 ConstIterFixture/run/iterations:6000/repeats:5/threads:8 17.5 ns 135 ns 48000 ConstIterFixture/run/iterations:6000/repeats:5/threads:8 16.8 ns 134 ns 48000 ConstIterFixture/run/iterations:6000/repeats:5/threads:8 16.9 ns 133 ns 48000 ConstIterFixture/run/iterations:6000/repeats:5/threads:8_mean 17.1 ns 133 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:8_median 16.9 ns 133 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:8_stddev 0.396 ns 1.64 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:8_cv 2.32 % 1.24 % 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:16 7.82 ns 125 ns 96000 ConstIterFixture/run/iterations:6000/repeats:5/threads:16 8.64 ns 136 ns 96000 ConstIterFixture/run/iterations:6000/repeats:5/threads:16 13.2 ns 204 ns 96000 ConstIterFixture/run/iterations:6000/repeats:5/threads:16 7.25 ns 114 ns 96000 ConstIterFixture/run/iterations:6000/repeats:5/threads:16 11.0 ns 169 ns 96000 ConstIterFixture/run/iterations:6000/repeats:5/threads:16_mean 9.57 ns 149 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:16_median 8.64 ns 136 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:16_stddev 2.47 ns 36.7 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:16_cv 25.83 % 24.56 % 5

Thinkpad X1C 2019

Run on (12 X 1780.93 MHz CPU s) CPU Caches: L1 Data 32 KiB (x6) L1 Instruction 32 KiB (x6) L2 Unified 256 KiB (x6) L3 Unified 12288 KiB (x1) Load Average: 0.09, 0.03, 0.08 ----------------------------------------------------------------------------------------------------------- Benchmark Time CPU Iterations ----------------------------------------------------------------------------------------------------------- ConstIterFixture/run/min_time:3.000/threads:1 63.8 ns 63.7 ns 65480842 ConstIterFixture/run/min_time:3.000/threads:2 35.3 ns 70.6 ns 57795198 ConstIterFixture/run/min_time:3.000/threads:6 28.4 ns 170 ns 19480434 ConstIterFixture/run/min_time:3.000/threads:11 2491 ns 27350 ns 370425 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 144 ns 144 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 145 ns 144 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 144 ns 144 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 137 ns 136 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1 128 ns 128 ns 6000 ConstIterFixture/run/iterations:6000/repeats:5/threads:1_mean 140 ns 139 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:1_median 144 ns 144 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:1_stddev 7.14 ns 7.04 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:1_cv 5.11 % 5.06 % 5 ConstIterFixture/run/iterations:6000/repeas:5/threads:6 40.1 ns 241 ns 36000 ConstIterFixture/run/iterations:6000/repeats:5/threads:6 38.5 ns 231 ns 36000 ConstIterFixture/run/iterations:6000/repeats:5/threads:6 41.1 ns 246 ns 36000 ConstIterFixture/run/iterations:6000/repeats:5/threads:6 39.6 ns 238 ns 36000 ConstIterFixture/run/iterations:6000/repeats:5/threads:6 38.1 ns 228 ns 36000 ConstIterFixture/run/iterations:6000/repeats:5/threads:6_mean 39.5 ns 237 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:6_median 39.6 ns 238 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:6_stddev 1.20 ns 7.48 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:6_cv 3.03 % 3.16 % 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:12 37.3 ns 446 ns 72000 ConstIterFixture/run/iterations:6000/repeats:5/threads:12 36.2 ns 434 ns 72000 ConstIterFixture/run/iterations:6000/repeats:5/threads:12 35.5 ns 426 ns 72000 ConstIterFixture/run/iterations:6000/repeats:5/threads:12 34.7 ns 416 ns 72000 ConstIterFixture/run/iterations:6000/repeats:5/threads:12 37.6 ns 450 ns 72000 ConstIterFixture/run/iterations:6000/repeats:5/threads:12_mean 36.3 ns 434 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:12_median 36.2 ns 434 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:12_stddev 1.21 ns 13.8 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:12_cv 3.34 % 3.19 % 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:24 12.8 ns 307 ns 144000 ConstIterFixture/run/iterations:6000/repeats:5/threads:24 11.9 ns 286 ns 144000 ConstIterFixture/run/iterations:6000/repeats:5/threads:24 11.6 ns 277 ns 144000 ConstIterFixture/run/iterations:6000/repeats:5/threads:24 13.6 ns 326 ns 144000 ConstIterFixture/run/iterations:6000/repeats:5/threads:24 12.5 ns 300 ns 144000 ConstIterFixture/run/iterations:6000/repeats:5/threads:24_mean 12.5 ns 299 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:24_median 12.5 ns 300 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:24_stddev 0.783 ns 18.8 ns 5 ConstIterFixture/run/iterations:6000/repeats:5/threads:24_cv 6.27 % 6.28 % 5

29 条回复 2023-10-17 10:59:58 +08:00

Geekgogo

2023-10-12 14:10:52 +08:00

大佬

JL1990

2023-10-12 14:14:20 +08:00

强

duandashen

2023-10-12 14:23:11 +08:00

不得不服

o562dsRcFqYl375i

2023-10-12 14:53:22 +08:00

这可能就是热爱吧，羡慕

hankai17

2023-10-12 15:07:32 +08:00

看起来跟我之前维护的很像核心是多队列环形缓冲区

heelerdeer

2023-10-12 15:57:05 +08:00

cmhonker

2023-10-12 16:46:42 +08:00

C 语言太蛋疼了，目前还在用 C 的只剩下信仰了吧。

pengtdyd

2023-10-12 19:03:28 +08:00

c 还是牛皮啊，搞 java ，搞 js ，搞 dart ，最后我还是被迫要搞 c ，底层不懂永远好像是少条腿走路。。。。。。

zhs227

2023-10-12 19:36:23 +08:00

滚动日志支持打成压缩包吗

zooo

2023-10-12 19:45:51 +08:00

纯 C 。。

我宁愿用 C++，都不想用 C

hitmanx

2023-10-12 19:48:35 +08:00

有一点小建议是，可能很多人都像我一样，对你这个挺感兴趣。但是既没看过这个论文，不知道创新在哪里；也不知道你这个 benchmark 究竟每一项测的是什么，甚至这个 benchmark 是你自己创造的而不是广为人知的。

如果你这个卖点就是 performance ，可能和别的产品进行相对比较会比列上几十上百个绝对值更好一些……

zooo

2023-10-12 19:57:42 +08:00

给大佬点赞，能做出来已经很

我以为原版非 C++/C ，还想着用 C++去实现呢，结果原版是 C++实现的。

weidaizi

2023-10-12 19:58:18 +08:00

@huangzongzhuan 谢谢夸奖！纯粹是兴趣，乐在其中，祝你也能对技术保持长久好奇心！

weidaizi

2023-10-12 20:06:19 +08:00

@zhs227 这个的确可以加一下，但是考虑到保持日志库本身的简单，不对外部的有依赖；所以得想一下如何实现
* 自己实现
* 或是从允许商用的 LICENSE 开源压缩库里扒代码
* 或是以 extra 的形式增加一个依赖外部 gzip 的 handler
十分感谢提醒！！！

weidaizi

2023-10-12 20:07:17 +08:00

@zhs227 之后我加好了，一定来回复您！ (*^_^*)

weidaizi

2023-10-12 20:18:30 +08:00

@hitmanx 感谢提醒！的确是一个好建议！我之后会另外开一个库，可以用同一个 benchmark 的参数，来测多个不同的库，届时来回复您~

另外，项目中的 benchmark 确实我没在 README 中解释很详细，这个我的锅
其实就是使用 google benchmark 在测两部分场景
1. 设定最小的测试时间(google benchmark 中的 MinTime)，这时间中尽可能的压力测试写日志，看看当缓冲区高度紧张的情况下，日志前端写入效率如何。这个场景下测试了当线程数为 1/2/${CPU 数量的一半}/${CPU 数量 - 1} 的情况
2. 设定迭代和重复次数(google benchmark 中的 Iterations + Repetitions)，看看当缓冲区没被打满的情况下，能跑多快。这个场景下测试了当线程数为 1/${CPU 数量的一半}/${CPU 数量}/${2 倍 CPU 数量} 的情况

KMpAn8Obw1QhPoEP

2023-10-12 20:27:22 +08:00 via Android

好顶赞

weidaizi

2023-10-12 20:32:37 +08:00

@zooo 啊哈，是的呢，如果感兴趣可以看看我这边的源码，或者也可以看看 Nanolog 那边的源码，虽然思路相同，但是实现是完全不一样的，不过都藏了很多有趣的东西呢！
就比如一个很简单的问题：为什么 haclog 和 Nanolog 都要限定 format 字符串为字符串常量呢？感兴趣可以去代码里探索一下呀，哈哈哈哈哈

weidaizi

2023-10-12 20:33:43 +08:00

@zooo 啊~ 刚刚打漏了~ 谢谢你的夸奖！(*^_^*)

xmtpw

2023-10-12 22:22:23 +08:00

厉害了，大佬

icyalala

2023-10-12 22:26:26 +08:00

我也喜欢 C 。
对于性能对比，建议画个直方图在 Readme 里，这对于宣传性能来说真的很重要。

weidaizi

2023-10-12 22:34:45 +08:00

@icyalala 感谢提醒！上面也有位朋友提到了可以横向对比一下，我之后准备另外开一个库，跑 C/C++ 的不同日志库的 benchmark 看看，这样也可以发现还有什么库是特别快的

bashbot

2023-10-13 10:04:57 +08:00

挺好的轮子，之前也手撸过一个。
想问下多队列环形缓冲区能否保证多线程下日志的时间序？

之前为了保证时间序，写了一个可扩充的多生产单消费环形缓冲区。
但是在数据竞争上有点漏洞，导致多线程竞争时有偶发的丢日志，后来只能加锁搞定，性能下降了好多。
另外，运行时基于标记和级别的日志过滤，都没人用吗，看到好多日志库都没这些功能。

junmoxiao

2023-10-13 10:14:58 +08:00

厉害呀大佬。可以加到 xmake-repo 的仓库里

weidaizi

2023-10-13 10:51:07 +08:00

@bashbot 啊哈，只能保证同一线程的顺序，不能保证多线程的顺序；不过想了一下即使是单缓冲区，其实也是不能完全保证，除非是把加时间戳的代码段都包含在某个锁中，这个就太废了; 回到日志本身，因为带有时间戳，所以即使不同线程在日志文件中乱序，而且乱序也只是在一个消费者循环中，问题也不太大，得看使用场景权衡取舍吧

weidaizi

2023-10-13 10:53:04 +08:00

@junmoxiao 谢谢！我平时不太用 xmake ，我之后去探索一下要如何加，哈~

Masoud2023

2023-10-13 15:37:39 +08:00

昨天没事的时候简单的扫了一眼这个论文

我能不能简单的把这个理解为一个异步的带压缩的结构化 logger...

weidaizi

2023-10-13 17:31:58 +08:00

@Masoud2023 是的，Nanolog 编译会生成一个 decompressor ，如果要以文本形式展示，得通过这程序解压一下日志~

weidaizi

2023-10-17 10:59:58 +08:00

@hitmanx
@icyalala
感谢两位上周的建议，这几天我写了一个 C/C++ Benchmark 项目, 用于横向对比一些知名的或以低延时为目标的 C/C++ 日志库, 并图表化显示
地址: https://github.com/MuggleWei/cc_log_benchmark