git reset –hard HEAD^ 回退到上个版本
git reset –hard HEAD~3 回退到前3次提交之前，以此类推，回退到n次提交之前
git reset –hard commit_id 退到/进到 指定commit的sha码
强推到远程：
git push origin HEAD –force
Git回滚代码到某个commit
发表评论
分类目录归档：Linux
简单记录一下青龙面板的设置
如何部署就不赘述了，网上很多文章都有介绍。
今天早上发现自制的黑铁威马NAS的内存占用达到了70%，（安装的是一根2G的内存条），再一看发现是docker的容器很吃内存。
我运行了一个librespeed测速服务器，一个自动签到，一个青龙面板。可以看到青龙面板和自动签到就占用了接近1.2GB的内存。
然后拆机更换为一根4GB的内存，由于当初配置的时候设置的镜像是不自动启动的，所以必须手工启动它们。结果手贱在自动重新启动应用前面打了对勾并按下了应用，等了好久还是打不开青龙面板的页面，再一看青龙的容器居然被删除了！
瞬间一万个羊驼从脑海奔过，这特么的真是一个手贱导致要浪费大把时间的节奏啊，关键是距上一次从0开始设置已经过去几个月时间了，都已经忘记了具体操作步骤了。
没办法，这次就多花点时间精力记录一下，免得下次设置时候又要浪费时间搜索爬文。
青龙面板运行后设置完账户密码，登录到面板界面。
然后在ssh下面用root用户运行
docker ps
显示所有容器。
然后选择你需要进入的容器名称，比如我的青龙是f8ed1db3309c
运行docker exec -it f8ed1db3309c /bin/bash 进入青龙容器
然后运行ql check，坐等一两分钟，会输出下面一堆信息。
/ql/shell/check.sh: line 94: /root/.bashrc: No such file or directory
## 开始执行… 2022-10-18 08:23:34
=====> 开始检测
changed 1 package in 21s
Progress: resolved 1, reused 0, downloaded 0, added 0
Progress: resolved 3, reused 0, downloaded 3, added 0
Progress: resolved 4, reused 0, downloaded 3, added 0
Progress: resolved 35, reused 0, downloaded 17, added 0
Progress: resolved 54, reused 0, downloaded 34, added 0
Progress: resolved 83, reused 2, downloaded 57, added 0
WARN deprecated uuid@3.4.0: Please upgrade to version 7 or higher. Older versions may use Math.random() in certain circumstances, which is known to be problematic. See https://v8.dev/blog/math-random for details.
Progress: resolved 127, reused 7, downloaded 95, added 0
Progress: resolved 174, reused 14, downloaded 133, added 0
Packages: +3 -2
+++–
Progress: resolved 198, reused 17, downloaded 179, added 3, done
/root/.local/share/pnpm/global/5:
– pm2 5.2.0
+ pm2 5.2.2
WARN Issues with peer dependencies found
.
└─┬ ts-node 10.9.1
└── ✕ missing peer @types/node@”*”
Peer dependencies that should be installed:
@types/node@”*”
Done in 10.9s
—> 1. 复制通知文件
—> 复制一份 /ql/sample/notify.py 为 /ql/data/scripts/notify.py
‘/ql/sample/notify.py’ -> ‘/ql/data/scripts/notify.py’
—> 复制一份 /ql/sample/notify.js 为 /ql/data/scripts/sendNotify.js
‘/ql/sample/notify.js’ -> ‘/ql/data/scripts/sendNotify.js’
—> 通知文件复制完成
—> 2. 复制nginx配置文件
‘/ql/docker/nginx.conf’ -> ‘/etc/nginx/nginx.conf’
‘/ql/docker/front.conf’ -> ‘/etc/nginx/conf.d/front.conf’
—> 配置文件复制完成
=====> 检测面板
<!DOCTYPE html>
<html>
<head>
<meta charset=”utf-8″ />
<meta
name=”viewport”
content=”width=device-width, initial-scale=1, maximum-scale=1, minimum-scale=1, user-scalable=no”
/>
<link rel=”shortcut icon” type=”image/x-icon” href=”/images/favicon.svg” />
<link rel=”stylesheet” href=”/umi.1a1e4a3d.css” />
<script>
window.routerBase = “/”;
</script>
<script>
//! umi version: 3.5.34
</script>
</head>
<body>
<div id=”root”></div>
<script src=”https://gw.alipayobjects.com/os/lib/react/16.13.1/umd/react.production.min.js”></script>
<script src=”https://gw.alipayobjects.com/os/lib/react-dom/16.13.1/umd/react-dom.production.min.js”></script>
<script src=”/umi.171fdc21.js”></script>
</body>
</html>
=====> 面板服务启动正常
=====> 检测nginx服务
94 root 0:00 nginx: master process nginx -c /etc/nginx/nginx.conf
95 root 0:00 nginx: worker process
96 root 0:00 nginx: worker process
=====> nginx服务正常
—> pm2日志
2022-10-18T07:26:42: info: ✌️ DB loaded
2022-10-18T07:26:42: info: ✌️ Init file down
2022-10-18T07:26:43: info: ✌️ Sentry loaded
2022-10-18T07:26:45: info: ✌️ Dependency Injector loaded
2022-10-18T07:26:45: info: ✌️ Express loaded
2022-10-18T07:26:45: info: ✌️ init data loaded
2022-10-18T07:26:45: info: ✌️ link deps loaded
2022-10-18T07:26:45: info: ✌️ init task loaded
2022-10-18T07:26:46: info: ✌️ Sock loaded
2022-10-18T07:26:46: info: [创建interval任务]，任务ID: token，任务名: 生成token，执行命令: node /ql/static/build/token.js
2022-10-18T07:26:46: debug: ✌️ Back server launched on port 5600
2022-10-18T07:26:47: info: 任务 node /ql/static/build/token.js 进程id: 228 退出，退出码 0
2022-10-18T08:16:49: info: [取消定时任务]，任务名：KR
2022-10-18T08:16:49: info: [创建cron任务]，任务ID: 1，cron: 0 1 * * *，任务名: KR，执行命令: ql repo “https://github.com/KingRan/KR.git” “” “” “” “” “”
2022-10-18T08:17:12: error: 执行任务 ql repo “https://github.com/KingRan/KR.git” “” “” “” “” “” 失败，时间：2022-10-18 8:17:12, 错误信息：”Cloning into ‘/ql/data/repo/KingRan_KR’…\n”
2022-10-18T08:18:59: info: 任务 task KingRan_KR/h5st.ts 进程id: 10679 退出，退出码 0
2022-10-18T08:19:17: info: 任务 task KingRan_KR/jd_bean_change_pro.js 进程id: 12067 退出，退出码 0
2022-10-18T08:23:15: info: 任务 ql repo “https://github.com/KingRan/KR.git” “” “” “” “” “” 进程id: 239 退出，退出码 0
=====> 检测后台
{“code”:401,”message”:”jwt malformed”}
=====> 后台服务启动正常
启动面板服务
启动定时任务服务
启动公开服务
=====> 检测结束
## 执行结束… 2022-10-18 08:24:20 耗时 46 秒
运行之后应该就解决了脚本的依赖关系的问题。不用手工一个个去设置了。
再然后去青龙面板添加名称为JD_COOKIE的变量，填入你的cookie即可，至于如何获取京东cookie，大家自行搜索爬文，这里就不赘述了。
再接下来去青龙面板的订阅管理里面按下图添加KR库然后运行一下即可，各个脚本就会被添加到定时任务里面。
对了，在运行订阅管理脚本之前去青龙面板的配置文件里，改一下下面这个参数即可，加上ts。
## ql repo命令拉取脚本时需要拉取的文件后缀，直接写文件后缀名即可
RepoFileExtensions=”js py ts”
搞定。
20221021 update
还是需要在青龙面板里面手工安装依赖的
NodeJs 依赖库
crypto-js
prettytable
dotenv
jsdom
date-fns
tough-cookie
tslib
ws@7.4.3
ts-md5
jsdom -g
jieba
fs
form-data
json5
global-agent
png-js
@types/node
require
typescript
js-base64
axios
moment
got
md5
request
download
tunnel
ws
qrcode-terminal
Python3 依赖库
requests
canvas
ping3
jieba
aiohttp
Linux 依赖库安装失败，不清楚是什么情况。
bizCode
bizMsg
lxml
青龙面板配置备份
openwrt：
root@OpenWrt:~# find / -name env.sh
/opt/overlay2/d9479246f2de51b54782fd2275cb4d8dedc571cfe4fe714d91a16fb5c98a9a0e/merged/ql/data/config/env.sh
/opt/overlay2/d9479246f2de51b54782fd2275cb4d8dedc571cfe4fe714d91a16fb5c98a9a0e/diff/ql/data/config/env.sh
/opt/overlay2/4edf900d43ecb765c9e85a4c0c849697cb5053e3ff40708754d5d372e7cbcb83/diff/ql/data/config/env.sh
铁威马：
]# find / -name env.sh
/mnt/md0/appdata/docker/overlay2/63c768eae6e9faf7564128ea62dfdda9c0dd3c4e2fe89dd7b932812716e8efd7/merged/ql/data/config/env.sh
/mnt/md0/appdata/docker/overlay2/63c768eae6e9faf7564128ea62dfdda9c0dd3c4e2fe89dd7b932812716e8efd7/diff/ql/data/config/env.sh
复制到新的面板下面对应文件夹覆盖即可
经测试不行，并不会显示，而且重启青龙会被清空。
青龙面板安装依赖库
我是在铁威马的docker里面操作的，openwrt以及其他系统下面的docker应该是大同小异。
docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
5b46dabac8c9 whyour/qinglong “./docker/docker-e…” 9 hours ago Up 9 hours whyour_qinglong
73d7315f0339 adolfintel/speedtest “docker-php-entryp…” 9 hours ago Up 9 hours 0.0.0.0:70->80/tcp adolfintel_speedtest
docker exec -it 5b46dabac8c9 bash
输入下面的安装命令，回车，坐等结束。
curl -fsSL https://raw.githubusercontent.com/FlechazoPh/QLDependency/main/Shell/QLOneKeyDependency.sh | sh
然后去青龙面板里面手工增加对应的依赖管理。
NodeJs 依赖库
crypto-js
prettytable
dotenv
jsdom
date-fns
tough-cookie
tslib
ws@7.4.3
ts-md5
jsdom -g
jieba
fs
form-data
json5
global-agent
png-js
@types/node
require
typescript
js-base64
axios
Python3 依赖库
requests
canvas
ping3
jieba
aiohttp
Linux 依赖库
bizCode
bizMsg
lxml
在青龙面板依赖库中添加后会自动执行安装，点击日志或者刷新页面可以查看是否安装成功，若安装失败可以点击重新安装。如果重新安装仍然失败，那要检查是不是有其他的问题。
比如linux的依赖就会安装失败。
输入 docker inspect 容器名 去查看容器地址。
# docker inspect 5b46dabac8c9
此处省略若干行。。。。。。
“MergedDir”: “/mnt/md0/appdata/docker/overlay2/63c768eae6e9faf7564128ea62dfdda9c0dd3c4e2fe89dd7b932812716e8efd7/merged”,
于是顺藤摸瓜找到目标文件夹是这个。
/mnt/md0/appdata/docker/overlay2/63c768eae6e9faf7564128ea62dfdda9c0dd3c4e2fe89dd7b932812716e8efd7/merged/usr/lib/python3.10
然后去https://pypi.org/project/lxml/#files 下载对应的包放到这个文件夹下面。
直接进入容器
docker exec -it 5b46dabac8c9 bash
然后，创建一个虚拟环境然后来安装，这样就没问题了。否则会报错。
:/ql $ pip install lxml
Looking in indexes: https://pypi.doubanio.com/simple/
Collecting lxml
Downloading https://pypi.doubanio.com/packages/a7/52/e72cbbbf43845313b9adfa7820aa75898b3832bd6bacc3bdb18dfdcbd8f8/lxml-4.9.1-cp310-cp310-musllinux_1_1_x86_64.whl (7.6 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 7.6/7.6 MB 14.5 MB/s eta 0:00:00
Installing collected packages: lxml
Successfully installed lxml-4.9.1
WARNING: Running pip as the ‘root’ user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
运行下面指令可破。
source tutorial-env/bin/activate
然后再运行 pip install lxml
:/ql $ pip install lxml
Looking in indexes: https://pypi.doubanio.com/simple/
Collecting lxml
Downloading https://pypi.doubanio.com/packages/a7/52/e72cbbbf43845313b9adfa7820aa75898b3832bd6bacc3bdb18dfdcbd8f8/lxml-4.9.1-cp310-cp310-musllinux_1_1_x86_64.whl (7.6 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 7.6/7.6 MB 6.7 MB/s eta 0:00:00
Installing collected packages: lxml
Successfully installed lxml-4.9.1
成功搞定。
但是在青龙面板里面linux的依赖依旧安装不成功，搞不懂了。
(tutorial-env) root@TNAS-EDDB:/ql $ pip install bizMsg
Looking in indexes: https://pypi.doubanio.com/simple/
ERROR: Could not find a version that satisfies the requirement bizMsg (from versions: none)
ERROR: No matching distribution found for bizMsg
(tutorial-env) root@TNAS-EDDB:/ql $ pip install bizCode
Looking in indexes: https://pypi.doubanio.com/simple/
ERROR: Could not find a version that satisfies the requirement bizCode (from versions: none)
ERROR: No matching distribution found for bizCode
其他两个目前pip安装失败。有时间再研究。
git下载指定版本的代码并制作patch以及如何打patch
首先使用git clone把代码更新到本地。
使用git log –grep=word 搜索指定的版本。
gcc@gcc-x64:/mnt/AX3600$ git log –grep AX3600
commit 9d8a34c9abb6c13f9bebc28d9c4c10fe512491d4 (HEAD -> newBranch)
Author: lean <coolsnowwolf@gmail.com>
Date: Mon Jun 14 20:08:28 2021 +0800
ipq807x: add Xiaomi AX3600 and ath11k support
生成指定版本的patch：
git format-patch -1 9d8a34c9abb6c13f9bebc28d9c4c10fe512491d4
应用patch：
先检查patch文件：git apply –stat newpatch.patch
检查能否应用成功：git apply –check newpatch.patch
打补丁：git am –signoff < newpatch.patch
(使用-s或–signoff选项，可以commit信息中加入Signed-off-by信息)
如果需要撤回刚才打上的那个Patch，使用命令：git apply -R ***.patch
参考：
https://blog.csdn.net/M_Eve/article/details/84327219
https://www.zhangshengrong.com/p/QrXebElo1d/
https://blog.csdn.net/robertsong2004/article/details/46893169
20220805 updated
使用git apply –reject file.patch 这个命令会自动合入不冲突的代码，然后保留冲突的部分，同时在冲突的文件夹下面会生成后缀为.rej的文件，用于保存没有合并进去的部分，可以参考这个进行冲突解决。
解决完冲突后，删除后缀为.rej文件，并执行git add . 添加改动到暂存区，然后git commit -m “注释语句” 增加commit。
最后git log 查看刚才的commit，然后生成指定版本的patch：
git format-patch -1 9d8a34c9abb6c13f9bebc28d9c4c10fe512491d4
参考网址:
https://www.its203.com/article/salmon_zhang/97015801
unixbench使用方法
wget –no-check-certificate https://github.com/teddysun/across/raw/master/unixbench.sh
chmod +x unixbench.sh
./unixbench.sh
登录ssh之后，输入上面的脚本回车即可开始测试。
I5-8250U在hyper-v下面使用unixbench测试性能
BYTE UNIX Benchmarks (Version 5.1.3)
System: gcc-x64: GNU/Linux
OS: GNU/Linux — 5.4.0-122-generic — #138-Ubuntu SMP Wed Jun 22 15:00:31 UTC 2022
Machine: x86_64 (x86_64)
Language: en_US.utf8 (charmap=”UTF-8″, collate=”UTF-8″)
CPU 0: Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz (3600.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
CPU 1: Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz (3600.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
CPU 2: Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz (3600.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
CPU 3: Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz (3600.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
CPU 4: Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz (3600.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
CPU 5: Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz (3600.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
CPU 6: Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz (3600.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
CPU 7: Intel(R) Core(TM) i5-8250U CPU @ 1.60GHz (3600.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET
06:46:06 up 7:49, 2 users, load average: 0.00, 0.00, 0.00; runlevel 5
————————————————————————
Benchmark Run: Sat Jul 23 2022 06:46:06 – 07:14:12
8 CPUs in system; running 1 parallel copy of tests
Dhrystone 2 using register variables 42608524.8 lps (10.0 s, 7 samples)
Double-Precision Whetstone 6489.4 MWIPS (9.9 s, 7 samples)
Execl Throughput 4129.9 lps (30.0 s, 2 samples)
File Copy 1024 bufsize 2000 maxblocks 635787.5 KBps (30.0 s, 2 samples)
File Copy 256 bufsize 500 maxblocks 169590.5 KBps (30.0 s, 2 samples)
File Copy 4096 bufsize 8000 maxblocks 1985937.5 KBps (30.0 s, 2 samples)
Pipe Throughput 865156.9 lps (10.0 s, 7 samples)
Pipe-based Context Switching 20744.7 lps (10.0 s, 7 samples)
Process Creation 7347.1 lps (30.0 s, 2 samples)
Shell Scripts (1 concurrent) 10401.9 lpm (60.0 s, 2 samples)
Shell Scripts (8 concurrent) 2980.9 lpm (60.0 s, 2 samples)
System Call Overhead 537140.1 lps (10.0 s, 7 samples)
System Benchmarks Index Values BASELINE RESULT INDEX
Dhrystone 2 using register variables 116700.0 42608524.8 3651.1
Double-Precision Whetstone 55.0 6489.4 1179.9
Execl Throughput 43.0 4129.9 960.5
File Copy 1024 bufsize 2000 maxblocks 3960.0 635787.5 1605.5
File Copy 256 bufsize 500 maxblocks 1655.0 169590.5 1024.7
File Copy 4096 bufsize 8000 maxblocks 5800.0 1985937.5 3424.0
Pipe Throughput 12440.0 865156.9 695.5
Pipe-based Context Switching 4000.0 20744.7 51.9
Process Creation 126.0 7347.1 583.1
Shell Scripts (1 concurrent) 42.4 10401.9 2453.3
Shell Scripts (8 concurrent) 6.0 2980.9 4968.2
System Call Overhead 15000.0 537140.1 358.1
========
System Benchmarks Index Score 1065.4
————————————————————————
Benchmark Run: Sat Jul 23 2022 07:14:12 – 07:42:44
8 CPUs in system; running 8 parallel copies of tests
Dhrystone 2 using register variables 153654544.7 lps (10.0 s, 7 samples)
Double-Precision Whetstone 34421.6 MWIPS (11.5 s, 7 samples)
Execl Throughput 13329.0 lps (29.9 s, 2 samples)
File Copy 1024 bufsize 2000 maxblocks 712096.5 KBps (30.0 s, 2 samples)
File Copy 256 bufsize 500 maxblocks 180312.6 KBps (30.0 s, 2 samples)
File Copy 4096 bufsize 8000 maxblocks 2250174.5 KBps (30.0 s, 2 samples)
Pipe Throughput 3111422.7 lps (10.0 s, 7 samples)
Pipe-based Context Switching 601761.1 lps (10.0 s, 7 samples)
Process Creation 22973.2 lps (30.0 s, 2 samples)
Shell Scripts (1 concurrent) 23595.3 lpm (60.0 s, 2 samples)
Shell Scripts (8 concurrent) 3313.3 lpm (60.0 s, 2 samples)
System Call Overhead 1990193.6 lps (10.0 s, 7 samples)
System Benchmarks Index Values BASELINE RESULT INDEX
Dhrystone 2 using register variables 116700.0 153654544.7 13166.6
Double-Precision Whetstone 55.0 34421.6 6258.5
Execl Throughput 43.0 13329.0 3099.8
File Copy 1024 bufsize 2000 maxblocks 3960.0 712096.5 1798.2
File Copy 256 bufsize 500 maxblocks 1655.0 180312.6 1089.5
File Copy 4096 bufsize 8000 maxblocks 5800.0 2250174.5 3879.6
Pipe Throughput 12440.0 3111422.7 2501.1
Pipe-based Context Switching 4000.0 601761.1 1504.4
Process Creation 126.0 22973.2 1823.3
Shell Scripts (1 concurrent) 42.4 23595.3 5564.9
Shell Scripts (8 concurrent) 6.0 3313.3 5522.1
System Call Overhead 15000.0 1990193.6 1326.8
========
System Benchmarks Index Score 3005.4
测试的时候，由于笔记本散热原因，CPU基本上长时间在2.1Ghz运行。
下面贴一个J1900CPU，宿主机运行openwrt，在docker里运行ubuntu使用unixbench测试的得分。
BYTE UNIX Benchmarks (Version 5.1.3)
System: OpenWrt: GNU/Linux
OS: GNU/Linux — 5.15.35 — #0 SMP Mon Apr 25 11:18:22 2022
Machine: x86_64 (x86_64)
Language: en_US.utf8 (charmap=”ANSI_X3.4-1968″, collate=”ANSI_X3.4-1968″)
CPU 0: Intel(R) Celeron(R) CPU J1900 @ 1.99GHz (4000.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET, Intel virtualization
CPU 1: Intel(R) Celeron(R) CPU J1900 @ 1.99GHz (4000.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET, Intel virtualization
CPU 2: Intel(R) Celeron(R) CPU J1900 @ 1.99GHz (4000.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET, Intel virtualization
CPU 3: Intel(R) Celeron(R) CPU J1900 @ 1.99GHz (4000.0 bogomips)
Hyper-Threading, x86-64, MMX, Physical Address Ext, SYSENTER/SYSEXIT, SYSCALL/SYSRET, Intel virtualization
15:47:42 up 7 days, 12:59, 0 users, load average: 0.74, 0.33, 0.14; runlevel
————————————————————————
Benchmark Run: Fri Jul 22 2022 15:47:42 – 16:15:46
4 CPUs in system; running 1 parallel copy of tests
Dhrystone 2 using register variables 11870208.3 lps (10.0 s, 7 samples)
Double-Precision Whetstone 2427.7 MWIPS (10.2 s, 7 samples)
Execl Throughput 1596.9 lps (30.0 s, 2 samples)
File Copy 1024 bufsize 2000 maxblocks 242133.1 KBps (30.0 s, 2 samples)
File Copy 256 bufsize 500 maxblocks 66194.7 KBps (30.0 s, 2 samples)
File Copy 4096 bufsize 8000 maxblocks 637394.7 KBps (30.0 s, 2 samples)
Pipe Throughput 466222.1 lps (10.0 s, 7 samples)
Pipe-based Context Switching 41094.0 lps (10.0 s, 7 samples)
Process Creation 2470.1 lps (30.0 s, 2 samples)
Shell Scripts (1 concurrent) 3385.2 lpm (60.0 s, 2 samples)
Shell Scripts (8 concurrent) 1181.3 lpm (60.0 s, 2 samples)
System Call Overhead 376589.3 lps (10.0 s, 7 samples)
System Benchmarks Index Values BASELINE RESULT INDEX
Dhrystone 2 using register variables 116700.0 11870208.3 1017.2
Double-Precision Whetstone 55.0 2427.7 441.4
Execl Throughput 43.0 1596.9 371.4
File Copy 1024 bufsize 2000 maxblocks 3960.0 242133.1 611.4
File Copy 256 bufsize 500 maxblocks 1655.0 66194.7 400.0
File Copy 4096 bufsize 8000 maxblocks 5800.0 637394.7 1099.0
Pipe Throughput 12440.0 466222.1 374.8
Pipe-based Context Switching 4000.0 41094.0 102.7
Process Creation 126.0 2470.1 196.0
Shell Scripts (1 concurrent) 42.4 3385.2 798.4
Shell Scripts (8 concurrent) 6.0 1181.3 1968.8
System Call Overhead 15000.0 376589.3 251.1
========
System Benchmarks Index Score 475.5
————————————————————————
Benchmark Run: Fri Jul 22 2022 16:15:46 – 16:43:51
4 CPUs in system; running 4 parallel copies of tests
Dhrystone 2 using register variables 46351886.4 lps (10.0 s, 7 samples)
Double-Precision Whetstone 9709.4 MWIPS (10.2 s, 7 samples)
Execl Throughput 4547.2 lps (29.8 s, 2 samples)
File Copy 1024 bufsize 2000 maxblocks 422497.9 KBps (30.0 s, 2 samples)
File Copy 256 bufsize 500 maxblocks 123753.2 KBps (30.0 s, 2 samples)
File Copy 4096 bufsize 8000 maxblocks 1023713.4 KBps (30.0 s, 2 samples)
Pipe Throughput 1829630.5 lps (10.0 s, 7 samples)
Pipe-based Context Switching 269682.6 lps (10.0 s, 7 samples)
Process Creation 9473.4 lps (30.0 s, 2 samples)
Shell Scripts (1 concurrent) 10449.0 lpm (60.0 s, 2 samples)
Shell Scripts (8 concurrent) 1413.0 lpm (60.1 s, 2 samples)
System Call Overhead 1377797.4 lps (10.0 s, 7 samples)
System Benchmarks Index Values BASELINE RESULT INDEX
Dhrystone 2 using register variables 116700.0 46351886.4 3971.9
Double-Precision Whetstone 55.0 9709.4 1765.3
Execl Throughput 43.0 4547.2 1057.5
File Copy 1024 bufsize 2000 maxblocks 3960.0 422497.9 1066.9
File Copy 256 bufsize 500 maxblocks 1655.0 123753.2 747.8
File Copy 4096 bufsize 8000 maxblocks 5800.0 1023713.4 1765.0
Pipe Throughput 12440.0 1829630.5 1470.8
Pipe-based Context Switching 4000.0 269682.6 674.2
Process Creation 126.0 9473.4 751.9
Shell Scripts (1 concurrent) 42.4 10449.0 2464.4
Shell Scripts (8 concurrent) 6.0 1413.0 2355.0
System Call Overhead 15000.0 1377797.4 918.5
========
System Benchmarks Index Score 1364.1
可以看出，J1900的CPU还是很强悍的。I5-8250U理论上相当于5倍的J1900性能，但是由于在hyper-v虚拟机下面测试，性能折损较大。
关于不同CPU性能测试，可以参考这篇文章。
http://www.wifizoo.net/archives/2017
linux下使用du指令查看所有文件夹大小并排序输出
du -hs * | sort -hr
du -s * | sort -hr | head 选出排在前面的10个，
du -s * | sort -hr| tail 选出排在后面的10个。
如果显示不正常，那么使用这个指令可以用非 【human-readable ，print sizes in human readable format (e.g., 1K 234M 2G)】方式显示。
du -s * | sort -nr
linux批量更改文件后缀名的脚本
#!/bin/sh
##change filename of *.txt to *.doc
##Written by adai
read -p "Please input a directory:" f
echo "Old filename:"
ls $f
for i in `ls $f | grep '.pcm' | awk -F"." '{print $1}'`
do
mv $f/$i.pcm $f/$i.mp4
done
echo "New filename:"
ls $f
docker进入容器命令
root@OpenWrt:~# docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
7ec95c1b7483 neurodebian:latest “bash” 2 days ago Up 2 days debian
9ea3192cbb9a adolfintel/speedtest:latest “docker-php-entrypoi…” 7 days
docker exec -it 7ec95c1b7483 /bin/bash 即可进入
如果从这个容器退出，容器不会停止，这就是为什么使用 docker exec 的原因。
root@OpenWrt:/# exit
exit