启动新会话:
tmux [new -s 会话名 -n 窗口名]
恢复会话:
tmux at [-t 会话名]
// Use Gists to store code you would like to remember later on | |
console.log(window); // log the "window" object to the console |
URL | HTTP Verb | Action |
---|---|---|
/photos/ | GET | index |
/photos/new | GET | new |
/photos | POST | create |
/photos/:id | GET | show |
/photos/:id/edit | GET | edit |
/photos/:id | PATCH/PUT | update |
/photos/:id | DELETE | destroy |
I was talking to a coworker recently about general techniques that almost always form the core of any effort to write very fast, down-to-the-metal hot path code on the JVM, and they pointed out that there really isn't a particularly good place to go for this information. It occurred to me that, really, I had more or less picked up all of it by word of mouth and experience, and there just aren't any good reference sources on the topic. So… here's my word of mouth.
This is by no means a comprehensive gist. It's also important to understand that the techniques that I outline in here are not 100% absolute either. Performance on the JVM is an incredibly complicated subject, and while there are rules that almost always hold true, the "almost" remains very salient. Also, for many or even most applications, there will be other techniques that I'm not mentioning which will have a greater impact. JMH, Java Flight Recorder, and a good profiler are your very best friend! Mea
#!/bin/bash | |
# install CUDA Toolkit v8.0 | |
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network)) | |
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb" | |
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG} | |
sudo dpkg -i ${CUDA_REPO_PKG} | |
sudo apt-get update | |
sudo apt-get -y install cuda |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
docker用来隔离应用还是很方便的,一来本身的操作较为简单,二来资源占用也比虚拟机要小得多,三来也较为安全,因为像数据库这样的应用不会再全局暴露端口,同时应用间的通信通过加密和端口转发,更加安全。
Gitlab是目前比较流行的开源类Github代码管理平台。Gitlab使用Rails开发,使用PostgreSQL或MySQL数据库,Redis做缓存。一般自己搭建私有代码仓库,Gitlab通常是首选。这里简单介绍一下dockerized Gitlab。
Gitlab的docker镜像早已有人做好了,并且维护相当不错。大家可以前往其GitHub仓库了解该镜像的情况。官方repo的readme中已经有详细的安装配置方案,这里我简单的梳理一下部署流程。
这里以Ubuntu 14.04发行版为例,在bash中输入一下命令安装最新的docker:
A curated list of AWS resources to prepare for the AWS Certifications
A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.
For more about AWS and AWS Certifications and updates to this Gist you should follow me @leonardofed
CREATE TABLE IF NOT EXISTS `country` ( | |
`id` int(11) NOT NULL AUTO_INCREMENT, | |
`iso` char(2) NOT NULL, | |
`name` varchar(80) NOT NULL, | |
`nicename` varchar(80) NOT NULL, | |
`iso3` char(3) DEFAULT NULL, | |
`numcode` smallint(6) DEFAULT NULL, | |
`phonecode` int(5) NOT NULL, | |
PRIMARY KEY (`id`) | |
) ENGINE=MyISAM DEFAULT CHARSET=latin1; |