- ~50GB MySQL Application
- Main motivation: PostGis
- Migration made with a custom tool(xml2pgcopy) and mysqldump on 45min
#!/bin/sh | |
export GIT_SSH_COMMAND='ssh -o ProxyCommand="connect -S 127.0.0.1:1080 %h %p"' | |
git config --global core.sshCommand 'ssh -o ProxyCommand="connect -S 127.0.0.1:1080 %h %p"' | |
git clone -c=core.sshCommand 'ssh -o ProxyCommand="connect -S 127.0.0.1:1080 %h %p"' git@github.com:larryli/ipv4.git | |
git config core.sshCommand 'ssh -o ProxyCommand="connect -S 127.0.0.1:1080 %h %p"' |
Port: 1080 | |
1. Create a file /YOUR PATH/gitproxy.sh with content: | |
#!/bin/sh | |
nc -X 5 -x 127.0.0.1:1080 "$@" | |
2. Edit your ~/.gitconfig | |
# For git:// |
** chronos | |
#+begin_src emacs-lisp | |
;;;; chronos plugin | |
(use-package chronos | |
:config | |
;; (use-package chronos) | |
;; https://github.com/dxknight/chronos | |
;; now is 17:00 | |
;; 5 gives an expiry time of 17:05 | |
;; 1:30 gives 18:30 |
An animated cheatsheet for smartparens using the example configuration specified here by the smartparens author. Inspired by this tutorial for paredit.
C-M-f | sp-forward-sexp |
C-M-b | sp-backward-sexp |
In response to this brief blog entry, @antirez tweeted for some documentation on high-performance techniques for Redis. What I present here are general high-performance computing (HPC) techniques. The examples are oriented to Redis. but they work well for any program designed to be single- or worker-threaded and asynchronous (e.g. uses epoll).
The motivation for using these techniques is to maximize performance of our system and services. By isolating work, controlling memory, and other tuning, you can achieve significant reduction in latency and increase in throughput.
My perspective comes from the microcosm of my own bare-metal (vs VM), on-premises deployment. It might not be suitable for all scenarios, especially cloud deployments, as I have little experience with HPC there. After some discussion, maybe this can be adapted as [redis.io documentation](https://redis.io/do
国内从 Docker Hub 拉取镜像有时会遇到困难,此时可以配置镜像加速器。Docker 官方和国内很多云服务商都提供了国内加速器服务。
Dockerized 实践 https://github.com/y0ngb1n/dockerized
Ubuntu 16.04+、Debian 8+、CentOS 7+
This is the second article in a series of articles around Rusts new async/await
feature. The first article about interfaces can be found
here.
In this part of the series we want to a look at a mechanism which behaves very
different in Rust than in all other languages which feature async/await
support. This mechanism is Cancellation.
I've been working with Apache Kafka for over 7 years. I inevitably find myself doing the same set of activities while I'm developing or working with someone else's system. Here's a set of Kafka productivity hacks for doing a few things way faster than you're probably doing them now. 🔥
CPU Usage :
(1 - avg(irate(node_cpu_seconds_total{mode="idle"}[10m])) by (instance)) * 100
Memory Usage :
100 * (1 - ((avg_over_time(node_memory_MemFree_bytes[10m]) + avg_over_time(node_memory_Cached_bytes[10m]) + avg_over_time(node_memory_Buffers_bytes[10m])) / avg_over_time(node_memory_MemTotal_bytes[10m])))