$ docker
(function() { | |
function DateDiff(date1, date2) { | |
this.days = null; | |
this.hours = null; | |
this.minutes = null; | |
this.seconds = null; | |
this.date1 = date1; | |
this.date2 = date2; |
#!/bin/bash | |
protected_branch='master' | |
current_branch=$(git symbolic-ref HEAD | sed -e 's,.*/\(.*\),\1,') | |
RED='\033[0;31m' | |
GREEN='\033[1;32m' | |
YELLOW='\033[1;33m' | |
NC='\033[0m' # No Color | |
# only run this if you are pushing to master | |
if [[ $current_branch = $protected_branch ]] ; then |
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