Why?
Because we wanted to achive the following while developing a webapp using websockets:
Static serving (nginx), Django application (gunicorn) and Websockets service (twisted)
- on the same IP
L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns
Compress 1K bytes with Zippy ............. 3,000 ns = 3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns = 20 µs
SSD random read ........................ 150,000 ns = 150 µs
Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs
| 1. Install Linux updates, set time zones, followed by GCC and Make | |
| sudo yum -y update | |
| sudo ln -sf /usr/share/zoneinfo/America/Indianapolis \ | |
| /etc/localtime | |
| sudo yum -y install gcc make | |
| 2. Download, Untar and Make Redis 2.8 (check here http://redis.io/download) |
| [ | |
| "Automotive", | |
| "Budgeting", | |
| "HVAC", | |
| "Heaters", | |
| "Hydraulics", | |
| "Logistics Management", | |
| "Management", | |
| "Negotiation", | |
| "Project Planning", |
| ### Install OpenJDK | |
| cd ~ | |
| sudo apt-get update | |
| sudo apt-get install openjdk-7-jre-headless -y | |
| ### Download and Install ElasticSearch | |
| ### Check http://www.elasticsearch.org/download/ for latest version of ElasticSearch and replace wget link below | |
| wget https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.3.1.deb | |
| sudo dpkg -i elasticsearch-1.3.1.deb |
| <html> | |
| <head> | |
| <title>D3 Axis Example</title> | |
| <script src="http://d3js.org/d3.v2.js"></script> | |
| </head> | |
| <body> | |
| <button id="rescale" onclick="rescale();">Rescale</button> | |
| <script> | |
| var width = 700, |
| #!/usr/bin/env python | |
| # -*- coding: utf-8 -*- | |
| """ | |
| pip install networkx distance pattern | |
| In Flipboard's article[1], they kindly divulge their interpretation | |
| of the summarization technique called LexRank[2]. |
| http://www.depesz.com/2011/12/02/the-secret-ingredient-in-the-webscale-sauce/ | |
| http://www.craigkerstiens.com/2012/11/30/sharding-your-database/ | |
| https://github.com/markokr/pghashlib | |
| http://www.niwi.be/2013/03/06/table-partitioning-with-postgresql/ | |
| https://blog.engineyard.com/2013/scaling-postgresql-performance-table-partitioning | |
| http://instagram-engineering.tumblr.com/post/10853187575/sharding-ids-at-instagram | |
| http://instagram-engineering.tumblr.com/post/40781627982/handling-growth-with-postgres-5-tips-from-instagram | |
| http://media.postgresql.org/sfpug/instagram_sfpug.pdf |