dupuy

Markdown and reStructuredText

GitHub supports several lightweight markup languages for documentation; the most popular ones (generally, not just at GitHub) are Markdown and reStructuredText. Markdown is sometimes considered easier to use, and is often preferred when the purpose is simply to generate HTML. On the other hand, reStructuredText is more extensible and powerful, with native support (not just embedded HTML) for tables, as well as things like automatic generation of tables of contents.

hellerbarde

Latency numbers every programmer should know

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

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

graphadvantage

##Neo4j GraphGist - Enterprise Architectures: Real-time Graph Updates using Kafka Messaging

Neo4j Use Case: Low Latency Graph Analytics & OLTP - Update 1M Nodes in 90 secs with Kafka and Neo4j Bolt

Introduction

A recent Neo4j whitepaper describes how Monsanto is performing real-time updates on a 600M node Neo4j graph using Kafka to consume data extracted from a large Oracle Exadata instance.

This modern data architecture combines a fast, scalable messaging platform (Kafka) for low latency data provisioning and an enterprise graph database (Neo4j) for high performance, in-memory analytics & OLTP - creating new and powerful real-time graph analytics capabilities for your enterprise applications.

kddnewton

require "json"

struct = { "a" => 1, "b" => 2, "c" => [1, 2, 3], "d" => [{ "e" => 3 }, nil, false, true, [], {}] }
source = JSON.dump(struct)

tokens = []
index = 0

until source.empty?
  tokens <<