jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

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

ragingwind

Backend Architectures

Twitter

ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats

• Introduce Gizzard of Twitter - 트위터의 새로운 분산 관리 라이브러리 Gizzard를 소개합니다.
• The Architecture Twitter Uses to Deal with 150M Active Users, 300K QPS, a 22 MB/S Firehose, and Send Tweets in Under 5 Seconds
• Scaling Twitter: Making Twitter 10000 Percent Faster

ChrisPenner

Optics By Example Cheat Sheets

The following are appendices from Optics By Example, a comprehensive guide to optics from beginner to advanced! If you like the content below, there's plenty more where that came from; pick up the book!

• Operators
• Composition Guide
• Substitution Guide
• Optical Constarints and Types

Operator Cheat Sheet

etorreborre

class Outer {
  class Inner
  type Type
}
trait Trait
object Object extends Outer {
  val inner = new Inner
}
class OuterP[A] {
  class InnerP[B]

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

scy

Opening and closing an SSH tunnel in a shell script the smart way

I recently had the following problem:

• From an unattended shell script (called by Jenkins), run a command-line tool that accesses the MySQL database on another host.
• That tool doesn't know that the database is on another host, plus the MySQL port on that host is firewalled and not accessible from other machines.

We didn't want to open the MySQL port to the network, but it's possible to SSH from the Jenkins machine to the MySQL machine. So, basically you would do something like

ssh -L 3306:localhost:3306 remotehost

bitemyapp

The Learning Haskell guide has been moved to a git repo to enable outside contribution

Find it here: https://github.com/bitemyapp/learnhaskell

jdegoes

object BenchmarkCommon {
  import scala.util.Random
  
  val DatasetSize = 10000
  val Iterations = 10000
  val ArrayPoolSize = 1000
  val ArrayPool = {
    def randomArray(): Array[Int] = {
      val array = new Array[Int](DatasetSize)
      

purefn

scala> val o: Option[Int] = Some(5)
o: Option[Int] = Some(5)

scala> val l: List[Int] = List(10)
l: List[Int] = List(10)

scala> l flatMap (_ => o)
res1: List[Int] = List(5)

scala> o flatMap (_ => l)