etorreborre

import scalaz.stream.{Process1, Process, io, process1}
import Process._
import java.security._
import scalaz._
import scala.collection.mutable
import java.math.BigInteger


  val P = Process

tpolecat

Hi, looking for scalac flags?

This gist has been upgraded to a blog post here.

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

tonymorris

The z in scalaz means this: it was early 2008 and I was working for a Java consultancy and so of course, I used the most appropriate tool for the job: scala. But it had *terrible* libraries, so I offered to fix those while also meeting my other objectives. Turns out that the Scala guys were extremely hostile to even half-decent libraries (and still are to this day). I still struggle to wrap my head around this sometimes.

Anyway, so I thought, well fuck it, I will just keep them to myself for now. My (awesome) employer had already agreed that we'd probably open-source such a thing, but I was concerned most about my primary goal. So then it came time to "name" this library. I had named it "scalax" simply so that I did not have the inclination to think of a proper name. Then I found out that such a library was being developed and with my internal name! Whatever, I thought.

So I looked at this scalax library, hoping that I could just abandon my efforts and jump on board with everyone else -- they too had figure

pchiusano

{-# Language ExistentialQuantification, GADTs #-}

module Control.Process where

import Data.Monoid
import Prelude hiding (zip, zipWith)
import Control.Applicative
import System.IO

data Process f a = Halt 

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

trodrigues

If you want to clone an svn repository with git-svn but don't want it to push all the existing branches, here's what you should do.

* Clone with git-svn using the -T parameter to define your trunk path inside the svnrepo, at the same time instructing it to clone only the trunk:
  
  git svn clone -T trunk http://example.com/PROJECT

* If instead of cloning trunk you just want to clone a certain branch, do the same thing but change the path given to -T:

  git svn clone -T branches/somefeature http://example.com/PROJECT

dbyrne

import collection.breakOut

val s = (0 until 1000000).toSet

def func(i: Int) = "" + i + i

Profiling.timed(Profiling.printTime("Jesper (original): ")){
   (s map { i => i -> func(i) }).toMap
}

retronym

class A
class A2 extends A
class B

trait M[X]

//
// Upper Type Bound
//
def upperTypeBound[AA <: A](x: AA): A = x