djspiewak

Introduction to scalaz-stream

Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.

The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca

paf31

This blog post series has moved here.

You might also be interested in the 2016 version.

kachayev

Channels Are Not Enough

... or Why Pipelining Is Not That Easy

Golang Concurrency Patterns for brave and smart.

By @kachayev

Intro

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

carl297r

package demo

// Adapted from Jonas Bonér's example https://gist.github.com/jboner/9990435

import akka.actor.{Props, ActorSystem}
import akka.persistence.{EventsourcedProcessor, SnapshotOffer}

object PersistedPingPong extends App {

  case object Ball            //The Command

honza

-- This is a Haskell implementation of aphyr's
-- "Clojure from the ground up - modeling"
--
-- http://aphyr.com/posts/312-clojure-from-the-ground-up-modeling
--
-- Compile this with:
-- 
--   $ ghc -O Rocket.hs

import GHC.Exts

jboner

Akka Cluster Implementation Notes

Slightly disorganized but reasonably complete notes on the algorithms, strategies and optimizations of the Akka Cluster implementation. Could use a lot more links and context etc., but was just written for my own understanding. Might be expanded later.

Links to papers and talks that have inspired the implementation can be found on the 10 last pages of this presentation.

Akka Gossip

Gossip state

This is the Gossip state representation:

massie

/*
 * Copyright (c) 2013. Regents of the University of California
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software

apurvam

/* Instructions on compilation and execution
 * =========================================
 *
 * Compile this program with pthreads:
 *
 *   g++ -Wall -lpthread -o graphdb-simulator graphdb-simulator.cpp
 *
 * Before you run this program, you need to create the following
 * directories:
 *

macintux

• https://ferd.ca/a-distributed-systems-reading-list.html
• http://the-paper-trail.org/blog/distributed-systems-theory-for-the-distributed-systems-engineer/
• https://github.com/palvaro/CMPS290S-Winter16/blob/master/readings.md
• http://muratbuffalo.blogspot.com/2015/12/my-distributed-systems-seminars-reading.html
• http://christophermeiklejohn.com/distributed/systems/2013/07/12/readings-in-distributed-systems.html
• http://michaelrbernste.in/2013/11/06/distributed-systems-archaeology-works-cited.html
• http://rxin.github.io/db-readings/
• http://research.microsoft.com/en-us/um/people/lamport/pubs/pubs.html
• http://pdos.csail.mit.edu/dsrg/papers/
• http://scalingsystems.com/2011/09/07/reading-list-for-distributed-systems/