jmatsushita

###
### [2023-06-19] UPDATE: Just tried to use my instructions again on a fresh install and it failed in a number of places. 
###.   Not sure if I'll update this gist (though I realise it seems to still have some traffic), but here's a list of 
###.   things to watch out for:
###      - Check out the `nix-darwin` instructions, as they have changed.
###      - There's a home manager gotcha https://github.com/nix-community/home-manager/issues/4026
###

# I found some good resources but they seem to do a bit too much (maybe from a time when there were more bugs).
# So here's a minimal Gist which worked for me as an install on a new M1 Pro.

costa

#!/bin/bash -e

INGESTER_DOMAIN_NAME="${INGESTER_DOMAIN_NAME:-$1}"

echo "CAUTION should be run from a secure directory"

if test -z "$INGESTER_DOMAIN_NAME"
then echo "needs INGESTER_DOMAIN_NAME"
     exit 1
else echo "INGESTER_DOMAIN_NAME=$INGESTER_DOMAIN_NAME"

jdegoes

package fpmax

import scala.util.Try
import scala.io.StdIn.readLine

object App0 {
  def main: Unit = {
    println("What is your name?")

    val name = readLine()

friedbrice

Denotational Semantics in a Nutshell

First off, I am not a programming language theorist, so please comment below if I say anything that's completely off-base or misleading. I'll be happy to make the necessary corrections.

Clears throat

Operational and Logical Semantics

thbkrkr

com.sun.management:type=DiagnosticCommand
com.sun.management:type=HotSpotDiagnostic
java.lang:name=CodeCacheManager,type=MemoryManager
java.lang:name=Code Cache,type=MemoryPool
java.lang:name=Compressed Class Space,type=MemoryPool
java.lang:name=G1 Eden Space,type=MemoryPool
java.lang:name=G1 Old Generation,type=GarbageCollector
java.lang:name=G1 Old Gen,type=MemoryPool
java.lang:name=G1 Survivor Space,type=MemoryPool
java.lang:name=G1 Young Generation,type=GarbageCollector

awesomebytes

Save an iPython session commands/code to a file

You must use the magic method %save:

In [1]: %save?
Type:       Magic function
String Form:<bound method CodeMagics.save of <IPython.core.magics.code.CodeMagics object at 0x7fb5d25bb1d0>>
Namespace:  IPython internal
File: /usr/lib/python2.7/dist-packages/IPython/core/magics/code.py

Fristi

package nl.mdj.fpinscala

import akka.actor.{Actor, ActorRef, ActorSystem, Props}
import akka.pattern.ask
import akka.util.Timeout
import nl.mdj.fpinscala.KeyValueStore.{KvS, ListKeys}

import scala.concurrent.duration._
import scala.concurrent.{ExecutionContext, Await, Future}
import scalaz.std.list._

colestanfield

// Create a new MergeStrategy for aop.xml files
val aopMerge: MergeStrategy = new MergeStrategy {
  val name = "aopMerge"
  import scala.xml._
  import scala.xml.dtd._

  def apply(tempDir: File, path: String, files: Seq[File]): Either[String, Seq[(File, String)]] = {
    val dt = DocType("aspectj", PublicID("-//AspectJ//DTD//EN", "http://www.eclipse.org/aspectj/dtd/aspectj.dtd"), Nil)
    val file = MergeStrategy.createMergeTarget(tempDir, path)

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

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: