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

jonathan-beard

#!/usr/bin/env perl
use strict;
use warnings;
##
# Stupid simple wrapper around ghostscript to join pdf's
##


##
# check for args < 2, just assume

stelleg

#include <qthread.h>
#include <qthread/sinc.h>

volatile int j = 0;

aligned_t task(void* arg){
  j ++;
}

int main(){

jonathan-beard

/**
 * hh.hpp - Highway Hash code that is constexpr compatible, this code
 * is inspired by and derives significant amount of code from 
 * https://github.com/google/highwayhash to produce a compatible hash,
 * that being said, it is an almost entirely different codebase at this 
 * point being far simpler (and less advanced than the original product),
 * but it does produce a decent compile time hash function. 
 *
 * @author: Jonathan Beard
 * @version: Sun Feb  7 05:46:48 2019

jonathan-beard

First, you'll need to decide where to setup the mount point. The most convenient place is within /System/Volumes/Data/Volumes/ given everything will just work if the directory is there. You don't need to create this directory yet since we'll make a script that'll automatically create it on boot. This path, let's say /System/Volumes/Data/Volumes/OurNFS is the mount point we use for the local ned of our NFS, we'll call this [path to local mountpoint] within the rest of the text.