skaurus

1. General Background and Overview

• 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.
• Models and Issues in Data Stream Systems
• 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
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

skaurus

#!/usr/local/bin/perl

use 5.026;
use warnings;

use FindBin qw/$RealBin/;
use lib $RealBin . '/../local/lib/perl5', $RealBin . '/../lib';

use Benchmark;
use LWP::Curl;

skaurus

#!/usr/local/bin/perl
 
package TestApp;
 
use Mojolicious::Lite;
 
use Mojo::Promise;
use Mojo::UserAgent;
 
my $ua = Mojo::UserAgent->new;

skaurus

Controller::method {
    my $promise = Utils::get_me_promise;
    return $promise->then(sub ($inner_promise) {
        say 'method outer resolved';
        return $inner_promise->then(sub ($something) {
            say 'method inner resolved';
            render $something;
        }, sub {
            log_error
        }

skaurus

# Setup https://github.com/trick77/dockerflix on Mikrotik router

:global portallerHosts " \
    ipinfo.io, \
    hulu.com, \
    netflix.com, \
    netflix.net, \
    mtv.com, \
    mtvnservices.com, \
    optimizely.com, \