JoshCheek

A small clone of Sinatra

For the purpose of learning.

Run the example app

johnynek

Unifying Sketch Monoids

As I discussed in Algebra for Analytics, many sketch monoids, such as Bloom filters, HyperLogLog, and Count-min sketch, can be described as a hashing (projection) of items into a sparse space, then using two different commutative monoids to read and write respectively. Finally, the read monoids always have the property that (a + b) <= a, b and the write monoids has the property that (a + b) >= a, b.

##Some questions:

1. Note how similar CMS and Bloom filters are. The difference: bloom hashes k times onto the same space, CMS hashes k times onto a k orthogonal subspaces. Why the difference? Imagine a fixed space bloom that hashes onto k orthogonal spaces, or an overlapping CMS that hashes onto k * m length space. How do the error asymptotics change?
2. CMS has many query modes (dot product, etc...) can those generalize to other sketchs (HLL, Bloom)?
3. What other sketch or non-sketch algorithms can be expressed in this dual mo

bokmann

# Thee will be more information here when I share the entire problem space I'm working on, but
# in short, this is preview material for my second talk in a series called "What Computer Scientists Know".
# The first talk is on recursion, and goes through several examples., leading up to a problem based
# on a simple puzzle that initial estimates based on performance of a previous puzzle would take years
# to solve on modern computers with the techniques shown in Ruby. That sets the stage for improving the
# performance of that problem with threading, concurrency, and related tuning.
#
# The second talk is on threading and concurrency, touching on algorithmic performance as well.
# Using some knowledge of the problem (board symmetry, illegal moves, etc), we reduce the problem space
# to about .5% of what we initially thought it was.  Still, the initial single threaded solution took more

passcod

# ...
gem 'sidekiq'
# ...

barelyknown

module Cacheable
  extend ActiveSupport::Concern

  def cacheback(relationship)
    if relationship.cacheable_attributes.any?
      relationship.target_attributes.each do |target_attribute|
        relationship.target.each { |member| member.send("calc_#{target_attribute}")}
      end
      relationship.target.each(&:save!)
    end

mbektimirov

/**
 * Part Zero : 10:15 Saturday Night
 *
 * (In which we will see how to let the type system help you handle failure)...
 *
 * First let's define a domain. (All the following requires scala 2.9.x and scalaz 6.0)
 */

import scalaz._
import Scalaz._

benedikt

# encoding: UTF-8

Capistrano::Configuration.instance(:must_exist).load do
  namespace :rails do
    desc "Open the rails console on one of the remote servers"
    task :console, :roles => :app do
      hostname = find_servers_for_task(current_task).first
      exec "ssh -l #{user} #{hostname} -t 'source ~/.profile && #{current_path}/script/rails c #{rails_env}'"
    end
  end