slpsys

class Player
  private_class_method :new
  
  class << self 
    def one ; 1 ; end
    def two ; 2 ; end
  end
end

class TTTEngine

slpsys

#!/bin/bash -ew

# Note that the question file accompanying this script came from 
# Jason Evanish's excellent blog post, the original text of which can
# be which can be found here:
# 
# https://jasonevanish.com/2014/05/29/101-questions-to-ask-in-1-on-1s/

# Number of questions to ask
NUM_QUESTIONS=3

slpsys

Keybase proof

I hereby claim:

• I am slpsys on github.
• I am slpsys (https://keybase.io/slpsys) on keybase.
• I have a public key whose fingerprint is 8CFC 55BC E288 6D63 FFD7 499F 1B05 8607 4149 659D

To claim this, I am signing this object:

slpsys

SELECT
  TRIM(pgn.nspname) AS schema,
  TRIM(a.name) AS table,
  CASE WHEN pgc.reldiststyle != 1 AND ti.sortkey_num = 0 THEN 'DISTSTYLE NOT KEY AND NO SORTKEY (TABLE IS GARBAGE)'
       WHEN pgc.reldiststyle != 1 THEN 'DISTSTYLE NOT KEY'
       WHEN ti.sortkey_num = 0 THEN 'NO SORTKEY'
       END as issue
FROM
  (
    SELECT db_id, id, name, SUM(rows) AS rows

slpsys

Execution plans

EXTRACT (YEAR FROM date_field) for a given year:

warehouse=# explain select count(*) from views.gamesave where EXTRACT (YEAR FROM event_created_at) = 2016;
                                 QUERY PLAN
-----------------------------------------------------------------------------
 XN Aggregate  (cost=8152608.99..8152608.99 rows=1 width=0)
   ->  XN Seq Scan on gamesave  (cost=0.00..8145820.80 rows=2715274 width=0)

slpsys

Business / Product

• https://medium.com/@noah_weiss/50-articles-and-books-that-will-make-you-a-great-product-manager-aad5babee2f7

Data Science /Stats

• https://www.countbayesie.com/blog/2016/5/1/a-guide-to-bayesian-statistics
• https://jeremykun.com/2016/02/08/big-dimensions-and-what-you-can-do-about-it/
• https://arogozhnikov.github.io/2016/04/28/demonstrations-for-ml-courses.html
• http://arogozhnikov.github.io/2016/06/24/gradient_boosting_explained.html
• http://arogozhnikov.github.io/2015/10/05/roc-curve.html
• https://www.youtube.com/watch?v=N4gDikiec8E

slpsys

Broadside.configure do |config|
  config.application = 'redshift_console'
  config.default_docker_image = # image location
  config.aws.ecs_default_cluster = # cluster name
  config.targets = {
    production_web: {
      scale: 1,
      env_file: '.env.production',
      service_config: {
        role: 'ecsServiceRole',

slpsys

import scala.reflect.runtime.{universe => ru}

// Trivial class hierarchy
class NotionalObject
class Car extends NotionalObject
class Dog extends NotionalObject

// Not part of the hierarchy
class AbstractExpressionism

slpsys

#!/bin/bash

i=0
step=0.1

while true
do
  b=$(echo "scale=3;(s($i)+1)*0.5" | bc -l)
  brightness $b

slpsys

Keynote, "I See What You Mean" by Peter Alvaro

Video

Synopsis

5/5. This is pretty academic, but it's pretty great, too. It starts with datalog, which heavily inspires his project Dedalus; there's a way better dissection of this talk here.

"Managing Containers at Scale with CoreOS and Kubernetes" by Kelsey Hightower