peter

-- Order by one indexed column (FAST)
newsdesk_production=# explain analyze select * from pressreleases order by published_at DESC limit 100;
                                                                                   QUERY PLAN                                                                                    
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Limit  (cost=0.00..249.91 rows=100 width=1207) (actual time=26.070..716.453 rows=100 loops=1)
   ->  Index Scan Backward using pressreleases_published_at_index on pressreleases  (cost=0.00..964766.62 rows=386042 width=1207) (actual time=26.067..716.343 rows=100 loops=1)
 Total runtime: 716.709 ms
(3 rows)

- Order by two separately indexed columns (SLOW)

hgmnz

Types of index scans

Indexes

Sequential Scan:

• Read every row in the table
• No reading of index. Reading from indexes is also expensive.

scottlowe

class Article < ActiveRecord::Base
  validates :title, :body, :presence => true

  # Note that ActiveRecord ARel from() doesn't appear to accommodate "?"
  # param placeholder, hence the need for manual parameter sanitization
  def self.tsearch_query(search_terms, limit = query_limit)
    words = sanitize(search_terms.scan(/\w+/) * "|")

    Article.from("articles, to_tsquery('pg_catalog.english', #{words}) as q").
      where("tsv @@ q").order("ts_rank_cd(tsv, q) DESC").limit(limit)

jhowarth

class SessionsController < Devise::SessionsController
  
  def create
    resource = warden.authenticate!(:scope => resource_name, :recall => :failure)
    return sign_in_and_redirect(resource_name, resource)
  end
  
  def sign_in_and_redirect(resource_or_scope, resource=nil)
    scope = Devise::Mapping.find_scope!(resource_or_scope)
    resource ||= resource_or_scope

chitchcock

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

cblunt

# ...

gem 'carrierwave'
gem 'fog', '~> 1.0.0' # Need to specify version, as carrierwave references older (0.9.0) which doesn't allow configuration of Rackspace UK Auth URL

chetan

YARD CHEATSHEET http://yardoc.org

May 2020 - updated fork: https://gist.github.com/phansch/db18a595d2f5f1ef16646af72fe1fb0e

cribbed from http://pastebin.com/xgzeAmBn

Templates to remind you of the options and formatting for the different types of objects you might want to document using YARD.

Modules

gcatlin

brew update
brew versions FORMULA
cd `brew --prefix`
git checkout HASH Library/Formula/FORMULA.rb  # use output of "brew versions"
brew install FORMULA
brew switch FORMULA VERSION
git checkout -- Library/Formula/FORMULA.rb    # reset formula

## Example: Using Subversion 1.6.17
#

henrik

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

hellerbarde

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs