An overview of Ruby, jRuby, Rails, Torquebox, and PostgreSQL that was presented as a 3 hour class to other programmers at The Ironyard (http://theironyard.com) in Greenville, SC in July of 2013. The Rails specific sections are mostly code samples that were explained during the session so the real focus of the slides is Ruby, "the rails way" / workflow / differentiators and PostgreSQL.

1. Exploring Ruby on Rails
and PostgreSQL

2. Who am I?
• I’m Barry Jones
• Application Developer since ’98
– Java, PHP, Groovy, Ruby, Perl, Python
– MySQL, PostgreSQL, SQL Server, Oracle, MongoDB
• Efficiency and infrastructure nut
• Believer in “right tool for the job”
– There is no silver bullet, programming is about
tradeoffs

3. The Silver Bullet
Ruby on Rails and PostgreSQL
j/k 
But it’s close

4. What do we look for in a language?
• Balance
– Can it do what I need it to do?
• Web: Ruby/Python/PHP/Perl/Java/C#/C/C++
– Efficient to develop with it?
• Ruby/Python/PHP
– Libraries/tools/ecosystem to avoid reinventing the wheel?
• Ruby/Python/PHP/Java/Perl
– Is it fast?
• Ruby/Python/Java/C#/C/C++
– Is it stable?
• Ruby/Python/PHP/Perl/Java/C#/C/C++
– Do other developers use it?
• At my company? In the area? Globally?
– Cost effective?
• Ruby/Python/PHP/Perl/C/C++
– Can it handle my architectural approach well?
• Ruby/Python/Java/C# handle just about everything
• CGI languages (PHP/Perl/C/C++) are very bad fits for frameworks, long polling, evented programming
– Will it scale?
• Yes. This is a subjective question because web servers scale horizontally naturally
– Will my boss let me use it?
• .NET shop? C#
• Java shop? Java (Groovy, Clojure, Scala), jRuby, jython
• *nix shop? Ruby, Python, Perl, PHP, C, C++
• Probable Winners: Ruby and Python

5. What stands out about Ruby?
• Malleability
– Everything is an object
– Objects can be monkey
patched
• Great for writing
Domain Specific
Languages
– Puppet
– Chef
– Capistrano
– Rails
“this is a string object”.length
class String
def palindrome?
self == self.reverse
end
end
“radar”.palindrome?

6. How is monkey patching good?
• Rails adds web specific capabilities to Ruby
– “ “.blank? == true
• Makes using 3rd party libraries much easier
– Aspect Oriented Development
• Not dependent on built in hooks
– Queued processing
record = Record.find(id)
record.delay.some_intense_logic
• DelayedJob
• Resque
• Sidekiq
• Stalker
– Cross integrations
Email.deliver
• MailHopper – Automatically deliver all email in the background
• Gems that specifically enhance other gems

7. How is monkey patching…bad?
• If any behavior is modified by a monkey patch
there is a chance something will break
• On a positive note, if you’re writing tests and
following TDD or BDD the tests should catch
any problems
• On another positive note, the ruby community
is very big on testing

8. Why was Ruby created?
• Created by Yukirio Matsumoto
• "I wanted a scripting language that was more
powerful than Perl, and more object-oriented
than Python.”
• "I hope to see Ruby help every programmer in
the world to be productive, and to enjoy
programming, and to be happy. That is the
primary purpose of Ruby language.”
– Google Tech Talk in 2008

9. Ruby Version Manager
• cd into directory
autoselects correct
version of ruby and
gemset
• Makes running multiple
projects with multiple
versions of ruby and
gem dependencies on
one machine dead
simple
.rvmrc file
rvm rubytype-version-patch@gemset
Examples:
rvm ruby-1.9.3-p327@myproject
rvm jruby-1.7.4@myjrubyproject
rvm ree-1.8.7@oldproject

10. Bundler and Gemfile
$ bundle install
Using rake (10.0.4)
Using i18n (0.6.1)
Using multi_json (1.7.2)
Using activesupport (3.2.13)
Using builder (3.0.4)
Using activemodel (3.2.13)
Using erubis (2.7.0)
Using journey (1.0.4)
Using rack (1.4.5)
Using rack-cache (1.2)
Using rack-test (0.6.2)
…
Your bundle is complete! Use `bundle show
[gemname]` to see where a bundled gem is
installed.
source 'https://rubygems.org'
source 'http://gems.github.com'
# Application infrastructure
gem 'rails', '3.2.13'
gem 'devise'
gem 'simple_form'
gem 'slim'
gem 'activerecord-jdbc-adapter’
gem 'activerecord-jdbcpostgresql-
adapter'
gem 'jdbc-postgres'
gem 'jruby-openssl'
gem 'jquery-rails'
gem 'torquebox', '2.3.0'
gem 'torquebox-server', '~> 2.3.0'

11. Foreman
Not Ruby specific but written in ruby
Used with Heroku
Drop in a Procfile
$ foreman start 
CTRL + C to stop everything
Procfile
web: bundle exec thin start -p $PORT
worker: bundle exec rake resque:work QUEUE=*
clock: bundle exec rake resque:scheduler

12. jRuby: Why?
Ruby isn’t perfect
• Some gems can create memory leaks
– esp. if they were written with native C
• Does not have kernel level threading
– Global Interpreter Lock
• Everything is an object means unnecessary
processing happens when doing things like
adding numbers leading to a performance hit

13. jRuby: So how does it fix things?
I hate writing Java…but the JVM is a work of art
• Java infrastructure is virtually bulletproof
– Most mature way to deploy a web application
– Enterprisey 
• JVM’s garbage collector is best of breed and eliminates the potential
memory leak issues
• JVM’s Just-In-Time compiler continually optimizes code the longer it runs
making it faster
• JVM gives Ruby kernel level threading
• jRuby inspects your Ruby code to see if you’re doing anything it would
prefer you didn’t…and turns it off if you’re not
– Eg. If you aren’t overloading the + operator on int’s, it will convert them to
basic types instead of running as objects
• Include and use very mature Java libraries directly in your Ruby code
– Significantly expands your toolbelt
– Allows easy integration into existing Java environments

14. The Sidekiq Test
Sidekiq is a multithreaded background
worker that provides tremendous
concurrency benefits
Creating 1,000,000 objects in 50
concurrent threads
Ruby
jRuby

15. The App Server Test
CPU Usage

16. The App Server Test
Free Memory

17. The App Server Test
Latency

18. The App Server Test
Throughput

19. Update and Clarification
• As of this posting to Slideshare, Torquebox has a mature version 3
and a prototype version 4 that operates in a “web server only”
mode. Ruby is at version 2.1.0 with dramatic improvements to
memory performance with forking which allows higher
concurrency.
• At this time, jruby still wins but it’s much closer. Based on chatter
from the #jruby IRC channels, a major new release of both jRuby
and Torquebox are expected to dramatically improve their
performance thanks to recent Java updates. The expected timeline
was late 2014 last I heard.
• Independent benchmarks can be found here:
http://www.techempower.com/benchmarks/#section=data-
r9&hw=peak&test=json

20. RUBY ON RAILS
Let’s take a break before covering…

21. What do we look for in a framework?
• Please don’t suck
– Rails does not suck
• Does it follow Model-View-Controller?
– Yes
– Since Rails 1 it’s been the standard bearer for how to do MVC on the web, copied in almost every language
• Does it help me avoid repeating myself (DRY)?
– Yes
• Is it self documenting?
– Yes, it has a set of rules that generally make most documentation unnecessary
• Is it flexible enough to bend to my application needs?
– Yes
• Do other people use it?
– Good gosh yes
• Will it work with my database?
– Yes
• Is it still going to be around in X years?
– Ruby has Rails
– Python has Django
– Groovy has Grails
– C# has MVC
– PHP has fragmented framework Hell (aka – who knows?)
– Java has a few major players (Struts 2, Play, etc)

22. Rails: The Basics
Browser
Rack
Router
Controller +
Models
View

23. Rails: Rack
Watch this excellent walkthrough of Rack
Middleware:
http://railscasts.com/episodes/151-rack-
middleware
Summary:
It’s a layer of ruby code that passes requests into your app and
sends responses back out. You can add layers to do pre/post
processing on all requests prior to beginning ANY of your
application code.

24. Rails: Models / ActiveRecord
class Post < ActiveRecord::Base
belongs_to :category
has_many :tags, through: :posts_tags
validates :title, presence: true
before_save :create_slug, only: :create
scope :newest_first, order(‘created_at DESC’)
scope :active, where(‘active = ?’,true)
scope :newest_active, newest_first.active
scope :search, lambda do |text|
where(‘title LIKE ?’,”%#{text}%”)
end
def create_slug
self.slug = title.downcase.squish.sub(‘ ‘,’-’)
end
end
post = Post.new(title: ‘Some title’)
post.save!
OR
post = Post.create(title: ‘Some title’)
post.slug # some-title
post.id # 1
post.created_at # Created datetime
post.updated_at # Updated datetime
post.title = ‘New title’
post.save!
# Relations
post.tags.first
post.tags.count
post.category.name
post = Post.include(:tags) # Eager load
post =
Post.search(‘some’).newest_active.first

25. Rails: Migrations
class CreateInitialTables < ActiveRecord::Migration
def up
create_table :posts do |t|
t.string :title
t.text :body
t.string :slug
t.integer :category_id
t.timestamps
end
# … create more tables…
add_index :tags, [:name,:something], unique: true
execute “UPDATE posts SET field = ‘value’ WHERE stuff = ‘happens’”
end
def down
drop_table :posts
end
def change
add_column :posts, :user_id, :integer
end
end
$ rake db:migrate

26. Rails: Controllers
Class PostsController < ApplicationController
before_filter :authenticate, only: :destroy
def index # GET /posts
end
def new # GET /posts/new
end
def create # POST /posts
end
def show # GET /posts/:id
end
def edit # GET /posts/:id/edit
end
def update # PUT /posts/:id
end
def destroy # DELETE /posts/:id
end
end
# Routes
resources :posts
OR limit it
resources :posts, only: [:create,:new]

27. Rails: Views
/app/views
/layouts
/application.html.erb
/posts
/new.html.slim
/new.json.rabl
/index.xml.erb
/_widget.html.erb
# slim example
.post
h2=post.title
.body.grid-8=post.body
# erb example
<div class=“post”>
<h2><%=post.title%></h2>
<div class=“body grid-8”>
<%=post.body%>
</div>
</div>

28. Rails: Testing with rspec
Describe Post do
describe ‘a basic test’ do
subject { FactoryGirl.build(:post,title: ‘Some title’) }
it ‘should be valid’ do
should_not be_nil
subject.valid?.should be_true
end
end
describe ‘something with a complicated dependency’ do
before do
Post.stub(:function_to_override){ true }
end
end
describe ‘a test with API hits’ do
use_vcr_cassette ‘all_a_twitter’, record: :new_episodes
end
end

29. POSTGRESQL
Let’s take a break before we talk about…

30. How do you pronounce it?
Answer Response Percentage
post-gres-q-l 2379 45%
post-gres 1611 30%
pahst-grey 24 0%
pg-sequel 50 0%
post-gree 350 6%
postgres-sequel 574 10%
p-g 49 0%
database 230 4%
Total 5267

31. What IS PostgreSQL?
• Fully ACID compliant
• Feature rich and extensible
• Fast, scalable and leverages multicore
processors very well
• Enterprise class with quality corporate
support options
• Free as in beer
• It’s kind’ve nifty

32. Laundry List of Features
• Multi-version Concurrency Control (MVCC)
• Point in Time Recovery
• Tablespaces
• Asynchronous replication
• Nested Transactions
• Online/hot backups
• Genetic query optimizer multiple index types
• Write ahead logging (WAL)
• Internationalization: character sets, locale-aware sorting, case sensitivity,
formatting
• Full subquery support
• Multiple index scans per query
• ANSI-SQL:2008 standard conformant
• Table inheritance
• LISTEN / NOTIFY event system
• Ability to make a Power Point slide run out of room

33. What are we covering today?
• Full text-search
• Built in data types
• User defined data types
• Automatic data compression
• A look at some other cool features and
extensions, depending how we’re doing on
time

34. Full-text Search
• What about…?
– Solr
– Elastic Search
– Sphinx
– Lucene
– MySQL
• All have their purpose
– Distributed search of multiple document types
• Sphinx
– Client search performance is all that matters
• Solr
– Search constantly incoming data with
streaming index updates
• Elastic Search excels
– You really like Java
• Lucene
– You want terrible search results that don’t even
make sense to you much less your users
• MySQL full text search = the worst thing in the world

35. Full-text Search
• Complications of stand alone search engines
– Data synchronization
• Managing deltas, index updates
• Filtering/deleting/hiding expired data
• Search server outages, redundancy
– Learning curve
– Character sets match up with my database?
– Additional hardware / servers just for search
– Can feel like a black box when you get a support
question asking “why is/isn’t this showing up?”

36. Full-text Search
• But what if your needs are more like:
– Search within my database
– Avoid syncing data with outside systems
– Avoid maintaining outside systems
– Less black box, more control

37. Full-text Search
• tsvector
– The text to be searched
• tsquery
– The search query
• to_tsvector(‘the church is AWESOME’) @@ to_tsquery(SEARCH)
• @@ to_tsquery(‘church’) == true
• @@ to_tsquery(‘churches’) == true
• @@ to_tsquery(‘awesome’) == true
• @@ to_tsquery(‘the’) == false
• @@ to_tsquery(‘churches & awesome’) == true
• @@ to_tsquery(‘church & okay’) == false
• to_tsvector(‘the church is awesome’)
– 'awesom':4 'church':2
• to_tsvector(‘simple’,’the church is awesome’)
– 'are':3 'awesome':4 'church':2 'the':1

38. Full-text Search
• ALTER TABLE mytable ADD COLUMN search_vector tsvector
• UPDATE mytable
SET search_vector = to_tsvector(‘english’,coalesce(title,’’) || ‘ ‘ ||
coalesce(body,’’) || ‘ ‘ || coalesce(tags,’’))
• CREATE INDEX search_text ON mytable USING gin(search_vector)
• SELECT some, columns, we, need
FROM mytable
WHERE search_vector @@ to_tsquery(‘english’,‘Jesus & awesome’)
ORDER BY ts_rank(search_vector,to_tsquery(‘english’,‘Jesus & awesome’))
DESC
• CREATE TRIGGER search_update BEFORE INSERT OR UPDATE
ON mytable FOR EACH ROW EXECUTE PROCEDURE
tsvector_update_trigger(search_vector, ’english’, title, body, tags)

39. Full-text Search
• CREATE FUNCTION search_trigger RETURNS trigger AS $$
begin
new.search_vector :=
setweight(to_tsvector(‘english’,coalesce(new.title,’’)),’A’) ||
setweight(to_tsvector(‘english’,coalesce(new.body,’’)),’D’) ||
setweight(to_tsvector(‘english’,coalesce(new.tags,’’)),’B’);
return new;
end
$$ LANGUAGE plpgsql;
• CREATE TRIGGER search_vector_update
BEFORE INSERT OR UPDATE OF title, body, tags ON mytable
FOR EACH ROW EXECUTE PROCEDURE search_trigger();

40. Full-text Search
• A variety of dictionaries
– Various Languages
– Thesaurus
– Snowball, Stem, Ispell, Synonym
– Write your own
• ts_headline
– Snippet extraction and highlighting

41. Datatypes: ranges
• int4range, int8range, numrange, tsrange, tstzrange, daterange
• SELECT int4range(10,20) @> 3 == false
• SELECT numrange(11.1,22.2) && numrange(20.0,30.0) == true
• SELECT int4range(10,20) * int4range(15,25) == 15-20
• CREATE INDEX res_index ON schedule USING gist(during)
• ALTER TABLE schedule ADD EXCLUDE USING gist (during WITH &&)
ERROR: conflicting key value violates exclusion constraint
”schedule_during_excl”
DETAIL: Key (during)=([ 2010-01-01 14:45:00, 2010-01-01
15:45:00 )) conflicts with existing key (during)=([ 2010-01-01
14:30:00, 2010-01-01 15:30:00 )).

42. Datatypes: hstore
• properties
– {“author” => “John Grisham”, “pages” => 535}
– {“director” => “Jon Favreau”, “runtime” = 126}
• SELECT … FROM mytable
WHERE properties -> ‘director’ LIKE ‘%Favreau’
– Does not use an index
• WHERE properties @> (‘author’ LIKE “%Grisham”)
– Uses an index to only check properties with an ‘author’
• CREATE INDEX table_properties ON mytable USING gin(properties)

43. Datatypes: arrays
• CREATE TABLE sal_emp(name text, pay_by_quarter integer[],
schedule text[][])
• CREATE TABLE tictactoe ( squares integer[3][3] )
• INSERT INTO tictactoe VALUES (‘{{1,2,3},{4,5,6},{7,8,9}}’)
• SELECT squares[1:2][1:1] == {{1},{4}}
• SELECT squares[2:3][2:3] == {{5,6},{8,9}}

44. Datatypes: JSON
• Validate JSON structure
• Convert row to JSON
• Functions and operators very similar to hstore

45. Datatypes: XML
• Validates well-formed XML
• Stores like a TEXT field
• XML operations like Xpath
• Can’t index XML column but you can index the
result of an Xpath function

46. Data compression with TOAST
• TOAST = The Oversized Attribute Storage Technique
• TOASTable data is automatically TOASTed
• Example:
– stored a 2.2m XML document
– storage size was 81k

47. User created datatypes
• Built in types
– Numerics, monetary, binary, time, date, interval, boolean,
enumerated, geometric, network address, bit string, text search, UUID,
XML, JSON, array, composite, range
– Add-ons for more such as UPC, ISBN and more
• Create your own types
– Address (contains 2 streets, city, state, zip, country)
– Define how your datatype is indexed
– GIN and GiST indexes are used by custom datatypes

48. Further exploration: PostGIS
• Adds Geographic datatypes
• Distance, area, union, intersection, perimeter
• Spatial indexes
• Tools to load available geographic data
• Distance, Within, Overlaps, Touches, Equals,
Contains, Crosses
• SELECT name, ST_AsText(geom)
FROM nyc_subway_stations
WHERE name = ‘Broad St’
• SELECT name, boroname
FROM nyc_neighborhoods
WHERE ST_Intersects(geom,
ST_GeomFromText(‘POINT(583571 4506714)’,26918)
• SELECT sub.name, nh.name, nh.borough
FROM nyc_neighborhoods AS nh
JOIN nyc_subway_stations AS sub
ON ST_Contains(nh.geom, sub.geom)
WHERE sub.name = ‘Broad St”

49. Further exploration: Functions
• Can be used in queries
• Can be used in stored procedures and triggers
• Can be used to build indexes
• Can be used as table defaults
• Can be written in PL/pgSQL, PL/Tcl, PL/Perl,
PL/Python out of the box
• PL/V8 is available an an extension to use
Javascript

50. Further exploration: PLV8
• CREATE OR REPLACE FUNCTION plv8_test(keys text[], vals text[])
RETURNS text AS $$
var o = {};
for(var i = 0; i < keys.length; i++) {
o[keys[i]] = vals[i];
}
return JSON.stringify(o);
$$ LANGUAGE plv8 IMMUTABLE STRICT;
SELECT plv8_test(ARRAY[‘name’,’age’],ARRAY[‘Tom’,’29’]);
• CREATE TYPE rec AS (i integer, t text);
CREATE FUNCTION set_of_records RETURNS SETOF rec AS $$
plv8.return_next({“i”: 1,”t”: ”a”});
plv8.return_next({“i”: 2,”t”: “b”});
$$ LANGUAGE plv8;
SELECT * FROM set_of_records();

51. Further exploration: Async commands
/ indexes
• Fine grained control within functions
– PQsendQuery
– PQsendQueryParams
– PQsendPrepare
– PQsendQueryPrepared
– PQsendDescribePrepared
– PQgetResult
– PQconsumeInput
• Per connection asynchronous commits
– set synchronous_commit = off
• Concurrent index creation to avoid blocking large tables
– CREATE INDEX CONCURRENTLY big_index ON mytable (things)

52. ARCHITECTURE
And finally…

53. Biggest Issue with Frameworks
• Framework Dependency
• Trying to do everything in application code
• Race conditions
• Package dependency

54. Old School
• Service Oriented Architecture
– Getting more popular because of REST
– Had been happening for years prior with WSDL
• Database managed your data
– Constraints, triggers, functions, stored procedures
– If it was in the database…it was valid
• Nothing has changed…this is still the best way

55. If you really leverage your database…
• You can easily break your application into
logical parts
• You don’t need to create APIs through your
core code base when direct DB access there
• You can use a different language for certain
things if it makes sense to do so
– Node.js is great for APIs
– Using a library that only runs on Windows
• Database can provide granular access controls

56. Architecture: Before

57. Architecture: After

58. Architecture: Scaled

59. THANKS!

60. Credits / Sources
• NOTE: Some code samples in this presentation have minor alterations for
presentation clarity (such as leaving out dictionary specifications on some
search calls, etc)
• http://www.postgresql.org/docs/9.2/static/index.html
• http://workshops.opengeo.org/postgis-intro/
• http://stackoverflow.com/questions/15983152/how-can-i-find-out-how-big-a-
large-text-field-is-in-postgres
• https://devcenter.heroku.com/articles/heroku-postgres-extensions-postgis-full-
text-search
• http://railscasts.com/episodes/345-hstore?view=asciicast
• http://www.slideshare.net/billkarwin/full-text-search-in-postgresql
• http://sourceforge.net/apps/mediawiki/postgres-xc/index.php?title=Main_Page
• http://railscasts.com/episodes/151-rack-middleware
• http://joshrendek.com/2012/11/sidekiq-vs-resque/
• http://torquebox.org/news/2011/10/06/torquebox-2x-performance/
• http://jruby.org/
• https://rvm.io/
• http://ddollar.github.io/foreman/
• http://en.wikipedia.org/wiki/Ruby_(programming_language)
• http://bundler.io/
• http://www.techempower.com/benchmarks/#section=data-r9&hw=peak&test=json