Lessons Learnt in 2009

Lessons learnt in 2009 Pratik Naik Jobless

Lessons learnt in 2009 Pratik Naik Freelancer/ ActionRails Blogger m.onkey.org Rails Core Team member

And some hobby apps http://planetrubyonrails.com http://tweetmufﬂer.com

• My ﬁrst ever presentation. • Usually don’t like any conferences • But it’s Brazil!!

So if I screw up... DONT Tweet FFS

Overview • Using Ruby Enterprise Edition • Testing • Faster tests • Factory v/s Fixtures • Security • Auto escaping for XSS prevention • More MessageVeriﬁer • Asynchronous job processing with DJ • How to use • Fork based batch processing • Scaling • Scaling ﬁle uploads with mod_porter • Better Pagination

This talk is targeted at Ruby Web Developers Not everything may apply to things outside the web Also if this doesn’t interest you, now is the time to go the next room :-)

Lesson 1 Always use REE

What is REE ?

Ruby + COW GC And a bunch of other cool patches

Maintained by (Photo acquired by the use of force) (That was just googling) The Phusion Guys

Who uses REE ? And many others

Who uses REE ? And many others In Production

Why should you use it for the development ?

Topmost Reason Super Fast Tests

MRI - Ruby 1.8.6 $ time rake real 1m45.293s user 0m54.341s sys 0m33.008s

REE - Ruby 1.8.6 $ time rake real 1m30.219s user 0m40.290s sys 0m25.433s

That’s15 seconds faster Completely Free YMMV

Only Catch Twitter’s GC Settings

.proﬁle RUBY_HEAP_MIN_SLOTS=500000 RUBY_HEAP_SLOTS_INCREMENT=250000 RUBY_HEAP_SLOTS_GROWTH_FACTOR=1 RUBY_GC_MALLOC_LIMIT=50000000 http://blog.evanweaver.com/articles/2009/04/09/ruby-gc- tuning/

Second Reason ruby-prof & Rails Performance Tests

What are Rails Performance tests ? Integration Tests + ruby-prof

http://guides.rubyonrails.org/performance_testing.html

$ script/generate performance_test Home exists test/performance/ create test/performance/home_test.rb class HomeTest < ActionController::PerformanceTest def test_homepage get '/' end end

MRI $ rake test:proﬁle HomeTest#test_homepage (29 ms warmup) wall_time: 25 ms memory: 0.00 KB objects: 0 Needs a custom installation with special Patches

REE $ rake test:proﬁle HomeTest#test_homepage (48 ms warmup) wall_time: 16 ms memory: 698.18 KB objects: 21752 Just “works”

Lesson 2 Efﬁcient Testing • Faster Tests • Factory • More Integration Tests & Less Unit Tests

Faster Tests Tickle http://github.com/lifo/tickle

$ script/plugin install git://github.com/lifo/tickle.git

Benchmarks ( they’re real ) $ time rake real 1m30.219s user 0m40.290s sys 0m25.433s

Benchmarks ( they’re real ) $ time rake tickle real 0m55.691s user 0m37.532s sys 0m22.563s

That’s another 35 seconds ( On top of the 15 seconds initially saved by REE )

To get the Best of Tickle • Experiment with the number of processes • Create more test databases It’s all in the README

Parallel Specs http://github.com/jasonm/parallel_specs

Faster Tests fast_context http://github.com/lifo/fast_context

Problem That’s 5 DB Queries and 5 GET Requests

Solution That’s 1 DB Query and 1 GET Request 5x Faster w/ one word change

Catch ? • Tests no longer atomic • Developers should not need to care about atomicity of the tests • It’s an optimization

Writing more effective tests in less time

Factory v/s Fixtures ★ Slow ★ Fast ★ Very easy to manage ★ Hard to manage ★ Describes the data ★ Doesn’t describe the being tested data ★ Hardly Breaks ★ Very Brittle ★ Runs all the callbacks ★ Does not run callbacks

Example : Fixtures What can go wrong ? • Someone could change users(:lifo) to be no longer a ‘free’ account holder • Someone could add more items to ‘lifo’ • Someone could remove lifo’s item! • ‘create_more_items’ could fails because ‘lifo’ failed validations

Example : Factory What can go wrong ? Not much

Factory + Faker Awesome Development Data (Clients and Designers Love it)

Writing Good Factories • Should be able to loop 10.times { Factory(:user) } • No associations in the base Factory Factory(:user) and Factory(:user_with_items) • Should pass the validations

Integration Tests > Unit Tests

Lesson 3 Improved Security

To know more http://guides.rubyonrails.org/security.html

rails_xss http://github.com/NZKoz/rails_xss By Michael Kozkiarski of http://therailsway.com/

rails_xss Without rails_xss With rails_xss <%= “<script>alert(‘foo’)</script>” %> <%= “<script>alert(‘foo’)</script>” %> => => <script>alert(‘foo’)</script> <script>alert('foo')</script> Must use h() explicitly No need of h()

rails_xss • Built in Rails 3 • Enabled by the rails_xss plugin in Rails 2.3.next • Requires Erubis

rails_xss Introduces the concept of SafeBuffer ( * just the relevant bits )

rails_xss >> buffer = ActionView::SafeBuffer.new => "" >> buffer << "Hello ! " => "Hello ! " >> buffer << "<script>" => "Hello ! <script>"

rails_xss • Uses Erubis hooks to make <%= %> tags to always return a SafeBuffer • Modiﬁes all the relevant Rails helpers and mark them as html_safe!

rails_xss When you don’t want to escape <%= "<a href='#{foo_path}'>foo</a>".html_safe! %>

MessageVeriﬁer http://api.rubyonrails.org/classes/ActiveSupport/MessageVeriﬁer.html

MessageVeriﬁer Secret Ruby Data Signed Message (Derived from Cookie Session Store)

MessageVerifier >> verifier = ActiveSupport::MessageVerifier.new("my super secret") => #<ActiveSupport::MessageVerifier:0x2d559ec @secret="my super secret", @digest="SHA1"> >> data = [1, 10.days.from_now.utc] => [1, Sat Oct 24 05:28:07 UTC 2009] >> token = verifier.generate(data) # Generate a token that is safe to distribute => "BAhbB2kGSXU6CVRpbWUNBWcbgO7HdXAGOh9AbWFyc2hhbF93aXRoX3V0Y19jb2Vy Y2lvblQ=--ff41cf5575006a2797cad49e6738361346292bfa" >> id, expiry_time = verifier.verify(token) # Get the data back => [1, Sat Oct 24 05:28:07 UTC 2009]

MessageVeriﬁer Example use case “Remember Me” Functionality

MessageVeriﬁer When you store the ‘remember me’ tokens in the db • Extra column • More maintenance Expiring tokens after every use or after password reset • Doesn’t play well with multiple browsers

MessageVeriﬁer # User.rb def remember_me_token User.remember_me_veriﬁer.generate([self.id, self.salt]) end # Controller - when user checks the ‘remember me’ def send_remember_cookie! cookies[:auth_token] = { :value => @current_user.remember_me_token, :expires => 20.years.from_now.utc } end

MessageVeriﬁer • Use a different secret for every use of MessageVeriﬁer rake secret • Make sure to use the ‘salt’ for generating the token, making sure the token expires on the password change

bcrypt http://bcrypt-ruby.rubyforge.org

bcrypt Bcrypt MD5/SHA1 ★ Designed for generating password ★ Designed for detecting data hash tampering ★ Meant to be “slow” ★ Meant to be super “fast”

bcrypt • bcrypt-ruby gem by Coda Hale works great • Reduces the need of ‘salt’ column by storing the salt in the encrypted password column • Allows you to increase the ‘cost factor’ as the computers get faster

Lesson 4 Background processing with the DJ http://github.com/tobi/delayed_job

What is DJ ? DJ Worker Webserver DJ Jobs Database Jobs Worker Webserver DJ Worker Database backed asynchronous priority queue

How to use DJ ? Minimal Example using Delayed::Job.enqueue

How to use DJ ? More practical example

How to use DJ ? Using send_later

How to use DJ ? Using handle_asynchronously

Batch Processing w/ DJ

Batch Processing w/ DJ Tweetmufﬂer Requirement That’s average 4-10 external calls per user. Every 2 minutes.

Batch Processing w/ DJ Initial Implementation 1 job/user

Batch Processing w/ DJ Problems with that ?

Batch Processing w/ DJ DID NOT SCALE • Too Slow • Way too much memory required • Too many workers required

Batch Processing w/ DJ Solution Fork based workers w/ REE

Batch Processing w/ DJ

Batch Processing w/ DJ Has scaled great so far • 10x faster • Uses 40% less memory • Just 1 worker needed

Batch Processing w/ DJ General things to remember when forking w/ Ruby • Always reset the database connections • Always reset any open ﬁle handlers • Make sure the child calls exit! from an ensure block • Make sure mysql allows sufﬁcient number of connections

Batch Processing w/ DJ REE Speciﬁc things to remember when forking • Call GC.start before you fork • Call GC.copy_on_write_friendly = true as early as possible. Possibly from the top of the Rakeﬁle and environment.rb

Lesson 5 Scaling

http://modporter.com Scaling ﬁle uploads

Mod Porter What’s the problem ? • Rails processes are resource intensive • Multipart parsing for large ﬁles can get slower • Keeping a Rails process occupied for multipart parsing of large ﬁles can have serious scaling issues

Mod Porter How does mod_porter work ? • mod_porter is an apache module built on top of libapreq • libapreq does the heavy job of multipart parsing in a cheap little apache process • mod_porter sends those multipart ﬁles as tmpﬁle urls to the Rails app • mod_porter Rails plugin makes the whole thing transparent to the application

Mod Porter Apache Conﬁg File <VirtualHost *:8080> ServerName actionrails.com DocumentRoot /Users/actionrails/application/current/public Porter On PorterSharedSecret secret </VirtualHost> Rails Conﬁgration class ApplicationController < ActionController::Base self.mod_porter_secret = "secret" end

will_paginate Does not scale

will_paginate The common pattern SELECT * FROM `posts` LIMIT 10,10

will_paginate Scaling Problems • Large OFFSET are harder to scale • Problems clear when you have more rows than the memory can hold • Very hard to cache • Extra COUNT queries

How to scale Pagination?

Scalable Pagination Github

Scalable Pagination Twitter

Scalable Pagination What’s common with Github and Twitter ? • Don’t show all the page links • Don’t show the total count • AJAX is much easier to scale when it comes to pagination • Pagination query does not use OFFSET, just LIMIT.

Scalable Pagination Page 1 page1 = SELECT * FROM `posts` LIMIT 10 WHERE id > 0 ASC id page2_min_id = page1.last.id Page 2 page2 = SELECT * FROM `posts` LIMIT 10 WHERE id > page2_min_id ASC id

Scalable Pagination Beneﬁts ? • Using no OFFSET is much faster • Plays great with caching. No records ever get repeated • A little less user friendly as you cannot show all the page numbers

Source http://www.scribd.com/doc/14683263/Efﬁcient-Pagination-Using-MySQL By the Yahoo folks

That’s all !

Thank you. Blog http://m.onkey.org @lifo

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Lessons Learnt in 2009

by pratiknaik on Oct 18, 2009

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Lessons Learnt in 2009 — Presentation Transcript