scaling twitter 12758

Big Bird.(scaling twitter)

Rails Scales.(but not out of the box)

First, Some Facts

• 600 requests per second. Growing fast.

• 180 Rails Instances (Mongrel). Growing fast.

• 1 Database Server (MySQL) + 1 Slave.

• 30-odd Processes for Misc. Jobs

• 8 Sun X4100s

• Many users, many updates.

Oct Nov Dec Jan Feb March Apr

Joy Pain

IM IN UR RAILZ

MAKIN EM GO FAST

1. Realize Your Site is Slow

2. Optimize the Database

3. Cache the Hell out of Everything

4. Scale Messaging

5. Deal With Abuse

It’s Easy, Really.

1. Realize Your Site is Slow

2. Optimize the Database

3. Cache the Hell out of Everything

4. Scale Messaging

5. Deal With Abuse

6. Profit

It’s Easy, Really.

{ Part the First }

themoreyouknow

We Failed at This.

Don’t Be Like Us

• Munin

• Nagios

• AWStats & Google Analytics

• Exception Notifier / Exception Logger

• Immediately add reporting to track problems.

Test Everything

• Start Before You Start

• No Need To Be Fancy

• Tests Will Save Your Life

• Agile Becomes Important When Your Site Is Down

Benchmarks?let your users do it.

<!-- served to you through a copper wire by kolea.twitter.com at 22 Apr 15:00 in 409 ms (d 88 / r 307). thank you, come again. -->

<!-- served to you through a copper wire by raven.twitter.com at 22 Apr 15:01 in 450 ms (d 96 / r 337). thank you, come again. -->

<!-- served to you through a copper wire by quetzal at 22 Apr 15:01 in 384 ms (d 70 / r 297). thank you, come again. -->

<!-- served to you through a copper wire by sampaati at 22 Apr 15:02 in 343 ms (d 102 / r 217). thank you, come again. -->

<!-- served to you through a copper wire by kolea.twitter.com at 22 Apr 15:02 in 235 ms (d 87 / r 130). thank you, come again. -->

<!-- served to you through a copper wire by firebird at 22 Apr 15:03 in 2094 ms (d 643 / r 1445). thank you, come again. -->

The Database{ Part the Second }

“The Next Application I Build is Going to Be Easily Partitionable” - S. Butterfield

“The Next Application I Build is Going to Be Easily Partitionable” - S. Butterfield

“The Next Application I Build is Going to Be Easily Partitionable” - S. Butterfield

Too Late.

Index Everything

class AddIndex < ActiveRecord::Migration def self.up add_index :users, :email end

def self.down remove_index :users, :email endend

Repeat for any column that appears in a WHERE clause

Rails won’t do this for you.

Denormalize A Lot

class DenormalizeFriendsIds < ActiveRecord::Migration def self.up add_column "users", "friends_ids", :text end

def self.down remove_column "users", "friends_ids" endend

class Friendship < ActiveRecord::Base belongs_to :user belongs_to :friend

after_create :add_to_denormalized_friends after_destroy :remove_from_denormalized_friends

def add_to_denormalized_friends user.friends_ids << friend.id user.friends_ids.uniq! user.save_without_validation end

def remove_from_denormalized_friends user.friends_ids.delete(friend.id) user.save_without_validation endend

Don’t be Stupid

bob.friends.map(&:email)Status.count()

“email like ‘%#{search}%’”

That’s where we are.

Seriously.If your Rails application is doing anything more

complex than that, you’re doing something wrong*.

* or you observed the First Rule of Butterfield.

Partitioning Comes Later.(we’ll let you know how it goes)

The Cache{ Part the Third }

MemCache

MemCache

MemCache

!

class Status < ActiveRecord::Base class << self def count_with_memcache(*args) return count_without_memcache unless args.empty? count = CACHE.get(“status_count”) if count.nil? count = count_without_memcache CACHE.set(“status_count”, count) end count end alias_method_chain :count, :memcache end after_create :increment_memcache_count after_destroy :decrement_memcache_count ...end

class User < ActiveRecord::Base def friends_statuses ids = CACHE.get(“friends_statuses:#{id}”) Status.find(:all, :conditions => [“id IN (?)”, ids]) endend

class Status < ActiveRecord::Base after_create :update_caches def update_caches user.friends_ids.each do |friend_id| ids = CACHE.get(“friends_statuses:#{friend_id}”) ids.pop ids.unshift(id) CACHE.set(“friends_statuses:#{friend_id}”, ids) end endend

Active

Recor

d

The Future

90% API RequestsCache Them!

“There are only two hard things in CS: cache invalidation and naming things.”

– Phil Karlton, via Tim Bray

Messaging{ Part the Fourth }

You Already Knew All That Other Stuff, Right?

ProducerProducerProducer

MessageQueue

ConsumerConsumerConsumer

DRb

• The Good:

• Stupid Easy

• Reasonably Fast

• The Bad:

• Kinda Flaky

• Zero Redundancy

• Tightly Coupled

Jabber Client(drb)

PresenceIncomingMessages

OutgoingMessages

ejabberd

MySQL

ServerDRb.start_service ‘druby://localhost:10000’, myobject

Clientmyobject = DRbObject.new_with_uri(‘druby://localhost:10000’)

Rinda

• Shared Queue (TupleSpace)

• Built with DRb

• RingyDingy makes it stupid easy

• See Eric Hodel’s documentation

• O(N) for take(). Sigh.

SELECT * FROM messages WHERE substring(truncate(id,0),-2,1) = #{@fugly_dist_idx}

Timestamp: 12/22/06 01:53:14 (4 months ago)Author: latticeMessage: Fugly. Seriously. Fugly.

It Scales.(except it stopped on Tuesday)

Options

• ActiveMQ (Java)

• RabbitMQ (erlang)

• MySQL + Lightweight Locking

• Something Else?

erlang?

What are you doing?

Stabbing my eyes out with a fork.

Starling

• Ruby, will be ported to something faster

• 4000 transactional msgs/s

• First pass written in 4 hours

• Speaks MemCache (set, get)

Use Messages to Invalidate Cache

(it’s really not that hard)

Abuse{ Part the Fifth }

The Italians

9000 friends in 24 hours(doesn’t scale)

http://flickr.com/photos/heather/464504545/http://flickr.com/photos/curiouskiwi/165229284/http://flickr.com/photo_zoom.gne?id=42914103&size=lhttp://flickr.com/photos/madstillz/354596905/http://flickr.com/photos/laughingsquid/382242677/http://flickr.com/photos/bng/46678227/