Overview of MongoDB at Dallas.rb Ruby group. Thanks to John Nunemaker for sharing slides!

1. MongoDB
Ruby friendly document storage that doesn’t rhyme with ouch.
Dallas.rb

2. Wynn Netherland
@pengwynn
http://squeejee.com
http://locomotivation.com

3. Not every data problem looks like this

4. So why do so many databases look like this?

5. and this?

6. When are RDBMS less than ideal?
Your data is stored and retrieved mainly by primary key,
without complex joins.
You have a non-trivial amount of data, and the
thought of managing lots of RDBMS shards and
replication failure scenarios gives you the fear.
http://www.metabrew.com/article/anti-rdbms-a-list-of-distributed-key-
value-stores/

7. Enter key value stores

8. Some of the players
Project Voldemort
Ringo
Scalaris
Kai
Dynomite
MemcacheDB
ThruDB
CouchDB
Cassandra
HBase
Hypertable
Tokyo Cabinet/Tyrant
http://www.metabrew.com/article/anti-rdbms-a-list-of-distributed-key-value-stores/

9. Tokyo Cabinet:
Popular with Rubyists, Big in Japan

10. Go kick the tires
• Lightning fast
• Works best for at objects
• Tokyo Tyrant for network access
http://www.igvita.com/2009/02/13/tokyo-cabinet-beyond-key-value-
store/

11. More document-oriented solutions

13. CouchDB
Apache CouchDB is a distributed, fault-tolerant and
schema-free document-oriented database accessible
via a RESTful HTTP/JSON API.
http://couchdb.apache.org/

14. Erlang + Javascript

15. Map + reduce

16. Very cool

17. Plenty o’ Ruby to go around

18. Ruby libraries for CouchDB
• CouchRest
• Basic model
• RelaxDB
• CouchPotato
• CouchFoo
• ActiveCouch
http://www.slideshare.net/brianthecoder/couchdb

19. Throw out everything
you learned about DB design

20. SQL CouchDB
Prede ned, explicit schema Dynamic, implicit schema
Collection of named documents with varying
Uniform tables of data
structure
Normalized. Objects spread across tables. Denormalized. Docs usually self contained. Data
Duplication reduced. often duplicated.
Must know schema to read/write a complete
Must know only document name
object
Dynamic queries of static schemas Static queries of dynamic schemas
http://damienkatz.net/files/What is CouchDB.pdf

21. SQL CouchDB
Prede ned, explicit schema Dynamic, implicit schema
Collection of named documents with varying
Uniform tables of data
structure
Normalized. Objects spread across tables. Denormalized. Docs usually self contained. Data
Duplication reduced. often duplicated.
Must know schema to read/write a complete
Must know only document name
object
Dynamic queries of static schemas Static queries of dynamic schemas

22. In walks Mongo

24. INTRO

25. INTRO
• Built For Speed
• Document/Collection Oriented
• Dynamic Queries and Indexes
• Replication and Failover

26. GREAT FOR
• Websites
• Caching
• High volume, low value
• High scalability
• Storage of program objects and json

27. NOT AS GREAT FOR
• Highly transactional
• Ad-hoc business intelligence
• Problems requiring SQL

28. INSTALLATION
• mkdir -p /data/db
• download pre-built for OSX and unzip to /usr/local/
• cp -R /usr/local/pathtomongo/bin /usr/local/bin

29. DATABASE
• same concept as mysql
• made up of collections

30. COLLECTION
• Think table, but with no schema
• For grouping documents into smaller query sets (speed)
• Eachtop level entity in your app would have its own collection
(users, articles, etc.)
• Indexable by one or more key

31. DOCUMENT
• Stored in a collection, think record or row
• Can have _id key that works like primary keys in MySQL
• Two options for relationships: subdocument or db reference

32. STORAGE (BSON)
{ author: 'joe',
created: Date('03-28-2009'),
title: 'Yet another blog post',
text: 'Here is the text...',
tags: [ 'example', 'joe' ],
comments: [ { author: 'jim', comment: 'I disagree' },
{ author: 'nancy', comment: 'Good post' }
]
}
http://www.mongodb.org/display/DOCS/BSON

33. THAT LOOKS LIKE JSON
Where’s the Ruby?

34. QUERYING
• db.collection.find({‘first_name’: ‘John’}) # finds all Johns
• db.collection.find({‘first_name’: /^J/}) # regex
• db.collection.find_first({‘_id’:1}) # finds first with _id of 1
• db.collection.find({‘age’: {‘$gt’: 21}}) # finds possible drinkers
• db.collection.find({‘author.first_name’:‘John’}) # subdocument
• db.collection.find({$where:‘this.age >= 6 && this.age <= 18’})

35. MORE QUERYING
• $in, $nin, $all, $ne, $gt, $gte, $lt, $lte, $size, $where
• :fields (like :select in active record)
• :limit, :offset for pagination
• :sort ascending or descending [[‘foo’, 1], [‘bar’, -1]]
• count and group (uses map/reduce)

36. HOW DO YOU
USE IT WITH RUBY
• mongo-ruby-driver http://github.com/mongodb/mongo-ruby-
driver
• activerecord adapter http://github.com/mongodb/
activerecord-mongo-adapter
• mongorecord http://github.com/mongodb/mongo-
activerecord-ruby

37. NUNEMAPPER
(MONGOMAPPER)
• Mongo is not MySQL
• DSL for modeling domain should also teach you Mongo
• It sounded fun
• Almost finished and sitting in private GitHub repo

38. FEATURES
• Typecasting • Create and Update with
single or multiple
• Callbacks(ActiveSupport
Callbacks) • Delete and Destroy and _all
counterparts
• Validations (using my fork of
validatable) • Find: id, ids, :all, :first, :last
• Connection and database • Associations (incomplete)
can differ per document

39. EXAMPLE
class User
include MongoMapper::Document
key :name, String, :required => true, :length => 5..100
key :email, String, :required => true, :index => true
key :age, Integer, :numeric => true
key :active, Boolean, :default => true
one :address
many :articles
end
class Address
include MongoMapper::Document
key :street, String
key :city, String
key :state, String, :length => 2
key :zip, Integer, :numeric => true, :length => 5
end

40. RANDOM AWESOMENESS
• Capped collections (think memcache, actually used for
replication)
• Upserts db.collection.update({‘_id’:1}, {‘$inc’:{‘views’:1}})
• Multikeys (think tagging and full text search)
• GridFS and auto-sharding

41. John Nunemaker
http://orderedlist.com
http://railstips.org
Links
http://www.10gen.com
http://mongodb.com

42. Wynn Netherland
@pengwynn
http://squeejee.com
http://locomotivation.com