1. RedDotRubyConf 2011
Benefits of MongoDB:
Reduce Complexity &
Adapt to Changes
Vinova Pte Ltd

2. About me
• Alex Nguyen
• Co-founder at Vinova
• http://vinova.sg/
• https://github.com/vinova/

3. Agenda
• What’s MongoDB?
• Why MongoDB reduce complexity?
• Why MongoDB adapt to changes better?
• Case studies

4. I don’t hate SQL
Just found a better tool
for most of my use
cases

5. What’s MongoDB?
“MongoDB (from "humongous") is a scalable, high-
performance, open source, document-oriented
database”
mongodb.org

6. What’s MongoDB?
http://www.slideshare.net/kbanker/mongodb-schema-design-mongo-chicago

7. What’s MongoDB?
• Collections ~ Tables
• Documents ~ Rows

8. MongoDB Philosophy
• Reduce transactional semantics for
performance
• No-relational is the best way to scale
horizontally
mongodb.org

9. MongoDB Features
• JSON style documents • Map / Reduce
• Index on any attribute • GridFS to store files
• Rich queries • Server-side JavaScript
• In-place update • Capped collections
• Auto-sharding • Full-text-search
(coming soon)

10. MongoDB's flexibility data structure, ability to index &
query data, and auto-sharding make it a strong tool that
adapt to changes well. It also help to reduce complexity
comparing to tradition RDBMS.

11. Why MongoDB reduce
complexity?
• Get rid of migrations
• Get rid of relationships (most of)
• Reduce number of database requests
• JSON (client, server, and database)

12. Get rid of migrations
• No create table
• No alter column
• No add column
• No change column

13. Get rid of relationships
• Many one-to-one and one-to-many
relationships is not necessary
• User :has_one :setting
• User :has_many :addresses
• User :has_many :roles
• Post :has_many :tags

14. Reduce number of
database requests
• Pre-joined
• Rich queries
• Atomic, in-place updates

15. JSON
• MongoDB knows JSON
• Don’t have to convert data from / to JSON

16. Adapt to changes
• Changes in schema
• Changes in data & algorithms
• Changes for performance & scaling

17. Changes in schema
• In modern apps, schema changes quite
often (weekly, monthly ...)
• Alter tables are expensive in RDBMS
• Dynamic schema document makes those
changes seamlessly

18. Changes in data &
algorithms
• Atomic, in-place updates are very
powerful to modify data
$inc, $set, $unset, $push, $pop, $rename, $bit
• Rich$all, $exists,and aggregators
$in,
queries
$size, $type, regexp
count(), size(), distinct(), min(), max()
• Map/Reduce

19. Changes for
performance & scaling
• Very fast & ready to scale =>
• Don’t have to use additional tools
(memcached ...)
• Don’t have to change platforms

20. Case Studies
• Store crawled info as embedded documents
• Product listing
• Find unique slug
• Voting

21. Store crawled info as
embedded documents
• Data from 3rd party sources
• Sources and data formats can be changed in
the future

22. Store crawled info as
embedded documents
product = {
"_id" : ObjectId("4d8ace4b0dc3e43231bb930d"),
"name" : "Product ABC",
"amazon" : {
"asin" : ...,
"price" : ...,
....
}
};

23. Store crawled info as
embedded documents
product = {
"_id" : ObjectId("4d8ace4b0dc3e43231bb930d"),
"name" : "Product ABC",
"amazon" : {
"asin" : ...,
"price" : ...,
"shipping_cost" : ...,
...
}
};

24. Store crawled info as
embedded documents
product = {
"_id" : ObjectId("4d8ace4b0dc3e43231bb930d"),
"name" : "Product ABC",
"amazon" : {
"asin" : ...,
"price" : ...,
"shipping_cost" : ...,
....
},
"walmart" : {
"price" : ...,
...
}
};

25. Store crawled info as
embedded documents
def Product.find_by_asin(asin)
Product.where('amazon.asin' => asin).first
end

26. Product listing
• A product can be listed on multiple
categories on certain months

27. Product listing
• Need an extra table to express which
product is listed in which category and
on which month
product_id category_id month
1 2 2011-03
1 2 2011-04
SQL

28. Product listing
• To query products listed in category 2 and
month ‘2011-04’
Product.join(:listings).where('category_id = ? AND month = ?', 2,
‘2011-04’)
SQL

29. Product listing
• Store listings in product itself
product = {
"_id" : ObjectId("4d8ace4b0dc3e43231bb930d"),
"name" : "Product ABC",
"listings" : [ [1, "2011-01"], [1, "2011-04"], [3,
"2011-01"] ]
};
Mongo

30. Product listing
• Store listings in product itself
product = {
"_id" : ObjectId("4d8ace4b0dc3e43231bb930d"),
"name" : "Product ABC",
"listings" : [ [1, "2011-01"], [1, "2011-04"], [3,
"2011-01"] ]
};
• Query is simpler
Product.where("listings" => [1, '2011-04'])
Mongo

31. Product listing
• Store listings in product itself
product = {
"_id" : ObjectId("4d8ace4b0dc3e43231bb930d"),
"name" : "Product ABC",
"listings" : [ [1, "2011-01"], [1, "2011-04"], [3,
"2011-01"] ]
};
• Query is simpler
Product.where("listings" => [1, '2011-04'])
• Can index listings array
db.products.ensureIndex({"listings" : 1 });
Mongo

32. Product listing
• Clearer but more data storage
product = {
"_id" : ObjectId("4d8ace4b0dc3e43231bb930d"),
"name" : "Product ABC",
"listings" : [
{"category_id" : 1, "month" : "2011-01" }, {"category_id" : 1,
"month" : "2011-04" }, {"category_id" : 3, "month" : "2011-01" }]
};
db.products.find("listings" : {"category_id" : 1, "month" :
"2011-04" })
Mongo

33. Find unique slug
• book1 = #<Book id: .., title => “Ruby”, ... >
• book2 = #<Book id: .., title => “Ruby”, ... >
• book2.uniq_slug => /books/ruby-1
• Need n queries to find an unique slug
def uniq_slug
slug = original_slug = title.to_slug
counter = 0
while (where(:slug => slug).count > 0)
counter += 1
slug = "#{original_slug}-#{counter}"
end
slug
end SQL

34. Find unique slug
• Need one query using regexp matching
def find_uniq_slug
original_slug = title.to_slug
slug_pattern = /^#{original_slug}(-d+)?$/
book = where(:slug => slug_pattern).
order(:slug.desc).limit(1)
if book
max_counter = book.slug.match(/-(d+)$/)[1].to_i
"#{original_slug}-#{max_counter + 1}"
else
original_slug
end
end
db.books.ensureIndex({"slug" : -1 })
Mongo

35. Voting
• A user can only vote each post once
• up / down votes has different points
• Cached votes_count and votes_point in
post for sorting and querying
• Post.max(:votes_point)
• Post.order_by(:votes_count.desc)

36. Voting
• Use extra votes table to store vote data
SQL

37. Voting
def vote(user_id, post_id, value)
# Validate
not_voted = Vote.where(:user_id => user_id,
:post_id => post_id).count == 0
if not_voted
# Create a new vote
Vote.create(
:user_id => user_id,
:post_id => post_id,
:value => value
)
# Get post
post = Post.find(post_id)
# Update votes_point & votes_count
post.votes_point += POINT[value]
post.votes_count += 1
post.save
end
end SQL

38. Voting
def vote(user_id, post_id, value)
# Validate
not_voted = Vote.where(:user_id => user_id,
:post_id => post_id).count == 0
if not_voted
# Create a new vote
Vote.create(
:user_id => user_id, 4 requests
:post_id => post_id,
:value => value
)
# Get post
post = Post.find(post_id)
# Update votes_point & votes_count
post.votes_point += POINT[value]
post.votes_count += 1
post.save
end
end SQL

39. Voting
def unvote(user_id, post_id)
# Get current vote
vote = Vote.where(:user_id => user_id,
:post_id => post_id).first
# Check if voted
if vote
# Destroy vote
vote.destroy
# Get post
post = Post.find(post_id)
# Update votes_point & votes_count
post.votes_point -= POINT[vote.value]
post.votes_count -= 1
post.save
end
end SQL

40. Voting
def unvote(user_id, post_id)
# Get current vote
vote = Vote.where(:user_id => user_id,
:post_id => post_id).first
# Check if voted
if vote
# Destroy vote 4 requests
vote.destroy
# Get post
post = Post.find(post_id)
# Update votes_point & votes_count
post.votes_point -= POINT[vote.value]
post.votes_count -= 1
post.save
end
end SQL

41. Voting
• Embed votes data to post
• use arrays to store who vote up and who
vote down
post = {
"_id" : ObjectId("4d8ace4b0dc3e43231bb930d"),
"title" : "Post ABC",
....
"votes" : {
"up" : [ user_id_1 ],
"down" : [ user_id_2 ],
"count" => 2,
"point" => -1
Mongo
}
};

42. def vote(user_id, post_id, value)
# Find post with post_id that was not up voted or down voted by user_id
query = {
'post_id' => post_id,
'votes.up' => { '$ne' => user_id },
'votes.down' => { '$ne' => user_id }
}
# Push user_id to votes.up_ids if vote up or votes.down_ids if vote_down
# and update votes.point and votes.count
update = {
'$push' => {
(value == :up ? 'votes.up' : 'votes.down') => user_id
},
'$inc' => {
'votes.point' => POINT[value],
'votes.count' => +1
}
}
# Validate, update and get result
post = Post.collection.find_and_modify(
:query => query,
:update => update,
:new => true # return post after update votes data
)
end Mongo

43. def vote(user_id, post_id, value)
# Find post with post_id that was not up voted or down voted by user_id
query = {
'post_id' => post_id,
'votes.up' => { '$ne' => user_id },
'votes.down' => { '$ne' => user_id }
}
# Push user_id to votes.up_ids if vote up or votes.down_ids if vote_down
# and update votes.point and votes.count
update = {
'$push' => {
(value == :up ? 'votes.up' : 'votes.down') => user_id
},
'$inc' => {
'votes.point' => POINT[value],
'votes.count' => +1
}
}
# Validate, update and get result
post = Post.collection.find_and_modify(
:query => query, one request
:update => update,
:new => true # return post after update votes data
)
end Mongo

44. def unvote(user_id, post_id)
# Find post with post_id that was up voted or down voted by user_id
query = {
'post_id' => post_id,
'$or' => { 'votes.up' => user_id, 'votes.down' => user_id }
}
# Pull user_id from both votes.up_ids and votes.down_ids
# and update votes.point and votes.count
update = {
'$pull' => {
'votes.up' => user_id,
'votes.down' => user_id
},
'$inc' => {
'votes.point' => -POINT[value],
'votes.count' => -1
}
}
# Validate, update and get result
post = Post.collection.find_and_modify(
:query => query,
:update => update,
:new => true # return post after update votes data
)
end Mongo

45. def unvote(user_id, post_id)
# Find post with post_id that was up voted or down voted by user_id
query = {
'post_id' => post_id,
'$or' => { 'votes.up' => user_id, 'votes.down' => user_id }
}
# Pull user_id from both votes.up_ids and votes.down_ids
# and update votes.point and votes.count
update = {
'$pull' => {
'votes.up' => user_id,
'votes.down' => user_id
},
'$inc' => {
'votes.point' => -POINT[value],
'votes.count' => -1
}
}
# Validate, update and get result
post = Post.collection.find_and_modify(
:query => query, one request
:update => update,
:new => true # return post after update votes data
)
end Mongo

46. Voting
• For a complete solution:
• gem install voteable_mongoid
• visit https://github.com/vinova/voteable_mongoid

47. Summary
• MongoDB is
• Flexible
• Powerful
• Fun

48. Thank you
Alex Nguyen
@tiendung
alex@vinova.sg

49. References
Introduction to MongoDB
• http://scribd.com/doc/26506063/Introduction-To-MongoDB
• http://slideshare.net/jnunemaker/why-mongodb-is-awesome
Schema Design
• http://slideshare.net/kbanker/mongodb-schema-design-mongo-chicago
Indexing & Query Optimization
• http://slideshare.net/mongodb/indexing-with-mongodb
• http://slideshare.net/mongodb/mongodb-indexing-the-details