This talk will introduce the features of MongoDB by walking through how one can building a simple location-based application using MongoDB. The talk will cover the basics of MongoDB's document model, query language, map-reduce framework and deployment architecture.

1. Building Applications
With MongoDB
An Introduction
With Steve Francia
@spf13

2. Agenda
•MongoDB: Data modeling, queries,
geospatial, updates, map reduce
•Using a location-based app as an example
•Example Works in MongoDB JS shell

3. Why MongoDB
• Open source
• Designed for today
• Today’s hardware / environments
• Today’s challenges
• Great developer experience
• Reliable
• Scalable

4. Use Cases
• RDBMS replacement for high-traffic web
applications
• Content Management-type applications
• Real-time analytics
• High-speed data logging
Web 2.0, Media, SaaS, Gaming, Finance, Telecom, Healthcare

5. In Good Company

6. Let’s Design An App
• Users Check-in to a Location
• Leave Notes and Comments About That
Location
• Requirements, then Documents

7. Terminology
RDBMS MongoDB
Table, View ➜ Collection
Row ➜ JSON Document
Index ➜ Index
Join ➜ Embedded Document
Partition ➜ Shard
Partition Key ➜ Shard Key

8. Documents
{
_id : ObjectId("4c4ba5c0672c685e5e8aabf3"),
author : "spf13",
date : "Sat Jul 24 2010 19:47:11",
text : "MongoSF",
tags : [ "San Francisco", "MongoDB" ]
}
Note: _id is unique, but can be anything
you’d like

9. Collections
Doc 1 Doc 4 Doc 7
Doc 2 Doc 5 Doc 8
Doc 3 Doc 6 Doc 9
Places Users Check-Ins

10. Application Goals
(1)
Q: Current location (3) Record user
A: Places near location checkins
(2) Add user (4) Stats about
generated checkins
content
Places Check ins

11. Places v1
place1 = {
name : "10gen HQ",
address : "134 5th Avenue 3rd Floor",
city : "New York",
zip : "10011"
}

12. Places v2
place1 = {
name : "10gen HQ",
address : "134 5th Avenue 3rd Floor",
city : "New York",
zip : "10011"
}
> db.posts.find({zip: "10011"}).limit(10)

13. Places v2
place1 = {
name : "10gen HQ",
address : "134 5th Avenue 3rd Floor",
city : "New York",
zip : "10011",
tags : [ "business", "awesome" ]
}

14. Places v3
place1 = {
name : "10gen HQ",
address : "134 5th Avenue 3rd Floor",
city : "New York",
zip : "10011",
tags : [ "business", "awesome" ]
}
> db.posts.findOne({ zip: "10011",
tags: "awesome" })

15. Places v3
place1 = {
name : "10gen HQ",
address : "134 5th Avenue 3rd Floor",
city : "New York",
zip : "10011",
tags : [ "business", "awesome" ],
latlong : [40.0,72.0]
}

16. Places v3
place1 = {
name : "10gen HQ",
address : "134 5th Avenue 3rd Floor",
city : "New York",
zip : "10011",
tags : [ "business", "awesome" ],
latlong : [40.0,72.0]
}
> db.places.ensureIndex({latlong : "2d"})

17. Places v3
place1 = {
name : "10gen HQ",
address : "134 5th Avenue 3rd Floor",
city : "New York",
zip : "10011",
tags : [ "business", "awesome" ],
latlong : [40.0,72.0]
}
> db.places.ensureIndex({latlong : "2d"})
> db.places.find({latlong:{$near:[40,70]}})

18. Places v4
place1 = {
name : "10gen HQ",
address : "134 5th Avenue 3rd Floor",
city : "New York",
zip : "10011",
tags : [ "business", "awesome" ],
latlong : [40.0,72.0],
tips : [ { user : "ryan",
time : 6/26/2010,
tip : "stop by for office hours on
Wednesdays from 4-6pm"},
{.....}]
}

19. Inserting Places
Initial Data Load
> db.places.insert(place1)

20. Querying Your Place
Creating Your Index
> db.places.ensureIndex({latlong : "2d"})
> db.places.ensureIndex({ tags : 1 })
> db.places.ensureIndex({ name : 1 })

21. Querying Places
Finding Places
> db.places.find({latlong:{$near:[40,70]}})
With Regular Expressions
> db.places.find({name: /^typeAheadString/ })
By Tag
> db.posts.find({tags: "business" })

22. Application Goals
(1)
Q: Current location (3) Record user
A: Places near location checkins
(2) Add user (4) Stats about
generated checkins
content
Places Check ins

23. Updating Places
Using Update to Add Tips
> db.places.update({name:"10gen HQ"},
{ $push : {tips: {user:"nosh", time:
6/26/2010, tip:"stop by for office hours on
Wednesdays from 4-6"}}}})

24. Atomic Updates
• $set, $unset, $rename
• $push, $pop, $pull, $addToSet
• $inc

25. Application Goals
(1)
Q: Current location (3) Record user
A: Places near location checkins
(2) Add user (4) Stats about
generated checkins
content
Places Check ins

26. Users
user1 = {
name : "ben",
address : "ben@email.com",
...
checkins : [4b97e62bf1d8c7152c9ccb74,
5a20e62bf1d8c736ab]
}
checkins [] = ObjectId reference to check-in
collection

27. Check-Ins
checkin1 = {
place : "10gen HQ",
ts : 9/20/2010 10:12:00,
userId : <objectId of user>
}

28. Checking In
2 Operations
• Insert check in object
[checkin collection]
• Update ($push) user object
[user collection]

29. Querying Your Place
Creating Your Index
> db.checkins.ensureIndex({place:1,ts:1})
> db.checkins.ensureIndex({ ts:1 })

30. Application Goals
(1)
Q: Current location (3) Record user
A: Places near location checkins
(2) Add user (4) Stats about
generated checkins
content
Places Check ins

31. Simple Stats
> db.checkins.find({place : "10gen HQ"})
> db.checkins.find({place : "10gen
HQ"}).sort({ts:-1}).limit(10)
> db.checkins.find({place : "10gen HQ", ts:
{ $gt: <midnight>}}).limit()
> db.checkins.find().sort({ts:-1}).limit(50)

32. Stats With MapReduce
mapFunc = function() { emit(this.place, 1); }
reduceFunc = function(key, values) {
return Array.sum(values);
}
db.checkins.mapReduce(mapFunc,reduceFunc, { query:
{ timestamp: {$gt:<nowminus3hrs>}}, out: result })
result = [{_id:”10gen HQ”, value: 17}, {…..}, {….}]
db.result.find({ value: {$gt: 15},
_id: {$in: [….., ….., …..]}
})

33. Application Goals
(1)
Q: Current location (3) Record user
(2) Add user
generated
content
:)A: Places near location checkins
(4) Stats about
checkins
Places Check ins

34. MongoDB
Deployments

35. Replica Sets
Primary Primary Primary
Secondary Secondary Secondary
Secondary Arbiter Secondary
Secondary
Secondary

36. Sharding
App App App
Server Server Server
MongoS MongoS MongoS
ConfigD
ConfigD
ConfigD
MongoD MongoD MongoD MongoD
MongoD MongoD MongoD MongoD
MongoD MongoD MongoD MongoD

37. Try it for yourself at
try.mongodb.org

38. spf13.com
github.com/spf13
@spf13
Questions?
download at mongodb.org
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