Save 10% off ANY FITC event with discount code 'slideshare' See our upcoming events at www.fitc.ca OVERVIEW This session will focus on the role of MongoDB within the MEAN stack. We will examine how easy it is to get started building scalable Web applications using MongoDB, Express, Angular and Node.js. We will then take a look at a sample application and discuss some best practises for building your first MEAN application. Presented live at FITC's Spotlight: MEAN Stack event on March 28th, 2014. More info at FITC.ca

1. Spotlight: MEAN Stack
Building your first MEAN app
Solution Architect, MongoDB, Inc.
dbaev@mongodb.com
Dmitry Baev

2. Agenda
• Designing your schema in MongoDB
• How to be MEAN
• Visualizing your MongoDB data in a MEANingful
way!
• Scalability &Availability
• DeploymentArchitectures & Operations

3. The Document Model

4. Terminology
MongoDB RDBMS
Collection Table
Document Row
Index Index
Embedded Document Join
Reference Foreign Key

5. Focus on data storage
Focus on data use

6. What answers do I have?
What questions do I have?

7. 7
Document Data Model
Relational MongoDB
{
first_name: „Paul‟,
surname: „Miller‟,
city: „London‟,
location: [45.123,47.232],
cars: [
{ model: „Bentley‟,
year: 1973,
value: 100000, … },
{ model: „Rolls Royce‟,
year: 1965,
value: 330000, … }
}
}

8. 8
Documents are Rich Data Structures
{
first_name: „Paul‟,
surname: „Miller‟,
cell: „+447557505611‟
city: „London‟,
location: [45.123,47.232],
Profession: [banking, finance, trader],
cars: [
{ model: „Bentley‟,
year: 1973,
value: 100000, … },
{ model: „Rolls Royce‟,
year: 1965,
value: 330000, … }
}
}
Fields can contain an array of
sub-documents
Fields
Typed field values
Fields can
contain arrays

9. 9
Document Model Benefits
• Agility and flexibility
– Data model supports business change
– Rapidly iterate to meet new requirements
• Intuitive, natural data representation
– Eliminates ORM layer
– Developers are more productive
• Reduces the need for joins, disk seeks
– Programming is more simple
– Performance delivered at scale

10. 10
Better Data
Locality
Performance
In-Memory
Caching
In-Place
Updates

11. 11
MongoDB is Fully Featured

12. 12
Do More With Your Data
MongoDB
Rich Queries
• Find Paul’s cars
• Find everybody in London with a car
built between 1970 and 1980
Geospatial
• Find all of the car owners within 5km of
Trafalgar Sq.
Text Search
• Find all the cars described as having
leather seats
Aggregation
• Calculate the average value of Paul’s
car collection
Map Reduce
• What is the ownership pattern of colors
by geography over time? (is purple
trending up in China?)
{
first_name: „Paul‟,
surname: „Miller‟,
city: „London‟,
location: [45.123,47.232],
cars: [
{ model: „Bentley‟,
year: 1973,
value: 100000, … },
{ model: „Rolls Royce‟,
year: 1965,
value: 330000, … }
}
}

13. 13
Drivers & Ecosystem
Drivers
Support for the most popular
languages and frameworks
Frameworks
Morphia
MEAN Stack
Java
Python
Perl
Ruby

14. Let’s get MEAN

15. MEAN Stack
Database
Server
Client
Angularjs-nvd3
-----------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------

16. How to be MEAN!
ServerClient
------------------------------------------------------
View
Controller
Service Route
Controller
Model
REST API
call

17. Node.js MongoDB Driver
• Install using npm
• Basic CRUD
• Mongos
• Aggregation
• Replica Set
• Sharding
• Read preferences

18. Mongoose
• Provides “elegant MongoDB object modeling for Node.js”
using Schemas and Models
• Each schema maps to a MongoDB collection
• Models can be instantiated based on a schema
• Instances of models represent documents in MongoDB
• Support for CRUD, aggregation, validation, pseudo-joins, rich
query builder + lots more!
• Install using npm

19. Mongoose (getting started)
• Require Node module
• Connect to MongoDB
• Define your schema in JSON
• Create the model object

20. Mongoose (example)
• Create/ Update
– #model.save()
• Read
– #model.findOne()
– #model.find()
• Update
– #model.update()
• Delete
– #model.remove()
• Aggregate
– #model.aggregate()

21. Visualizing data
• D3.js – JavaScript library for manipulating
documents based on data – bring your data to life
• NVD3.js – reusable charts for d3.js
• Angularjs-nvd3-directives – Angular‟s way of
extending HTML to create new elements and
functionality

22. D3.js
NVD3.js
Visualizing data
Angularjs
-nvd3-
directives

23. Real-time streaming charts
• Socket.IO (Node.js module)
– “aims to make realtime apps possible in every browser and mobile device”
• MongoDB Tailable Cursors
– requires a capped collection
• NVD3.js Event Listeners
– charts can be refreshed continuouslyas data is inserted/update in
MongoDB collection

24. Demo:
Visualizing your MongoDB data in a
MEANingful way!

25. City of Toronto – Open Data
• Data source: REST ServiceAPI
– To retrieve a list of service requestbetween Feb 1, 2012 to Feb 7, 2012
https://secure.toronto.ca/webwizard/ws/requests.json?start_date=2012-02-
01T00:00:00Z&end_date=2012-02-07T00:00:00Z&jurisdiction_id=toronto.ca
• Output format: JSON
• Refresh rate: continuously - real time refresh

26. Getting started with MEAN
• MEAN.io – ready to use MEAN stack boilerplate
• Yeoman – scaffolding tool for building modern web apps
– CommunityMEAN stack generators:
• https://github.com/wlepinski/generator-meanstack
• https://github.com/jrcryer/generator-mean
• https://github.com/chrisenytc/generator-meanis

27. Scalability & Availability

28. 28
Scalability
Auto-Sharding
• Increase capacity as you go
• Commodity and cloud architectures
• Improved operational simplicity and cost visibility

29. 29
High Availability
• Automated replication and failover
• Multi-data center support
• Improved operational simplicity (e.g., HW swaps)
• Data durability and consistency

30. 30
MongoDB Architecture

31. Deployment Architectures &
Operations

32. 32
Single Data Center
• Automated failover
• Tolerates server failures
• Tolerates rack failures
• Number of replicas
defines failure tolerance
Primary – A Primary – B Primary – C
Secondary – A Secondary – ASecondary – B
Secondary – BSecondary – CSecondary – C

33. 33
Active/Active Data Center
• Tolerates server, rack, data center failures, network
partitions
Data Center - West
Primary – A Primary – B Primary – C
Secondary – A Secondary – BSecondary – C
Data Center - East
Secondary – A Secondary – B Secondary – C
Secondary – B Secondary – C Secondary – A
Data Center - Central
Arbiter – A Arbiter – B Arbiter – C

34. 34
Read Global/Write Local
Primary:NYC
Secondary:NYC
Primary:LON
Primary:SYD
Secondary:LON
Secondary:NYC
Secondary:SYD
Secondary:LON
Secondary:SYD

35. References
• MEAN.io - http://www.mean.io
• MongoDB - http://mongodb.com
• Express - http://expressjs.com
• Angular - http://angularjs.org
• Node - http://nodejs.org
• Socket.IO- http://http://socket.io
• Angularjs-nvd3-directives - http://cmaurer.github.io/angularjs-nvd3-
directives

36. mongodb.org/downloads

37. Online Training at MongoDB University

38. For More Information
Resource Location
MongoDB Downloads mongodb.org/downloads
Free Online Training education.mongodb.com
Webinars and Events mongodb.com/events
White Papers mongodb.com/white-papers
Case Studies mongodb.com/customers
Presentations mongodb.com/presentations
Documentation docs.mongodb.org
Additional Info info@mongodb.com
Resource Location

39. Thank You
Solution Architect, MongoDB, Inc.
dbaev@mongodb.com
Dmitry Baev