The document is an introduction to MongoDB, highlighting its features as a high-performance, horizontally scalable, and open-source document database. It covers basic concepts, data modeling, and queries for building applications, using a monitoring system as a practical example. The document also emphasizes the importance of MongoDB's drivers for various programming languages and mentions the community's contribution to its development.

1. #mongodb
Build your first app;
an introduction to MongoDB
Christian Amor Kvalheim
Developer Experience Team Lead, MongoDB

2. Christian Kvalheim
• Team Lead MongoDB Drivers
• Node.js driver developer
• Been using MongoDB for 5 years
• Working at MongoDB last 3 years

3. What is MongoDB?

4. MongoDB is a ___________
database
• Document
• Open source
• High performance
• Horizontally scalable
• Full featured

5. Document Database
• Not for .PDF & .DOC files
• A document is essentially an associative array
• Document = JSON object
• Document = PHP Array
• Document = Python Dict
• Document = Ruby Hash
• etc

6. Open Source
• MongoDB is an open source project
• On GitHub
• Licensed under the AGPL
• Started & sponsored by MongoDB Inc
• Commercial licenses available
• Contributions welcome

7. High Performance
• Written in C++
• Extensive use of memory-mapped files
i.e. read-through write-through memory caching.
• Runs nearly everywhere
• Data serialized as BSON (fast parsing)
• Full support for primary & secondary indexes
• Document model = agile development

8. Database Landscape

9. Full Featured
• Flexible schema
• Rich ad-hoc queries
• Real time aggregation
• Strongly consistent
• Geospatial features
• Built-in automatic failover
• Horizontally scalable reads/writes
• Support for most programming languages

10. mongodb.org/downloads

11. Running MongoDB
$ tar zxf mongodb-osx-x86_64-2.6.4.tgz
$ cd mongodb-osx-x86_64-2.6.4/bin
$ mkdir –p /data/db
$ ./mongod

12. Mongo Shell
$ mongo
MongoDB shell version: 2.6.4
connecting to: test
> db.test.insert({text: 'Welcome to MongoDB'})
> db.test.find().pretty()
{
"_id" : ObjectId("51c34130fbd5d7261b4cdb55"),
"text" : "Welcome to MongoDB"
}

13. Building an App with
MongoDB

14. Terminology
RDBMS MongoDB
Table, View ➜ Collection
Row ➜ Document
Index ➜ Index
Join ➜ Embedded Document
Foreign Key ➜ Reference
Partition ➜ Shard

15. Let’s Build a Monitoring System

16. First step in any application is
Determine basic requirements

17. Basic Monitoring Requirements
• Data generated at per-second intervals
• Metrics to capture (ex. CPU, memory, IO)
• Document structure for fast writes and easy reads

18. In a relational base app
We would start by doing schema
design

19. Relational Schema Options
CPU Metrics
Memory Metrics
IO Metrics
Events
• Timestamp
• CPU metrics
• Memory metrics
• IO metrics
Or

20. In a MongoDB based app
We start with a generic model
and let the documents evolve

21. MongoDB Document Modeling
Events
Timestamp (min)
CPU []
• Second
• Metric
Memory []
• Second
• Metric
IO []
• Second
• Metric

22. Working With MongoDB

23. Start with the Mongo Shell
$ mongo
MongoDB shell version: 2.6.4
connecting to: test
>
Full Javascript shell

24. Switch to Your DB
> use monitoring
switching to db monitoring
DB files are created once you save a
document

25. Create an Empty Event
> var event = {
ts: ISODate(“2014-09-16T09:00:00”),
cpu: [ 0, 0, …, 0 ],
memory: [ 0, 0, …, 0 ],
io: [ 0, 0, …, 0 ],
}
Insert zeroed-out arrays to fill in later

26. Insert the Event
> db.events.insert(event)
No collection creation necessary

27. Find One Record
> db.events.findOne()
{
"_id" : ObjectId("50804d0bd94ccab2da652599"),
”ts" : ISODate(“2014-09-16T09:00:00”),
”cpu" : [ 0, 0, …, 0 ],
”memory" : [ 0, 0, …, 0 ],
“io” : [ 0, 0, …, 0 ]
}

28. How do you capture events?
Serve
r
Serve
r
Serve
r
MongoD
B
memory
interaction
interaction
interaction

29. Adding a New Event
> db.events.update(
{ ts: ISODate(“2014-09-16T09:00:00”) }
{ $set: {
“cpu.0” : 50,
“memory.0”: 1500,
“io.0”: 10 }
}
)
Use atomic in-place updates to add metric values

30. How do you plot charts?

31. Finding an Hour of Events
> db.events.find({
ts: {
$gte: ISODate(“2014-09-16T09:00:00”),
$lt: ISODate(“2014-09-16T10:00:00”)
}
}).sort({ts:1})
Find using a range and sort results
ascending

32. How do you roll up the data?
Hour Avg Cpu
0 50
1 65
2 75
3 40
4 45
5 60
6 25
… …
23 30

33. Aggregate Metrics
> db.events.aggregate([
{ $match: { ts: { $gte: date0, $lt: date1 } } },
{ $project: { _id: 0, ts: 1, cpu: 1 } },
{ $unwind: “$cpu” },
{ $group: {
_id: { $hour: “$ts” },
avg_cpu: { $avg: “$cpu” } } }
])
Use Aggregation Framework to roll up data

34. How do you scale this workload
• Replica Sets
– Add data redundancy
– Automatic failover
– Tunable durability, consistency
• Sharding
– Scale reads and writes
– Support dynamic data growth
– Automatically partitions workload
– Horizontally scalable

35. MongoDB Drivers

36. Real applications are not
built in the shell

37. MongoDB has native
bindings for over 12
languages

40. MongoDB Drivers
• Official Support for 12 languages
• Community drivers for tons more
• Drivers connect to MongoDB servers
• Drivers translate BSON into native types
• Shell is not a driver, but works like one in some ways
• Installed using typical means (npm, pecl, gem, pip)

41. docs.mongodb.org

42. Online Training at MongoDB
University

43. Suggestions for Talks
• Talk to me at Meet the Experts
– 11 am – 12 pm
– 1 pm – 2 pm
– Or catch me in the hallway
• MongoDB for the internet of things
• Socialite the Open Source Status Feed
• The Future of MongoDB Storage

44. Questions?

45. #mongodb
Thank You
Christian Amor Kvalheim
Developer Experience Team Lead, MongoDB