1. MongoDB Basic Concepts
Norberto Leite
Senior Solutions Architect, 10gen

2. Agenda
• Overview
• Replication
• Scalability
• Consistency & Durability
• Flexibility / Developer Experience
2

3. But first ...

4. Happy
Hanukkah!!!

5. Who’s this guy?

6. Norberto Leite
Senior Solutions Architect
@nleite / norberto@10gen.com
6

7. Norberto Leite
Senior Solutions
Architect
@nleite /
norberto@10gen.com
Barcelona
7

8. Norberto Leite
Senior Solutions
Architect
@nleite /
norberto@10gen.com
Barcelona
Love MongoDB
8

9. Norberto Leite
Senior Solutions
Architect
@nleite /
norberto@10gen.com
Barcelona
Love MongoDB
and others ...
9

10. Your Data

13. Fundamentals
Document
Application
High Oriented
{
Performance
name: ‘Norberto Leite’,
position: ‘SA’,
nick: ‘WingMan’,
based: [‘Barcelona’, ‘London’]
}
mongoDB mongoDB mongoDB mongoDB Fully
Consistent
Horizontal Scalability
13

14. Replication

15. Why do we need Replication?
• Failover
• Backups
• Secondary Batch Jobs
• High Availability
15

16. Outages
• Planned
– Hardware upgrade
– OS or file-system tuning
– Software upgrade
– Relocation of data to new file-system / storage
• Un-planed
– Human Error
– Hardware Failure
– Data Center / Region Outage
– Application Corruption
16

17. Replica Sets
• Data Protection
– Multiple copies of data
– Data spread across data centers, AZ’s etc
• High Availability
– Automated Failover
– Automated Recovery
17

18. Asynchronous
Replication
App Write
Primary
Read
(default)
Secondary
Read
(optional)
Secondary
Read
(optional)

19. Failover
App Write
Primary
Read
(default)
Secondary
Read
(optional)
Secondary
Read
(optional)

20. Automatic Failover
Primary Election
App
Primary
Write
Primary
Read
(default)
Secondary
Read
(optional)

21. Automatic Recovery
App
Read Recovery
Secondary
(optional)
Write
Primary
Read
(default)
Secondary
Read
(optional)

22. Sharding

23. Sharding
• Data Location Transparent to Code
• Data Distribution is Automatic
– as well as re-distribution
• Aggregation System resources Horizontally
• No CODE Changes!!!
23

24. sh.shardCollection("test.tweets", {_id: 1} , false)
Range
Distribution
shard01 shard02 shard03
a-i j-m n-z

25. Chunk Split
shard01 shard02 shard03
a-i ja-jz
j-m n-z
ka-kj
k-m
ki-m

26. Auto Balancing
shard01 shard02 shard03
a-i ja-jz
j-m n-z
ka-kj
ki-m

27. Routed
db.tweets.find( {_id: Queries
‘norberto’})
shard01 shard02 shard03
a-i ja-jz
j-m n-z
ka-kj
ki-m

28. db.tweets.find( {email:
‘norberto@10gen’})
Scatter Gather
shard01 shard02 shard03
a-i ja-jz
j-m n-z
ka-kj
ki-m

29. Caching
96 GB Mem
3:1 Data/Mem
shard01
a-i
300 GB Data
j-r
n-z
300 GB

30. Horizontal Distribution
96 GB Mem 96 GB Mem 96 GB Mem
1:1 Data/Mem 1:1 Data/Mem 1:1 Data/Mem
shard01 shard02 shard03
a-i a-i
j-r n-z
300 GB Data
100 GB 100 GB 100 GB

31. Consistency and
Durability

32. Consistency
• Eventual Consistency
– Allow updates when a system as been partitioned
– Resolve conflicts later
– Ex: Cassandra, CouchDB
• Immediate Consistency
– Single Master
– Avoids conflicts
– Example: MongoDB
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33. Durability
• For how long is my data available?
• When do I know my data is safe?!
• Where is it safe?
• MongoDB style:
– Fire and Forget
– Get Last Error
– Journal Sync
– Replica Safe
33

34. Durability
Multiple Data Centers
Memory Journal Secondary Nodes
RDMS
Async
w=1
(default)
j=true
w=majority
w=”tag”
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35. Flexibility

36. Data Model
• Why Json?
– Well understood data format
– Maps simply to objects
– Linking & Embedding to describe relationships
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37. JSON
place1 = { : "578 Broadway 7th Floor",
name : "10gen HQ",
address
city : "New York",
zip "business", "tech" ]}
: "10011",
tags : [
}

38. Relational Way

39. MongoDB Way
embedding
linking

40. JSON & Scale Out
• Embedding removes the need for:
– Distributed Joins
– Two Phase Commit
• Enables data to be distributed across many
nodes without penalty
40