From A Morning with MongoDB - Milan on October 24, 2012.

1. MongoDB Basic Concepts
Norberto Leite
Senior Solutions Architect, EMEA
norberto@10gen.com
@nleite
Thursday, 25 October 12

2. Agenda
•Overview
•Replication
•Scalability
•Consistency & Durability
•Flexibility, Developer Experienc
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3. Your data needs started here...
http://bit.ly/OT71M4
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4. ...but soon you had to be here
http://bit.ly/Oxcsis
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5. Basic Concepts
Application Document
Oriented
High { author : “steve”,
date : new Date(),
text : “About MongoDB...”,
Performance tags : [“tech”, “database”]}
Fully
Consistent
Horizontally Scalable
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6. Tradeoff: Scale vs Functionality
• memcached
scalability & performance
•key/value
• RDBMS
depth of functionality
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7. Replication
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8. Why do we need replication
•Failover
•Backups
•Secondary batch jobs
•High availability
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9. Replica Sets
Data Availability across nodes
• Data Protection
• Multiple copies of the data
• Spread across Data Centers, AZs
• High Availability
• Automated Failover
• Automated Recovery
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10. Replica Sets
App Write
Primary
Asynchronous
Read Replication
Secondary
Read
Secondary
Read
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11. Replica Sets
App Write
Primary
Read
Secondary
Read
Secondary
Read
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12. Replica Sets
App
Primary
Write
Primary Automatic Election of
new Primary
Read
Secondary
Read
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13. Replica Sets
App
Recovering
Write New primary serves
Primary data
Read
Secondary
Read
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14. Replica Sets
App
Secondary
Read
Write
Primary
Read
Secondary
Read
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15. Scalability
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16. Horizontal Scalability
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17. Sharding
Data Distribution across nodes
• Data location transparent to your code
• Data distribution is automatic
• Data re-distribution is automatic
• Aggregate system resources horizontally
• No code changes
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18. Sharding - Range distribution
sh.shardCollection("test.tweets", {_id: 1} , false)
shard01 shard02 shard03
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19. Sharding - Range distribution
shard01 shard02 shard03
a-i j-r s-z
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20. Sharding - Splits
shard01 shard02 shard03
a-i ja-jz s-z
k-r
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21. Sharding - Splits
shard01 shard02 shard03
a-i ja-ji s-z
ji-js
js-jw
jz-r
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22. Sharding - Auto Balancing
shard01 shard02 shard03
a-i ja-ji s-z
ji-js
js-jw js-jw
jz-r jz-r
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23. Sharding - Auto Balancing
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
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24. Sharding - Routed Query
find({_id: "norberto"})
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
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25. Sharding - Routed Query
find({_id: "norberto"})
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
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26. Sharding - Scatter Gather
find({email: "norberto@10gen.com"})
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
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27. Sharding - Scatter Gather
find({email: "norberto@10gen.com"})
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
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28. Sharding - Caching
96 GB Mem
3:1 Data/Mem
shard01
a-i
300 GB Data
j-r
n-z
300 GB
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29. Aggregate Horizontal Resources
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 j-r n-z
300 GB Data
100 GB 100 GB 100 GB
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30. Consistency & Durability
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31. Two choices for consistency
•Eventual consistency
•Allow updates when a system has been partitioned
•Resolve conflicts later
•Example: CouchDB, Cassandra
•Immediate consistency
•Limit the application of updates to a single master
node for a given slice of data
•Another node can take over after a failure is detected
•Avoids the possibility of conflicts
•Example: MongoDB
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32. Durability
•For how long is my data available?
•When do I now that my data is safe?
•Where?
•Mongodb style
•Fire and Forget
•Get Last Error
•Journal Sync
•Replica Safe
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33. Data Durability
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34. Flexibility
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35. Data Model
• Why JSON?
• Provides a simple, well understood
encapsulation of data
• Maps simply to the object in your OO language
• Linking & Embedding to describe relationships
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36. Json
place1 = {
name : "10gen HQ",
address : "578 Broadway 7th Floor",
city : "New York",
zip : "10011",
tags : [ "business", "tech" ]
}
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37. Schema Design
Relational Database
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38. Schema Design
MongoDB embedding
linking
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39. Schemas in MongoDB
Design documents that simply map to
your application
post = {author: "Hergé",
date: new Date(),
text: "Destination Moon",
tags: ["comic", "adventure"]}
> db.posts.save(post)
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40. Embedding
> db.blogs.find( { author: "Hergé"} )
{ _id : ObjectId("4c4ba5c0672c685e5e8aabf3"),
author : "Hergé",
date : ISODate("2011-09-18T09:56:06.298Z"),
text : "Destination Moon",
tags : [ "comic", "adventure" ],
comments : [
! {
! ! author : "Kyle",
! ! date : ISODate("2011-09-19T09:56:06.298Z"),
! ! text : "great book"
! }
]
}
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41. JSON & Scaleout
• Embedding removes need for
• Distributed Joins
• Two Phase commit
• Enables data to be distributed across many nodes
without penalty
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42. http://bit.ly/UmUnsU
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43. http://bit.ly/cnP77L
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44. http://bit.ly/ODoMhh
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45. http://bit.ly/uW2nk
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46. download at mongodb.org!
norberto@10gen.com
Support, Training, Consulting, Events, Meetups
http://www.10gen.com
Facebook! Twitter! LinkedIn!
http://bit.ly/mongofb! http://twitter.com/mongodb! http://linkd.in/joinmongo!
Thursday, 25 October 12