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MongoDB Basic Concepts Norberto Leite Senior Solutions Architect, EMEA [email protected] @nleite Thursday, 25 October 12
MongoDB Basic Concepts
Norberto Leite
Senior Solutions Architect, [email protected]
@nleite
Thursday, 25 October 12
Agenda
•Overview•Replication•Scalability•Consistency & Durability•Flexibility, Developer Experienc
Thursday, 25 October 12
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Your data needs started here...
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Thursday, 25 October 12
Basic Concepts
Horizontally Scalable
{ author : “steve”, date : new Date(), text : “About MongoDB...”, tags : [“tech”, “database”]}
Document Oriented
Application
Fully Consistent
High Performance
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depth of functionality
scal
abili
ty &
per
form
ance •memcached
•key/value
• RDBMS
Tradeoff: Scale vs Functionality
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Replication
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Why do we need replication
•Failover •Backups•Secondary batch jobs •High availability
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Replica SetsData 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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Replica Sets
Primary
Secondary
Secondary
Read
Write
Read
Read
App
Asynchronous Replication
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Replica Sets
Primary
Secondary
Secondary
Read
Write
Read
Read
App
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Replica Sets
Primary
Primary
Secondary
Read
Write
Read
Automatic Election of new Primary
App
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Replica Sets
Recovering
Primary
Secondary
Read
Write
Read
New primary serves data
App
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Replica Sets
Secondary
Primary
Secondary
Read
Write
Read
Read
App
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Scalability
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Horizontal Scalability
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ShardingData 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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Sharding - Range distribution
shard01 shard02 shard03
sh.shardCollection("test.tweets", {_id: 1} , false)
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Sharding - Range distribution
shard01 shard02 shard03
a-i j-r s-z
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Sharding - Splits
shard01 shard02 shard03
a-i ja-jz s-z
k-r
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Sharding - Splits
shard01 shard02 shard03
a-i ja-ji s-z
ji-js
js-jw
jz-r
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Sharding - Auto Balancing
shard01 shard02 shard03
a-i ja-ji s-z
ji-js
js-jw
jz-r
js-jw
jz-r
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Sharding - Auto Balancing
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
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Sharding - Routed Query
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
find({_id: "norberto"})
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Sharding - Routed Query
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
find({_id: "norberto"})
js-jw
jz-r
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Sharding - Scatter Gather
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
find({email: "[email protected]"})
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Sharding - Scatter Gather
shard01 shard02 shard03
a-i ja-ji n-z
ji-js
js-jw
jz-r
find({email: "[email protected]"})
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Sharding - Caching
shard01
a-i
j-r
n-z
300
GB
Dat
a
300 GB
96 GB Mem3:1 Data/Mem
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Aggregate Horizontal Resources
shard01 shard02 shard03
a-i j-r n-z
96 GB Mem1:1 Data/Mem
100 GB 100 GB 100 GB
300
GB
Dat
a
96 GB Mem1:1 Data/Mem
96 GB Mem1:1 Data/Mem
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Consistency & Durability
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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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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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Data Durability
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Flexibility
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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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Json
place1 = { name : "10gen HQ", address : "578 Broadway 7th Floor", city : "New York", zip : "10011", tags : [ "business", "tech" ]}
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Schema DesignRelational Database
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Schema DesignMongoDB embedding
linkingThursday, 25 October 12
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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> 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"! } ] }
Embedding
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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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