morning with mongodb paris 2012 - mongodb basic concepts

MongoDB Basic Concepts

Norberto Leite

Senior Solutions Architect, EMEAnorberto@10gen.com

@nleite

Thursday, 8 November 12

Agenda

•Overview•Replication•Scalability•Consistency & Durability•Flexibility, Developer Experience•Roadmap

http://bit.ly/OT71M4

Your data needs started here...

http://bit.ly/Oxcsis

...but soon you had to be here

Basic Concepts

Horizontally Scalable

{ author : “steve”, date : new Date(), text : “About MongoDB...”, tags : [“tech”, “database”]}

Document Oriented

Application

Fully Consistent

High Performance

depth of functionality

ance •memcached

•key/value

• RDBMS

Tradeoff: Scale vs Functionality

Replication

Why do we need replication

•Failover •Backups•Secondary batch jobs •High availability

Replica SetsData Availability across nodes• Data Protection

• Multiple copies of the data• Spread across Data Centers, AZs

• High Availability• Automated Failover• Automated Recovery

Replica Sets

Primary

Secondary

Asynchronous Replication

Replica Sets

Primary

Secondary

Replica Sets

Primary

Secondary

Automatic Election of new Primary

Replica Sets

Recovering

Primary

Secondary

New primary serves data

Replica Sets

Secondary

Primary

Secondary

Scalability

Horizontal Scalability

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

Sharding - Range distribution

shard01 shard02 shard03

sh.shardCollection("test.tweets", {_id: 1} , false)

Sharding - Range distribution

a-i j-r s-z

Sharding - Splits

a-i ja-jz s-z

Sharding - Splits

a-i ja-ji s-z

Sharding - Auto Balancing

a-i ja-ji s-z

Sharding - Auto Balancing

a-i ja-ji n-z

Sharding - Routed Query

a-i ja-ji n-z

find({_id: "norberto"})

Sharding - Routed Query

a-i ja-ji n-z

find({_id: "norberto"})

Sharding - Scatter Gather

a-i ja-ji n-z

find({email: "norberto@10gen.com"})

Sharding - Scatter Gather

a-i ja-ji n-z

find({email: "norberto@10gen.com"})

Sharding - Caching

shard01

300 GB

96 GB Mem3:1 Data/Mem

Aggregate Horizontal Resources

a-i j-r n-z

100 GB 100 GB 100 GB

Consistency & Durability

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

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

Data Durability

Flexibility

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

place1 = { name : "10gen HQ", address : "578 Broadway 7th Floor", city : "New York", zip : "10011", tags : [ "business", "tech" ]}

Schema DesignRelational Database

Schema DesignMongoDB embedding

linkingThursday, 8 November 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)

> 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

JSON & Scaleout

• Embedding removes need for• Distributed Joins• Two Phase commit

• Enables data to be distributed across many nodes without penalty

Roadmap

2.4 Roadmap

Must• Kerberos integration• LDAP/AD integration

Nice To Have• Hash Shard Key• Background Index Build on Secondaries• V8 for Map/Reduce (replaces Spider Monkey)• Geo: intersecting polygons, Geo shard key• Agg: $out, more functions, speed improvements

And beyond

• Full Text Search• Collection / Extent level locking• Field level security• Audit

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download at mongodb.org!

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Support, Training, Consulting, Events, Meetupshttp://www.10gen.com

norberto@10gen.com

We are Hiring!!!

morning with mongodb paris 2012 - mongodb basic concepts

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