MongoDB Basic Concepts Overview

MongoDB Basic Concepts

Norberto Leite

Senior Solutions Architect, EMEA
norberto@10gen.com
@nleite

Thursday, 8 November 12

Agenda

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


Your data needs started here...

http://bit.ly/OT71M4

...but soon you had to be here

http://bit.ly/Oxcsis


Basic Concepts
Application Document
Oriented
High { author : “steve”,
date : new Date(),
text : “About MongoDB...”,
Performance tags : [“tech”, “database”]}

Fully
Consistent

Horizontally Scalable


Tradeoff: Scale vs Functionality

• memcached
scalability & performance

•key/value

• RDBMS

depth of functionality

Replication


Why do we need replication

•Failover
•Backups
•Secondary batch jobs
•High availability


Replica Sets
Data Availability across nodes
• Data Protection
• Multiple copies of the data
• Spread across Data Centers, AZs
• High Availability
• Automated Failover
• Automated Recovery


Replica Sets

App Write
Primary
Asynchronous
Read Replication

Secondary
Read

Secondary
Read


Replica Sets

App Write
Primary
Read

Secondary
Read

Secondary
Read


Replica Sets

App
Primary

Write
Primary Automatic Election of
new Primary
Read

Secondary
Read


Replica Sets

App
Recovering

Write New primary serves
Primary data
Read

Secondary
Read


Replica Sets

App
Secondary
Read

Write
Primary
Read

Secondary
Read


Scalability


Horizontal Scalability


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


Sharding - Range distribution

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

shard01 shard02 shard03


Sharding - Range distribution


a-i j-r s-z


Sharding - Splits


a-i ja-jz s-z
k-r


Sharding - Splits


a-i ja-ji s-z
ji-js
js-jw
jz-r


Sharding - Auto Balancing


a-i ja-ji s-z
ji-js
js-jw js-jw
jz-r jz-r


Sharding - Auto Balancing


a-i ja-ji n-z
ji-js
js-jw
jz-r


Sharding - Routed Query
ﬁnd({_id: "norberto"})


a-i ja-ji n-z
ji-js
js-jw
jz-r


Sharding - Scatter Gather
ﬁnd({email: "norberto@10gen.com"})


a-i ja-ji n-z
ji-js
js-jw
jz-r


Sharding - Caching
96 GB Mem
3:1 Data/Mem

shard01

a-i
300 GB Data

j-r
n-z

300 GB


Aggregate Horizontal Resources
96 GB Mem 96 GB Mem 96 GB Mem
1:1 Data/Mem 1:1 Data/Mem 1:1 Data/Mem


a-i j-r n-z
300 GB Data

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


Json

place1 = {

name : "10gen HQ",

address : "578 Broadway 7th Floor",

city : "New York",

zip : "10011",
tags : [ "business", "tech" ]
}

Schema Design
Relational Database


Schema Design
MongoDB embedding

linking

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)


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"
! }
]
}


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


http://bit.ly/UmUnsU

http://bit.ly/cnP77L

http://bit.ly/ODoMhh

http://bit.ly/uW2nk

download at mongodb.org!
norberto@10gen.com

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

We are Hiring!!!

Facebook! Twitter! LinkedIn!
http://bit.ly/mongofb! http://twitter.com/mongodb! http://linkd.in/joinmongo!


MongoDB Basic Concepts Overview

Recommended

Recommended

More Related Content

Viewers also liked

Viewers also liked (18)

Similar to MongoDB Basic Concepts Overview

Similar to MongoDB Basic Concepts Overview (20)

More from MongoDB

More from MongoDB (20)

MongoDB Basic Concepts Overview