A Morning with MongoDB Barcelona: MongoDB Basic Concepts

MongoDB Basic Concepts

Norberto Leite

Senior Solutions Architect, EMEAnorberto@10gen.com

@nleite

Sunday, 21 October 12

Agenda

•Overview•Replication•Scalability•Consistency & Durability•Flexibility, Developer Experienc

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

Fire and Forget

Driver Primary

Fire and Forget

Driver Primary

Fire and Forget

Driver Primary

apply in memory

Get Last Error

Driver Primary

Get Last Error

Driver Primary

getLastError

Get Last Error

Driver Primary

getLastErrorapply in memory

Get Last Error

Driver Primary

Journal Sync

Driver Primary

Journal Sync

Driver Primary

j:true

Journal Sync

Driver Primary

j:true

write to journal

Journal Sync

Driver Primary

j:true

write to journal

Replicas Safe

Driver Primary Secondary

Replicas Safe

Driver Primary

Secondary

Replicas Safe

Driver Primary

replicate

Secondary

Replicas Safe

Driver Primary

replicate

Secondary

Flexibility

• Cost effective operationalize abundant data (clickstreams, logs, tweets, ...)

• Relaxed transactional semantics enable easy scale out

• Auto Sharding for scale down and scale up

• Applications store complex data that is easier to model as documents

• Schemaless DB enables faster development cycles

What MongoDB solves

Agility

Flexibility

Challenges for Databases

✓ Build a database for scaleout• Run on clusters of 100s of commodity machines

•… that enables agile development

•… and is usable for a broad variety of applications

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

linkingSunday, 21 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)

> 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

http://bit.ly/UmUnsUSunday, 21 October 12

http://bit.ly/cnP77LSunday, 21 October 12

http://bit.ly/ODoMhhSunday, 21 October 12

http://bit.ly/uW2nk

A Morning with MongoDB Barcelona: MongoDB Basic Concepts

Documents

Transcript of A Morning with MongoDB Barcelona: MongoDB Basic Concepts

MongoDB: What, why, when. Solutions Architect, MongoDB Inc. Massimo Brignoli #mongodb.

MongoDB Europe 2016 - MongoDB Atlas

Morning with MongoDB Paris 2012 - MongoDB Basic Concepts

How to Scale MongoDB - DataOps Barcelona · How to Scale MongoDB ... • What is HA, how MongoDB achieves HA • Replica set, components, deployment topologies • Scaling (Vertical

MongoDB Revised Sharding Guidelines MongoDB 3.x_Kimberly_Wilkins

Morning with MongoDB Paris 2012 - Fast Connect

A Morning with MongoDB Barcelona: Introduction

Barcelona MUG MongoDB + Hadoop Presentation

A Morning with MongoDB Barcelona: MongoDB and Tapp

MongoDB - derickrethans.nlderickrethans.nl/talks/mongo-bbmw.pdf10gen, the company behind MongoDB 10gen began the MongoDB project Development, support, and services for MongoDB 100

MongoDB Europe 2016 - MongoDB 3.4 preview and introduction to MongoDB Atlas

A Morning with MongoDB Barcelona: From Oracle to MongoDB

The MongoDB Strikes Back / MongoDB 의 역습

MongoDB World 2016: MongoDB & IBM

MongoDB in use(김인범, mongodb korea)

MongoDB Europe 2016 - Debugging MongoDB Performance

Time Series Data in MongoDB Senior Solutions Architect, MongoDB Inc. Massimo Brignoli #mongodb.

MongoDB 3.0 migration - MongoDB Days Munich

Morning with MongoDB Paris 2012 - Accueil et Introductions

MongoDB Days Germany: Data Processing with MongoDB