Introduction àCouchbase Server 2.0

Tugdual GrallTechnicalEvangelist

@tgrall

{“about” : “me”}

Tugdual “Tug” Grall• Couchbase

• Technical Evangelist• eXo

• CTO• Oracle

• Developer/Product Manager• Mainly Java/SOA

• Developer in consulting firms

• Web• @tgrall• http://blog.grallandco.com• Tgrall

• NantesJUG co-founder

• Pet Project :• http://www.resultri.com

Agenda

1. Introduction to Couchbase Server

2. Cluster Management

3. Operation and Document Design

4. Introduction to Views and Queries

5. Cross Data Center Replication

6. Q&A

Couchbase Developer Day Paris is this Friday! http://couchbase.com/events

Couchbase Server 2.0

Couchbase ServerNoSQL Document Database

Couchbase Open Source Project

• Leading NoSQL database project focused on distributed database technology and surrounding ecosystem

• Supports both key-value and document-oriented use cases

• All components are available under the Apache 2.0 Public License

• Obtained as packaged software in both enterprise and community editions.

Couchbase Open Source Project

Easy Scalabili

ty

Consistent High

Performance

Always On

24x365

Grow cluster without application changes, without downtime with a single click

Consistent sub-millisecond read and write response times

with consistent high throughput

No downtime for software upgrades, hardware maintenance, etc.

JSONJSONJSON

JSONJSON

PERFORMANCE

Flexible Data Model

JSON document model with no fixed schema.

Couchbase Server

New in 2.0

JSON support Indexing and Querying

Cross data center replicationIncremental Map Reduce

JSONJSONJSON

JSONJSON

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Distributed Erlang21100 - 21199

Erlang/OTP

storage interface

Couchbase EP Engine

11210Memcapable 2.0

Moxi

11211Memcapable 1.0

Memcached

New Persistence Layer

8092Query API

Query

Eng

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Data Manager Cluster Manager

Couchbase Server 2.0 Architecture

New Persistence Layer

storage interface

Couchbase EP Engine

11210Memcapable 2.0

Moxi

11211Memcapable 1.0

Object-level Cache

Disk Persistence

8092Query API

Query

Eng

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HTTP8091

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Server/Cluster Management & Communication

(Erlang)

RAM Cache, Indexing & Persistence

Management(C & V8)

The Unreasonable Effectiveness of C by Damien Katz

Couchbase Server 2.0 Architecture

33 2

Single node - Couchbase Write Operation

Managed Cache

Dis

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Disk

Replication Queue

App Server

Couchbase Server Node

Doc 1Doc 1

Doc 1

To other node

GET

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33 2

Single node - Couchbase Read Operation

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Managed Cache

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To other node

Couchbase Server Node

COUCHBASE SERVER CLUSTER

Basic Operation

• Docs distributed evenly across servers

• Each server stores both active and replica docsOnly one server active at a time

• Client library provides app with simple interface to database

• Cluster map provides map to which server doc is onApp never needs to know

• App reads, writes, updates docs

• Multiple app servers can access same document at same time

User Configured Replica Count = 1

READ/WRITE/UPDATE

ACTIVE

Doc 5

Doc 2

Doc

Doc

Doc

SERVER 1

ACTIVE

Doc 4

Doc 7

Doc

Doc

Doc

SERVER 2

Doc 8

ACTIVE

Doc 1

Doc 2

Doc

Doc

Doc

REPLICA

Doc 4

Doc 1

Doc 8

Doc

Doc

Doc

REPLICA

Doc 6

Doc 3

Doc 2

Doc

Doc

Doc

REPLICA

Doc 7

Doc 9

Doc 5

Doc

Doc

Doc

SERVER 3

Doc 6

APP SERVER 1

COUCHBASE Client Library

CLUSTER MAP

COUCHBASE Client Library

CLUSTER MAP

APP SERVER 2

Doc 9

Add Nodes to Cluster

• Two servers addedOne-click operation

• Docs automatically rebalanced across clusterEven distribution of docsMinimum doc movement

• Cluster map updated

• App database calls now distributed over larger number of servers

REPLICA

ACTIVE

Doc 5

Doc 2

Doc

Doc

Doc 4

Doc 1

Doc

Doc

SERVER 1

REPLICA

ACTIVE

Doc 4

Doc 7

Doc

Doc

Doc 6

Doc 3

Doc

Doc

SERVER 2

REPLICA

ACTIVE

Doc 1

Doc 2

Doc

Doc

Doc 7

Doc 9

Doc

Doc

SERVER 3 SERVER 4 SERVER 5

REPLICA

ACTIVE

REPLICA

ACTIVE

Doc

Doc 8 Doc

Doc 9 Doc

Doc 2 Doc

Doc 8 Doc

Doc 5 Doc

Doc 6

READ/WRITE/UPDATE READ/WRITE/UPDATE

APP SERVER 1

COUCHBASE Client Library

CLUSTER MAP

COUCHBASE Client Library

CLUSTER MAP

APP SERVER 2

COUCHBASE SERVER CLUSTER

User Configured Replica Count = 1

Fail Over Node

REPLICA

ACTIVE

Doc 5

Doc 2

Doc

Doc

Doc 4

Doc 1

Doc

Doc

SERVER 1

REPLICA

ACTIVE

Doc 4

Doc 7

Doc

Doc

Doc 6

Doc 3

Doc

Doc

SERVER 2

REPLICA

ACTIVE

Doc 1

Doc 2

Doc

Doc

Doc 7

Doc 9

Doc

Doc

SERVER 3 SERVER 4 SERVER 5

REPLICA

ACTIVE

REPLICA

ACTIVE

Doc 9

Doc 8

Doc Doc 6 Doc

Doc

Doc 5 Doc

Doc 2

Doc 8 Doc

Doc

• App servers accessing docs

• Requests to Server 3 fail

• Cluster detects server failedPromotes replicas of docs to activeUpdates cluster map

• Requests for docs now go to appropriate server

• Typically rebalance would follow

Doc

Doc 1 Doc 3

APP SERVER 1

COUCHBASE Client Library

CLUSTER MAP

COUCHBASE Client Library

CLUSTER MAP

APP SERVER 2

User Configured Replica Count = 1

COUCHBASE SERVER CLUSTER

Demo Time

Operation & Document Design

Basic Store & Retrieve Operations

• get(key)Retrieve a document

• set(key, value)Store a document or replace if it exists

• add(key, value)Store a document and fail if it exists

• replace(key, value)Replace a document and fail if it does not exist

Lots of other Operations

• Atomic Counters (increment, decrement)

• Append/Prepend

• CAS (Compare and Set) Optimistic Locking

• “Get with Lock” Write Lock on Objects

• Bulk Operations Saves network overhead

• Stats

• View operations

Couchbase 2.0 Bonus Points: JSON

• JSON is a lightweight format to represent document structure in a language-independent manner.

• If JSON documents are stored, the View engine can be used.

• Allows to build secondary indexes on your datasets.

• Makes it possible to ask questions like“Give me all user documents by lastname”.

Flexible Data Model

• No need to worry about the database when changing your application

• Records can have different structures, there is no fixed schema

• Allows painless data model changes for rapid application development

{ “ID”: 1, “FIRST”: “Dipti”, “LAST”: “Borkar”, “ZIP”: “94040”, “CITY”: “MV”, “STATE”: “CA”}

JSONJSON

JSON JSON

Aggregate View of Data

http://martinfowler.com/bliki/AggregateOrientedDatabase.html

Store and Retrieve Aggregates

• Easier to Distribute Data• More Flexibility• Reduced Latency

order::1001{uid: ji22jd,customer: Ann,line_items: [

{ sku: 0321293533, quan: 3, unit_price: 48.0 },{ sku: 0321601912, quan: 1, unit_price: 39.0 },{ sku: 0131495054, quan: 1, unit_price: 51.0 }

],payment: { type: Amex, expiry: 04/2001,

last5: 12345 }}

Demo Time

Official SDKs

Community SDKs

www.couchbase.com/develop

PythonRuby

Go Clojure

Indexing and Querying

Indexing and Querying – The basics

• Define materialized views on JSON documents and then query across the data set

• Using views you can define• Primary indexes • Simple secondary indexes (most common use case)• Complex secondary, tertiary and composite indexes• Aggregations (reduction)

• Indexes are eventually indexed

• Queries are eventually consistent

• Built using Map/Reduce technology • Map and Reduce functions are written in Javascript

COUCHBASE SERVER CLUSTER

Indexing and Querying

User Configured Replica Count = 1

ACTIVE

Doc 5

Doc 2

Doc

Doc

Doc

SERVER 1

REPLICA

Doc 4

Doc 1

Doc 8

Doc

Doc

Doc

APP SERVER 1

COUCHBASE Client Library

CLUSTER MAP

COUCHBASE Client Library

CLUSTER MAP

APP SERVER 2

Doc 9

• Indexing work is distributed amongst nodes

• Large data set possible

• Parallelize the effort

• Each node has index for data stored on it

• Queries combine the results from required nodes

ACTIVE

Doc 5

Doc 2

Doc

Doc

Doc

SERVER 2

REPLICA

Doc 4

Doc 1

Doc 8

Doc

Doc

Doc

Doc 9

ACTIVE

Doc 5

Doc 2

Doc

Doc

Doc

SERVER 3

REPLICA

Doc 4

Doc 1

Doc 8

Doc

Doc

Doc

Doc 9

Query

Demo Time

Cross Data Center Replication(XDCR)

Cross Data Center Replication – The basics

• Replicate your Couchbase data across clusters

• Clusters may be spread across geos

• Configured on a per-bucket (per-database) basis

• Supports unidirectional and bidirectional operation

• Application can read and write from both clusters Active – Active replication

• Replication throughput scales out linearly

• Different from intra-cluster replication

Cross Data Center Replication (XDCR)COUCHBASE SERVER CLUSTER

USACTIVE

Doc

Doc 2

SERVER 1

Doc 9

SERVER 2 SERVER 3

RAM

Doc Doc Doc

ACTIVE

Doc

Doc

Doc RAM

ACTIVE

Doc

Doc

DocRAM

DISK

Doc Doc Doc

DISK

Doc Doc Doc

DISK

COUCHBASE SERVER CLUSTEREMEA

ACTIVE

Doc

Doc 2

SERVER 1

Doc 9

SERVER 2 SERVER 3

RAM

Doc Doc Doc

ACTIVE

Doc

Doc

Doc RAM

ACTIVE

Doc

Doc

DocRAM

DISK

Doc Doc Doc

DISK

Doc Doc Doc

DISK

Couchbase Handles Real World Scale

Q & A

• Couchbase DeveloperDays Paris This Friday !

Presentations & Labs

Information

• http://www.couchbase.com/events

Use the promo code TUG

Thank you!tug@couchbase.com

@tgrall

Get Couchbase Server at http://www.couchbase.com/download