MySQL Cluster 7.2 e 7.3 - por Andrew Morgan

MySQL Cluster Introduction & Update

Andrew Morgan MySQL High Availability – Product Management

@andrewmorgan

www.clusterdb.com

17th October 2012

Copyright © 2012, Oracle and/or its affiliates. All rights reserved. | 17th October 2012 | Oracle reserves the right to change the timing and content of any future release 2

Safe Harbour Statement

The following is intended to outline our general product direction. It is

intended for information purposes only, and may not be incorporated into any

contract.

It is not a commitment to deliver any material, code, or functionality, and

should not be relied upon in making purchasing decisions. The development,

release, and timing of any features or functionality described for Oracle’s

products remains at the sole discretion of Oracle.


Table of Contents

MySQL Cluster – Introduction

Customer case studies

Architecture

MySQL Cluster 7.2 (GA)

MySQL Cluster 7.3 (DMR & labs)

Commercial additions

The future


MySQL Cluster introduction

• Shared-nothing in-memory parallel database server

• ACID compliant relational database

Carrier Grade Database

• Five nines (99.999%) availability

• Self-healing, sub-second failover Highly Available

• High load, real-time performance

• Predictable low latency, bounded access times

Real-time Performance

• Incrementally grow out with application demands

• Linearly scale with distribution awareness Linearly Scalable

• Open Source, multiple data access

• High performance APIs (C++, Java, SQL, LDAP) Open Development


Web applications

demanding:

Development velocity:

Simplicity & flexibility of

data model & APIs

Scalability &

performance: high write

throughput and

Key/Value access

Support for “Big Data”

NoSQL – Why the demand?

40% DATA

GROWTH PER

YEAR

5.9BN MOBILE SUBS IN 2011

1 BILLION iOS & ANDROID

APPS DOWNLOADED PER WEEK

85% HANDSETS

SHIPPED WITH A

BROWSER

$1TR BY 2014

$700BN IN 2011

2.1BN USERS

8X DATA GROWTH IN 5 YRS

70+ NEW DOMAINS EVERY 60 SECONDS

350m TWEETS PER DAY

900M USERS

20M APPS PER DAY

60 HOURS UPLOADED

EVERY MINUTE


Massive scalability

No application-level sharding Performance High Availability/Fault Tolerance Ease of use

Simple operations/administration

Simple APIs

Quickly evolve application &

schema

What NoSQL must deliver

Scalability

Performance

HA

Ease of use


No best single solution

fits all

Mix and match

Still a role for the RDBMS?

NoSQL

Simple access patterns

Compromise on consistency for performance

Ad-hoc data format

Simple operation

RDBMS

Complex queries with joins

ACID transactions

Well defined schemas

Rich set of tools

Scalability

Performance

HA

Ease of use

SQL/Joins

ACID Transactions


Scalability a

Performance a

HA a

Ease of use a

SQL/Joins a

ACID Transactions a


Who’s Using MySQL Cluster?


Copyright © 2012, Oracle and/or its affiliates. All rights reserved. | 17th October 2012 | Oracle reserves the right to change the timing and content of any future release 11 11

http://www.mysql.com/why-mysql/case-studies/mysql-alcatel-casestudy.php

COMPANY OVERVIEW Leading provider of communications

platforms, solutions & services €15.2bn Revenues (2009), 77k employees

across 130 countries

CHALLENGES / OPPORTUNITIES

Converged services driving migration to next

generation HLR / HSS systems

New IMS platforms for Unified

Communications

Reduce cost per subscriber and accelerate

time to value

SOLUTION MySQL Cluster Carrier Grade Edition MySQL Support & Consulting Services

CUSTOMER PERSPECTIVE

“MySQL Cluster won the performance test hands-down, and it fitted our needs perfectly.

We evaluated shared-disk clustered databases, but the cost would have been at

least 10x more.” -- François Leygues, Systems Manager

Results Scale out on standard ATCA hardware to

support 60m+ subscribers on a single platform

Low latency, high throughput with 99.999%+ availability

Enabled customers to reduce cost per subscriber and improve margins

Delivered data management solution at 10x less cost than alternatives


PLAYFUL PLAY OVERVIEW

Developer of Latin America’s most popular FaceBook game

Based on El Chavo, massive success in LatAM, US and Spain


2m users in 4 months, growing at 30k per day

Targeting 50m users in 5 years

Massive scale, especially of database writes

99.999% uptime

Data integrity

DATABASE REQUIREMENTS

10k TPS on commodity hardware, in the cloud

Managing user avatars and sessions

In-App Purchases

Digital marketing + user response data


"The MySQL support service has been essential in

helping us for troubleshooting and giving

recommendations for the production cluster, Thanks"

Carlos Morales – DBA, Playfulplay.com México

RESULTS

• 45% improvement in performance

• 80% reduction in DBA overhead

• 99.999% uptime

https://blogs.oracle.com/MySQL/entry/mysql_cluster_powers_el_chavo

SOLUTIONS

• MySQL Cluster Carrier Grade Edition

• MySQL Cluster Manager

• MySQL Support & Consulting Services


Co-Located MySQL Servers + Data Nodes

MySQL Cluster

https://apps.facebook.com/lavecindaddeelchavo/

Playful Play Architecture


http://www.mysql.com/customers/view/?id=1160

COMPANY OVERVIEW Division of Docudesk Deliver Document Management SaaS


Provide a single repository for customers to

manage, archive, and distribute documents

Implement scalable, fault tolerant, real time data management back-end

PHP session state cached for in-service personalization

Store document meta-data, text (as BLOBs), ACL, job queues and billing data

Data volumes growing at 2% per day

SOLUTION

MySQL Cluster deployed on EC2

USER PERSPECTIVE

“MySQL Cluster exceeds our requirements for low

latency, high throughput performance with

continuous availability, in a single solution that

minimizes complexity and overall cost.”

-- Casey Brown, Manager of Dev & DBA Services,

Docudesk

Results Successfully deployed document

management solution, eliminating paper trails from legal processes

Integrate caching and database into one layer, reducing complexity & cost

Support workload with 50:50 read/write ratio

Low latency for real-time user experience and document time-stamping

Continuous database availability



MySQL Cluster Architecture

MySQL Cluster Data Nodes

Data Layer

Clients

Application Layer

Management




Data Layer

Clients

Application Layer

Management Management




Data Layer

Application Layer

Management Management

Clients


On-line Scheduled Maintenance

Scale

Upgrade

Backup

Evolve


Data Node 1

Data Node 2

Data Node 3

Data Node 4 A fragment is a copy of a partition

Number of fragments = # of partitions * # of replicas

Table T1

P2

P3

P4

Px Partition

4 Partitions * 2 Replicas = 8 Fragments

P1

Automatic Data Partitioning


Data Node 1

Data Node 2

F1

Primary Fragment

Secondary Fragment

Data Node 3

Data Node 4 Fx

Fx

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1

Primary Fragment

Secondary Fragment

F1

Data Node 3

Data Node 4 Fx

Fx

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4 Fx

Fx

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4 Fx

Fx

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4

F2

Fx

Fx

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4

F2

F2

Fx

Fx

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4

F2

F4 F2


Fx

Fx

Table T1

P2

P3

P4

Px Partition

P1



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Fx

Fx

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F3

Primary Fragment

Secondary Fragment

F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Node Group 1

Fx

Fx

Table T1

P2

P3

P4

Px Partition


P1

F1

F3



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Node Group 1

Node Group 2 Fx

Fx

- Node groups are created automatically

- # of groups = # of data nodes / # of replicas

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Node Group 1

Node Group 2 Fx

Fx As long as one data node in each

node group is running we have a complete copy of

the data

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Node Group 1

Node Group 2 Fx



the data

Table T1

P2

P3

P4

Px Partition


P1



Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

F3 F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Node Group 1

Node Group 2 Fx



the data

Table T1

P2

P3

P4

Px Partition


P1



Table T1 Data Node 1

Data Node 2

F1 F3

Primary Fragment

Secondary Fragment

P2

P3

P4

Px Partition

F3 F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Node Group 1

Node Group 2


Fx

Fx

- No complete copy of the data

- Cluster shutdowns automatically

P1



writes


MySQL Cluster 7.2 GA

• 70x Higher Complex Query Performance: Adaptive Query Localization

• Native Memcached API

• MySQL 5.5 Server Integration

• Multi-Threaded Data Node Extensions

• VM Support

Enabling Next Generation Web Services

• Multi-Site Clustering

• Simplified Active / Active Replication

Enhancing Cross Data Center Scalability

• MySQL Cluster Manager 1.1

• Consolidated Privileges

Ease of Use


Comparing MySQL Cluster Performance 8x Higher Performance per Node

0

2

4

6

8

10

12

14

16

18

20

MySQL Cluster 7.1 MySQL Cluster 7.2

Read

s p

er

Seco

nd

(M

illio

ns)

• 1 Billion+ Reads per Minute, 8 node Intel Xeon cluster

• Multi-Threaded Data Node Extensions

• NoSQL C++ API, flexaSynch benchmark


1.2 Billion UPDATEs per Minute

• 30 x Intel E5-2600 Intel Servers

• NoSQL C++ API, flexaSynch benchmark

• ACID Transactions, with Synchronous Replication

0

5

10

15

20

25

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Mil

lio

ns o

f U

PD

AT

Es

per

Se

co

nd



Adaptive Query Localization Scaling Distributed Joins

70x

More

Performance

mysqld

Data Nodes

mysqld

A

Q

L

Data Nodes

• Perform Complex Queries

across Shards

• JOINs pushed down to

data nodes

• Executed in parallel

• Returns single result set

to MySQL

• Opens Up New Use-Cases

• Real-time analytics

• Recommendations

engines

• Analyze click-streams


MySQL Cluster 7.2 AQL Test Query Web-Based Content Management System


Web-Based CMS

Must Analyze tables for best results

mysql> ANALYZE TABLE <tab-name>;

0

10

20

30

40

50

60

70

80

90

100

MySQL Cluster 7.1 MySQL Cluster 7.2

Query Execution Time Seconds

87.23 seconds

1.26 seconds

70x

More

Performance


NoSQL Access to MySQL Cluster data

ClusterJ

MySQL

JDBC

Apps

JPA

JNI

Python Ruby

ClusterJPA

Apps Apps Apps Apps Apps

Node.js

JSON

Apps

mod-ndb

Apache

Apps

ndb-eng

Memcached

Apps Apps

NDB API (C++)


Apps

PHP PERL

Apps


• Domain Object Model Persistence API (ClusterJ): • Java API

• High performance, low latency

• Feature rich

• JPA interface built upon this new Java layer: • Java Persistence API compliant

• Implemented as an OpenJPA plugin

• Uses ClusterJ where possible, reverts to JDBC for

some operations

• Higher performance than JDBC

• More natural for most Java designers

• Easier Cluster adoption for web applications

MySQL Cluster 7.1: ClusterJ/JPA


• Memcached is a distributed memory based hash-

key/value store with no persistence to disk

• NoSQL, simple API, popular with developers

• MySQL Cluster already provides scalable, in-

memory performance with NoSQL (hashed) access

as well as persistence

• Provide the Memcached API but map to NDB

API calls

• Writes-in-place, so no need to invalidate cache

• Simplifies architecture as caching & database

integrated into 1 tier

• Access data from existing relational tables

MySQL Cluster 7.2: Memcached


Traditional Memcached Architecture Two levels of hashing

Memcache

httpd memcached

memcached

memcached memcache key

PHP/Perl

friends:12389

hash key

to find data


Memcache Protocol Elements

• Key Up to 250 characters

• Expire Time A number in seconds, up to 30 days

• Flags 32-bit number for application use

• CAS ID 64-bit incrementing version number on value

• Value Value stored for key; traditionally up to 1 MB.


Memcache Protocol Commands (1)

• get key Fetch value for this key

• set key value Store this data

• add key value Store this data (strict insert)

• replace key value Store this data (strict update)

• cas key value cas-id Update with version number check


Memcache Protocol Commands (2)

• append key value Append text to current value

• prepend key value Insert text before current value

• incr key amount Add to current stored integer value

• decr key amount Subtract from current stored value

• delete key Delete a key and value

• flush_all Delete all stored values on the server

• stats stat-name Fetch server statistics


NDB & Memcache Architecture: Memcache protocol + NDB storage

MySQL

Cluster

Data Node memcached

Memcache

Client

Application

MySQL

Cluster

Data Node

NDB Engine


Goals

• Access stored data directly from memcache client

• Memcached perspective:

• MySQL Cluster is a write-scalable, replicated data store

• with reliable in-memory storage,

• plus on-disk storage when data is too big for memory.

• MySQL Cluster perspective:

• memcache is a high performance API

• providing easy access to in-memory data,

• plus an extra layer of caching when data is on disk.


Memcached/MySQL Cluster latency

memcachetest -t 2 -M 7000 -c 25000


Cluster & Memcached – Schema-Free

<town:maidenhead,SL6>

key value


key value

Key Value

town:maidenhead SL6

generic table

Application view

SQL view


Cluster & Memcached – Configured Schema


prefix key value


key value

Prefix Table Key-col Val-col policy

town: map.zip town code cluster

Config tables

town ... code ...

maidenhead ... SL6 ...

map.zip

Application view

SQL view



Multi-Site Clustering

Split data nodes across data

centers

– Synchronous replication

and auto-failover between

sites

– Improved heartbeating to

handle network partitions

Extends HA Options

Active/Active with no need

for conflict handling

Node Group 2

Node Group 1

Data Node 1

Data Node 3

Data Node 2

Data Node 4

Synchronous

Replication


Active/Active Geographic Replication

Replicating complete clusters

across data centers

– DR & data locality

– No passive resources

Simplified Active / Active

Replication

– Eliminates requirement for

application & schema changes

– Transaction-level rollback

Geographic

Replication



Simplified Provisioning & Maintenance User Privilege Consolidation



DMR1


EA


EA



MySQL Cluster 7.3 DMR1: Foreign Keys

Brings MySQL Cluster to a broader range of workloads

– Packaged apps, custom projects

Adds powerful functionality while reducing complexity

– App logic & data model

Enabled by default

Enforced for SQL

& NoSQL APIs

On-line add and drop



Implementation goal: compatibility with InnoDB

– Easy migration of solutions already working with InnoDB

Foreign keys are natively implemented in the storage

engine

Created in SQL

Enforced in SQL & NoSQL (C++, ClusterJ, memcached,

node.js)




Downloading MySQL Cluster 7.3 DMR

http://dev.mysql.com/downloads/cluster/

Development Release Tab


MySQL Cluster 7.3 EA: Node.js NoSQL API Native JavaScript access to MySQL Cluster

– End-to-End JavaScript: browser to the app and

database

– Storing and retrieving JavaScript objects directly

in MySQL Cluster

– Eliminate SQL transformation

Implemented as a module for node.js

– Integrates full Cluster API library within the web

app

Couple high performance, distributed apps, with

high performance distributed database

V8 JavaScript Engine

MySQL Cluster Node.js Module


Clients


MySQL Cluster 7.3 EA: Auto-Installer

Fast configuration

Auto-discovery

Workload optimized

Repeatable best

practices

For MySQL Cluster

7.2 + 7.3

Specify Workload

Auto-Discover

Define Topology Deploy


Define Hosts


Auto-Discovery


Modify hosts


Define nodes


Refine config


Deploy


Downloading MySQL Cluster EA

http://labs.mysql.com/


MySQL Cluster Manager Enhancing DevOps Agility, Reducing Downtime

Self-Healing Automated

Management HA Operations

• Start / Stop node or

whole cluster

• On-Line Scaling

• On-Line

Reconfiguration

• On-Line Upgrades

• Node monitoring

• Auto-recovery

extended to SQL

+ mgmt nodes

• Cluster-wide

configuration

consistency

• Persistent

configurations

• HA Agents


How Does MySQL Cluster Manager Help? Example: Initiating upgrade from MySQL Cluster 7.0 to 7.2

• 1 x preliminary check of cluster state

• 8 x ssh commands per server

• 8 x per-process stop commands

• 4 x scp of configuration files (2 x mgmd & 2 x

mysqld)

• 8 x per-process start commands

• 8 x checks for started and re-joined processes

• 8 x process completion verifications

• 1 x verify completion of the whole cluster.

• Excludes manual editing of each configuration

file.

Total: 46 commands -

2.5 hours of attended operation

Before MySQL Cluster Manager With MySQL Cluster Manager upgrade cluster --package=7.1 mycluster;

Total: 1 Command -

Unattended Operation

Results

– Reduces the overhead and complexity of managing database clusters

– Reduces the risk of downtime resulting from administrator error

– Automates best practices in database cluster management


MySQL Cluster Manager

1. Download MCM/Cluster package from edelivery.oracle.com:

2. Unzip

3. Run agent, define, create & start Cluster!

$> bin\mcmd –bootstrap MySQL Cluster Manager 1.1.2 started

Connect to MySQL Cluster Manager by running "D:\Andrew\Documents\MySQL\mcm\bin\mcm" -a NOVA:1862

Configuring default cluster 'mycluster'...

Starting default cluster 'mycluster'...

Cluster 'mycluster' started successfully

ndb_mgmd NOVA:1186

ndbd NOVA

ndbd NOVA

mysqld NOVA:3306

mysqld NOVA:3307

ndbapi *

Connect to the database by running "D:\Andrew\Documents\MySQL\mcm\cluster\bin\mysql" -h NOVA -P 3306 -u root

Bootstrap single host Cluster


Scaling out with MySQL Cluster Manager

agent

ndb_mgmd

mysqld

192.168.0.10

agent

ndb_mgmd

mysqld

192.168.0.11

agent

ndbd

ndbd

192.168.0.12

agent

ndbd

ndbd

192.168.0.13

client



agent

ndb_mgmd

mysqld

192.168.0.10

agent

ndb_mgmd

mysqld

192.168.0.11

agent

ndbd

ndbd

192.168.0.12

agent

ndbd

ndbd

192.168.0.13

client

agent

ndbd

ndbd

192.168.0.14

agent

ndbd

ndbd

192.168.0.15



mcm> add hosts --hosts=192.168.0.14,192.168.0.15 mysite;

mcm> add package --basedir=/usr/local/mysql_7_0_9 --

hosts=192.168.0.14,192.168.0.15 7.0.9;

mcm> add process --

[email protected],[email protected],ndbd@192

.168.0.14,[email protected],[email protected],[email protected].

15 -s port:mysqld:52=3307,port:mysqld:53=3307 mycluster;

mcm> start process --added mycluster;

mysql> ALTER ONLINE TABLE <table-name> REORGANIZE PARTITION;

mysql> OPTIMIZE TABLE <table-name>;


MySQL Enterprise Monitor 2.3

Copyright 2011 Oracle Corporation 83


Query Analyzer in MySQL Enterprise Monitor



Performance Thread connection scaling

Capacity Disk-Based Indexes

Increased node-count support

Increased database object support

Flexibility Tunable disk commits

MySQL Cluster Development Priorities

Ease-of-Use

Increased automation

backup and restore

Auto-Installer enhancements

MySQL Cluster Manager GUI

MySQL Cluster Manager Imports


Most secure, scalable MySQL Database, Development / Management /

Monitoring Tools, backed by Oracle Premier Lifetime Support

Oracle Premier Support

Oracle Product Certifications/Integrations

MySQL Enterprise Security

MySQL Enterprise Scalability

MySQL Enterprise Backup

MySQL Enterprise Monitor/Query Analyzer

MySQL Workbench

MySQL Cluster CGE

MySQL Cluster

Manager




PLAYFUL PLAY OVERVIEW

Developer of Latin America’s most popular FaceBook game

Based on El Chavo, massive success in LatAM, US and Spain


2m users in 4 months, growing at 30k per day

Targeting 50m users in 5 years

Massive scale, especially of database writes

99.999% uptime

Data integrity

DATABASE REQUIREMENTS

10k TPS on commodity hardware, in the cloud

Managing user avatars and sessions

In-App Purchases

Digital marketing + user response data


"The MySQL support service has been essential in

helping us for troubleshooting and giving

recommendations for the production cluster, Thanks"

Carlos Morales – DBA, Playfulplay.com México

RESULTS

• 45% improvement in performance

• 80% reduction in DBA overhead

• 99.999% uptime

https://blogs.oracle.com/MySQL/entry/mysql_cluster_powers_el_chavo

SOLUTIONS

• MySQL Cluster Carrier Grade Edition

• MySQL Cluster Manager

• MySQL Support & Consulting Services


Co-Located MySQL Servers + Data Nodes

MySQL Cluster

https://apps.facebook.com/lavecindaddeelchavo/

Playful Play Architecture


“Since deploying MySQL Cluster as our eCommerce database, we have had continuous uptime with linear scalability enabling us to exceed our most stringent SLAs”

— Sean Collier, CIO & COO, Shopatron Inc

Shopatron: eCommerce Platform

Applications

– Ecommerce back-end, user authentication, order data & fulfilment, payment data & inventory tracking. Supports several thousand queries per second

Key business benefits

– Scale quickly and at low cost to meet demand

– Self-healing architecture, reducing TCO

Why MySQL?

– Low cost scalability

– High read and write throughput

– Extreme availability

http://www.mysql.com/why-mysql/case-studies/mysql_cs_shopatron.php


Zillow

Application

Zillow.com is an online real estate community where homeowners, buyers, sellers, and real estate agents and professionals can find and share vital information about homes.

Key Business Benefit

In May 2007, 4.2 million unique visitors came to Zillow.com, just 15 months after the company launched.

Why MySQL?

“MySQL Cluster has enabled us to manage our growth smoothly, cost-effectively, and intelligently plan for future expansion."

Brian Milnes Zillow.com



Seat Pagine Gialle

Application

Business directories (including yellow and white pages) & media services


MySQL Cluster delivers the performance and high throughput required and enables Seat Pagine Gialle to incrementally scale its business without having to invest in expensive hardware.

Why MySQL? Performance & low TCO

“MySQL Cluster provided overwhelmingly better performance, availability and strength from every perspective.”

http://www.paginegialle.it/ http://www.paginebianche.it/



SOLVIANS IT-Solutions / goldman-sachs.de

Application

Real time multi language financial web site with 18,000+ financial products; 400 updates and 1,200 reads per second


attractive price performance ratio, fast development and time-to-market

Why MySQL? Excellent support team

“With MySQL Cluster we are able to meet all our technical requirements. The excellent MySQL support team helped us to get in production within a very small time frame.”

Thomas Schwanhäuser, Managing Director

SOLVIANS IT-Solutions GmbH




COMPANY OVERVIEW Division of Docudesk Deliver Document Management SaaS


Provide a single repository for customers to

manage, archive, and distribute documents

Implement scalable, fault tolerant, real time data management back-end

PHP session state cached for in-service personalization

Store document meta-data, text (as BLOBs), ACL, job queues and billing data

Data volumes growing at 2% per day

SOLUTION

MySQL Cluster deployed on EC2

USER PERSPECTIVE

“MySQL Cluster exceeds our requirements for low

latency, high throughput performance with

continuous availability, in a single solution that

minimizes complexity and overall cost.”

-- Casey Brown, Manager of Dev & DBA Services,

Docudesk

Results Successfully deployed document

management solution, eliminating paper trails from legal processes

Integrate caching and database into one layer, reducing complexity & cost

Support workload with 50:50 read/write ratio

Low latency for real-time user experience and document time-stamping

Continuous database availability


When to Consider MySQL Cluster What are the consequences of downtime or failing to meet performance

requirements?

How much effort and $ is spent in developing and managing HA in your

applications?

Are you considering sharding your database to scale write performance?

How does that impact your application and developers?

Do your services need to be real-time?

Will your services have unpredictable scalability demands, especially for

writes ?

Do you want the flexibility to manage your data with more than just SQL

?


Where would I not Use MySQL Cluster? “Hot” data sets >3TB

– Replicate cold data to InnoDB

Long running transactions

Large rows, without using BLOBs

Foreign Keys

– Can use triggers to emulate:

– http://dev.mysql.com/tech-resources/articles/mysql-enforcing-foreign-keys.html

Full table scans

Savepoints

Geo-Spatial indexes

InnoDB storage engine would be the right choice

MySQL Cluster Evaluation Guide

http://mysql.com/why-mysql/white-papers/mysql_cluster_eval_guide.php

http://dev.mysql.com/tech-resources/articles/mysql-enforcing-foreign-keys.html










MySQL Cluster in Action Web Reference Architectures

Session Management eCommerce

MySQL Master

Content Management

Slave 1

MySQL Master Analytics

Slave 2 Slave 3 Slave 4 Slave 5

Slave 6 Slave 7 Slave 8 Slave 9 Slave 10

Slave N

Slave 2

Node Group 2

F2

F4 Nod

e

3

Nod

e 4

F2

F4

Node Group 1

F1

F3 Nod

e

3

Nod

e 4

F1

F3


MySQL Servers

Node Group 2

F2

F4 Nod

e

3

Nod

e 4

F2

F4

Node Group 1

F1

F3 Nod

e

3

Nod

e 4

F1

F3


MySQL Servers

Slave 1 Slave 3

Data

Refinery Memcache / Application Servers

Distributed

Storage

XOR 4 x Data Nodes: 10k+

page hits per second

Each page hit

generating 8 – 12

database operations


Next Steps

Learn More

• www.mysql.com/cluster

• Authentic MySQL Curriculum: http://oracle.com/education/mysql

Try it Out

• dev.mysql.com/cluster

• labs.mysql.com

Let us know what you think

• clusterdb.com

• @clusterdb

• forums.mysql.com/list.php?25


Paggo Application

Innovative payment solution to buy and sell products and services using mobile phones.


MySQL Cluster CGE has enabled Paggo to quickly add 40,000 merchants and 1.2 million subscribers to its network and handle over 750,000 financial transactions per month.

Why MySQL? High Availability & Scalability

“Paggo would not have been possible without MySQL Cluster. No other product would have give us the ability to start small, scale quickly and provide 24 x7 availability for our financial payment system.”

Cicero Torteli Founder, Paggo




COMPANY OVERVIEW Leading telecoms provider across Europe

and Asia. Largest Nordic provider 184m subscribers (Q2, 2010)


Extend OSS & BSS platforms for new

mobile services and evolution to LTE

OSS: IP Management & AAA

BSS: Subscriber Data Management &

Customer Support

SOLUTION MySQL Cluster MySQL Support Services


“Telenor has been using MySQL for fixed IP management since 2003 and are extremely satisfied with its speed, availability and flexibility. Now we also

support mobile and LTE IP management with our solution. Telenor has found MySQL Cluster to be the

best performing database in the world for our applications.”

- Peter Eriksson, Manager, Network Provisioning

Results Launch new services with no downtime, due to on-

line operations of MySQL Cluster Consolidated database supports Subscriber Data

Management initiatives MySQL Cluster selected due to 99.999%

availability, real time performance and linear scalability on commodity hardware



COMPANY OVERVIEW UK-based retail & wholesale ISP & Hosting

Services 2010 awards for best home broadband and

customer service Acquired by BT in 2007


Enter market for wholesale services, demanding

more stringent SLAs

Re-architect AAA systems for data integrity &

continuous availability to support billing sytems

Consolidate data to for ease of reporting and

operating efficiency

Fast time to market

SOLUTION MySQL Cluster MySQL Server with InnoDB


“Since deploying our latest AAA platform, the MySQL environment has delivered

continuous uptime, enabling us to exceed our most stringent SLAs”

-- Geoff Mitchell Network Engineer

Results Continuous system availability, exceeding

wholesale SLAs 2x faster time to market for new services Agility and scale by separating database

from applications Improved management & infrastructure

efficiency through database consolidation


Alcatel-Lucent

Application

Infrastructure for next generation converged services including subscriber database applications (HLR, HSS) and the XDMS contacts and presence management system


The team evaluated several databases but only MySQL Cluster Carrier Grade Edition could offer the scalability and the high availability required for the system. Plus, MySQL Cluster Carrier Grade Edition is very cost-effective, the cost of shared-disk clustered databases evaluated would have been at least 10x more.”


MySQL Cluster won the performance tests hands down, and it fitted our needs perfectly.”

Alain Chastagner Systems Manager, Alcatel-Lucent




COMPANY OVERVIEW Pyro provide comms technology solutions in Core

Network, OSS/BSS & VAS Deployed in 120+ networks worldwide Cell C, one of the largest mobile operators in

South Africa 560 roaming partners in 186 countries


FIFA 2010 world cup opens up network services

to millions of mobile subscribers

International roaming SDP to support up to 7m

roaming subscribers per day

Offer local pricing with home network functionality

Minimize cost and time to market

SOLUTION MySQL Cluster 7.1 & Services


”MySQL Cluster 7.1 gave us the perfect combination of extreme levels of transaction

throughput, low latency & carrier-grade availability. We also reduced TCO by being able to scale out on commodity server blades and eliminate costly

shared storage”

-- Phani Naik, Head of Technology at Pyro Group

Results Supported subscriber and traffic volumes Delivered continuous availability Implemented in 25% of the time of typical

SDP solutions Choice in deployment platforms to eliminate

vendor lock-in (migrated from Microsoft)


M1 – Singapore

Application

RewardsPlus enables M1 to run credit expiration campaigns, generate comparison reports on promotional efficiency and send customized SMS messages to subscribers


M1 has improved customer loyalty in a highly-competitive market where delivering new value-added services and growing your subscriber-base are key to success.

Why MySQL? Reliability & Scale-out

“We rely on MySQL Cluster as the key technology behind RewardsPlus, which helps us increase the Average Revenue per User and improve customer loyalty.”

Mr. Tan Tiong Heng General Manager of Core Network Planning M1, Singapore



Teligent

Application

The Swedish telecom vendor Teligent supplies innovative network services like voice message systems, Mobile data and VoIP to operators like BT, Deutsche Telekom, TeliaSonera, Telefónica and Vodafone.


While the products must excel in reliability and flexibility, performance to price ratio is always a concern. “Through the years, we have recognized that MySQL scales easily to meet increasing demands for performance and functionality.”

Why MySQL? Scalability & Low TCO

“One of our key customers and one of Europe’s top telecom operators recently praised our standardization on MySQL as an innovative adoption of the technology of the future.”

Hans Floberg Head of Platfrom Development Teligent

http://www.teligent.se/


Nokia Siemens Networks

Application

Next generation telecommunication subscriber register solution to cover all requirements for real-time subscriber data demanded by existing and new services in both mobile and converged networks.


The solution will provide greater flexibility in creating new subscriber services, enhanced capabilities for subscriber provisioning, and increased savings in operational costs .


“With this cooperation, we join forces with MySQL to establish a winning solution for mobile and converged operators.”

Christian Fredrikson Vice President Nokia Siemens Networks

http://www.nokiasiemensnetworks.com/


Art & Photos

MySQL Cluster 7.2 e 7.3 - por Andrew Morgan