MySQL Cluster Carrier Grade Edition: Introduction · PDF filecarrier-grade availability and...

MySQL Cluster Carrier Grade Edition: Introduction

Oracle Corporation Japan , MySQL Global Business Unit

Master Principal Solutions Specialist | APAC & Japan, Alexander Yu

2011/10/28

Copyright© 2011, Oracle. All rights reserved.

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.

Please Read


Agenda / Topics

• Intro: MySQL Cluster Real-time Database

• MySQL Cluster 7.2 DMR

• API Flexibility: SQL & NoSQL!

• MySQL Cluster Manager

• Q & A


40% DATA GROWTH PER YEAR

5.3BN MOBILE SUBS IN 2010

(78% PENETRATION)

13K iPHONE APPS DOWNLOADED PER MINUTE

370K CALL MINUTES EVERY 60 SECONDS

$1TR BY 2014

$700BN IN 2011

2.1BN USERS

8X DATA GROWTH IN 5 YRS

70+ NEW DOMAINS EVERY 60 SECONDS

100K TWEETS PER MINUTE

750M USERS

20M APPS PER DAY

600 NEW VIDEOS

EVERY 60 SECONDS


Selecting the Right HA Architecture


HA Solutions

Requirement MySQL Replication Heartbeat + DRBD Oracle VM Template MySQL Cluster

Availability

Platform SupportAll Supported by MySQL

ServerLinux Oracle Linux

All Supported by MySQL

Cluster

Automated IP Failover No Yes YesDepends on Connector and

Configuration

Automated Database

FailoverNo Yes Yes Yes

Automatic Data

ResynchronizationNo Yes N/A - Shared Storage Yes

Typical Failover Time User / Script DependentConfiguration Dependent, 60

seconds and Above

Configuration Dependent, 60

seconds and Above 1 Second and Less

Synchronous ReplicationNo, Asynchronous and Semi-

SynchronousYes N/A - Shared Storage Yes

Geographic Redundancy

SupportYes Yes, via MySQL Replication Yes, via MySQL Replication Yes, via MySQL Replication

Scalability

Number of Nodes One Master, Multiple SlavesOne Active (primary), one

Passive (secondary) Node

One Active (primary), one

Passive (secondary) Node255

Built-in Load BalancingReads, via MySQL

Replication

Reads, via MySQL

Replication

Reads, via MySQL

Replication & During FailoverYes, Reads and Writes

Read-Intensive Workloads Yes Yes Yes Yes

Write-Intensive WorkloadsYes, via Application-Level

Sharding

Yes, via Application-Level

Sharding to Multiple

Active/Passive Pairs

Yes, via Application-Level

Sharding to Multiple

Active/Passive Pairs

Yes, via Auto-Sharding

Scale On-Line (add nodes,

repartition, etc.)No No No Yes

http://www.mysql.com/support/supportedplatforms/database.html

http://www.mysql.com/support/supportedplatforms/database.html

http://www.mysql.com/support/supportedplatforms/cluster.html

http://www.mysql.com/support/supportedplatforms/cluster.html


MySQL Cluster Real-time Carrier Grade Database


Customers & ApplicationsHigh Scale, Transactional, Real-Time with HA: Web & Telecoms

• Web

– eCommerce

– User Profile Management

– Session Management & Caching

– Content Management

– On-line Gaming

• Telecoms

– Subscriber Databases (HLR/HSS)

– Service Delivery Platforms

– VoIP, IPTV & VoD

– Mobile Content Delivery

– IP Management

– Payment Gateways

http://www.mysql.com/customers/cluster/

http://www.mysql.com/industry/telecom/

Pre & Post Paid


HLR / HSS

Billing, AuC, VLR

AuC, Call

Routing, Billing

Location

Updates

MySQL Cluster in Action: http://bit.ly/oRI5tF

• Massive volumes of write traffic

• <3ms database response

• Downtime & lost transactions = lost $

Use-Cases: Cellular Network

http://bit.ly/oRI5tF


http://mysql.com/customers/view/?id=1080

Use-Cases: eCommerce

• Integrated Service Provider platform

– eCommerce

– Payment processing

– Fulfillment

• Supports 1k+ manufacturers & 18k retail

partners

• Requirements

– Scaling, On-Demand

– HA: failures & on-line upgrades

– High batch & real time loads

– Low TCO: capex and opex




Use Cases: Flight Control

• US Navy aircraft carriers

• Consolidated flight operations management

system

– Maintenance records

– Fuel loads

– Weather conditions

– Flight deck plans

• Requirements

– No Single Points of Failure

– Complete redundancy

– Small footprint, harsh environment

– 4 x MySQL Cluster nodes, Linux and Windows


MySQL Cluster 7.1 Momentum

Pyro InRoam SDP is an intelligent

application enabling subscribers to

communicate with ease across borders

MySQL Cluster selected as a result of high

transactional throughput, low latency,

carrier-grade availability and low cost

Migrated from a Microsoft platform with

SQL Server

1,000 Downloads per Day

“MySQL Cluster 7.1 gave us the

perfect combination of extreme levels

of transaction throughput, low

latency & carrier-grade availability,

while reducing TCO”

Phani Naik, Pyro Group

MySQL Cluster database

supports 7 million roaming

subscribers per day


• ACID Compliant Relational Database• SQL & NoSQL interfaces

• Write-Scalable & Real-Time• Distributed, multi-master, auto-sharding

• Optimized in-memory structures & indices

• Near-linear scalability, transparent load balancing

• 99.999% Availability• Shared-nothing, integrated clustering, sub-second recovery

• Local & geographic replication, on-line operations

• Low Barriers to Entry• Open-source, elastic, multiple APIs, management and monitoring tools

• Commodity hardware

MySQL Cluster Carrier Grade: Key Advantages


MySQL Cluster Data Nodes

MySQL Cluster Application Nodes

Clients

MGM Node

MySQL Cluster Architecture

•Shared-nothing distributed database with no SPOF:

High Read & Write Performance & 99.999% uptime

NDB API (C++)

ND

B A

PI

ND

B A

PI

MGM Client

MGM Node

MGM API (C)


• Transparent to the application• No need for application-layer sharding logic

• Partitioning based on hashing the primary key or user defined key

• Each node stores primary fragment for 1 partition and back-up fragment for another

• Transparency maintained during failover, upgrades and scale-out

• No need to limit application to single-shard transactions

Automatic Data Partitioning/Sharding


Data Node 1

Data Node 2

F1 F3

Primary Fragment

F3 F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Node Group 1

Node Group 2Fx

Fx- Node groups are created automatically- # of groups = # of data nodes / # of replicas

Table T1

P2

P3

P4

Px Partition

4 Partitions * 2 Replicas = 8 Fragments

P1

Automatic Data PartitioningTransparent Load Balancing

Secondary Fragment (fragment replica)


• 8 Intel servers• Dual-6-core CPUs @2.93 GHz

• 24GB RAM

• 2 Data Nodes per server

• flexAsync benchmark• 16 parallel threads, each issuing 256

simultaneous transactions

• Read / Write 100KB attribute

• Access via NDB API

4.3M

QPS

Scale-Out on Commodity Hardware



MySQL Cluster Application Nodes

Clients

MGM Node

MySQL Cluster: Extreme Resilience

•Shared-nothing distributed database with no SPOF:

High Read & Write Performance & 99.999% uptime

NDB API (C++)

ND

B A

PI

ND

B A

PI

MGM Client

MGM Node

MGM API (C)

JDBC (Java)NDB API (C++)ClusterJ (Java)OpenJPA (Java)PHP/P*/ODBCOpenLDAP

ClusterJ

SQL Nodes


Data Node 1

Data Node 2

F1 F3

Primary Fragment

F3 F1

Data Node 3

Data Node 4

F2 F4

F4 F2

Node Group 1

Node Group 2Fx

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

4 Partitions * 2 Replicas = 8 Fragments

P1

Automatic Data PartitioningTransparent Load Balancing

Secondary Fragment (fragment replica)


Online Operations

• Scale the cluster for additional throughput or capacity

–Data and SQL Nodes

–Automatic repartition of tables

• Recover failed nodes

• Rolling

–Upgrade / patch servers & OS

–Upgrade / patch MySQL Cluster

• Backup

• Schema changes


On-Line Scaling & Maintenance

• Can also update schema on-line

• Upgrade hardware & software with no downtime

• Perform back-ups on-line

1. New node group added

2. Data is re-partitioned

3. Redundant data is deleted

4. Distribution is switched to share load with new node group


Real-Time, On-Line Schema Changes

• Fully online – transaction response

times unchanged

• Add and remove indexes, add new

columns and tables

• No temporary table creation

• No recreation of data or deletion

required

• Faster and better performing table

maintenance operations

• Less memory and disk requirements

CREATE OFFLINE INDEX b ON t1(b);

Query OK, 1356 rows affected (2.20 sec)‏

DROP OFFLINE INDEX b ON t1;


CREATE ONLINE INDEX b ON t1(b);


DROP ONLINE INDEX b ON t1;


ALTER ONLINE TABLE t1 ADD COLUMN d INT;

Query OK, 0 rows affected (0.36 sec)


Backup & Restore

• Online Backup for the Data only

– Data dump/backup for each Data Node

– Schema dump via mysqldump

• What to configure

– Backup path

• Choose local disk, SAN or NAS

– Backup files can then be picked up by external backup managers

– Compressed backup

• Space optimization/saving

• Backup Initiation

– Schema dump initiated via mysql on a SQL Node

– Backup snapshot of Data at end of backup or start of backup via ndb_mgm

• Backup command

– $ ndb_mgm -e “START BACKUP SNAPSHOTSTART"

• Restore command

– $ ndb_restore -c „192.168.10.10‟ -n 2 -b 1 -p 1 -m (once!)

– $ ndb_restore -c „192.168.10.10‟ -n 2 -b 1 -p 1 -r

– Restore data command issued for each Data Node

– Point-In-Time Recovery

• Need to enable Binary-Logging on MySQL Server

• Replay changes up-to a time using binary logs


Replication

• Multiple replication topologies available

• Master - Master (Bi-directional)

– Conflict detection and resolution

• Master - Slave(s)

• Circular

• etc


Cluster 1

Synchronous replication

Cluster 2

MyISAM MyISAM InnoDB

Asynchronous replication

• Synchronous (two phase commit)

replication within a Cluster node

group for HA

• Bi-Direction asynchronous

replication to remote Cluster for

geographic redundancy

• Asynchronous replication to non-

Cluster databases for specialised

activities such as report

generation

• Mix and match replication types


Geographical Replication

• A SQL Node/MySQL Server is responsible for the replication

– NDB Binlog injector thread

– Subscribes to events in MySQL Cluster

• Injects rows into the Binlog

– All changes in the cluster

– Row-based replication

• Two replication channels

– No single point of failure


Failure Detection: Majority Rules!

Data Node 1 Data Node 2

Data Node 3 Data Node 4

• Node 2

– One node from each node group? => No

– Shutdown

Network split/shutdown

HB


Disk Data Tables

• Disk Data Tables– Not enough memory to store all data

– Non-Indexed columns are stored on disk

• Tablespace

• A disk data based table stores its data in a tablespace

• Contains one more data files

• Log File Groups– In order to facilitate rollback

– Undo data in one or more undo log files


MySQL Cluster Processes

• Data Nodes

– ndbd/ndbdmt daemon (single threaded/multithreaded)

– Data storage

– Transaction Coordination

• SQL Node

– mysqld daemon

– provides SQL access to dataset

– Handles geographical replication

• Management Nodes

– ndb_mgmd daemon

– cluster configuration, cluster log, default arbitrator

• Management Clients

– ndb_mgm, cluster command line client (interactive/non-interactive)

– start/stop backups, node restarts, filter cluster log.

– mysql, CLI for accesing the SQL Node

• API Nodes/Applications

– Via SQL Node (JDBC/ODBC)

– Direct APIs (C++/Java apps)

– LDAP, Web Services

• MySQL Cluster Manager Agent

– mcmd agent daemon

– mysql, CLI for agent cluster management commands


• Example 1: Check memory usage/availability

mysql> select * from ndbinfo.memoryusage;

+---------+--------------+--------+------------+-----------+-------------+

| node_id | memory_type | used | used_pages | total | total_pages |

+---------+--------------+--------+------------+-----------+-------------+

| 3 | Data memory | 917504 | 28 | 104857600 | 3200 |

| 3 | Index memory | 221184 | 27 | 11010048 | 1344 |

| 4 | Data memory | 917504 | 28 | 104857600 | 3200 |

| 4 | Index memory | 221184 | 27 | 11010048 | 1344 |

+---------+--------------+--------+------------+-----------+-------------+

• Note that there is a DATA_MEMORY and INDEX_MEMORY row for each data node in the cluster

• If the Cluster is nearing the configured limit then increase the DataMemory and/or IndexMemory

parameters in config.ini and then perform a rolling restart

MySQL Cluster 7.1: ndbinfo


MySQL Enterprise Monitor 2.3


MySQL Cluster: DMR 2

MySQL Cluster 7.2.1 DMR


Adaptive Query LocalizationScaling Distributed Joins


A

Q

L

Data Nodes

70xMore

Performance

DON’T COMPROMISE FUNCTIONALITY TO

SCALE-OUT !!

mysqld

mysqld

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


Data

Node1

Data

Node2

MySQL

Server

MySQL Cluster 7.2 AQL Test QueryWeb-Based Content Management System

MySQL Cluster 7.2 70x Speedup! (DMR)


• 70x Speedup for real customer JOIN across

11 tables

• Try Analyze tables to optimize results

• mysql> ANALYZE TABLE <tab-name>;

7.2 = 1.26s

7.1 = 87.23s

7.2

analyzed=

65.3s


New

NoSQL

Access

Memcached Key-Value API

• Persistent, Scalable, HA Back-End to memcached

– No application changes: re-uses standard

memcached clients & libraries

–Faster Cloud Deployments/Integration

• Consolidate Caching & Database Tiers

–Eliminate cache invalidation

–Simpler re-use of data across services

–Improved service levels

• Flexible Deployment

–Schema or Schema-less storage


MySQL 5.5 Server Integration

• Exploit Latest Server / Storage Engine

Developments within a Single Application

– InnoDB: Foreign Keys, XA Transactions,

Large Rows

–MySQL Cluster: HA, High Write Rates, Real-

Time

• Reduces Complexity, Simplifies DevOps

• MySQL 5.5

–3x higher performance

– Improved partitioning, diagnostics, availability,

etc.


Geographic

Replication

Enhanced Cross Data Center ScalabilityGeographic 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


Data Node 1

Synchronous

ReplicationData Node 3

Data Node 2

Data Node 4

Enhanced Cross Data Center ScalabilityMulti-Site Clustering

• Split data nodes & node groups across

data centers

⁃ Synchronous replication & auto- failover

between sites

⁃ Improved heartbeating to handle network

partitions

• Extends Disaster Recovery Options

• More Resilient Cloud Deployments

• Active/Active with no need for conflict

handling


•SQL: Complex, relational queries

•HTTP / memcached: Key-Value web services

•Java: Enterprise Apps

•NDB API: Real-time services

Mix

&

Match

Data Nodes

NDB API

Clients

Native memcached HTTP/REST

JDBC / ODBC

PHP / PERL

Python / Ruby

API Flexibility:SQL & NoSQL Combined


SQL and NoSQL Combined!

Mix & Match!

Same data accessed

simultaneously through

SQL & NoSQL interfaces

•NoSQL – Multiple ways to bypass SQL, and maximize performance:

•NDB API. C++ for highest performance, lowest latency

•Cluster/J for optimized access in Java

•NEW! Memcached. Use all your existing clients/applications


NoSQL With NDB API

Best possible performance


Applications with embedded NDB API Library

Clients • Application embeds the NDB API C++

interface library

• NDB API make intelligent decision (where

possible) about which data node to send

queries to– With a little planning in the schema design, achieve

linear scalability

• Used by all of the other application nodes

(MySQL, LDAP, ClusterJ,…)

• Best possible performance but requires >

development skill

• Favourite API for real-time network

applications

• Foundation for all interfaces


NoSQL with memcached

• 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

7.2DM

Memcached protocol


•Flexible:

• Deployment options

• Multiple Clusters

• Simultaneous SQL Access

• Can still cache in Memcached server

• Flat key-value store or map to multiple

tables/columns

Simple:set maidenhead 0 0 3

SL6

STORED

get maidenhead

VALUE maidenhead 0 3

SL6

END

7.2DMNoSQL with Memcached Pre-GA version available from labs.mysql.com


Cluster & Memcached – Schema-Free

<town:maidenhead,SL6>

key value


key value

generic table

Application view

SQL view

The existence, content and timing of future releases described here is included for information only and may be changed at Oracles discretion. October 3rd, 2011


Cluster & Memcached - Configured Schema


prefix key value


key value

Config tables map.zip

Application view

SQL view

The existence, content and timing of future releases described here is included for information only and may be changed at Oracles discretion. October 3rd, 2011


ClusterJ/JPA Plugin

49

• 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

• Rich set of existing MySQL connectors

exist but performance worse than NDB API

• New Domain Object Model Persistence API

(ClusterJ) :

⁃Java API

⁃High performance, low latency

⁃Feature rich

Copyright© 2011, Oracle. All rights reserved. 50

ClusterJ

• High Performance, Easy to Use

• In the style of Hibernate / JPA / JDO

• Domain Object Model DataMapper pattern–Data is represented as domain objects

–Domain objects are separate from business logic

–Domain objects are mapped to database tables

• Built on ndbjtie–JNI adapter

–integral part of MySQL Cluster

–Straight mapping of MySQL Cluster API (a.k.a NDB API) to Java

• Does not support relationships–Look at JDO / JPA for these modelling patterns


ClusterJ Objects

Session

Factory

Configuration

properties

Session &

Transaction

Session &

Transaction

Session &

Transaction

Domain

Object

Domain

Object

Domain

Object

Domain

Object

Domain

Object

Domain

Object

Domain

Object

Domain

Object

Domain

Object

Domain

Object

Domain

Object

Annotated

interface

Domain

Object

• SessionFactory

–One per Cluster per JVM

• Session

–Instance per user; represents a

Cluster connection

• Transaction

–Instance per Session

• Query

–Multiple instances per Session


// Create a session (connection to the database)

SessionFactory factory = ClusterJHelper.getSessionFactory(props);

Session session = factory.getSession();

// Create and initialise an Employee

Employee newEmployee = session.newInstance(Employee.class);

newEmployee.setId(988);

newEmployee.setFirst("John");

newEmployee.setLast("Jones");

newEmployee.setStarted("1 February 2009");

newEmployee.setDepartment(666);

// Write the Employee to the database

session.persist(newEmployee);

// Fetch the Employee from the database

Employee theEmployee = session.find(Employee.class, 988);

// Make some changes to the Employee & write back to the database

theEmployee.setDepartment(777);

theEmployee.setCity("London");

session.updatePersistent(theEmployee);

// Retrieve the set all of Employees in department 777

QueryBuilder builder = session.getQueryBuilder();

QueryDomainType<Employee> domain = builder.createQueryDefinition(Employee.class);

domain.where(domain.get("department").equal(domain.param("department")));

Query<Employee> query = session.createQuery(domain);

query.setParameter("department",777);

List<Employee> results = query.getResultList();

ClusterJ Application Code Example


ClusterJPA

• Removes ClusterJ limitations:⁃Persistent classes

⁃Relationships

⁃Joins in queries

⁃Lazy loading

⁃Table and index creation from object model

• Implemented as an OpenJPA plugin

• Better JPA performance for insert, update,

Copyright© 2011, Oracle. All rights reserved.© 2011 Oracle Corporation – Proprietary and Confidential

• @Entity(name = "department")

• public class Department {

private int Id;

private String Site;

• public Department(){}

•

@Id public int getId()

{return Id;}

public void setId(int id)

{Id=id;}

•

@Column(name="location")

public String getSite()

{return Site;}

public void setSite(String site)

{Site=site;}

• }

mysql> describe department;

+----------+--------------+------+-----+---------+-------+

| Field | Type | Null | Key | Default | Extra |

+----------+--------------+------+-----+---------+-------+

| id | int(11) | NO | PRI | NULL | |

| location | varchar(255) | YES | | NULL | |

+----------+--------------+------+-----+---------+-------+

Note that OpenJPA will create this table if it doesn’t already exist but user

needs to change the storage engine to NDB:

mysql> ALTER TABLE department=ndb;

ClusterJPA Annotated class example


EntityManagerFactory entityManagerFactory =

Persistence.createEntityManagerFactory("clusterdb");

EntityManager em = entityManagerFactory.createEntityManager();

EntityTransaction userTransaction = em.getTransaction();

userTransaction.begin();

Department dept = new Department();

dept.setId(101);

dept.setSite(“London”);

em.persist(dept);

userTransaction.commit();

userTransaction.begin();

Department theDepartment = em.find(Department.class, 101);

theDepartment.setSite(“Edinburgh”);

userTransaction.commit();

em.close();

entityManagerFactory.close();

ClusterJPA Application code example


Performance


MySQL Cluster Manager


MySQL Cluster Manager 1.1 Features

Delivered as part of MySQL Cluster CGE 7.1


How Does MySQL Cluster Manager Help ?

Example: Initiating upgrade from MySQL Cluster 6.3 to 7.1

•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 Managerupgrade 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


Terms used by MySQL Cluster Manager

• Site: the set of physical hosts which are to run

Cluster processes to be managed by MySQL

Cluster Manager. A site can include 1 or more

clusters.

• Cluster: represents a MySQL Cluster

deployment. A Cluster contains 1 or more

processes running on 1 or more hosts

• Host: Physical machine, running the MySQL

Cluster Manager agent

• Agent: The MySQL Cluster Manager process

running on each host

• Process: an individual MySQL Cluster node;

one of: ndb_mgmd, ndbd, ndbmtd, mysqld &

ndbapi*

• Package: A copy of a MySQL Cluster

installation directory as downloaded from

mysql.com, stored on each host

*ndbapi is a special case, representing a slot for an external application

process to connect to the cluster using the NDB API

Site

Host Host Host Host

Cluster

Pro

ce

ss

Pro

ce

ss

Pro

ce

ss

Pro

ce

ss

Pro

ce

ss

Pro

ce

ss

Pro

ce

ss

Pro

ce

ss

Pro

ce

ss

Pro

ce

ss

agent agent agent agent

Cluster


1. Download MCM from edelivery.oracle.com:

• Package including Cluster

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

4. Connect to Cluster & start using database

•

http://www.clusterdb.com/mysql-cluster/mysql-cluster-manager-1-1-2-creating-a-cluster-is-now-trivial

New in MySQL Cluster Manager 1.1.2

Bootstrap single host Cluster



























Creating & Starting a Cluster

1.Define the site:–Mysql> create site --hosts=192.168.0.10,192.168.0.11,

-> 192.168.0.12,192.168.0.13 mysite;

2.Expand the MySQL Cluster tar-ball(s) from mysql.com

to known directory

3.Define the package(s):•Mysql> add package --basedir=/usr/local/mysql_7_1_15 7.1;

Mysql> add package --basedir=/usr/local/mysql_7_2_1 7.2;

• Note that the basedir should match the directory used

in Step 2.

4.Create the Cluster–Mysql> create cluster --package=7.1

-> [email protected],[email protected],

-> [email protected],[email protected], [email protected],

-> [email protected],[email protected],[email protected]

-> mycluster;

• This is where you define what nodes/processes make

up the Cluster and where they should run

5.Start the Cluster:–Mysql> start cluster mycluster;

agent

1. ndb_mgmd

7. mysqld

192.168.0.10

agent

2. ndb_mgmd

8. mysqld

192.168.0.11

agent

5. ndbd

3. ndbd

192.168.0.12

agent

6. ndbd

4. ndbd

192.168.0.13

mysql

client









mailto:[email protected]








Upgrade Cluster


• Upgrade from MySQL Cluster 7.1.15 to 7.2.1:

• Automatically upgrades each node and

restarts the process – in the correct order to

avoid any loss of service

• Without MySQL Cluster Manager, the

administrator must stop each process in turn,

start the process with the new version and wait

for the node to restart before moving onto the

next one

agent

1. ndb_mgmd

7. mysqld

192.168.0.10

agent

2. ndb_mgmd

8. mysqld

192.168.0.11

agent

5. ndbd

3. ndbd

192.168.0.12

agent

6. ndbd

4. ndbd

192.168.0.13

mysql

client

mysql> upgrade cluster --package=7.2 mycluster;

Check the status of the Cluster


• Request the status of the Cluster processes–mysql> show status --process mycluster;

–+------+----------+--------------+---------+-----------+

| Id | Process | Host | Status | Nodegroup |

+------+----------+--------------+---------+-----------+

| 1 | ndb_mgmd | 192.168.0.10 | running | |

| 2 | ndb_mgmd | 192.168.0.11 | running | |

| 3 | ndbd | 192.168.0.12 | running | 0 |

| 4 | ndbd | 192.168.0.13 | running | 0 |

| 5 | ndbd | 192.168.0.12 | running | 1 |

| 6 | ndbd | 192.168.0.13 | running | 1 |

| 7 | mysqld | 192.168.0.10 | running | |

| 8 | mysqld | 192.168.0.11 | running | |

+------+----------+--------------+---------+-----------+

• Get the status of the hosts & agents–mysql> list hosts mysite;

–+--------------+-----------+---------+

| Host | Status | Version |

+--------------+-----------+---------+

| 192.168.0.10 | Available | 1.0.1 |

| 192.168.0.11 | Available | 1.0.1 |

| 192.168.0.12 | Available | 1.0.1 |

| 192.168.0.13 | Available | 1.0.1 |

+--------------+-----------+---------+

agent

1. ndb_mgmd

7. mysqld

192.168.0.10

agent

2. ndb_mgmd

8. mysqld

192.168.0.11

agent

5. ndbd

3. ndbd

192.168.0.12

agent

6. ndbd

4. ndbd

192.168.0.13

mysql

client

64


• Service is maintained for all Cluster processes

(i.e., automatically restart process)

• Without MySQL Cluster Manager, an angel

process would recreate failed ndbd processes

but not mysqld or ndb_mgmd processes

• Cluster continues to function if one or more

agents fail or is stopped (e.g. To upgrade it)– To restore management functions, the agent should be

restarted

agent

1. ndb_mgmd

7. mysqld

192.168.0.10

agent

2. ndb_mgmd

8. mysqld

192.168.0.11

agent

5. ndbd

3. ndbd

192.168.0.12

agent

6. ndbd

4. ndbd

192.168.0.13

HA provided by MySQL Cluster Manager


MySQL Cluster Manager

• On-line add-node– mysql> add hosts --hosts=192.168.0.35,192.168.0.36 mysite;

– mysql> add package --basedir=/usr/local/mysql_7_1_15 –

hosts=192.168.0.35,192.168.0.36 7.2;

– mysql> add process --

[email protected],[email protected],[email protected]

68.0.35,[email protected] mycluster;

– mysql> start process --added mycluster;

• Restart optimizations

• Fewer nodes restarted on some parameter changes



































MySQL Cluster in Action


Resources to Get Started

Learn More

Evaluate MySQL Cluster 7.2 Quick Start Guides

MySQL Cluster on the webwww.mysql.com/cluster/

Download Todayhttp://dev.mysql.com/downloads/cluster/

http://labs.mysql.com(memcached)

Linux, Solaris, Windowshttp://www.mysql.com/products/cluster/get-started.html#quickstart

Session Management Webinar: http://tinyurl.com/3dmtf9r


http://www.mysql.com/cluster/

http://www.mysql.com/cluster/

http://labs.mysql.com





More Products Releases Than Ever Before

Continuous Innovation

Q2 CY2010 Q3 CY2010 Q4 CY2010 Q1 CY2011

• MySQL Workbench 5.2

GA!

• MySQL Database 5.5

• MySQL Enterprise Backup 3.5

• MySQL Enterprise Monitor 2.3

• MySQL Cluster Manager 1.1

All GA!

A Better MySQL

Q2-4 CY2011

•MySQL Enterprise Monitor 2.2

•MySQL Cluster 7.1

• MySQL Cluster Manager 1.0

All GA!

MySQL Database 5.6

MySQL Cluster 7.2

DMR*

and MySQL Labs!

(“early and often”)

*Development Milestone Release

• MySQL Enterprise

Backup 3.6

• Oracle VM Template

for MySQL Enterprise

Edition

GA!


Recommended Hardware


The Perfect MySQL Server

• 16-24 cores for 5.5 and above

• x86_64 - 64 bit for more memory is important

- Data/Memory ration 1/3 to 1/10 to good (rule of thumb)

- The more the better

• Linux or Solaris best, Windows and Unix also fine.

• RAID 10 for most, RAID 5 OK if very read intensive

• Hardware RAID battery backed up cache critical!

- More disks are always better!

- 4+ recommended, 8-16 can increase IO performance if needed

• At least 2 x NICs for redundancy

• Slaves should be as powerful as the Master

• Oracle Sun X4170 for example


MySQL Cluster Hardware Selection -RAM & CPU

• Storage Layer (Data nodes)

• One data node can (7.0+) use 8 cores

• CPU: 2 x 4 core (Nehalem works really well). Faster CPU → faster processing of messages.

• RAM: As much as you need

• a 10GB data set will require 20GB of RAM (because of redundancy

• Each node will then need 2 x 10 / # of data nodes. (2 data nodes → 10GB of RAM → 16GB RAM is good)

• SQL Layer (MySQL Servers)

• CPU: 2 – 16 cores

• RAM: Not as important – 4GB enough (depends on connections and buffers)


low-end mid-end high-end

1 x SATA 7200 RPM

• For read-mostly

• No redundancy

(but other data node is

the mirror)

1 x SAS 10K RPM

• Heavy duty (many MB/s)

• No redundancy

(but other data node is

the mirror)

4 x SAS 10K RPM

• Heavy duty (many MB/s)

• Disk redundancy (RAID1+0)

hot swap

• REDO, LCP, BACKUP – written sequentially in small chunks (256KB)

• If possible, use Odirect = 1

LCP

REDOLOG

LCP

REDOLOG

LCP / REDOLOG

MySQL Cluster Hardware SelectionDisk Subsystem

for Checkpoints & Logs


Minimal recommended High-end

2 x SAS 10K RPM (preferably)

• Use High-end for heavy read / write workloads (1000's of 10KB records per sec) of data

(e.g. Content Delivery platforms)

• SSD for TABLESPACE an option to consider

• Having TABLESPACE on separate disk is good for read performance

• Enable WRITE_CACHE on devices

TABLESPACE

LCP

REDOLOG

UNDOLOG

UNDOLOG

LCP

(REDO LOG / UNDO

LOG)

TABLESPACE 1

TABLESPACE 2

4 x SAS 10-15K RPM (preferably)

(REDO LOG)

MySQL Cluster Hardware SelectionDisk Data

Storage


MySQL Cluster Hardware Selection

Network

• Dedicated >= 1Gb/s networking

– On Oracle Sun CMT servers it may be necessary to bond 4 or more NICs

together because typically many data nodes are on the same physical host.

• Prevent network failures (NIC x 2, Bonding, dual switches)

• Use dedicated network for cluster communication

– Put Data nodes and MySQL Servers on e.g 10.0.1.0 network and let MySQL

listen on a “public” interface.

• No security layer to management node

• Enable port 1186 access only from cluster nodes and administrators


Case Studies


• 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

• SOLUTIONS

• 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

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

http://www.mysql.com/products/cluster/get-started.html#quickstart











• 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

• SOLUTIONS

• 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)



• 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

Copyright© 2011, Oracle. All rights reserved. 53

“Since deploying MySQL Cluster as our eCommerce database, we have had

continuous uptime with linear scalability enabling us to exceed our uptime requirements”

— 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








• UK-based retail and 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

• SOLUTIONS

• 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

MySQL Cluster Carrier Grade Edition: Introduction · PDF filecarrier-grade availability and...

Documents

Transcript of MySQL Cluster Carrier Grade Edition: Introduction · PDF filecarrier-grade availability and...