Download pdf - Geographically Distributed Multi-Master MySQL Clusters

©Continuent 2014

Geographically Distributed Multi-Master MySQL Clusters

Robert Hodges, CEO Jeff Mace, Director of Services

©Continuent 2014

Introducing Continuent

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• The leading provider of clustering and replication for open source DBMS

• Our Product: Continuent Tungsten

• Clustering - Commercial-grade HA, performance scaling and data management for MySQL

• Replication - Flexible, high-performance data movement

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Quick Continuent Facts

• Largest Tungsten clustering installation processes up to 700M transactions daily

• Over 100 customers including many household names

• Multiple multi-site, multi-master deployments in production

• ... And more are on the way

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Tungsten Clustering in Two Minutes

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Tungsten Database-as-a-Service

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Tungsten clusters combine off-the-shelf open source DBMS servers into data services with: !

• 24x7 data access • Scaling of load on replicas • Simple management commands !...without app changes or data migration

Amazon US West

apache /php

GonzoPortal.com

Connector Connector

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Cluster Detailed View

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Application

Tungsten Connector

Application

Tungsten Connector

Replicator

Db2

Replicator

Db3Db1

Replicator

Slave SlaveMaster

Manager Manager Manager

Monitoring and Control

Monitoring and Control

Data Service: sjc

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Tungsten Replication in Four Minutes

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Tungsten Replicator Overview

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Master

(Transactions + Metadata)

Slave

THL

DBMS Logs

Replicator

(Transactions + Metadata)

THLReplicator

Download transactions via network

Apply using JDBC

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Replication Pipelines

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Extract Filter Apply

StageExtract Filter Apply

Stage

Pipeline

Master DBMS

Transaction History Log

In-Memory Queue

Slave DBMS


Stage

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Multiple Services Per Replicator

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NYCReplicator

London

Service nyc

FrankfurtReplicator

Service fra

Replicator

Service nyc

Service fra

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Using Services for Multi-Master Replication

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New York LondonReplicator

lhr (master)

jfk (slave)

Replicator

lhr (slave)

jfk (master)

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Introducing Multi-Site Multi-Master Clustering

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Why Multi-Site? Why Multi-Master?

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• Get data close to global applications

• Avoid latency cost of commit between sites

• Keep running during intermittent network failures between sites

• Keep running if a site fails

• Enable simple recovery when it comes back

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Multi-Site Multi-Master Clustering: the Marketecture

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No app or data coupling across regions

ApplicationApplications ApplicationApplications

Amazon Region Amazon Region

Live data and apps

in all regions

Multi-AZ deployment

Async replication between sites

Run in Amazon or on-premises

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Detailed Topology

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US-West-1 US-East-1

master

slave east1

east1

west

west1

master

slave

Important Note: Continuent recommends 3 nodes for clusters


Demo Setting up Multi-Master Clustering

across Sites

US-East-1 US-West-1

©Continuent 2014

Puppet Installation and Apply

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$> puppet module install continuent/tungsten $> puppet apply ~/tungsten.pp

See https://github.com/continuent/continuent-vagrant for more examples


Failures in Multi-Master Topologies

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Best Practice Deployment in Amazon

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Multi-AZ clustering with asynchronous multi-master across regions

US-East-1

AZAZ

AZ AZ

EU- West-1

AZ

AZ AZ

US- West-1

AZ

AZ AZ AZAZ AZ AZAZ

Availability ZoneRegion

AZ AZ AZ

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Normal Multi-Master Configuration

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master

slave

master

slaveeast1

east1

west

west1

US-West-1 US-East-1

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Failed master

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master

master

master

slave

masterXeast1

east1

west

west1

US-West-1 US-East-1

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Failed Slave

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master

slave

master

slaveX east1

east1

west

west1

US-West-1 US-East-1

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Failed Multi-Master Replicator

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master

slave

master

slaveeast1

east1

west

west1X

US-West-1 US-East-1

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Full-Site Failure

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master

slave

master

slaveeast1

east1

west

west1XUS-West-1 US-East-1


Enabling Data Replication Policies with Filters

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What Are Replication Filters?

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Stage

Master Pipeline

Master DBMS


In-Memory Queue

Inspect Change Drop

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Problem: Handling PII Data

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CREATE TABLE `personal_info` ( ìd` int(11) NOT NULL AUTO_INCREMENT, ùserid` varchar(250) DEFAULT NULL, `personal_code` varchar(250) DEFAULT NULL, `birth_date` date DEFAULT NULL, èmail` varchar(250) DEFAULT NULL, PRIMARY KEY (ìd`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8

Requirement 1: Do not replicate personally identifiable information

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Problem: Application-Specific Rules

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mysql> select * from personal_info; +----+--------+---------------+------------+-----------------+ | id | userid | personal_code | birth_date | email | +----+--------+---------------+------------+-----------------+ | 1 | fre11 | secret | 1985-01-16 | [email protected] | | 2 | bill | verysecret | 1995-01-16 | [email protected] | +----+--------+---------------+------------+-----------------+

Requirement 2: prevent userid ‘bill’ from replicating

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Adding Filters to Meet Requirements

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Extract Filter(s) Apply


Stage

Master Pipeline

Master DBMS


In-Memory Queue

colnames killbill dropcolumns

dropcolumns.json

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Creating a dropcolumn.json File

[ { "schema": "test", "table": "personal_info", "columns": [ "personal_code", "birth_date", "email" ] } ]

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Table name

Columns to delete

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Writing a Custom killbill.js Filter

function filter(event) {! data = event.getData();! if(data != null) {! for (i = 0; i < data.size(); i++) {! d = data.get(i);! if(d != null && d instanceof com.continuent.tungsten.replicator.dbms!.RowChangeData) {! rowChanges = d.getRowChanges();! for(j = 0; j < rowChanges.size(); j++) {! oneRowChange = rowChanges.get(j);! schema = oneRowChange.getSchemaName();! table = oneRowChange.getTableName();! if (schema == "test" && table == "personal_info") {! columnValues = oneRowChange.getColumnValues();! for (row = 0; row < columnValues.size(); row++) {! raw = columnValues.get(row).get(1).getValue();! user = new java.lang.String(raw);! if (user.equals("bill")) {! logger.info("Dropping transaction from bill!");! return null;!} } } } } } } }!

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Drop transaction

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Killbill.tpl file for Filter Installation

# Drop transactions for bill. replicator.filter.killbill=com.continuent.tungsten.replicator.filter.JavaScriptF ilter replicator.filter.killbill.script=/opt/continuent/share/killbill.js

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©Continuent 2014

Installing the Filters...

cp dropcolumn.json /opt/continuent/share cp killbill.js /opt/continuent/share cp killbill.tpl /opt/tungsten/tungsten-replicator/samples/conf/filters/default !/opt/continuent/tungsten/tools/tpm update \ --svc-extractor-filters=colnames,killbill,dropcolumn \ --property=replicator.filter.dropcolumn.definitionsFile=/opt/continuent/share/dropcolumn.json \ --start-and-report=true

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Resulting Data on Slave(s)

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mysql> select * from personal_info; +----+--------+---------------+------------+-------+ | id | userid | personal_code | birth_date | email | +----+--------+---------------+------------+-------+ | 1 | fre11 | NULL | NULL | NULL | +----+--------+---------------+------------+-------+ 1 row in set (0.00 sec) !

Requirement 2: No bill!

Requirement 1: PII columns cleared

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Conclusion

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©Continuent 2014

How Do I Get Started?

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• Documentation for all products http://docs.continuent.com

• Download registration for Tungsten clustering: http://www.continuent.com/downloads/software

• Downloads for open source Tungsten Replicator http://code.google.com/p/tungsten-replicator/

• Vagrant project for setting up test topologies https://github.com/continuent/continuent-vagrant/tree/master/examples/MSMM

©Continuent 2014

Continuent Web Page: http://www.continuent.com

!

Tungsten Replicator: http://code.google.com/p/tungsten-replicator

Our Blogs: http://scale-out-blog.blogspot.com http://datacharmer.org/blog http://www.continuent.com/news/blogs

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