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Webinar: Scaling MySQLCatch 22 of Read Write Splitting                                   January 17, 2013
Agenda       1. Who We Are       2. The Scalability Problem       3. How We Solve it with Read/Write Splitting       4. Cu...
Who We Are    Presenters:                                     Paul Campaniello,                                           ...
Who We AreScaleBase allows appsto cost-effectively scaleto an infinite number of users,with NO disruption to the existing ...
The ScaleBase Data Traffic Manager                                                     •    Database Scalability          ...
Pain Points – The Scalability Problem• Thousands of new online and mobile  apps launching every day• Demand climbs for the...
Big Data = Big Scaling Needs       Big Data = Transactions + Interactions + Observations               Sensors/RFID/Device...
Scalability PainInfrastructureCost $                   Large                     You just lost                   Capital  ...
Ongoing “Scaling MySQL” Series    • August 16 & September 20, 2012       – Scaling MySQL: ScaleUp versus Scale Out    • Oc...
The Database Engine is the Bottleneck... • Every write operation is At Least 4 write operations inside the DB:     – Data ...
The Database Engine is the Bottleneck • Every write operation is At Least 4 write operations inside the DB:     – Data seg...
So… Let’s get to work! • I’m growing, have more users, need to support more   throughput thru scale-out • Solution:     – ...
Read / Write Splitting                          Replication13
If Done Alone…• Application code needs to be changed• Maintain 2 connection pools      – Write – master      – Reads – A b...
Read / Write Splitting with ScaleBase •   0 code changes and 0 code maintenance •   Reads run faster •   Writes run faster...
Read / Write Splitting                             Current                                              Replication       ...
Read/Write Splitting                                 Read                                 Write             APPLICATION / ...
Scale Out with Amazon AWS RDS Read Replica                         Current                                           RDS R...
Choose Your Scale-out Path                              Data Distribution           Database Size                         ...
Scaling Out Achieves Unlimited Scalability             160000             140000             120000             100000Thro...
Detailed Scale Out Case Studies     One of worlds largest &     most widely respected     manufacturers of smart          ...
Summary     • Database scalability is a significant problem         – App explosion, Big Data, Mobile     • Scale Up helps...
Questions (please enter directly into the GTW side panel)617.630.2800www.ScaleBase.comdoron.levari@scalebase.compaul.campa...
Thank You24
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Scaling MySQL: Catch 22 of Read Write Splitting

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This webinar will explore the secrets, dos and don’ts, benefits and caveats behind Read-write Splitting.

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Scaling MySQL: Catch 22 of Read Write Splitting

  1. 1. Webinar: Scaling MySQLCatch 22 of Read Write Splitting January 17, 2013
  2. 2. Agenda 1. Who We Are 2. The Scalability Problem 3. How We Solve it with Read/Write Splitting 4. Customer ROI/Case Studies 5. Q & A (please type questions directly into the GoToWebinar side panel)2
  3. 3. Who We Are Presenters: Paul Campaniello, VP of Global Marketing 25 year technology veteran with marketing experience at Mendix, Lumigent, Savantis and Precise. Doron Levari, Founder A technologist and long-time veteran of the database industry. Prior to founding ScaleBase, Doron was CEO to Aluna.3
  4. 4. Who We AreScaleBase allows appsto cost-effectively scaleto an infinite number of users,with NO disruption to the existing infrastructure4
  5. 5. The ScaleBase Data Traffic Manager • Database Scalability – Scale out relational databases to unlimited users – Real-time elasticity • Database Availability – Enable high availability of all apps • Centralized Management – Removes complexity and provides a unified point of management for distributed database environments • Improves performance Requires NO changes to your existing infrastructure5
  6. 6. Pain Points – The Scalability Problem• Thousands of new online and mobile apps launching every day• Demand climbs for these apps and databases can’t keep up• App must provide uninterrupted access and availability• Database performance and scalability is critical6
  7. 7. Big Data = Big Scaling Needs Big Data = Transactions + Interactions + Observations Sensors/RFID/Devices Mobile Web User Generated Content Spatial & GPS Coordinates BIG DATAPetabytes User Click Stream Sentiment Social Interactions & Feeds Web Logs Dynamic Pricing Search Marketing WEB Offer History A/B Testing Affiliate NetworksTerabytes External Demographics Segmentation Customer Touches CRM Business Data Offer Details Support Contacts FeedsGigabytes HD Video, Audio, Images Behavioral ERP Purchase Detail Targeting Speech to Text Purchase Record Product/Service Logs Payment Record Dynamic Funnels SMS/MMSMegabytes Increasing Data Variety and Complexity 7 The 451 Group & Teradata
  8. 8. Scalability PainInfrastructureCost $ Large You just lost Capital customers Expenditure Predicted Demand Opportunity Traditional Cost Hardware Actual Demand Dynamic Scaling time 8
  9. 9. Ongoing “Scaling MySQL” Series • August 16 & September 20, 2012 – Scaling MySQL: ScaleUp versus Scale Out • October 23, 2012 – Methods and challenges to Scale out MySQL • December 13, 2012 – Benefits of Automatic Data Distribution • Today – Catch 22 of read-write splitting9
  10. 10. The Database Engine is the Bottleneck... • Every write operation is At Least 4 write operations inside the DB: – Data segment – Index segment – Undo segment – Transaction log • And Multiple Activities in the DB engine memory: – Buffer management – Locking – Thread locks/semaphores – Recovery tasks10
  11. 11. The Database Engine is the Bottleneck • Every write operation is At Least 4 write operations inside the DB: – Data segment – Index segment – Undo segment Now multiply – Transaction log by 10TB accessed by • And Multiple Activities in the DB engine memory: 10000 – Buffer management concurrent – Locking sessions – Thread locks/semaphores – Recovery tasks11
  12. 12. So… Let’s get to work! • I’m growing, have more users, need to support more throughput thru scale-out • Solution: – Create replicated database servers – Distribute the sessions across those database servers. Read / Write splitting: – Reads use the slaves – Writes go to the master • Benefits: – Better resource consumption – Get more read throughput – Get more write throughput – Awesome!12
  13. 13. Read / Write Splitting Replication13
  14. 14. If Done Alone…• Application code needs to be changed• Maintain 2 connection pools – Write – master – Reads – A blend of all slaves• Every flow, in its beginning, disclaims: – “I will do only reads” – “I will do reads and writes” – What’s the default?• Result: – Writing code, maintaining code – Maintaining database ops in the app: add/remove slaves, change IPs... – Master database is far more occupied than it should be – Reads are not well balanced – What if replication breaks? – Can I read stale data? 14
  15. 15. Read / Write Splitting with ScaleBase • 0 code changes and 0 code maintenance • Reads run faster • Writes run faster • Better resource utilization/load balancing • Improved data consistency/transaction isolation • Built-in failover with high availability • Database aware, replication state aware, replication lag aware • Real time monitoring and alerts • Centralized management dashboard15
  16. 16. Read / Write Splitting Current Replication With ScaleBase Replication Application Experience16
  17. 17. Read/Write Splitting Read Write APPLICATION / USERS WEB SERVERS Replication17
  18. 18. Scale Out with Amazon AWS RDS Read Replica Current RDS Read Replicas With ScaleBase RDS Read Replicas Application Experience18
  19. 19. Choose Your Scale-out Path Data Distribution Database Size Read/Write Splitting 1 DB? Good for me! # of concurrent sessions19
  20. 20. Scaling Out Achieves Unlimited Scalability 160000 140000 120000 100000Throughput 84000 80000 Throughput (TPM) Total DB Size (MB) 60000 60000 # Connections 48000 40000 36000 24000 2500 20000 2000 12000 1500 1500 6000 1000 0 500 500 1 2 4 6 8 10 14 Number of Databases 20
  21. 21. Detailed Scale Out Case Studies One of worlds largest & most widely respected manufacturers of smart phones and telecommunications hardware & software AppDynamics Mozilla Solar Edge • Device Apps App • Next gen APM • New Product/ • Next Gen • Availability company Next Gen App/ Monitoring App • Scalability • Scalability for the AppStore • Massive Scale • Geo-clustering Netflix • Scalability • Monitors real implementation • Geo-sharding time data from • 100 Apps thousands of • 300 MySQL DB distributed systems21
  22. 22. Summary • Database scalability is a significant problem – App explosion, Big Data, Mobile • Scale Up helps somewhat, but Scale Out provides a long-term, cost-effective solution • ScaleBase has an effective Scale Out solution with a proven ROI – Improves performance & requires NO changes to your existing infrastructure • Choose your scale-out path.... – The ScaleBase platform enables you to start with R/W splitting and grow into automatic data distribution22
  23. 23. Questions (please enter directly into the GTW side panel)617.630.2800www.ScaleBase.comdoron.levari@scalebase.compaul.campaniello@scalebase.com23
  24. 24. Thank You24

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