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Jiazhang Liu ; Yiren Ding Team 8 [ 1 0/22/13]

Jiazhang Liu ; Yiren Ding Team 8 [ 1 0/22/13]. Traditional Database. Servers Database Admin DBMS. 1. Traditional Database. High cost Lack of e lasticity Hard to maintain. 1. Introduction. Relational Cloud: “database-as-a-service” ( DBaaS ) Why is it attractive?

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Jiazhang Liu ; Yiren Ding Team 8 [ 1 0/22/13]

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  1. JiazhangLiu;YirenDing Team 8 [10/22/13]

  2. Traditional Database • Servers • Database Admin • DBMS 1

  3. Traditional Database • High cost • Lack of elasticity • Hard to maintain 1

  4. Introduction • RelationalCloud:“database-as-a-service”(DBaaS) • Whyisitattractive? • Hardwareandenergycostmuchlower • Thecostisproportionaltoactualuse(pay-per-use) • So,howtomakeRelationalCloudmore attractive? • Efficient multi-tenancy • Elastic scalability • Database privacy 2

  5. Efficient multi-tenancy • Given a set of databases and workloads, what is the best way to serve them from a given set of machines? 3

  6. Efficient multi-tenancy • Solution: • uses a single database server on each machinewhichhostsmultiplelogicaldatabases. • RelationalCloudperiodically determines which databases should be placed on which machines using a novel non-linear optimization formulation. • a cost model that estimates the combined resource utilization of multiple databases running on a machine. 3

  7. Elastic scalability • A good DBaaS must support database and work- loads of different sizes. • The challenge arise when a database work- load exceeds the capacity of a single machine. • Must support scale-out, whereresponsibility for query processing is partitioned among multiple nodes to achieve higher throughput. 4

  8. DatabasePrivacy • Encrypt all the data stored in the DBaaS. • privacy concerns would largely be eliminated. • However,anyimpactonprocessingencrypteddata? 5

  9. DatabasePrivacy • DevelopedCryptDB:to provide privacy with an acceptable impact on performance (22.5% reduction in throughput) 5

  10. Databasepartitioning • to scale a single database to multiple nodes, useful when the load exceeds the capacity of a single machine. • to enable more granular placement and load balance on the back-end machines compared to placing entire databases. 6

  11. DatabasePlacement • Resource allocation is a major challenge when designing a scalable, multi-tenant Service like Relational Cloud. 7

  12. DatabasePlacement • Resource Monitor Monitor the resource requirements of each workload • Combined Load Predictor Predicting the load multiple workloads will generate when run together on a server • Consolidation Engine Assigning workloads to physical servers 7

  13. SYSTEM DESIGN • RelationalCloudArchitecture 8

  14. 9

  15. Flipboard • Greg Scallan, Chief Architect at Flipboard says, “Our service currently runs 100% on AWS in multiple availability zones.” • “We chose AWS because they were able to provide a majority of the solution we needed as we built our data center. Also, we appreciated the flexibility as we tried out various solutions to our business vision.” 10

  16. Sources • Relational Cloud: A Database-as-a-Service for the Cloud：http://people.csail.mit.edu/nickolai/papers/curino-relcloud-cidr.pdf • AWS Case Study: Flipboardhttps://aws.amazon.com/solutions/case-studies/flipboard/ • AWS Documentationhttp://docs.aws.amazon.com/AWSEC2/latest/UserGuide/concepts.html 11

  17. Questions? 12

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