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Virtualization and Databases

Virtualization and Databases. Ashraf Aboulnaga University of Waterloo. Conclusion. Virtualization: a layer of indirection between the abstract view of computing resources and their implementation Helps in, for example, resource consolidation

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Virtualization and Databases

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  1. Virtualization and Databases Ashraf AboulnagaUniversity of Waterloo

  2. Conclusion • Virtualization: a layer of indirection between the abstract view of computing resources and their implementation • Helps in, for example, resource consolidation • Database systems will increasingly run in virtualized environments • Need to make them run more efficiently, and to take advantage of the capabilities of virtualization

  3. Virtual Machine Monitor (VMM) Machine Virtualization App 1 App 2 App 3 Operating System Virtual Machine Machine CPU CPU Mem Physical Machine CPU CPU Mem Net

  4. Virtual Machine 1 Virtual Machine 2 CPU CPU CPU Mem Mem Net Machine Virtualization App 1 App 2 App 3 App 4 App 5 Operating System Operating System Virtual Machine Monitor (VMM) Physical Machine CPU CPU Mem Net

  5. Storage Server Storage Virtualization App 1 App 2 App 3 Operating System Machine Virtual Disk CPU CPU Mem Physical Storage

  6. Research Directions 1- Tuning the virtualization environment in an application informed way • Pass information about the application (database system) to the virtualization layer • Use this information for configuration and tuning • What information and how to use it? 2- Using the capabilities provided by the virtualization environment to improve manageability, availability, …

  7. Virtual Machine Configuration • If N virtual machines running database systems share a physical server, how much of the server’s resources to give to each one? • Ask query optimizer for workload costs

  8. Caching in Storage Servers • Which of a database system’s I/O requests should a storage server cache? • Hints from database system to storage server

  9. Scheduling Hadoop Tasks • Given a set of Hadoop (Map-Reduce) jobs, how to run them to minimize execution time? • How many nodes for each job? Which jobs can share nodes?

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