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Performance and Scalability

Performance and Scalability. Performance and Scalability Challenges. Optimizing Performance. Scaling Up. Scaling Out. Performance and Scalability SQL Server 2008. Scalable shared databases. 64. +. Scalable shared databases for Analysis Services. Workload prioritization.

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Performance and Scalability

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  1. Performance and Scalability

  2. Performance and Scalability Challenges • Optimizing Performance • Scaling Up • Scaling Out

  3. Performance and Scalability SQL Server 2008 Scalable shared databases 64 + Scalable shared databases for Analysis Services Workload prioritization Distributed partitioned views TPC benchmarks NUMA Tuning and optimization tools Data dependent routing Peer-to-peer replication Improved BI performance Multi-instance architecture Query notifications Service Broker Enterprise health monitoring Hot-add hardware 64-bit technologies NUMA Support

  4. Optimizing Performance • Optimizing Performance • Optimizing Performance • Scaling Up • Scaling Out

  5. Relational Database Performance

  6. Relational Database PerformanceResource Governor SQL Server • Ability to differentiate workloads such as app_name, login, and so on • Per-request limits: • Max memory % • Max CPU time • Grant timeout • Max requests • Resource monitoring Backup OLTP Activity Executive Reports Admin Tasks Ad-hoc Reports High Admin Workload OLTP Workload Report Workload Min Memory 10% Max Memory 20% Max CPU 20% Max CPU 90% Admin Pool Application Pool

  7. Relational Database PerformancePerformance Studio

  8. Data Warehouse and Analysis Performance

  9. Reporting Performance Reporting Services

  10. ETL Performance

  11. Scaling Up

  12. Hardware Support

  13. Concurrency

  14. Scaling Out • Distributed Partitioned Views • Scalable Shared Databases • Peer-to-Peer Replication • Query Notifications • Scalable Shared Databases for Analysis Services

  15. Scalable Shared Databases • Read-only database in SAN • Mounted by multiple reporting servers • Applications access a consistent copy from any server

  16. Distributed Partitioned Views • Data is partitioned horizontally across multiple servers • Transact-SQL view retrieves all data with a UNION ALL clause • Requests can be directed by using data dependent routing

  17. Peer-to-Peer Replication • Data is replicated to local servers • Local modifications are propagated throughout the enterprise

  18. Query Notifications • Application is notified when queried data changes • Optimal cache refresh behavior

  19. Scalable Shared Databases for Analysis Services • Centralized, read-only Analysis Services database shared by multiple instances • Client applications connect to a single virtual IP address

  20. © 2009 Microsoft Corporation. All rights reserved. This presentation is for informational purposes only. Microsoft makes no warranties, express or implied, in this summary.

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