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Performance and Scalability. Performance and Scalability Challenges Optimizing PerformanceScaling UpScaling Out.

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Presentation on theme: "Performance and Scalability. Performance and Scalability Challenges Optimizing PerformanceScaling UpScaling Out."— Presentation transcript:

1 Performance and Scalability

2 Performance and Scalability Challenges Optimizing PerformanceScaling UpScaling Out

3 Performance and Scalability SQL Server 2008 Real-world, predictable performance Scale up with today’s hardware Scale out for the enterprise TPC benchmarks Workload prioritization Tuning and optimization tools Enterprise health monitoring Improved BI performance Multi- instance architecture 64-bit technologies NUMA Support Hot-add hardware Scalable shared databases Distributed partitioned views Peer-to-peer replication Query notifications Service Broker Data dependent routing Scalable shared databases for Analysis Services

4 Optimizing PerformanceScaling UpScaling OutOptimizing Performance

5 Relational Database Performance Measurable, real- world performance TPC-E TPC-H SAP-SD Performance optimization tools SQL Server Profiler Database Engine Tuning Advisor High performance query processing engine Cost-based optimization Read-ahead scans Partitioning

6 Admin Workload Backup Admin Tasks Report WorkloadOLTP Workload OLTP Activity Executive Reports Ad-hoc Reports High SQL Server Min Memory 10% Max Memory 20% Max CPU 20% Admin Pool Max CPU 90% Application Pool 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 Relational Database Performance Resource Governor

7 Data providers SQL Trace Performance Counters Transact-SQL Low overhead performance data collection Management Data Warehouse Centralized performance data storage Comprehensive performance data reporting Relational Database Performance Performance Studio

8 Data Warehouse and Analysis Performance Data Warehouse Performance Star join query optimizations Improved parallelism Partition aligned indexed views Data compression MERGE GROUPING SETS Analysis Services Performance Block computations Write-back to MOLAP

9 Reporting Performance On-demand processing Effective caching and memory management Re- engineered rendering architecture Reporting Services

10 ETL Performance High performance lookup operations Pipeline performance

11 Scaling Up Hardware Support Concurrency

12 64-bit Multi-core, multi- processor Large-scale memory NUMA hardware Hot-Add hardware Memory Processor

13 Concurrency Transaction isolation Read uncommitted Read committed Repeatable read Serializable Read committed (with row versioning) Snapshot Lock escalation granularity Row Page Partition Table

14 Distributed Partitioned ViewsPeer-to-Peer ReplicationQuery NotificationsScalable Shared DatabasesScalable Shared Databases for Analysis Services Scaling Out

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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