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José Blakeley Partner Architect SQL Server Engine Microsoft Corporation BB07.

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Presentation on theme: "José Blakeley Partner Architect SQL Server Engine Microsoft Corporation BB07."— Presentation transcript:

1 José Blakeley Partner Architect SQL Server Engine Microsoft Corporation BB07

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6 Dynamic Development Beyond Relational Pervasive Insight Enterprise Data Platform

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10 TPC Results as of July 15, 2008. Graph includes both current and withdrawn (historical) results. See www.tpc.org for a complete list of TPC-C results. Performance per socket scales with Moore's law

11 TPC Results as of July 15, 2008. Graph includes both current and withdrawn (historical) results. See www.tpc.org for a complete list of TPC-C results. More than 1 tpmC on standard servers

12 3-Tier SAP SD Benchmark Users on Windows and SQL Server – Industry Standard Servers Enough capacity for most SAP customers

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15 CreateBasket Remote Mirror (Log Shipping) Load Balancer Partitioned Shopping Baskets Partitioned Customer Account Data Presentation Order Processing Catalog Browsing CustomerData Replicated Catalog Submit Order A Commerce Service App HTTP, REST

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19 Access Series Order Maker Matching Engine JournalParticipantInstrumentJournalParticipantInstrument Single instance Single database Large server hardware Scale-up option Limited performance Limited scalability Ease of development Access Journal Participant Data Instrument Data 50,000 Trades/sec Transactional Messaging QueueBatch Messaging Queue

20 Access Series Order Maker Matching Engine Journal data ParticipantInstrumentParticipantInstrument Access Journal Participant Data Instrument Data Increased performance Increased scalability Application changes 70,000 Trades/sec Two instances Two databases Scale-up & out options Transactional Messaging QueueBatch Messaging Queue

21 Access Series Order Maker Matching Engine Journal data Partitions Partitions Participant Data Partitions Partitions Instrument Data Partitions Partitions Access Journal Multi-queue Pipe Participant Data Multi-queue Pipe Instrument Data Multi-queue Pipe Increased performance Unlimited scalability Application changes Three or more instances Three or more databases Scale-up & out Participant Data Partitions Partitions Partitions Participant Data Partitions Instrument Data Partitions Partitions Partitions Instrument Data Partitions Journal data Partitions Partitions Journal Data Partitions Journal Data Partitions 125,000 Trades/sec Transactional Messaging QueueBatch Messaging Queue

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24 APP 1 SQL Engine APP 2

25 Roger Doherty Sr. Technical Evangelist Developer and Platform Evangelism Microsoft Corporation

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28 Initiator service stores message in transmission queue until service broker can forward to target service endpoint Logging service calls send message SP with incoming message Target service enqueues message Activation stored procedure fires, dequeues message, calls CLR deserialization procedure with message, then inserts row into RawLog table Client constructs message and calls logging service Send message SP starts dialog between initiator and target service and sends message

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30 Silverlight 2.0 Clients 60% IE, 40% other IP Load Balancer (Redundant Pair) 5.4 million hits during peak day 40 million unique users Web Tier (15 Web Servers) WS2K8, IIS 7.0, ASP.NET, WCF SQL2K8 SSB Initiator Queues Data Tier (Write Only) WS2K8, SQL2K8 SQL2K8 SSB Target Queue, RawLog Table Data Warehouse (Read Only) WS2K8, SQL2K8, SSIS, SSRS, SSAS RawLog Dimensional Model

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34 The application’s data is factored into entities, each of which has a unique id Each entity will reside on a single node (ignoring replication & H/A) Entity Id = “A21” Entity Id = “W47” Entity Id = “Q17” Entity Id = “U15”

35 Entity “JKL” Entity “EFG” Entity “FXQ” Entity “ABC” Entity “DEF” Entity “XYZ” Entity “LMN” Entity “XYZ” Entity “LMN” Entity “ABZ” Entity “GHI” Entity “RST” Entity “XYZ” Entity “RST” Entity “LMN” Entity “JKL” Entity “RAA” Entity “KZU” Entity “JAA” Entity “NAO” Entity “MOE” No promise that two different entities stay on the same node!! Entity “GHI” Entity “FAW”

36 Entity “A21” Entity “D24” Transaction

37 Hala Al-Adwan Vice President of Data

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39 MySpace DB Average Connections/Server Average Requests/sec/Server Profile6,8001,100 Mail4,400775 Shared2,0001,600 Features800400 Security4,8003,700 Search300500 Browse80500 Dispatcher61200

40 MySpace. com Web Server Tier Service Layer Cache Persistent Data Store User Data Pre- populator Transaction Manager Transaction Manager Service Dispatcher

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43 Initiator Database Target Database Dispatcher Database Client Initiator Service Client Target Service Gateway Gateway Gateway

44 SQL Server Data Platform Basic concepts – common ground Assumptions Workloads Design patterns for scale Functional partitioning Case study 1 – A large US stock exchange Messages connect the functional pieces Case Study 2 – Beijing Olympics Monitoring Data partitioning and transactions Case study 3 – MySpace.com  Summary

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46 Please fill out your evaluation for this session at: This session will be available as a recording at: www.microsoftpdc.com

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51 © 2008 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.


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