Data Management Conference Data Warehousing John Plummer TSP Architect

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Presentation transcript:

Data Management Conference Data Warehousing John Plummer TSP Architect

Agenda SQL Server Data Warehousing Fast Track Overview Fast Track Case Study Resources

What Is Data Warehousing? WHAT WE WANT CRM LOB ERP Data Warehouse Data Integration Analysis Reporting Performance Management WHAT WE NEED NEED

Dynamic Development Beyond Relational Pervasive Insight Enterprise Data Platform Mobile and Desktop OLAP FILE XML RDBMS Services Query AnalysisReportingIntegrationSynch Search Cloud Server SQL Server 2008 Enterprise Edition

SQL Server 2008 Enterprise Edition Data Warehousing Improvements across the box −Integration Services, Database Engine, Analysis Services Improvements throughout the product −Focus on performance and scalability End-to-end testing on large-scale, customer-driven configurations −Database Engine: to 100 billion fact table rows −Analysis Services: to 25 billion fact table rows MERGE statement Change Data Capture Lookup Enhancements SSIS Pipeline threading DML Audit Enhancements Star-Join Optimisations Resource Governor Data Compression Backup Compression Partition Parallelism Spatial Sub-space computation Design-time advice MOLAP writeback Report Engine scale Improved charting.....

Accelerate scalable Data Warehouse deployments at lower TCO 6 Pre-configured, HW reference architectures (4-32 TB) Fast Track DW Appliance-like time to value Flexibility through choice of HW platforms Low TCO through commodity hardware and value pricing. Reduced risk through pre-tested and pre-tuned configurations Available NOW for SQL Server 2008 EE SI Solution Templates

Key Principle 1: Tight Specification 7 Software: SQL Server 2008 Enterprise Windows Server 2008 Hardware: Tight specifications for servers, storage and networking ‘Per core’ building block Configuration guidelines: Physical table structures Indexes Compression SQL Server settings Windows Server settings Loading

Key Principle 2: Balanced Across All Components A Holistic Approach FC HBA A B A B FC HBA A B A B FC SWITCH STORAGE CONTROLLER A B A B CACHE SERVER CACHE SQL SERVER WINDOWS CPU CORES CPU Feed RateHBA Port RateSwitch Port RateSP Port Rate A B DISK LUN DISK LUN SQL Server Read Ahead Rate LUN Read RateDisk Feed Rate SQL Server 2008 Potential Performance Bottlenecks

SMP SQL Server 2008 Minimum Server Configuration - Core Balanced Using Dual Read on EMC CX4 4 Gb/s FC switch EMC CX4-240 SP – A 500 MB/s SP – B 500 MB/s B A A B A B B A All ports marked A/B are rated at 4Gb/s 200 MB/s per Core FC HBA 2 4 Gb/s 200 MB/s per Core FC HBA 1 4 Gb/s Quad Core CPU CPU core rates based on tested hardware Number and type of drives limited to available throughput 370MB/s between DAE and SP. 370 MB/s A LUN 1 User Data, TempDB and Staging FG B B A DAE 1 DAE 2 Per CX4 Drive Details Each DAE can hold 15 drives Each DAE has 1 LUN per SP port Each LUN has (2) 300GB 15k SAS drives RAID1 LUN RAID MB/s LUN 2 User Data, TempDB and Staging FG LUN 3 User Data, TempDB and Staging FG LUN 4 User Data, TempDB and Staging FG Vault Drive (5) 146GB 10k Hot Spare (1) 300GB 15k Log Drive (2) 72GB 10k Hot Spare (1) 300GB 15k

Key Principle 3: Sequential I/O Sequential I/O Ideal for data warehousing Scalable, predictable performance Large reads & writes Requires 1/3 or fewer drives for same performance Random I/O Ideal for OLTP Not as predictable & scalable for data warehousing Small reads and writes Requires large number of drives Best practices focus on preserving the sequential order of data

Data File Layout (per 4 CPU cores)

Fast Track DW Deployment All necessary hardware purchased from one vendor Dedicated SAN based storage OS installed Customer required to: −Install system −Install SQL Server 2, 4 & 8 socket Intel / AMD based servers 1.6 to 36 TB of capacity

Fast Track Data Warehouse Configurations

Fast Track DW Considerations Simple recovery mode −Understand replication limitations Compression highly recommended −Except for highly random data Indexing −Use a clustered index for data ranges or common restrictions −Minimize use of non-clustered indexes  drives random I/O Fragmentation negates sequential I/O benefits (File / Table / Index) −Pre-allocate files and manually grow −Use large extents (-E) −Use multi-step loading techniques in white paper −Trade-off: query performance versus load performance

Fast Track Case Study – Environment Current Environment DW:Teradata 4-node (5450 model) 6TB of user data BI: Business Objects ETL: Informatica Proposed Microsoft Platform SQL Server Fast Track Data Warehouse HP DL580 Server - 4 Quad core Processors 256 GB Memory SAN Storage: MSA TB of user data BI: Business Objects ETL: SQL Server and SSIS

Fast Track Case Study – Results Teradata SQL Server Fast Track DW Comparison Loading Subject Area 1 5:10:21 total time51:31 total time  6x faster Loading Subject Area 2 4:36:08 total time1:50.01 total time  2.5x faster Query times Subject Area 1 3:03 avg query time (using 9 benchmark queries) 0:15 avg query time (using 9 benchmark queries)  12x faster Query times Subject Area 2 56:44 avg query time (using 4 benchmark queries) 8:09 avg query time (using 4 benchmark queries)  7x faster

Fast Track Case Study – Pricing Microsoft Fast Track Pricing Hardware (8TB capacity)$152,500 SQL Server – Software Cost$ 26,119 Total Price w/CAL license$178, 619 Teradata Pricing Considerations Current Annual Maintenance Fee$300,000 (6 TB System) Upgrade existing system – 8 TB$280,000, plus maint (~$40K) Total Price $620,000 A faster, Microsoft solution for $178k or $620k for Teradata maintenance and upgrade?

Fast Track Benefits Summary 18 Appliance-like time to value Reduces DBA effort; fewer indexes, much higher level of sequential I/O Appliance-like time to value Reduces DBA effort; fewer indexes, much higher level of sequential I/O Choice of HW Platforms Dell, HP, Bull – more in future Choice of HW Platforms Dell, HP, Bull – more in future Low TCO Through Commodity Hardware and value pricing; Lower storage costs. Low TCO Through Commodity Hardware and value pricing; Lower storage costs. High Scale New reference architectures scale up to 32 TB (assuming 2.5x compression) High Scale New reference architectures scale up to 32 TB (assuming 2.5x compression) Reduced Risk Tested by Microsoft; better choice of hardware; application of Best Practice Reduced Risk Tested by Microsoft; better choice of hardware; application of Best Practice

Data Warehouse Roadmap Survey review of your DW environment Identify Cost savings Performance benefits Deliver BI to more end-users Better control for IT Prepare To take advantage of the latest innovations

Requirements Existing DW Volume of end-user data 1TB+ Considering change to BI or DW infrastructure On site survey Interview of key stake holders in Data Warehouse environment Performed by IMGROUP Architect 1-2 days duration Deliverables Presentation of key findings Report detailing findings Results delivered approximately 10 days after survey Data Warehouse Roadmap Service

Call to Action... Speak to Partners here today about Fast Track Speak to Partners here today about Data Warehouse Roadmap Service

© 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.