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My first (out of three) slide deck from the SQL Explore event.
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Extreme Analysis ServicesCTO | Twingoאיתי בראון |
www.twingo.co.il
• SSAS Best Practices• Deep Dive to SSAS• What’s new in SSAS Code Name “Denali”
• Part I - SSAS Best Practices– BI Trends– Microsoft BI Road Map– Guest Lecturer Ronen Chen – Pyramid Analytics– Design Best Practices
אג'נדה
• Part II – Deep Dive to SSAS 2008– White Papers and Tools– Partitions Best Practices– Near Real Time OLAP– Processing Methods– Cache Warmer– Monitoring and DMV– MDX Best Practices
אג'נדה
• Part III – What’s New in SSAS “Denali”– BI Semantic Model– Using Vertipaq– PowerPivot Models– What’s new in SSIS and SSRS “Denali”
אג'נדה
• Current – CTO and owner of Twingo – www.twingo.co.il
• Worked 2 years as PFE in Microsoft UK• Manager of the BI User Group
– We meet every last Wednesday of the month
• My blog: http://blogs.microsoft.co.il/blogs/itaybraun/
Few words about me
BI TRENDS
• Big Data• BI Everywhere• Democratize BI – Power to the people • Mobile BI• Self Service BI• Cloud BI
Hot BI Trends (and buzzwords)
MICROSOFT BI ROAD MAP
Seamless Transition of the Semantic Model Across BI Spectrum
Team BI
Our Context
BI Solution created by power user. Context is for a small team & it’s managed on a server.
Personal BI Corporate BI
My Context
BI solution created by user. Context is only for
user & exists as document.
The Org’s Context
BI Solution created by IT, Established corporate context & is reusable,
scalable and backed up.
PowerPivot for Excel PowerPivot for SharePoint Analysis Services
Empowered Aligned
Tabular and multidimensional APIs for client toolsTabular and multidimensional modeling environmentsSophisticated business logic using DAX and MDXCached and pass-through storage options
For reporting, analytics, scorecards, dashboardsFor all users – Personal BI, Team BI, Organizational BIOne model for client tools, two ways to build it – tabular and multidimensional
One Semantic Model for BI
Powerful and Flexible
Optimized for latest hardware – multi-core, in-memorySupports enterprise grade security and data volumesProfessional development and management tools
Enterprise Ready
The BI Semantic Model
PYRAMID ANALYTICS
• An “Office Like” OLAP Viewer• Friendly and easy to develop• Enterprise Ready• Enterprise class Analytics• http://pyramidanalytics.com/
Pyramid Analytics
SSAS DESIGN BEST PRACTICES
• The “Big Picture”– Data Warehouse– Using the right technology
• OLAP• ROLAP • Relational DB• In-Memory BI
– Not using the wrong technology
Design Best Practices
• What to design / redesign / review / double check– Data Source Views– Dimensions
• Attributes, Attributes Relationships
– Cubes• Measure Groups and Partitions• Dimension Usage• Aggregations• Security• Calculations
Design Best Practices
• SSAS 2008 Performance Guide• SSAS 2008 R2 Operation Guide• Analysis Services 2005 Performance Guide• Identifying and Solving MDX Bottlenecks• Distinct Count Optimization• Scale Out Queries• www.sqlcat.com • OLAP Design Best Practices for Analysis Service
s 2005
Something to read
• SQL Server 2008 R2 Best Practice Analyzer
Free Tools
• BIDS Helper
Free Tools
• MDX Studio– Used to deeply analyze MDX Queries.– Compares behavior on cold vs. warm cache.– Shows used partitions
Free Tools
What do Tier 1 Solutions have in Common?
• Design and Query Considerations
• High Concurrent User Count
• Increased Hardware Requirements
• IO Hungry!• Real Time Implications
Design and Query Considerations
• Simplicity is Key– Parent child use– Many to Many– Cell by Cell vs. Block Mode– Data Types
• Partitioning and Locking– Threading – Sizing– Distinct Count Performance – Hashing and Locking Pools
Managing Multi User Concurrency
• Scaling Out– Synchronization– Read-Only DB’s– SAN Snapshots
• System Engineering• Heap/Virtual Memory
One Two Three Four0
50
100
150
200
250
300
238.5634875
150.3148394
101.9169981
FE Heavy (80 cc users)
One Two Three Four0
20
40
60
80
100
120
88.177996003996
25.1254835164835
102.022311407161
28.3542539550375
SE Heavy
50 CC Users60 CC Users
Scale Out
Storage Area Network
OLAP Processing Server
Windows Server 2003 x64 SP2SQL Server Enterprise Edition
32 GB RAM, 8 Xeon procs (16 cores)
Staging Data Warehouse
Windows Server 2003 x64 SP2SQL Server Integration Services
Network Load Balancing
Data Feeds
HBA BHBA A
Windows Server 2003 x64 SP2SQL Server Analysis Services
64GB RAM, 8 Xeon procs (16 cores)
OLAP Standby Server
SAN Fabric A
SAN Fabric B
HBA BHBA A HBA BHBA A
Host Bus Adapters: 400 MB/sec each
HBA BHBA A HBA BHBA A HBA BHBA A
adCenter Production Environment
Windows Server 2003 x64 SP2SQL Server Analysis Services
64GB RAM, 8 Xeon procs (16 cores)
OLAP LUNStandby OLAP LUN
19200 Max Reads9600 Max Writes
DW LUN
180 300GB 10K Drives
RAID 119200 Max Reads9600 Max Writes
180 300GB 10K Drives
RAID 12560 Max Reads2560 Max Writes
32 300GB 10K Drives
RAID 1
Xbox Live – SSD Performance
Day Week Month Quarter 7 months
Dev SSD 14 29 101 203 506
Dev HDD 14 29 104 610 1191
UAT SAN 9 73 445 1025 2800
V2 Cube, SSD 5 10 15 31 72
V2 Cube, HDD 5 7 30 244 540
250
750
1250
1750
2250
2750
Usage Cube Distinct Count Performance Amount of Data
Run
Tme
(sec
onds
)
• You HAVE to get the design right if you want to scale
• Partitioning is absolute crucial• Partition for processing speed
• Partition for data latency (real time vs. Stale)
• Partition for archival of old data
• Secondary concern to above: partition for query speed
• Hardware really matters for large cubes• Carefully balance IOPS vs. Memory, consider hot portion
of cube
Summarizing
