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largeDB.ppt
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largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
largeDB.ppt
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largeDB.ppt
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largeDB.ppt

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  • 1. Howard Fosdick (630)-279-4286 (C) 2004 FCI World’s Largest Databases
  • 2.
    • Who Am I?
    • Hands-on DBA (and SA) for …
      • Oracle, DB2, SQL Server
      • Unix, Linux, Windows
    • Founder IDUG, MWDUG, CAMP
    • Author, Speaker
    Independent Contractor (630)-279-4286 [email_address]
  • 3.
    • Outline
    1. What’s a “Big Database” 2. DSS 3. OLTP 4. Observations
  • 4.
    • Statistics Sources
    • 1. Winter Corp.
    • -- Database Top Ten
    • -- Yearly survey
      • -- Vendor neutral
      • -- Free at: www.wintercorp.com
    • 2. Survey.com
    • -- High-End BI/DW Competitive Analysis
    • -- Survey of 150 companies w/ big warehouses
    • -- Free at: www.survey.com
    “ Thank You” to both sources
  • 5.
    • Classifying Large Databases
    DSS OLTP Decision Support Systems (DSS) Online Analytical Processing (OLAP) Data Warehouses (DW) Multi-dimensional Databases (MDD) + Query oriented, mainly Read-only Online Transaction Processing (OLTP) + Update with short transactions ( transaction = small CPU & data resources) Commercial IT vs. Scientific/Research databases
  • 6.
    • What’s a Large Database ?
    Database Size - User data - User data plus metadata & indexes - DASD farm Users - Concurrent users - Total user population Load - Concurrent queries - Queries / day or hour (simple vs complex queries) VLDB = Very Large Database Good definitions and measurements are key to success
  • 7. II. World’s Biggest DSS Systems
  • 8.
    • Data Warehouses VS. Data Marts
    DW DM
    • Application neutral
    • Service multiple organizational needs
    Largest systems are usually data warehouses
    • Application specific
    • Organizationally focused
  • 9.
    • What’s Driving the Growth of
    • Large Data Warehouses ?
    Web Sites -- - Clickstream data Retail -- - Transaction Level Detail (TLD) !!!!! Super Big Groceries !!!!! Preferred Customer Card #283736 Hello, I’m Scot94 03/04/04 02:38 3284 03 2918 33 Store 493 Loc 229 PRETTY-LADY HAIRCLR 1 5.99 AARP MAGAZINE 1 4.95 DIAPERS 2 10.00 BEER SIX-PACK 1 3.45 Tax 2.40 BAL 36.79 Cash 40.00 Change 3.21 Save this Receipt – Get $2.00 off on Prozac When You Buy Super-Baby Food ! Understanding customer behavior means $$$ !
  • 10.
    • What’s Driving the Growth of
    • Large Data Warehouses ?
    • Necessary Preconditions --
    • Cheap Hardware
    • Higher reliability / availability
    • (based on dynamic hardware swapping)
    • Better Software
    • Lax privacy laws in USA
      • EU curtails cross-usage of data
      • EU has stronger privacy laws
  • 11.
    • World’s Largest DSS Systems
    • Way bigger than just 3 years ago
    • All Unix “mainframes”
    • All use SANs (Storage Area Networks) (aka ESS)
    • No IBM Mainframes
    • No Windows or Wintel
    • No SQL Server
    • No Linux or Open Source databases
    • NCR/Teradata niche market at 2.7% (Gartner 05/28/03)
    • Goodbye Informix!
    © 2003 Winter Corp. Database Size = disk storage for user tables, indices, aggregates
  • 12.
    • Large DSS Systems
    Sun E12/15K HP Superdome IBM Regatta Unix “mainframe” Storage Area Network Query Users EMC Hitachi HP LSI
    • Unix “mainframes” –
      • + Dynamically add/drop CPUs, RAM
        • (Sun calls it partitioning )
      • + High reliability
      • (as good as clusters or Mainframes)
      • + Capacity on Demand
    • SANs –
      • + Flash ( “snap” ) backup
        • (OS-level backup)
      • + Large Cache
      • + Intelligent data
      • placement/movement
  • 13. Example Evolution – Scaling a Unix “Mainframe” 8 CPUs @ 16 Gig RAM 12 concurrent users 32 CPUs @ 64 Gig RAM 64 CPUs @ 64 Gig RAM 25 concurrent users 35 concurrent users Other upgrades: Oracle 8i -> 9i Sun E10K -> E12K
  • 14.
    • World’s Largest DSS Systems -- Windows
    • Way smaller than Unix systems
    • Way bigger than just 3 years ago
    • Oracle vs SQL Server (like market share battle for Windows DBMSs)
    • Also use SANs (Storage Area Networks)
    • No IBM DB2 UDB
    • No Teradata
    © 2003 Winter Corp.
  • 15.
    • World’s Largest DSS Systems
    • -- By Peak Workload
    © 2003 Winter Corp. © 2003 Winter Corp.
  • 16. Where did IBM Mainframes Go ? Big Silicon Big Iron
    • + Hello Linux !
    • + Good for --
    • + Consolidation platform
      • + Legacy systems
      • + Virtualization
      • (multi-OS platform)
    Poof!
    • -- Goodbye…
      • -- Largest databases
      • -- Smaller mainframes (VM, VSE)
    • -- Reliability advantage eroded
    • -- High cost per CPU
    1994 2004
  • 17. Oracle Rising
    • Joined the Top Ten list 3 to 5 years ago
    • 8i added essential DSS technologies ...
      • + Partitions
      • + New ROW ID (for bigger databases)
      • + Thorough Parallelism (DML, DDL, utilities)
      • + Index improvements
      • (bit mapped IXs, function-based, desc, others)
      • + Resource Manager (proactive)
      • + Materialized Views
      • + Large memory mgmt
      • + Optimizer is Partition-aware
      • + Online DDL operations and Utilities
  • 18. Example Oracle Warehouses   © 2003 Winter Corp.   Amazon Best Buy Colgate Telecom Italia Mobile           System HP Superdome Sun 15K IBM p690 Regatta HP AlphaServer Architecture SMP SMP SMP Cluster Storage EMC EMC IBM EMC Processors 64 24 24 2 node cluster Oracle Version 9i 8i 9i 8i DB Size 13 T 6.3 T 3.8 T 16 T Number of Tables 600 4025 27,000 1,200 Detail Data Clickstream data Sales Transaction data Varied detail data Call detail records User Population 800 16,000 6,200 400 Concurrent Users 55-60 600-700 600-700 55 DBAs 2 2 n/a 3 Peak Workload 4300 queries / day 150,000 queries / 4 hour period 14,200 steps / day 700 M records loaded / day
  • 19. Why Not Oracle Clustering ? + Great for non-disruptive scaling of existing systems . . . But the biggest systems tend not to use it -- Unix “mainframe” no longer requires clustering for reliability, availability or easy scalability -- Clustering means complexity in minimizing the… -- Locking issues 9i improved this via Cache Fusion – but SMP Unix “mainframe” will still be favored
  • 20. Where’s SQL Server 2000 ?
    • Big in OLTP but lacks essential DSS technologies ...
      • -- Parallelism restricted to SELECTs
        • -- Needs it for other DML, DDL, utilities
      • -- Partitions
      • -- Wintel restriction
    (Features = partitioning, database mirroring, mirrored backups, online Indexing & Restore, fast recovery, ANSI 1999 T-SQL, CLR support, native XML, XML Query, better . NET support, Reporting Services, Service Broker (async messaging), extensible data types…) Yukon ? -- Many new features. . . ready for “Top Ten” DSS ?
  • 21. Where’s Open Source ?
    • Linux
    • + 2.6 kernel now out
    • + More CPUs (to 16)
    • + More RAM (> 4+ Gig)
    • + Better threading, file system support
    • MySQL and PostgresQL
      • -- Top out at 500,000 page views per day ( EWeek 2003)
      • (or 15 per second)
      • + Improving rapidly
    Prediction – open source will support big databases but not “Top Ten” list sites
  • 22. Risks of Large DWs
    • 40% of IT projects fail due to … Management ( time & budget issues )
    • “ Large warehouses are unforgiving” -- Survey.com
    • Design issues critical
      • Database Design
      • Query design (and EXPLAINs)
      • ETL design and scheduling
    • Pre-program wherever possible
    • (control users and the resources they use)
    • Monitoring and alerts
    • Scale gradually (staggered loads on a schedule…)
    • Benchmarks (after each Scaling Point)
  • 23. Risks of Large DWs
    • Partitioning data properly is critical
      • For better physical management (utilities)
      • Optimizers use this info
      • Parallelism via multiple partitions
    • How to partition
      • Depends on data usage
      • Examples: geographical, hash, unique id, ranges…
  • 24. III. World’s Biggest OLTP Systems
  • 25.
    • World’s Largest OLTP Systems
    © 2003 Winter Corp.
    • Wintel “mainframes” arrive !
    • SQL Server arrives
    • Use SANs
    • CA can do the job (but has tiny overall database market share)
    • Oracle has big systems -- but not in the top ten
  • 26.
    • World’s Largest OLTP Systems
    • -- Unix -- Windows
    © 2003 Winter Corp. © 2003 Winter Corp.
  • 27.
    • World’s Largest OLTP Systems
    • -- By Number of Rows
    © 2003 Winter Corp. © 2003 Winter Corp.
  • 28. OLTP Observations
    • Wintel “mainframes” w/ SQL Server displace MVS/CICS
    • SQL Server dominates Wintel OLTP
      • Great for pre-programmed, resource-limited txns
    • Oracle dominates Unix OLTP
  • 29. IV. Observations
  • 30. Architectures Large SMP “ mainframe” Shared-disk Clusters Shared-nothing (Massively Parallel Processing or MPP) The “architectural debate” means far less than it used to !
  • 31. Vendor Architectures     Product : Architecture : Implementation :       DB2 UDB for z/OS Shared-disk clustering DB2 Data Sharing on Sysplex DB2 UDB for LUW Shared nothing DB2 UDB ESE partitioning feature Oracle Shared-disk clustering or SMP Real Application Clusters (RAC) -- previously known as Oracle Parallel Server (OPS) SQL Server 2000 Shared nothing or SMP Customer-developed partitioning based on SQL Server features Teradata Shared nothing Teradata on NCR MPP
  • 32. DBMS Licensing Costs Open Source (MySQL, PostgreSQL) SQL Server 2000 DB2 UDB Oracle Teradata Database pricing varies by the options selected and by the deal an IT organization cuts with the vendor. Your mileage may vary! Biggest DSS Systems $$$$$ Biggest OLTP Systems TCO ? + Low-cost SQL Server supports the biggest OLTP systems -- Pressure on Teradata to keep its niche + Open Source DBMSs have a role but it’s not “Top Ten” databases $
  • 33. DW Labor Costs © 2002 Survey.com
    • Like TCO, Labor Costs may be an un-measurable …
    • Figures applicable across sites ?
    • Every vendor claims lowest labor costs
    • “ Terabytes per DBA” may be non-linear!
    • 1 or 2 DBAs for a 24/7 site ?
    • Development staff will be larger than Maintenance staff
    • Your mileage will vary
  • 34. Multi- Machine Mixed Systems Trend ! 45 Linux w/ MySQL servers (Transactional updates) EWeek , 2/23/04 Sabre / Travelocity 17 Himalaya Non-stop w/ Master database (Fare look-up and routing)
  • 35. Multi- Machine Mixed Systems Trend ! Omaha Steaks 17 Linux w/ MySQL servers (Shopping cart) (Transactional updates) * 50,000 to 68,000 daily sessions * 1 year in Production / 8 Million sessions ISeries DB2 EWeek 2003
  • 36. Conclusions
    • Databases are growing exponentially
    • IT is closing in on Scientific/Research databases
    • “ Multiple machine” mixed systems are becoming popular
    • (Monolithic central databases are no longer the only game in town)
    • “ Mixed use” databases are becoming more common
      • Multiple applications
      • Read and update
    • Open Source supports large systems -- but not “Top Ten”
    • VLDBs are instructive – but unique in some ways
    Trends !
  • 37.
    • ?
    ? ? ? ? questions... ? ? ? ?

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