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Lowering your IT Costs with Oracle Database 11g Release 2 Thomas Kyte http://asktom.oracle.com
Continuous Innovation     Exadata Storage   Real Application Testing   Advanced Compression   Automatic Storage Management    Transparent Data Encryption  Self Managing Database    XML Database   Oracle Data Guard   Real Application Clusters   Flashback Query   Virtual Private Database   Built in Java VM   Partitioning Support   Built in Messaging   Object Relational Support   Multimedia Support   Data Warehousing Optimizations   Parallel Operations   Distributed SQL & Transaction Support   Cluster and MPP Support   Multi-version Read Consistency   Client/Server Support   Platform Portability   Commercial SQL Implementation Oracle 2 Oracle 9 i Oracle 5 Oracle 6 Oracle 7 Oracle 8 Oracle 8 i Oracle 10g Oracle 11g
<Insert Picture Here> Clustering
Consolidate onto the Grid Using low-cost server and storage grids Automatic Storage Management In-Memory Database Cache Real Application Clusters Enterprise Manager
Oracle Database 11g Release 2 Dynamic Cluster Partitioning via Server Pools ,[object Object],[object Object],[object Object],[object Object],Back Office Front Office Depart/LOB Free
RAC One Node New Enterprise  feature  for mass consolidation ,[object Object],[object Object],[object Object],[object Object],DB B DB C DB D DB E DB F DB A
<Insert Picture Here> Hardware
Sun Oracle Database Machine Get on the Grid Faster - OLTP & Data Warehousing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Sun Exadata Storage Server Hardware 24 GB DRAM 12 x 3.5” Disk Drives  2  Quad-Core Intel ®  Xeon ®   Processors Disk Controller HBA with 512M battery backed cache InfiniBand QDR (40Gb/s) dual port card Dual-redundant, hot-swappable power supplies 4 x 96GB Sun Flash PCIe Cards
Flash Cache How it works 120 GB  Flash Cache 16 GB  SGA Memory 360 GB Magnetic Disks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Extended Buffer Cache
World’s Fastest OLTP Machine With Sun FlashFire Technology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
<Insert Picture Here> IMDB
Oracle In Memory Database Cache Offload Data processing to Middle Tier resources ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Cached tables Business Applications Cached tables Business Applications
<Insert Picture Here> Warehousing
Oracle Database 11g Release 2 In-Memory Parallel Execution ,[object Object],[object Object],[object Object],[object Object],[object Object],Real Application Clusters
In-Memory Parallel Execution How it works SQL statement Determine the size of the table being looked at Fragments of Table are read into each node’s buffer cache Read into the buffer cache on any node Table is extremely small  Always use direct read from disk Table is a good candidate for In-Memory Parallel Execution Table is extremely Large Only parallel server on the same RAC node will access each fragment
Automated Degree of Parallelism How it works SQL statement Statement is hard parsed And optimizer determines the execution plan Statement executes serially Statement executes in parallel Optimizer determines ideal DOP If estimated time greater than threshold Actual DOP = MIN(default DOP, ideal DOP) If estimated time less than threshold PARALLEL_MIN_TIME_THRESHOLD
Parallel Statement Queuing How it works SQL statements Statement is parsed and Oracle automatically determines DOP If enough parallel servers available execute immediately If not enough parallel servers available queue FIFO Queue 128 16 32 64 8 When the required number of parallel servers become available the first stmt on the queue is dequeued and executed  128 16 32 64
Query Processing: The problem with traditional storage What Were Yesterday’s Sales? SUM Oracle Database Server Grid Storage Array Retrieve Entire Sales Table Select sum(sales) where salesdate= ‘15-Sep-2009’ …
Query Processing:  Using Sun Oracle Exadata Storage Server What Were Yesterday’s Sales? SUM Oracle Exadata Storage Grid Select sum(sales) where salesdate= ‘15-Sep-2009’ … Retrieve Sales for Sep 15 2009 Oracle Database Server Grid
<Insert Picture Here> Storage
Reduce storage costs by factor of 10x Data growth continues to outpace budget growth Source: Winter TopTen Survey, Winter Corporation, Waltham MA, 2008. 200 400 600 800 1000 1998 2000 2002 2004 2006 2008 2010 Terabytes of Data Rate of Database Growth  Actual Projected
Automatic Storage Management Lowers the cost of storage management ,[object Object],[object Object],[object Object],HR SALES ERP
Oracle Database 11g Release 2 ASM Cluster File System ,[object Object],[object Object],[object Object],HR SALES ERP Database Files Oracle Binaries Files
Oracle Database 11g Release 2 Other ASM Enhancements ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Infrequently  Accessed Data Frequently  Accessed Data © 2009 Oracle Corporation – Proprietary and Confidential
Manage Data Growth  Partition for performance, management and cost 5% Active 95% Less Active ORDERS TABLE (7 years) 2003 2009 Low End Storage Tier  2-3x less per terabyte 2008 High End Storage Tier
Significantly Reduce Storage Usage Advanced OLTP Compression ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Compression 4X Up To
Sun Oracle Exadata Storage Server Hybrid Columnar Compression ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],50X Up To
<Insert Picture Here> Availability
Oracle Maximum Availability Architecture Fully Utilizing Redundancy Automatic Storage Management Real Application Clusters Secure  Backups to Cloud and Tape Active Data Guard Fast Recovery Area Data Guard
Traditional Testing Approach  Production – 1,000s of Real Online Users PRODUCTION
Limited Testing Capabilities  Few users trying to be 1,000s of users TEST PRODUCTION
Real Application Testing Workload for 1,000s of Online Users Captured Capture PRODUCTION Workload
Real Application Testing Workload for 1,000s of Online Users Replayed Replay PRODUCTION TEST Capture Workload
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Online Application Upgrade Edition-based redefinition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
<Insert Picture Here> How to get there
What are my upgrade paths? Predictable performance post-upgrade    10.2.0.2    11.1.0.6 10.1.0.5 9.2.0.8 11.2 SQL Plan Management Automated SQL tuning
Rolling Database Upgrades Initial SQL Apply Config Clients Redo Version X Version X 1 Switchover to B, upgrade A Redo 4 Upgrade X+1 X+1 Run in mixed mode to test Redo 3 X+1 X Upgrade node B to X+1 Upgrade Logs Queue X 2 X+1 Major  Release Upgrades Patch Set Upgrades Cluster  Software &  Hardware  Upgrades B A B A A B A B
Make Change Safe -  Realistic Testing with Database Replay ,[object Object],[object Object],[object Object],[object Object],… … Capture DB Workload Middle   Tier Storage Oracle DB Replay DB Workload Production 9i, 10g, 11g Test 11g Release 1 and above Client Client … Client
For More Information http://search.oracle.com or www.oracle.com/database oracle database 11g

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11g R2

  • 1. Lowering your IT Costs with Oracle Database 11g Release 2 Thomas Kyte http://asktom.oracle.com
  • 2. Continuous Innovation Exadata Storage Real Application Testing Advanced Compression Automatic Storage Management Transparent Data Encryption Self Managing Database XML Database Oracle Data Guard Real Application Clusters Flashback Query Virtual Private Database Built in Java VM Partitioning Support Built in Messaging Object Relational Support Multimedia Support Data Warehousing Optimizations Parallel Operations Distributed SQL & Transaction Support Cluster and MPP Support Multi-version Read Consistency Client/Server Support Platform Portability Commercial SQL Implementation Oracle 2 Oracle 9 i Oracle 5 Oracle 6 Oracle 7 Oracle 8 Oracle 8 i Oracle 10g Oracle 11g
  • 4. Consolidate onto the Grid Using low-cost server and storage grids Automatic Storage Management In-Memory Database Cache Real Application Clusters Enterprise Manager
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  • 9. Sun Exadata Storage Server Hardware 24 GB DRAM 12 x 3.5” Disk Drives 2 Quad-Core Intel ® Xeon ® Processors Disk Controller HBA with 512M battery backed cache InfiniBand QDR (40Gb/s) dual port card Dual-redundant, hot-swappable power supplies 4 x 96GB Sun Flash PCIe Cards
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  • 14. <Insert Picture Here> Warehousing
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  • 16. In-Memory Parallel Execution How it works SQL statement Determine the size of the table being looked at Fragments of Table are read into each node’s buffer cache Read into the buffer cache on any node Table is extremely small Always use direct read from disk Table is a good candidate for In-Memory Parallel Execution Table is extremely Large Only parallel server on the same RAC node will access each fragment
  • 17. Automated Degree of Parallelism How it works SQL statement Statement is hard parsed And optimizer determines the execution plan Statement executes serially Statement executes in parallel Optimizer determines ideal DOP If estimated time greater than threshold Actual DOP = MIN(default DOP, ideal DOP) If estimated time less than threshold PARALLEL_MIN_TIME_THRESHOLD
  • 18. Parallel Statement Queuing How it works SQL statements Statement is parsed and Oracle automatically determines DOP If enough parallel servers available execute immediately If not enough parallel servers available queue FIFO Queue 128 16 32 64 8 When the required number of parallel servers become available the first stmt on the queue is dequeued and executed 128 16 32 64
  • 19. Query Processing: The problem with traditional storage What Were Yesterday’s Sales? SUM Oracle Database Server Grid Storage Array Retrieve Entire Sales Table Select sum(sales) where salesdate= ‘15-Sep-2009’ …
  • 20. Query Processing: Using Sun Oracle Exadata Storage Server What Were Yesterday’s Sales? SUM Oracle Exadata Storage Grid Select sum(sales) where salesdate= ‘15-Sep-2009’ … Retrieve Sales for Sep 15 2009 Oracle Database Server Grid
  • 22. Reduce storage costs by factor of 10x Data growth continues to outpace budget growth Source: Winter TopTen Survey, Winter Corporation, Waltham MA, 2008. 200 400 600 800 1000 1998 2000 2002 2004 2006 2008 2010 Terabytes of Data Rate of Database Growth Actual Projected
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  • 26. Manage Data Growth Partition for performance, management and cost 5% Active 95% Less Active ORDERS TABLE (7 years) 2003 2009 Low End Storage Tier 2-3x less per terabyte 2008 High End Storage Tier
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  • 29. <Insert Picture Here> Availability
  • 30. Oracle Maximum Availability Architecture Fully Utilizing Redundancy Automatic Storage Management Real Application Clusters Secure Backups to Cloud and Tape Active Data Guard Fast Recovery Area Data Guard
  • 31. Traditional Testing Approach Production – 1,000s of Real Online Users PRODUCTION
  • 32. Limited Testing Capabilities Few users trying to be 1,000s of users TEST PRODUCTION
  • 33. Real Application Testing Workload for 1,000s of Online Users Captured Capture PRODUCTION Workload
  • 34. Real Application Testing Workload for 1,000s of Online Users Replayed Replay PRODUCTION TEST Capture Workload
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  • 45. <Insert Picture Here> How to get there
  • 46. What are my upgrade paths? Predictable performance post-upgrade  10.2.0.2  11.1.0.6 10.1.0.5 9.2.0.8 11.2 SQL Plan Management Automated SQL tuning
  • 47. Rolling Database Upgrades Initial SQL Apply Config Clients Redo Version X Version X 1 Switchover to B, upgrade A Redo 4 Upgrade X+1 X+1 Run in mixed mode to test Redo 3 X+1 X Upgrade node B to X+1 Upgrade Logs Queue X 2 X+1 Major Release Upgrades Patch Set Upgrades Cluster Software & Hardware Upgrades B A B A A B A B
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  • 49. For More Information http://search.oracle.com or www.oracle.com/database oracle database 11g

Editor's Notes

  1. CVU = Cluster Verification Utilities