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Better, Faster, Cheaper:
Optimizing Application
Performance and Availability
Part I: Infrastructure
Agenda

Business Drivers and Pain Points

Oracle Solution


Oracle Virtual Machine
Clustering
ASM
 RAC
 Coherence





Partitioning
Active Data Guard
Advanced Compression
Summary/Contact Info
IT Challenges – Quality of Service

Data centers are out of power, space and cooling

People are expensive and skills are hard to find

IT pressured to do more with less

Much of the infrastructure is underutilized

IT challenged to keep pace with rapid business change
Infrastructure Trends

Infrastructure trends are shaping IT’s response to
these challenges…
 Increasingly powerful low-cost commodity servers
 Virtualization


Server Virtualization
• Virtual Machines
• Server Partitioning
Server Pooling
• Scaling workloads across multiple servers
2009 CIO Deployment Priorities
60%
50%
40%
53%
44%
39%
30%
20%
10%
0%
Source: Morgan Stanley CIO Survey, 12/18/2008
35%
27%
19%
18%
Virtualization—Two Approaches
Server Virtualization:
Disaggregating a single physical
server into multiple logical servers
(VMs) or partitions
Virtual Machines
Virtualization Layer
Hardware Platform
Server Pooling:
Aggregating many physical servers to
appear like a single logical server
Server Virtualization Technologies
Server
Virtualization
Hardware
Partitions
•
Can provide electrical as well
as fault, OS, and resource
isolation
•
Can provide fault, OS, and
resource isolation
•
Mostly focused on x86
platforms
• Available
on most Risc
platforms
•
•
Evolution from static to
dynamic resource allocation.
•
Supports both dedicated and
shared resource models
•
OS
Level
Virtual Machines
•
•
Can provide process level
resource isolation as well as
some fault isolation
•
Extension of some operating
systems
Fully dynamic environment
can support cross server
resource sharing.
•
Enables efficient resources
sharing for OS environments at
the same level.
Based on a shared resource
model, can support pinning
of resources
•
Shared resource model
•
Requires all environments to be
at same OS level.
•
Minimal overhead.
Runs at native speed
•
Operations overhead can be
significant.

Platform




Application





Variation in usage
Resource over-commitment



Nirvana
CPU intensive
Context switching
Memory usage
I/O access
Workloads


CPU generation
Server platform
Virtualization technique
CPU
Memory
I/O
Native OS performance
Overhead varies widely
DB on
Oracle VM
(Linux)
DB on
VMware
Acceleration
+10%
Overhead
-10%
-95%
Memory Intensive
CPU
Intensive
I/O
Intensive
Memory, CPU, I/O Over-commitment
Introducing Oracle High Performance and
Availability Infrastructure
Oracle VM
Data
Warehouse
Sales
Application
ERP
Application
Mid-Tier Clusters
Real Application Clusters
Oracle Enterprise
Manager
Automatic Storage Management
Custom
Application
Oracle VM
Oracle
Database
Fusion
Middleware
Oracle
Applications
Oracle
Enterprise Linux
Oracle
Enterprise Linux
Oracle
Enterprise Linux
Non-Oracle
Applications
Oracle or Red Hat
Enterprise Linux
Non-Oracle
Applications
Microsoft
Windows
Oracle VM
• Free product based on Xen 3.1
• Oracle tested and supported server
virtualization technology
• Maximizes consolidation of Linux
and Windows servers, saves on
power, cooling and space
• Virtual Machine templates for
automated deployment
•
Live migration included at no
additional cost
• Integrated, browser-based
management console
• Downloadable pre-built images for
Oracle products
• Enterprise-quality support at low
annual cost
Oracle Product Certification with Oracle VM

Oracle Database

Oracle Application Server

Oracle Enterprise Manager

Oracle Berkeley DB

Oracle TimesTen

Oracle E-Business Suite

Oracle PeopleSoft

Oracle Siebel

Oracle Hyperion

More information on Metalink Note 464754.1
Virtualization—Two Approaches
Server Virtualization:
Disaggregating a single physical
server into multiple logical servers
(VMs) or partitions
Virtual Machines
Virtualization Layer
Hardware Platform
Server Pooling:
Aggregating many physical servers to
appear like a single logical server
Evolution of Server Pooling – Standalone SMP to Grid
Computing
SMP
Dominance
RAC
Clusters
for
Availability
Grids of
low cost
hardware and
storage
Cluster Technology:
Foundation for Server Pooling
Cluster Benefits:
Workload Balancing
Workload Failover
Optimal Capacity Planning
Lower Hardware Costs
Increased I/O Throughput
Reduced administrative costs and
downtime (e.g., rolling upgrades)
ASM: Storage Grid

Oracle Automatic
Storage Manager (ASM)




Provisions storage
capacity automatically to
Oracle 10g as needed
Stripes and Balances I/O
Mirrors: Immune to disk
failure
Oracle Automatic
Backup and Recovery


Single backup area
for all Grid databases
Archive to tape
RAC: The Database Grid
Network
Users
Centralized
Management
Console
Interconnect
High Speed
Switch or
Interconnect
No Single
Point Of Failure
Clustered
Database Servers
Hub or
Switch
Fabric
Mirrored Disk
Subsystem
Storage Area Network
Drive and Exploit
Industry Advances in
Clustering
Before Clusters - Higher Costs

Poor Resource Utilization

Built for peak periods



Standby hardware and software costs virtually double the
investment and further reduce useful utilization
Management happens in silos

Uneven process maturity across managed silos





Gartner estimates average server utilization rate at 5-10%!
Availability, security, performance
Increased staff
Proliferation of tools that have overlapping capabilities
Software patching/testing, upgrade tasks are multiplied
Increases information complexity and lowers agility

More data movement required (i.e. increased latency, increased
storage, increased integrity issues)
Proven for Production – 8+ RAC Node Customers
 Citigroup
 Burlington Coat
 SAIC
Factory
 J2 Global
Communications
 Genworth Financial
 Amazon.com
 MSDS
 Mercado Libre
 Yahoo! Overture
 Babcock Engineering
 Ordnance Survey
 Dell
 Yahoo!
 ADESLAS
 Fairmont Hotels
 Evite.com
 Quelle AG
 Telstra
 Gas Natural
 MyTravel
 Thomson
 AOL
 Vivo
 Sagawa Kyubin
Rolling Patch Upgrades With RAC
Clients
A
B
1
Clients
A
B
B
2
Initial RAC Configuration
A
A
B
B
4
Clients on A, Patch B
Patch A
A
Patch
Oracle
Patch
Upgrades
Operating
System
Upgrades
B
3
Hardware
Upgrades
Upgrade Complete
Clients on B, Patch A
Oracle Clustering - Not Just RAC!
Web Tier
Network
Web
Cache
Application Tier
Web
Servers
Application
Servers
Coherence
Data Grid
HTML Data Structures in
Memory
Java Data Structures
in Memory
Offload Web Servers,
Improve Network
Performance via
Compression
Cache Java Structures
in Memory; Very Fast
Access to Java Data in
Memory across Mid-Tier
Grid
Database Tier
In-Memory
Cache
RAC
SQL Data Structures
in Memory
Provide Scalability to
Database Data
improving Query &
Transaction Write
Performance
Confidential
20
Oracle Coherence Data Grid Service
Distributed, In Memory
Real Time Clients
Application Servers
Applications
Databases
SOA Infrastructure
Coherence Clients
For Data Access, Analytics, Transactions, Events
Distributed, In Memory Oracle Coherence Data Grid
Coherence Data Grid Service
Distributed In-Memory Data Management
Provides a reliable data tier with a single, consistent view of data
Enables dynamic data capacity including fault tolerance and load balancing
Ensures that data capacity scales with processing capacity
Summary: Virtualization + Server Pooling
Comprehensive Perf/HA Architecture

Optimize within a server and across servers

Server Virtualization benefits

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
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Easy consolidation of underutilized servers
Reduced floor space, power, and cooling requirements
Easy provisioning for test and dev environments
Server Pooling benefits
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True business continuity
Scalability across servers
Higher performance (high overhead with VMs)
A reduction in management burden (app/db consolidation)
Server virtualization best for small workloads, test,
dev, and non-critical applications
 Server pooling (RAC) best for mid-to-large and business
critical applications

Oracle Partitioning: A History of Innovation
Core functionality
Performance
Manageability
Oracle8
Range partitioning
Global range indexes
“Static” partition
pruning
Basic maintenance
operations: add,
drop, exchange
Oracle8i
Hash and composite
range-hash partitioning
Partition-wise joins
“Dynamic” pruning
Merge operation
Oracle9i
List partitioning
Oracle9i R2
Composite range-list
partitioning
Oracle10g
Global hash indexes
Oracle10g R2
1M partitions per table
Oracle
Database 11g
More composite choices
REF Partitioning
Virtual Column Partitioning
Global index
maintenance
Fast partition split
Local Index
maintenance
“Multi-dimensional”
pruning
Fast drop table
Interval Partitioning
Partition Advisor
New in 11g - Interval Partitioning

Partitioning is key-enabling functionality for
managing large volumes of data



Application
One logical object for application transparency
Multiple physical segments for Administration
SQL
CDRs
Improves Manageability, Availability, and
Performance
BUT
Mar
Jan
Feb
• Physical segmentation requires additional data
management overhead
• E.g. new partitions must be created on-time for new data
Solution: Automate partition management
New in 11g - REF Partitioning
Table ORDERS
...
Jan 2006
Feb 2006
...
PARTITION BY REFERENCE
• Partitioning key inherited through PKFK relationship
Table LINEITEMS
...
Jan 2006
Feb 2006
...
• Related tables benefit from
same partitioning strategy
• Eliminates data and
maintenance overhead
• Intuitive modelling
• Enhanced Performance and
Manageability
Partitioning-based Rolling Window Operations
Order Table
(partitioned by quarter)
Q1’07
Q2’07
Q3’07
Q4’07
Drop
Other data & queries not affected
Add
Q1’08
Unlocking the Value of Standby DBs
Standby
for DR
and Backup
Logical Standby
for Realtime
Query
Standby
for Online
Upgrade,
Auto Failover
Standby
for Testing,
Readable
Physical
Disaster Recovery Challenge
Investment in Disaster Recovery only
Real-time
Queries
Production
Database
Standby
Database
• Applications, backups, reports run on production only
With Oracle Active Data Guard
Offload production reporting to standby
Real-time
Queries
Production
Database
Standby
Database
• Simultaneously available in read and recovery mode
Active Data Guard Real-time Query
Concurrent
Real-Time Query
Continuous Redo
Shipment and Apply
Primary
Database

Physical Standby
Database
Read-only queries on physical standby concurrent with redo apply
Supports RAC on primary and/or standby
 Queries see transactionally consistent results
 Handles all data types, but not as flexible as logical standby

With Oracle Active Data Guard
Offload database backups to standby
Production
Database
• Complete database and fast incremental backups
Standby
Database
With Oracle Data Guard
Test changes
Production
Database
•• Switch
‘snapshot’
standby for testing purposes
Switch to
back
to standby
Standby
Database
•• Preserves
zero data applies
loss, although
no real-time
query or failover
Backs out changes,
production
logs
Rolling Release Upgrades w/Data Guard
Upgrade
Patch Set
Upgrades
Redo
Clients
A
Version X
B
Logs
Queue
Version X
1 Initial SQL Apply Config
A
X
2
X+1
Upgrade node B to X+1
Redo
Redo
Upgrade
B
A
B
X+1
X+1
4 Switchover to B, upgrade A
A
X
B
X+1
3 Run in mixed mode to test
Major
Release
Upgrades
Cluster
Software &
Hardware
Upgrades
Introducing Advanced Compression

Advanced compression in Oracle Database 11g

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
Structured data compression
Unstructured data compression
Compression for backup data
Network transport compression
Reduces resource requirements and costs



Storage System
Network Bandwidth
Memory Usage
Physical
Standby
Backups
Advanced Compression
New in Oracle Database 11g

Extends table compression for OLTP data



New algorithm significantly reduces write overhead



Support for conventional DML Operations (INSERT and UPDATE)
Block level compression dictionary is dynamic, making it adaptive to
frequent data changes in OLTP environments
Batched compression ensures no impact for most transactions
Makes compression feasible for OLTP systems as performance is not
compromised for DML operations
Available with new Advanced Compression option

Table Compression for bulk load operations continues to be available
as a feature at no extra charge
Real World Compression Results
10 Largest ERP Database Tables
Data Storage
2500
2000
1500
Table Scans
1000
0.4
500
0.3
DML Performance
0
3x Savings
0.2
40
0.1
30
0
20
2.5x Faster
10
0
< 3% Overhead
Unstructured Data Compression
Oracle Database 11g - SecureFiles

SecureFiles is a new database feature designed to break the
performance barrier keeping file data out of databases

Similar to LOBs but much faster, and with more capabilities




Transparent encryption, compression, deduplication, etc.
Preserves the security, reliability, and scalability of database
Superset of LOB interfaces allows easy migration from LOBs
Enables consolidation of file and relational data



Single security model
Single view of data
Single management of data
SecureFiles Deduplication
Secure Hash
• Enables storage of a single physical image for duplicate data
• Significantly reduces space consumption
• Dramatically improves writes and copy operations
• No adverse impact on read operations
• Duplicate detection happens within a table, partition or sub-partition
• Ideal for content management, email and data archival applications
• Part of the Advanced Compression Option
Advanced Compression – Summary
Compress Large Application Tables
•Transaction
processing, data warehousing
Compress All Data Types
•Structured,
unstructured, backup data
Typical Compression of 2-4X
•Cascade
storage savings throughout data center
Up To
4X
Compression
TUSC – Trusted Oracle Expertise Across Techology
and Applications
Database and
Grid Computing
Fusion
Middleware
Information Age
Applications
• Database
• Real Application Clusters
(RAC)
• Enterprise Manager
• Partitioning
• OLAP
• Security
• Lite
• Times Ten
• Application Server
• Integration / SOA
• Hot-Pluggable
• Business Intelligence
• Identity Management
• Data Hubs
• Collaboration Services
• Process Orchestration
• Java Development Tools
• Oracle E-Business Suite
• PeopleSoft Enterprise
• Siebel CRM
• JD Edwards EnterpriseOne
• JD Edwards World
• Oracle Retail
• i-flex
• Communications Billing
• ProfitLogic
• G-Log
Contact Us

West: Brian Decker, [email protected], (626) 836-9574

South/Central: Lisa DiNitto, [email protected], (770) 325-2191

East/Central: Mike Margulies, [email protected], (203) 293-4422

For additional information and consultation

Oracle Investment Value Analysis™
Review of existing Oracle topology and architecture, including
deployment growth and capacity analysis
 Review of existing Oracle licenses ownership and license surplus/exposure
analysis
 License optimization recommendations, including leveraging maximum
available discounts and financing options

Solutions Requirements Assessments
 Performance/HA Architecture healthcheck and high-level roadmap
 Quickstart options
