Oracle RAC 10 g : Running Mixed Workloads
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Oracle RAC 10g: Running Mixed Workloads
Gordon SmithDirector, RAC Product Management
Oracle Corporation
Session id:
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Agenda
Business Goals Today’s Inadequate Solutions Key Technical Elements of the Solution
– Non-Blocking Queries– Real Application Clusters– Other Great Tools
Oracle 10g Enterprise Grids – Putting It All Together
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Business Goals
Goals– Report off current live data– No impact on online performance– Simplicity – Low cost
Focusing on reporting – Not full blown Data Warehouse
DW a much more complex problem Oracle offers good “On Time” solution
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Today’s Inadequate Solutions
Wait until off-hours when online systems aren’t being used
Problems– The Internet and 21st Century business changed
online to 24 X 7– Data not current
Off-Hours Batch
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Today’s Inadequate Solutions
Copy database to second system for reporting Problems
– Not current data– Complicated, multi-step process with many
failure points– Poor hardware utilization – Data is growing and getting harder to copy– Cloning (or re-silvering) can impact performance
Reporting DB Clones
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Today’s Inadequate Solutions
Why not just run reports against the data on my disaster recovery (DR) standby system
– The standby is just sitting there underutilized– Data can be very current
Problems– Nearly all DR solutions don’t let you access data
on standby system, e.g., Remote disk mirroring systems Oracle DataGuard (physical mode)
Traditional DR Solutions
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Key Technical Elements of the Solution
Non-Blocking Queries Real Application Clusters Other Great Tools
– Automatic Undo Management– Resource Manager– Logical Data Guard
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Non-Blocking Queries
Provides consistent reads– Never sees uncommitted
“dirty” data– Never sees some changes
from a transaction but not other changes
– Bottom line: You Get The Right Answer
Doesn’t block updates Doesn’t get blocked by updates
Account Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
For example, say you need to add up the balances for all accounts …
Account Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
For example, say you need to add up the balances for all accounts …
Account Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
For example, say you need to add up the balance for all accounts …
Account Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
1,000 <- The Right Answer
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Non-Blocking Queries
Now let’s run a transaction at the same time that transfers $50 from one account to another
– Without using Non-Blocking Queries
– Without using read locks
Account Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
Now let’s run a transaction at the same time that transfers $50 from one account to another
– Without using Non-Blocking Queries
– Without using read locks
Account Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
Now let’s run a transaction at the same time that transfers $50 from one account to another
– Without using Non-Blocking Queries
– Without using read locks
Account Balance
0001 100
0002 100
0003 50
0004 100
0005 100
0006 100
0007 100
0008 100
0009 150
0010 100
-$50
+$50
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Non-Blocking Queries
Now let’s run a transaction at the same time that transfers $50 from one account to another
– Without using Non-Blocking Queries
– Without using read locks
Account Balance
0001 100
0002 100
0003 50
0004 100
0005 100
0006 100
0007 100
0008 100
0009 150
0010 100
1,100 <- The Wrong Answer
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Non-Blocking Queries
Now let’s try read locksAccount Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
Now let’s try read locksAccount Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
Now let’s try read locksAccount Balance
0001 100
0002 100
0003 50
0004 100
0005 100
0006 100
0007 100
0008 100
0009 150
0010 100
-$50
Transaction Blocked!!!
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Non-Blocking Queries
Now let’s try read locks You get the right answer but
update transactions are blocked Similarly update transactions
can block queries
Account Balance
0001 100
0002 100
0003 50
0004 100
0005 100
0006 100
0007 100
0008 100
0009 150
0010 100
1,000 <- The Right Answer
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Non-Blocking Queries
Now let’s try non-blocking queries with read consistency
Account Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
• Now let’s try non-blocking queries with read consistency
Account Balance
0001 100
0002 100
0003 100
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
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Non-Blocking Queries
• Now let’s try non-blocking queries with read consistency
Account Balance
0001 100
0002 100
0003 50
0004 100
0005 100
0006 100
0007 100
0008 100
0009 150
0010 100
-$50
+$50
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Non-Blocking Queries
• Now let’s try non-blocking queries with read consistency
• Queries don’t block updates• Updates don’t block queries
Account Balance
0001 100
0002 100
0003 50
0004 100
0005 100
0006 100
0007 100
0008 100
0009 100
0010 100
1,000 <- The Right Answer
150
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Real Application Clusters
Users
Shared CacheShared CacheClustered
Database Servers
Storage Area NetworkMirrored Disk Subsystem
Low Latency InterconnectVIA or Proprietary
High Speed Switch or Interconnect
Hub or Switch Fabric
Centralized Management Console
Cache FusionCache Fusion
Runs all types of business applications on clusters
Maximum availability
Maximum scalability Lowest cost Efficient cache
fusion technology
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Oracle9i RAC SAP Scalability
1 Node 2 Nodes 4 Nodes
3,640
6,580
12,000
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
1 Node 2 Nodes 4 Nodes
# Users
Running on HPQ AlphaServer ComputersRunning on HPQ AlphaServer Computers
SD 3-Tier Parallel Benchmark Results Now Official
82%Scalability
82%Scalability
Certified
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Oracle9i RAC OLAP Scalability 75x better than the nearest competitor
0100002000030000400005000060000700008000090000
100000
Oracle Hyperion Microsoft
Can’t Say1,135
85,719
Ana
lytic
Que
ries
Per
Min
ute
(AQ
M)
World Record Performance
Source: DSS Lab, 2003
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RAC Workloads Survey
RAC Customer Workloads
OLTP
Mixed
DW
Unknow
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RAC Mixed Workload Customers
CJIS FannieMae Job Partners Telenor Mobile University of
Melbourne HealthPartners Cairns City
Council Guangfu
Securities Merrill Lynch STP Maisoning Vanderbilt
University EPL
China Unicom – Chonging
Supply Solutions Gas Authority of
India Ltd. Texas Tech
University Lithonia Lighting SoftChoice Tata Teleservices AusRegistry POSCO Six Sigma Dongbu Insurance Ashok Leyland Ltd. WeightWatchers.com
Gas Authority of India Ltd.
KITC Nextel Clearing Corp of India Daegu universwity Hite Brewery US Army Medical
Research & Material Command
Green Mountain Power Holmesglen TAFE Smartserv Bharti Televentures
Ltd.
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Mix Workload Customer Example
Telenor Mobile in Norway – 2-nodes, 16 CPU & 4 CPU HP-UX – OLTP - 4 CPUs node– DSS on 16 CPUs– Fail OLTP to DSS but not other way
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Other Great Tools
Resource Manager– Controls allocation of CPU to workloads– Limit execution times of long running operations– Limits # of active sessions per workload
Logical Data Guard– Allows queries to data on DR Standby– Allows updates to data only on Standby
Automatic Undo Management– Now fully automatic in Oracle9i
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Enterprise Grid – Putting It All Together
Low Cost Computing– You can “just throw CPUs at it”
Automatic Storage Management– You can “just throw disks at it”
Workload Management– Powerful new ways to manage different
workloads easily
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Enterprise Grid - Low Cost Computing
# Servers# Servers
Operating SystemOperating System
Processors/ServerProcessors/Server
ComponentComponent
Total CostTotal Cost
11
32 @1.3Ghz32 @1.3Ghz
UNIXUNIX
Large RISCLarge RISCSMP Server SMP Server
$1,250,000$1,250,000
Source: hardware vendor price lists
Memory/ServerMemory/Server 64Gb64Gb
88
4 @2Ghz4 @2Ghz
RedHat ASRedHat AS
Intel/Linux Intel/Linux ClusterCluster
$232,664$232,664
8Gb8Gb
88
4 @1.2Ghz4 @1.2Ghz
UNIXUNIX
RISC SMPRISC SMPClusterCluster
$431,960$431,960
8Gb8Gb
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Electronic Arts ROIDiscounted Cash Outlay
Comparison
0
5
10
15
$ M
illi
on
s
RAC 5.03 0.65 0.58 0.59 0.51 7.36
Sun 6.8 1.17 1.07 0.92 0.79 10.76
Year 1 Year 2 Year 3 Year 4 Year 5 Total
1st Year
Big SMP is 35%+ More Expensive
SMP
5 Years
Big SMP is 46%+ More Expensive
Total IT costs:•Hardware costs•Software costs•H&S maintenance•DBA costs•SysAdmin costs
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Enterprise Grid - Automatic Storage Management
Automatic StorageManagement
Eliminates the complexity and cost of 3rd party volume and file managers
Completely automates I/O tuning
Eliminates all fragmentation Optional mirroring
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Enterprise Grid - Automatic Storage Management
Automatic StorageManagement
Eliminates the complexity and cost of 3rd party volume and file managers
Completely automates I/O tuning
Eliminates all fragmentation Optional mirroring Allows disks to be added or
removed dynamically with fully automatic rebalancing
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Enterprise Grid - Automatic Storage Management
Eliminates the complexity and cost of 3rd party volume and file managers
Completely automates I/O tuning
Eliminates all fragmentation Optional mirroring Allows disks to be added or
removed dynamically with fully automatic rebalancingAutomatic Storage
Management
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Enterprise Grid - Workload Management
Hands-free assignment of servers to workloads based on rules
– Automatic assignment of servers to workloads at startup
– Re-assignment of servers to workloads as business needs change
– On server failure, automatic re-assignment of surviving servers to workloads
Works across all platforms
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Enterprise Grid – Workload Management
Normal Server Allocation
Reporting Order EntrySpare
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Enterprise Grid – Workload Management
Christmas Season
Reporting Order Entry
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Enterprise Grid – Workload Management
Post Christmas
Reporting Order Entry
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Enterprise Grid – Workload Management
Normal Server Allocation
Reporting Order EntrySpare
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Enterprise Grid – Workload Management
Node Failure
Reporting Order EntrySpare
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Enterprise Grid – Workload Management
Recovery
Reporting Order Entry
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Enterprise Grid – Workload Management
Another Node Failure
Reporting Order Entry
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Enterprise Grid – Workload Management
Recovery
Reporting Order Entry
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ConclusionA History of Innovation
Non-BlockingQueries
OPS
RealApplication
Clusters(RAC)
AutomaticStorage
Management
WorkloadManagment
Low-CostCommodity
ClustersResourceManager
DataGuard
EnterpriseEnterprise
GridsGrids
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Next Steps…. Recommended Oracle RAC sessions
– Oracle RAC 10g: Continuous Services for the Grid
Wednesday 11 am, Room 104– Oracle RAC: Best Practices on Linux
Wednesday 1 pm, Room 104– Oracle RAC: Customer Roundtable
Wednesday 4:30 pm, Room 104– Real Application Cluster Guru Chat
Thursday 12 noon, Guru Lounge See RAC demos in Database DEMOgrounds Visit the RAC web sites for more information
– http://otn.oracle.com/products/database/clustering/content.html
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AQ&Q U E S T I O N SQ U E S T I O N S
A N S W E R SA N S W E R S
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Reminder – please complete the OracleWorld online session survey
Thank you.
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