Agenda
• Oracle Exadata Database Machine Overview
• Consolidation on Oracle Exadata Database Machine
• Workload Management for Consolidated Systems
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Oracle Exadata Database Machine Extreme Performance - Simplified Deployment
Extreme database performance for…
• Data warehousing
• OLTP
• Consolidation
Simplified deployment…
• Pre-configured h/w, s/w combinations
• Industry-standard hardware
• Quarter, half, full-rack, multi-rack
• Oracle Database 11g Release 2
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Oracle Exadata Database MachineMassively Parallel Architecture
• Database Server Pool– Oracle Database 11g Release 2
– Oracle Real Application Clusters
• Storage Server Pool– 100 TB (SAS) or 336 TB (SATA) disk
– 5 TB flash storage
• Infiniband Network– 40 Gb/sec redundant switches
© 2010 Oracle Corporation
Oracle Exadata Database Machine X2-2Extreme Performance at Lowest Cost
• Database Servers– 8 Intel 2-socket compute servers (1U)
– 96 compute cores
– 768 GB memory
– Oracle Linux or Solaris 11 x86
– 10 Gig Ethernet to data center
• Storage Servers– 14 Intel storage servers (2U)
– 100 TB or 336 TB raw disk (mirrored)
– 5.3 TB Flash
• InfiniBand Network– 40 Gb/s redundant switches
• Database Grid– 2 Intel 8-socket servers (5U)
– 128 compute cores
– 2 TB memory
– Oracle Linux or Solaris 11 x86
– 10 Gig Ethernet (to data center)
• Storage Grid– 14 Intel storage servers (2U)
– 168 compute cores
– 100 TB or 336 TB raw disk (mirrored)
– 5.3 TB Flash
• InfiniBand Network– 40 Gb/s redundant switches
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Oracle Exadata Database Machine X2-8New Configuration for OLTP and DW Consolidation
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Consolidation
On the Oracle Exadata
Database Machine
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Consolidation Workloads
• Server rationalization
• OLTP + OLTP …
• Data mart + data mart…
• System life-cycle
• Production + test + development
• Mixed workload
• Operational BI
• Real-time data warehousing
• Embedded reports, analytics
• Schema integration
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Consolidation Considerations
• Application changes
• Schema name collisions
• Real Application Clusters
• Packaged application restrictions
• Application tier scaling
• Compatible SLAs?
• Recovery objectives
• Security
• Predictable response times
• CPU and I/O sharing
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Workload Management Setting Up a Workload Management System
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WorkloadManagement
Define Workloads
Filter Exceptions
Manage Parallelism
Manage CPU
Manage I/O
Monitor Workloads IORM
RAC OEM
DBRM
Workload Management for DWA Case Study
• Data Warehouse Mixed Workload• Real-time ETL – Continuous, near real-time data loading
• Batch ETL – Nightly loading, mostly during off-peak hours
• Analytic Reports – Medium priority run at set periods during the day
• OLTP Queries – High priority, short queries with aggressive SLAs
• Ad-hoc Workloads – Unpredictable resource-intensive queries
• Challenges• Manage contention for CPU, I/O and Parallel Server resources
• Address different performance objectives and priorities
• Deliver consistent performance
• Filter unwanted queries (poorly written or too resource intensive)
• Schedule different requirements at different times (day vs. night)
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Workload Management
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Request
Ad-hocWorkload
Each consumer group has•Resource allocation (e.g. 10% of CPU/IO)•Directives (e.g. 20 active sessions)•Thresholds (e.g. no jobs longer than 2 min)
RejectDowngrade
Assign
Each request assigned
to a consumer group•Username
•Application or module
•Action within module
•Administrative function
Queue
Execute
Each request• Executes on a RAC Service• Which limits the physical resources• Allows scalability across racks
Workload Management
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Request
Real-TimeETL
Batch ETL
Analytic Reports
OLTP Requests
Ad-hocWorkload
Assign
Reject
Queue
Execute
Downgrade
Execute
Workload Management
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Request
Real-TimeETL
Batch ETL
AnalyticReports
OLTPRequests
Ad-hocWorkload
Assign
RejectDowngrade
Queue
Ad-hoc 25%
Analytic Reports
50%
OLTP 5%
Batch 10%
R-T 10%
Queue
Queue
Queue
Queue
Enterprise Manager (EM)
As a DBA you would:
• Define workload policies for mixed workload
• Set priorities and allocate resources
• Set thresholds and throttles
• Monitor the workload
• Adjust workload policies as needed
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EM as Management Interface
�Define Workload
policies for Mixed
Workload
�Set priorities and
allocate resources
�Set thresholds and
throttles
�Monitor the Workload
�Adjust the Policies
over Time
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IORM
RAC OEM
DBRM
CPU and I/O Sharing
• Instance Caging
• Maximum number of CPUs the instance can use at any time
• cpu_count parameter
• Max CPU Utilization
• Maximum % of CPU a consumer group can use at any time
• max_utilization_limit directive
• IORM (I/O Resource Manager)
• Inter-db and intra-db I/O allocations
• Priority, ratio, hybrid allocation plans
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Instance Caging Results
0%
25%
50%
75%
100%
Off On
CP
U C
on
sum
pti
on
Instance Caging
idle
sys
user
Graph Explanation:
Test results showing Instance Caging at 2 CPUs on a 4 CPU server
Swingbench OLTP application
Graph Explanation:
Test results showing Instance Caging at 2 CPUs on a 4 CPU server
Swingbench OLTP application
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Instance Caging Results
0
1000
2000
3000
4000
5000
6000
0,6 1,5 2,4 3,3 4,2 5,1 6,0
Tra
nsactions P
er S
econd
cpu_count: <Instance 1>,<Instance 2>
Instance 1
Instance 2
Both Instances
Graph Explanation:
Test results varying Instance Caging from 0-6 CPUs across two instances
Graph Explanation:
Test results varying Instance Caging from 0-6 CPUs across two instances
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Maximum Utilization Limit
In 11g Release 2, the “max_utilization_limit” directive
limits the CPU consumption of an application
Specify minimum and maximum
CPU utilization limits Specify maximum CPU utilization
limits only
DB Consolidation Plan #1 DB Consolidation Plan #2
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Max_utilization_limit25% – 50% - 75% Proof Points
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Graph Explanation:
Test results indicating the max_utilization_limit directive set at no limit, 25%, 50%, 75%
Workload Description:
A mix of OLTP and DSS queries and DMLs from the Oracle Financials application
Graph Explanation:
Test results indicating the max_utilization_limit directive set at no limit, 25%, 50%, 75%
Workload Description:
A mix of OLTP and DSS queries and DMLs from the Oracle Financials application
I/O Resource Manager in Exadata
• Manages multiple databases sharing Exadata storage
• Inter-database plans
• Administered on Exadata storage servers
• Manages workloads within a database
• Intra-database plans
• Allocations between consumer groups
• Database’s current plan used for both CPU and I/O
• All background I/Os automatically handled
• Background I/Os scheduled according to their priority
• Includes ASM meta-data, ASM rebalances, standby recovery
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IORM ResultsOLTP + Report
Reclaim 92% of peak
TPS!
IORM
I/O
conten
tion
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Graph Explanation:
1.OLTP app gets 1,267 tps
2.Add Report, tps drops to 286
3.Add IORM, OLTP tps goes back to 1,167
Graph Explanation:
1.OLTP app gets 1,267 tps
2.Add Report, tps drops to 286
3.Add IORM, OLTP tps goes back to 1,167
IORM ResultsDSS + DSS
IORM
Reclaim 91% of
peak timeI/O contention
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Graph Explanation:
1.Query finishes fast in 192 seconds
2.Add 2nd query, 1st query jumps to 355 seconds
3.Add IORM, 1st query goes back to 210 seconds
Graph Explanation:
1.Query finishes fast in 192 seconds
2.Add 2nd query, 1st query jumps to 355 seconds
3.Add IORM, 1st query goes back to 210 seconds