database consolidation on oracle exadata

1 Copyright © 2012, Oracle and/or its affiliates. All rights

reserved.

Database Consolidation on Oracle Exadata

Quantifying the Advantage of Exadata


reserved.

The Objective

“Quantify the value of Exadata

for database consolidation,

compared to a system of

similar hardware.”


reserved.

The Approach

1. Consolidate heterogeneous database

workloads on an Exadata Database

Machine (OLTP, Batch, Analytics)

2. Measure with and without Exadata

features enabled

3. Compare the results


reserved.

Not All Exadata Features Can be Disabled

• These features can be turned on/off

– Smart Flash Cache / Flash Log

– Smart Scan (query offload to storage)

– Hybrid Columnar Compression

– I/O Resource Management

• These inherent features are always on

– Scale-out Exadata Storage

– InfiniBand 40Gb/sec Connectivity

– End-to-End Tuning

Actual Exadata Advantage Exceeds the Measured Results

NOTE:

Because inherent features

cannot be disabled, the true

Exadata advantage exceeds

the measured results


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How Exadata Features Improve Performance

• Smart Flash Cache

– Uses flash for physical I/O

• Smart Flash Log

– Uses flash to improve log I/O latency

• Smart Scan

– Runs portions of a database query in storage

• Hybrid Columnar Compression (HCC)

– Reduces the number of blocks (and I/O) for compressed data

• IO Resource Manager (IORM)

– Prioritizes I/O bandwidth based on database or workload within a database

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Test Setup


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Tested Workloads

• E-Business Suite (EBS)

– 500 Online Users

– Batch Order-to-Cash

• PeopleSoft

– Batch Payroll for 500,000 Employees

• Siebel

– 30,000 Online Users

(captured and replayed using DB Replay)

• Data Mart Workload

– Analytic Queries

Data Mart

Analytics


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Performance Metrics Tracked

Workload Metric

EBS – Online and Batch Orders processed per minute

Siebel - Online Service requests logged per minute

PeopleSoft - Batch Employees paid per minute

Data Mart Queries executed per minute


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Oracle Server Farm DB Replay (Siebel) EBS PeopleSoft

Test Configuration

Node 1 Node 2

Windows Server

HP LoadRunner

(EBS Online)

InfiniBand Network

EXADATA

STORAGE EXADATA

STORAGE

EXADATA

STORAGE

gigE Network

Workloads

deployed with

MAA and

Exadata Best

Practices

• Windows Server

– Driving EBS Online load

• Oracle Server Farm

– PeopleSoft and EBS

Applications

– DB Replay clients to drive

Siebel load

• Quarter Rack Exadata V2

– 2 x DB Servers, each with

• 8 CPU cores

• 72 GB RAM

– 3 x Exadata Storage Servers,

each with:

• 7.2 TB raw disk capacity

• 384 GB flash memory


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Consolidation Scenario

• 500 EBS and 30,000 Siebel users requiring

consistent, fast, online service

• EBS O2C (Order to Cash) batch processing

new orders in a continuous loop

• PeopleSoft Batch payroll processing end

of month employee pay checks

• Data Mart queries running throughout the day

End of Month, Daytime Processing


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Three Sets of Measurements

1. Baseline = Non-Consolidated, Exadata features off

– How each workload performs when it is the only workload running

– Equal to a separate server per database (traditional data center)

– Non-inherent Exadata features disabled

2. Consolidated with Exadata features off

– How each workload performs when all of them are running

– Non-inherent Exadata features disabled

3. Consolidated, Exadata with all features results

– How each workload performs when all of them are running

– All Exadata features enabled (with and without resource management)

Results


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1. Baseline Results – Exadata Features Off

Performance Metric

EBS – Online and Batch 1,744 Orders processed per minute

Siebel - Online 1,455 Service requests logged per minute

PeopleSoft - Batch 1,761 Employees paid per minute

Data Mart 1.64 Queries executed per minute

Traditional Data Center – Separate Systems per Database

• Each workload was measured in isolation (no consolidation)

• Non-inherent Exadata features were disabled

• This approximates a data center where each database runs on highly

tuned dedicated X86 servers with very fast storage


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Resource Utilization During Baseline Tests

DB Server CPU Disk Utilization Disk Throughput

(MB/s) Node 1 Node 2

Peak Mean Peak Mean Peak Mean Peak Mean

EBS 99% 40% 19% 10% 26% 5% 430 56

Siebel 25% 17% 25% 17% 15% 7% 220 30

PeopleSoft 63% 23% 51% 13% 1,000 58

Data Mart 75% 49% 48% 34% 2,400 1,686

Total if Combined 199% 106% 106% 51% 140% 59% 4,050 1,830

Oversubscribed = 32 Gb/s Oversubscribed


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2. Consolidated, Exadata Features Off Consolidation Significantly Degrades Each Workload

42 %

29 %

59 %

69 %

0 %

10 %

20 %

30 %

40 %

50 %

60 %

70 %

80 %

90 %

100 %

EBS - Online and Batch Siebel - Online PeopleSoft - Batch Data Mart

Pe

rfo

rma

nce R

ela

tive

to

Ba

se

lin

e

LO

SS

LO

SS

LO

SS

LO

SS


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3. Consolidated, Exadata Features On

• Smart Flash Cache created

– Top “Segments by Physical Read Requests” for Data Mart, EBS

and PeopleSoft marked “cell_flash_cache keep”

• Smart Flash Log created

• Smart Scan enabled for all databases

• HCC query high compression for all Data Mart tables


reserved.

42 %

29 %

59 %

69 %

80 %

92 % 99 %

120 %

0 %

20 %

40 %

60 %

80 %

100 %

120 %


Pe

rfo

rma

nc

e R

ela

tiv

e t

o B

as

eli

ne

Without Exadata Features With Exadata Features

3. Consolidated, Exadata Features On Exadata Significantly Improves Consolidated Performance

2x

3x 1.7x

1.7x


reserved.

The Conclusion

“Exadata features increase

the throughput of a

consolidated workload 2-3x,

compared to a similar

platform without Exadata

features.”

REMINDER:

Because some Exadata

features cannot be

disabled, the real Exadata

advantage exceeds the

measured results


reserved.

Secondary Objective

“Demonstrate the value of

Exadata’s Resource

Management to a

consolidated database

environment.”


reserved.

3. Consolidated, Exadata Results

• IORM limits

– PeopleSoft limit 50% of IO bandwidth

– Data Mart limit 10% of IO bandwidth

• Instance Caging

– Data Mart CPU_COUNT=2 (1 compute core)

Exadata Resource Management Features Applied


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The Value of Resource Management

46 % 39 %

74 %

237 %

80 % 92 % 99 %

120 %

0 %

50 %

100 %

150 %

200 %

250 %


Pe

rfo

rma

nce

Rela

tive

to

Ba

se

lin

e

Without Resource Management With Resource Management

Without Exadata Resource Management,

the Data Mart workload denies other

workloads their fair share of the system’s

resources. With Resource Management,

the Data Mart excess is redistributed


reserved.

The Bottom Line

“Exadata Features

Significantly Improve

Both the Performance

and the Control of a

Consolidated

Database

Environment.”


reserved.

database consolidation on oracle exadata

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