Oracle White Paper - Oracle | Integrated Cloud ... · An Oracle White Paper March 2014 Oracle Hyperion Financial Data Quality Management, Enterprise Edition Performance Benchmarks

An Oracle White Paper

March 2014

Oracle Hyperion Financial Data Quality Management, Enterprise Edition

Performance Benchmarks

Oracle Hyperion Financial Data Quality Management, Enterprise Edition - Performance

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1

Introduction

Finance organizations continually enhance the quality of their internal controls and reporting

processes. To meet these goals, a source-to-report view of financial data processes is

required. Oracle Hyperion Financial Data Quality Management, Enterprise Edition (FDMEE)

is a solution that allows business analysts to develop standardized financial data

management processes and validate data from any source system—all while reducing costs

and complexity. FDMEE puts the finance user in total control of the integration process to

define source data, create mapping rules to translate data into the required target format,

and to execute and manage the periodic data loading process.

This paper focuses on the performance of Oracle Hyperion Financial Data Quality

Management, Enterprise Edition for a specific hardware and network configuration. It

includes: hardware specifications, configuration details, and executed test scenarios.

Results of the tests performed are based on Release 11.1.2.3.200 using Oracle Application

Testing Suite 12.2.0.1. The performance numbers reported in this document use Oracle’s

specific configuration. Your hardware and software configurations may result in outcomes

other than what is described here. Any comparison to the actual performance results from

those reported in this document may be invalid based on these differences. Management of

data volumes, mapping rules, and database tuning may also be required to achieve the

desired performance outcomes.


2

Test Environment

Table 1: Server Specifications

64 Bit – Windows 2008 SP2, all servers are on the same network segment.

Application Components Model Speed RAM Proc.

Server1 HSS, Calculation

Manager, Oracle

Hyperion Enterprise

Performance

Management Architect,

Oracle WebLogic

Server

Quad -core Proliant DL380 G5 (4) 2.33 GHz 12 GB Intel

Xeon

E5345

Server2 Oracle Hyperion

Financial Data Quality

Management,

Enterprise Edition,

Oracle Data Integrator

2 processors with 6 cores each –

Total of 12 physical cores - Hyper-

threaded (24)

3.07 GHz 144 GB Intel

Xeon

X5675

Server3 Oracle Hyperion

Financial Management,

Oracle Essbase,

Oracle Hyperion

Planning

2 processors with 6 cores each –


threaded (24)


Xeon

X5675

DB Server Oracle Database

Server- Enterprise

Edition 11g R2

2 processors with 8 cores each -


threaded (32)


Xeon

E5-2690

Load Test

Server

Oracle Application

Testing Suite 12.2.0.1 -

Load testing tool

Dual Quad -core Proliant DL380 G5

(8)


Xeon

E5345


3

Environment Details

Software Release Version: 11.1.2.3.200

The default settings for these options were changed in the test environment.

Tuning:

Oracle Data Integrator

EBS_DATA_SERVER – Array Fetch Size: 3000 Batch update Size: 300

WebLogic

Connection Pool – aif_Datasource: Maximum Capacity 1000

Connection Pool – OdiMasterRepository: Maximum Capacity 500

Oracle Database 11g R2

Open Cursors 5000, Processes 1500, Sessions 2272

Java Heap Registry Entries

HyS9aifWeb_epmsystem3 -Xms 2048, -Xmx 4096

Database tablespace configuration

Separate Tablespaces for: Oracle Hyperion Financial Management, Oracle Hyperion Planning, Oracle

Essbase, Oracle Hyperion Financial Data Quality Management, Enterprise Edition

One Tablespace for: Oracle Hyperion Provider Services, Calculation Manager, Oracle Hyperion

Enterprise Performance Management Architect

Oracle Hyperion Financial Data Quality Management, Enterprise Edition Data Load

Mapping rules

211 rows of Account mappings using LIKE, EXPLICIT, and BETWEEN mapping types

140, LIKE rules

58, EXPLICIT rules

13, BETWEEN rules

Test Scenarios Single user (manual tests)

Volume file data loads from flat files (Number of rows in the file) 6k, 20k, 50k, 100k, 500k,

1M


4

Volume data load from remote EBS system, Oracle Hyperion Financial Management EPMA

application:

o 1 month - 121,519 records loaded to database table

o 3 months - 374,978 records loaded to database table

o 6 months - 730,864 records loaded to database table

o 12 months - 1,404,753 records loaded to database table

Metadata load from remote EBS system, Oracle Hyperion Planning Classic and EPMA

application, Oracle Hyperion Financial Management Classic and EPMA applications 920

Accounts, 107 Entities

Multi-user Concurrent

(Automated tests, Think time 10 seconds, 5 iterations for each user, iteration delay 120 sec.)

Data Load from Flat File, 6k files all users 1, 5, 10, 20 users (6,000 rows in the file)

Figure 1: Total Time to load Data from remote EBS server to FDMEE Figure 1 shows the total time it took to load the data into Oracle Hyperion Financial Data Quality Management, Enterprise Edition from an EBS server that was remote from our test environment and on a separate network segment. Because of the difference in the server locations, a variance of approximately 3 seconds for each response time measurement occurred.

0:02:38

0:12:24

0:17:11

0:25:16

0:00:00

0:02:53

0:05:46

0:08:38

0:11:31

0:14:24

0:17:17

0:20:10

0:23:02

0:25:55

0:28:48

h

h

:

m

m

:

s

s

FDMEE 11.1.2.3.200 Total time to load data from a remote EBS System

Data Load - Import Only - 1 month - Jun 2007

Data Load - Import Only - 3 months Apr-Jun 2007

Data Load - Import Only - 6 months Jan-Jun 2007

Data Load - Import Only - 12 months - Jun2006-May 2007


5

Figure 2: Total Time to load metadata from a remote EBS server Figure 2 shows the total time it took to load accounts and entities from a remote EBS server to our test environment. Four separate tests were executed, two loading to Oracle Hyperion Financial Management, and two loading to Oracle Hyperion Planning. For each application two types of application deployments were used: Classic and Oracle Hyperion Enterprise Performance Management Architect applications.

Figure 3: Total Time to load data from a flat File usingvarious load file sizes One important feature is a flat file import. In Figure 3 note the difference in the time it took to import flat files of various sizes ranging from 6,000 lines to one million lines. For this test, the data was imported to Oracle Hyperion Financial Data Quality Management, Enterprise Edition, then exported to a Classic Oracle Hyperion Financial Management application for one month using the replace option for the Import and Export Mode.

0:02:24

0:00:59

0:02:26

0:01:19

0:00:00

0:00:17

0:00:35

0:00:52

0:01:09

0:01:26

0:01:44

0:02:01

0:02:18

0:02:36

h

h

:

m

m

:

s

s

FDMEE 11.1.2.3.200 Metadata koad from a remote EBS System

919 accounts, 106 entities

Metadata Load - HP Classic

Metadata Load - HP EPMA

Metadata Load - HFM Classic

Metadata Load - HFM EPMA

0:00:34 0:00:45 0:01:15 0:02:50

0:13:51

0:30:04

0:00:00

0:07:12

0:14:24

0:21:36

0:28:48

0:36:00

h

h

:

m

m

:

s

s

FDMEE 11.1.2.3.200 Data load from a flat file

Volume Records - Total time to import/export (HFM)

File Import - 6K file





File Import - 1M file


6

Figure 4: Total Time to load Data from Flat File, various user loads Figure 4 depicts the response times for a fixed size of six thousand rows as scaled to the number of simultaneous users. All users loaded one month of data, exported to an Oracle Hyperion Financial Management application using replace options for the Import and Export mode. Each user repeated the import/export process five times before completing the test. The one ne user test is slightly higher than the five user test because the first user in the system bears the overhead of cacheing. Each user had a separate location and load file.

Figure 5: 6k Data Load from flat file import – multiple users– FDMEE Server CPU Utilization

CPU utilization of the FDMEE Server graph shows spikes that correlate to the actual File Import transaction for each of

the five iterations that each user completes. A value of two hundred on this chart is equivalent to two 1 CPUs one

thousand is equal to ten CPU’s. On this chart note the relationship between running a ten user and a twenty user test.

28 25

37

70

0

10

20

30

40

50

60

70

80

File Import - 1 User File Import - 5 Users File Import - 10 Users File Import - 20 Users

S

e

c

o

n

d

s

FDMEE 11.1.2.3.200 Data load from a 6K flat file

Total time to import/export( HFM) - Scale Users

0

500

1,000

1,500

2,000

8:5

4:4

7

8:5

5:3

7

8:5

6:2

7

8:5

7:1

7

8:5

8:0

7

8:5

8:5

7

8:5

9:4

7

9:0

0:3

7

9:0

1:2

7

9:0

2:1

7

9:0

3:0

7

9:0

3:5

7

9:0

4:4

7

9:0

5:3

7

9:0

6:2

7

9:0

7:1

7

9:0

8:0

7

9:0

8:5

7

9:0

9:4

7

9:1

0:3

7

9:1

1:2

7

9:1

2:1

7

9:1

3:0

7

9:1

3:5

7

9:1

4:4

7

9:1

5:3

7

C

P

U

U

t

i

l

i

z

a

t

i

o

n

Duration of test

FDMEE 11.1.2.3.200 6K file inport data load for 10 & 20 user loads

FDMEE Server CPU utilization

20 users 10 users


7

Conclusion

The Financial Data Quality Management Enterprise Edition server performed as expected during all

performance tests. It remained stable during the Scalability test for up to one hundred users and

during Uptime tests that ran over three to five days. Scalability and uptime tests showed transaction

times within tolerance. We used basic mapping rules for the tests. In a production environment the

mapping may be significantly more complicated. Performance times may change based on the

complexity of the customer’s mapping rules (see the breakdown above for the types of mapping rules

used).

The File Import Data Load process is a resource intensive process. When planning for a large number

of users and/or many file imports that will take place over a short period of time, consider increasing

the default WebLogic Maximum Capacity Connection Pool for the aif_Datasource.

A note about performance testing:

As with any benchmark testing, the results are based on a specific set of test cases for a specific set of

hardware, for a specific network configuration. Other test results vary based on differences in any of

these variables.

Oracle Hyperion Financial Data Quality

Management, Enterprise Edition - Performance

March 2014

Author: Dawn Watson

Contributing Authors: Mike Casey

Oracle Corporation

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Oracle White Paper - Oracle | Integrated Cloud ... · An Oracle White Paper March 2014 Oracle Hyperion Financial Data Quality Management, Enterprise Edition Performance Benchmarks