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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
Disclaimer
This document is for informational purposes only, and should not be used solely to base a purchasing decision. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing.
THIS DOCUMENT IS NOT PART OF A LICENSE AGREEMENT NOR CAN IT BE
INCORPORATED INTO ANY CONTRACTUAL AGREEMENT WITH ORACLE
CORPORATION OR ITS SUBSIDIARIES OR AFFILIATES.
Failure to adhere to these benchmarks does not constitute a breach of Oracle’s obligations.
We specifically disclaim any liability with respect to this document and no contractual
obligations are formed either directly or indirectly by this document. This document may not
be reproduced or transmitted in any form or by any means, electronic or mechanical, for any
purpose, without our prior written permission.
Oracle Hyperion Financial Data Quality Management, Enterprise Edition - Performance
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.
Oracle Hyperion Financial Data Quality Management, Enterprise Edition - Performance
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 –
Total of 12 physical cores - Hyper-
threaded (24)
3.07 GHz 144 GB Intel
Xeon
X5675
DB Server Oracle Database
Server- Enterprise
Edition 11g R2
2 processors with 8 cores each -
Total of 16 physical cores - Hyper-
threaded (32)
2.9 GHz 256 GB Intel
Xeon
E5-2690
Load Test
Server
Oracle Application
Testing Suite 12.2.0.1 -
Load testing tool
Dual Quad -core Proliant DL380 G5
(8)
2.33 GHz 12 GB Intel
Xeon
E5345
Oracle Hyperion Financial Data Quality Management, Enterprise Edition - Performance
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
Oracle Hyperion Financial Data Quality Management, Enterprise Edition - Performance
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
Oracle Hyperion Financial Data Quality Management, Enterprise Edition - Performance
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 - 20K file
File Import - 50K file
File Import - 100K file
File Import - 500K file
File Import - 1M file
Oracle Hyperion Financial Data Quality Management, Enterprise Edition - Performance
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
Oracle Hyperion Financial Data Quality Management, Enterprise Edition - Performance
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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