Post on 02-Dec-2014
Oracle® Hyperion Financial
Management 11.1.2.1
Performance Report
Hyperion Financial Management 11.1.2.1 Performance Report Page 2
Oracle® Hyperion Financial Management 11.1.2.1
Performance Report
TABLE OF CONTENTS Executive Overview ......................................................................................................... 4
Introduction ........................................................................................................................ 4
Test Configuration ........................................................................................................... 5
Hardware Setup ........................................................................................................... 5
Tuning .............................................................................................................................. 6
HFM Application Servers .................................................................................... 6
HFM Web Server .................................................................................................... 6
Test Scenario ................................................................................................................. 6
HFM Application Details ..................................................................................... 7
LoadRunner Scripts .............................................................................................. 8
Results ................................................................................................................................... 8
Non-Consolidation Tests .......................................................................................... 8
Response Time vs. Load ...................................................................................... 8
Resource Usage vs. Load .................................................................................. 14
Consolidation Tests ................................................................................................. 18
Response Times ................................................................................................... 18
Resource Usage .................................................................................................... 19
Conclusion ........................................................................................................................ 21
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Hyperion Financial Management 11.1.2.1 Performance Report Page 4
Oracle® Hyperion Financial Management 11.1.2 Performance Report
EXECUTIVE OVERVIEW This document summarizes performance testing carried out for Oracle® Hyperion Financial
Management, a component of Oracle’s Enterprise Performance Management (EPM) System. These
tests used EPM version 11.1.2.1 running on Windows 2003 servers. They demonstrated the ability
of the software to support 1000 users and dozens of concurrent consolidations on a basic
configuration, as well as the ability to scale to even larger user loads.
INTRODUCTION Oracle Hyperion Financial Management is a financial consolidation and reporting application built
with advanced Web technology, but used and maintained by the finance team. It provides financial
managers the ability to rapidly close and report financial results, meet global regulatory
requirements, reduce the cost of compliance and deliver confidence in the numbers. With Oracle
Hyperion Financial Management—one of Oracle’s enterprise performance management
applications—you can improve your closing and reporting process and reduce internal control
risks. Financial managers move from the role of scorekeeper to one of business partner—
delivering financial analysis that supports strategic and operational management decisions. With
purpose-built features, Oracle Hyperion Financial Management is the cornerstone of sustainable
compliance frameworks and helps businesses comply with stringent reporting regulations.
Performance testing and capacity planning for enterprise applications such as Oracle Hyperion
Financial Management is a complex task. To demonstrate Hyperion Financial Management’s ability
to support large user populations while delivering quick response times, Oracle completed testing
of a scaled out system. The results of these tests prove the scalability of Financial Management and
also provide data which can be used for preliminary sizing estimates. This paper focuses on the
performance testing of Hyperion Financial Management only. Tuning of database and web servers
is out of the scope of this paper.
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TEST CONFIGURATION
HARDWARE SETUP The configuration used for Financial Management consisted of seven servers as described below.
Server Processor Cores Memory Function
Workspace AMD Opteron 280 - Dual dual-core
at 2.41 GHz 4 cores 3.83 GB
Workspace,
Foundation
Services
HFM Web AMD Opteron 280 - Dual dual-core
at 2.41 GHz 4 cores 3.83 GB HFM Web Server
HFM App 1
HFM App 2
HFM App 3
Intel Xeon E5345 - Dual Quad –
core at 2.33 GHz
8 cores
each
12 GB
each
HFM Application
Servers
DB Server AMD Opteron 880 - Quad dual-
core at 2.40 GHz 8 cores 7.83 GB Oracle 10g RDBMS
Figure 1
Hardware Configuration
HFM App Server 1
8 cores x 2.33 GHz, 12 GB RAM
HFM App Server 2
8 cores x 2.33 GHz, 12 GB RAM
HFM App Server 3
8 cores x 2.33 GHz, 12 GB RAM
Workspace, HSS
4 cores x 2.41 GHz, 3.8 GB RAM
HFM Web Server
4 cores x 2.41 GHz, 3.8 GB RAM
`
LoadRunner
Controller/Agent
Database Server
8 cores x 2.40 GHz, 7.8 GB RAM
LDAP Server
2 cores x 2.79 GHz, 4 GB RAM
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The Oracle HTTP Server was installed on the Workspace server along with the Workspace Web
Application, Workspace Services and Foundation Services. The HFM Web Application was installed
on a separate, dedicated server. The HFM Application Server ran on three different boxes. A sixth
server hosted the Sun One Directory Server. The Oracle database ran on the seventh server. The
HFM Application Servers ran as 64-bit processes; all other components ran as 32-bit processes.
TUNING The following tuning adjustments were made to the system prior to running the tests described in
this paper.
HFM APPLICATION SERVERS HFM UI Configuration settings:
Number of Pooled DB Connections = 200
Registry Settings
MaxDataCacheSizeInMB – 4,000
MaxNumDataRecordsInRAM – 30,000,000
NumConsolidationThreads – 8
HFM WEB SERVER IIS
HfmAppPool Properties – No limits (i.e. boxes UNchecked) for:
Recycle worker processes (in Minutes)
Recycle worker processes (number of requests)
Maximum virtual memory (in Megabytes)
Maximum used memory (in Megabytes)
ASP
AspProcessorThreadMax="50"
TEST SCENARIO Client loads for the Financial Management testing were simulated using LoadRunner 9.5.
LoadRunner allows users to record browser actions into a file that can then be edited to add think
time, transaction definitions and parameters for substitution with random values. LoadRunner
records not only the HTTP requests made by the client, but also the data sent to the server. This
ability to record the network traffic is a requirement for testing Financial Management. Using
LoadRunner, Oracle developed a test scenario that included a list of host computers for clients, the
names of the test scripts and the number of simulated users running each script. The test scripts
were then run repeatedly for each simulated user until the defined test schedule terminated them.
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The nature of consolidation transactions makes them resource-intensive and also causes them to
lock data for updating. This can have an impact on the performance of other activities if the servers
are overloaded or consolidations have locked data needed by other users. In order to more
accurately measure response times and resource usage for non-consolidation activities, separate
tests were run without any consolidation activities running concurrently. Additional tests were
then run purely with consolidations to measure resource requirements for those.
HFM APPLICATION DETAILS The Hyperion Financial Management application used for these tests is an actual application in use
by a large, global financial company. Several of the consolidations used in testing are quite large.
Table 1 lists the number of members in each of the application dimensions.
Table 1
Application Statistics
Dimension Number of Members
Scenario 18
Entities 2862
Account 31854
Value 18
Year 14
Period 4
Currencies 66
C1 1160
C2 68
C3 2
C4 63
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LOADRUNNER SCRIPTS Eleven different LoadRunner scripts were prepared and user distributions were assigned as listed
in Table 2. Unique usernames were used for the virtual users and each was provisioned as a
typical user with a unique POV.
Table 2
LoadRunner Scripts and User Distribution – Non-consolidation
RESULTS
NON-CONSOLIDATION TESTS The first set of tests conducted focused on non-consolidation activities. Three tests were run, with
a single HFM Application Server, two HFM Application Servers and then with three HFM
Application Servers. The results of these tests showed that each HFM Application Server could
handle 300-350 users before response times exceeded acceptable limits.
RESPONSE TIME VS. LOAD Response times were measured using LoadRunner. LoadRunner replays communication from the
client to the server and measures the response time for the response to each communication. It
does not measure the amount of time needed for any client-side processing after the response is
received. This is acceptable for load and scalability testing since the focus is on how load affects
the server processes.
Activity % User
Distribution User Load
1 App Server User Load
2 App Servers User Load
3 App Servers
Load data file 0.5% 2 3 5
Load data Retrieve - Smart view 2.3% 12 17 23
JNL Entry/Posting and un posting 2.3% 12 17 23
WDEF - Enter data/save and Calculate 46.5% 233 352 465
Data Grid - Enter/Submit Data, Calculate 23.3% 116 174 233
Process Management - Force Calculate 2.3% 12 17 23
Process Management - Promote 3.5% 17 26 35
Run Journal report 2.3% 12 17 23
Run ICP report 0.7% 3 5 7
Run Retrieves - Smart View 11.6% 58 87 116
Hyperion Reports 4.7% 23 35 47
Total Users 100% 500 750 1,000
Hyperion Financial Management 11.1.2.1 Performance Report Page 9
Figure 2 below shows the average logon times from each of the three non-consolidation tests (1, 2
and 3 HFM Application Servers). The Logon requests are handled primarily by the Workspace and
Foundation Services. These processes were not a bottleneck in the tests so response times were
fast and stable throughout all three tests.
Figure 2
Workspace Logon Response Times
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In Figure 3 we see that after an initial, brief warm-up period open application times gradually
increased with load. Here we can see the improvement in response times and capacity when
additional HFM Application servers are added. Each server could was able to handle 350 users
while keeping the average response time at or below 7 seconds.
Figure 3
Open Application Response Times
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Figure 4 shows the response times for opening Web Data Entry Forms. Again we clearly see that
the addition of HFM Application Servers increases the load the system can handle while
maintaining sub-second response times. Figures 5 and 6 are similar charts for displaying ICP
Reports and Journal Reports. The initially higher response times for displaying Journal reports
with 3 HFM Application Servers are due to loading of new data that had not previously been
brought into memory. Once the data were loaded the response times were much faster.
Figure 4
Open Web Form Response Times
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Figure 5
Display ICP Reports Response Times
Figure 6
Display Journal Reports Response Times
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A variety of different POV selections were made by the different users. Response times for setting
the POV based on the Year dimension is shown in Figure 7.
Figure 7
Set Year POV Response Times
Journals transactions such as opening, processing, closing, submitting, approving and deleting
followed the same trends in response times as the majority of transactions in these tests. Figure 8
shows the response times for posting Journals with 1, 2 and 3 Application Servers.
Figure 8
Journal Posting Response Times
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RESOURCE USAGE VS. LOAD
CPU The busiest boxes were those running the HFM Application Servers. In the later stages of the tests
those servers were 50-70% busy with the HFM Application Servers using 5-6 of 8 CPU cores. The
CPU load was similar on the 3 Application Servers, but as expected due to the variable nature of
HFM requests it was not perfectly even. The HFM Web Server host averaged about 50-70% busy
(2-3 of 4 CPU cores) with the larger user loads. The Oracle RDBMS server occasionally spiked near
20-25% busy (2 of 8 CPU cores), coincident with increases in user load, but was otherwise about
10% busy. These are illustrated in Figures 9 and 10 below.
Figure 9
HFM Application Server CPU Usage
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Figure 10
HFM Web. Workspace and DB Server CPU Usage
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Memory HFM Application Server memory usage, both physical and virtual memory, is shown in Figure 11
for each of the 3 HFM HsvDataSource processes. Memory growth was minimal and evenly
distributed between the servers as load increased. A sudden jump in memory usage was observed
at 23:40 for one of the HFM Application Servers. This indicates that there was higher than average
concurrency at that point in time (due to random think times) or new data was accessed by the
server.
Figure 11
HFM Application Server Memory Usage
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Figure 12 shows the physical and virtual memory usage for the HFM Web, Workspace (Foundation
Services) and DB Server. The HFM web server memory grew slightly as load increased but
physical memory usage remained well below 1 GB. All other memory trends were generally flat.
Figure 12
HFM Web. Workspace and DB Server CPU Usage
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CONSOLIDATION TESTS A key function of Hyperion Financial Management is consolidations. We chose to run up to 15
concurrent consolidations on each of the 3 configurations (1, 2 and 3 HFM Application Servers).
The consolidations were run on 15 different years that each contained a copy of the same data and
rules. Therefore all 15 consolidations performed the same amount of work and had no overlapping
data. The consolidations were run as “All with Data”, an intensive consolidation.
RESPONSE TIMES The chart in Figure 13 shows the average execution times for each consolidation test. The three
different lines correspond to the three configurations. This shows that adding a second and third
HFM Application Server to the configuration noticeably improved response times. Adding a second
HFM Application Server increased capacity by 100% compared to the single HFM Application
Server configuration, while adding a third HFM Application Server added only 50% more capacity
compared to the two HFM Application Server configuration. As a result the reduction in response
times was greater going from 1 to 2 HFM Application Servers than it was going from 2 to 3 HFM
Application Servers. A single consolidation was run only with the 1 HFM Application Server
configuration since additional HFM Application Servers would have no effect on a single
consolidation. But the response time of a single consolidation provides a baseline for the other
tests, showing the minimum response time for this consolidation.
Figure 13
Consolidation Response Times
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RESOURCE USAGE
CPU CPU usage during consolidations is almost entirely on the HFM Application Servers. Figure 14
shows the server CPU usage for all servers in the 15 consolidation, 3 HFM Application Server test.
Since all 15 consolidations performed the same amount of work, the load was very evenly
distributed between the 3 HFM Application Servers. Aside from a spike at the beginning when the
consolidations were submitted, the HFM web server used virtually no CPU. The Shared Services
server was very lightly loaded and the DB server was about 10-15% busy at the peak.
Figure 14
Server CPU Usage – 15 Consolidations – Three Application Servers
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Memory Memory usage during the 15 consolidation, 3 Application Server test is shown in Figures 15 and 16.
Figure 15 focuses on the HFM Application Servers and shows very similar memory usage for all 3
HFM Application Servers. The software clearly benefited from running as a 64-bit process by
utilizing more than 2 GB of virtual memory per process to handle the large amount of data involved
with 15 consolidations. Memory usage for the HFM Web Server, OHS and the Shared Services was
much lighter and is depicted in Figure 16.
Figure 15
HFM Application Server Memory Usage – 15 Consolidations – Three Application Server
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Figure 16
HFM Web, OHS, Shared Services Memory – 15 Consolidations – Three Application Servers
CONCLUSION The data presented here show the scalability and performance of Oracle’s Hyperion Financial
Management software. Using a very large customer application and a scenario of ramping up
mixed activity user load at regular intervals, a system with a single HFM Web Server and 3 HFM
Application Servers was able to support 1000 non-consolidation users. On average each HFM
Application Server handled up to 300-350 non-consolidation users with little or no increase in
response times. The maximum user load was limited by available CPU on the HFM Application
Server hosts. Adding more Application Servers on additional machines would further increase the
capacity of the system. As in these tests, systems with large concurrent user loads and/or data
volumes will benefit from running HFM as a 64-bit application on a 64-bit operating system.
Memory could be a limiting factor on 32-bit systems.
Consolidation tests also showed excellent scalability as HFM Application Servers were added to the
system. Response times for concurrent consolidations improved significantly with more HFM
Application Servers. Very little overhead was noticed for multiple HFM Application Servers as 3
Hyperion Financial Management 11.1.2.1 Performance Report Page 22
HFM Application Servers handled 3 identical consolidations nearly as fast as a single consolidation
on a single HFM Application Server.
Many of the factors affecting capacity and performance are heavily dependent on the actual usage
of an environment and the design of the HFM applications. The application used in these tests was
above average in size and complexity. Smaller applications will require fewer resources and will
have less contention when consolidations are run. The only way to adequately predict
performance and capacity of a specific system is to perform load tests on that environment with
the applications and use cases that actual users will follow.
For information on tuning Hyperion Financial Management systems please see Hyperion Financial
Management (HFM) Performance Tuning Guide, Fusion Edition.
Hyperion Financial Management 11.1.2.1 Performance Report
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