FDMEE Sizing Guide Final

Oracle Hyperion Financial Data Quality Management, Enterprise Edition Sizing Guide – Performance Report ORACLE WHITE PAPER | JUNE 2015

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ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION - SIZING GUIDE

Table of Contents Disclaimer

1

Introduction

2

User Load, Monitoring and Tuning Environment Variables

3

User Load

3

Monitor

3

Tuning Environment Variables

4

Test Hardware Configuration Specifications Configuration Tuning

5 5

Tuned Settings for Test Configuration

5

Default Settings

6

Test scenarios

6

FDMEE Test Data Details

7

Results

8

Single User Test Results Multi-User Test Results

8 11

Clustering – Load Balancing

12

Database Sizing

12

Conclusion

12

Reference documents

13

1 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION - SIZING GUIDE

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 document provides some general guidance for sizing an FDMEE environment. It includes guidance on resource usage, (CPU utilization, Heap memory), expected response times and where to get more information on monitoring and tuning your system. A properly sized and tuned environment ensures a consistent experience for all your systems users. Tuning and optimization of other applications and databases is not covered under the scope of this paper. Consider three factors when analyzing the capacity of your current environment to ensure it meets your business requirements. Assessing both peak and off peak user load, monitoring the environment and tuning environment variables after monitoring. » User Load - Evaluating peak and off-peak user loads can help to create a properly sized environment. » Monitor - Monitor the environment to determine if adjustments are necessary. » Tuning environment Variables - Default values for the environment variables may need to be adjusted for your specific user load.

Estimating for user load, monitoring the system and adjusting tuning variables are the keys to a successful implementation. This document offers guidance on all three factors, and provides examples of what you can expect. It helps you plan for your initial installation and suggests when to make necessary adjustments to the resources supporting your installation for the future. Due to variations in system usage and volumes of data, your results may be different than what is described here.

Users of this guide should be familiar with Oracle Hyperion Financial Data Quality Management Enterprise Edition, database administration, and general operating system concepts.

Always make sure the latest patches have been applied to all the servers in your configuration.

2 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

User Load, Monitoring and Tuning Environment Variables User Load User load refers to the maximum number of users executing activities on the system at any given time. Concurrency refers to the number of users that are executing activities simultaneously. User activities can be broken down into two main categories; database read activities, for example running reports, and database write activities, for example Loading Data.

TABLE 1 – USER LOAD PLANNING Total overall system users ______________

User Activity

% Concurrency

% Users during peak

Read (examples: reports, drillthrough)

(example: 25%)

(example: 50%)

Write (examples: create rules, import mappings, load data)

(example: 25%)

(example: 50%)

Use this table to help with user load planning. % Concurrency ratio is the quantity of Read/Write users to the total number of Read/Write users executing an activity simultaneously. % Users during peak ratio is the quantity of Read/Write users to the total number of Read/Write users executing activities during peak times of the year.

Your goal should be to have your configuration operating about 75-85% capacity. The reason is that an overloaded system does not operate efficiently. If your environment operates consistently at above 85% CPU or memory capacity, consider whether your hardware or virtual images can support peak loads and future growth. Some questions to consider when sizing a system: 1. How long does my system operate at peak load, One week per month? One week per quarter? 2. Are there periods where there is significantly more write versus read activities?

Monitor Monitoring the environment during peak and off peak periods will provide you a greater understanding of your current usage capacity, and helps you anticipate and plan for future capacity requirements. Several tools are available to assist you in this activity.

» Oracle Enterprise Manager Fusion Middleware Control This tool allows you to manage, monitor and diagnose graphically the condition and status of your environment, in real time, while the system is up and running. Enterprise Manager contains live statistics some of which are: % CPU utilization, heap memory and datasources. For more information on using Oracle Enterprise Manager Fusion Middleware Control see: http://docs.oracle.com/cd/E11857_01/index.htm

» Windows Performance Monitor The recommended tool to monitor Windows performance is “Microsoft Windows Performance Monitor.” This tool allows you to set up a collection of data over time. You can collect many Windows metrics, among the most useful are % CPU utilization and Private Bytes.

» Linux Performance Monitor For Linux there are many options for gathering system statistics, some of which include dstat, vmstat and iostat.

3 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

Tuning Environment Variables Many variables determine the performance of an FDMEE configuration. They can be monitored easily and to correct many performance problems. The variables include: » CPU utilization (requires physical hardware upgrade) » Available RAM (requires physical hardware upgrade)

» Heap size » Datasources » Database tuning » Number of concurrent users » Frequency of specific user activities » Import format, Data Load Mapping and script complexity

Database read activities are less resource intensive, if you find your Data Management process includes more read activities then monitor CPU, heap and datasources. Then make adjustments to the following. » Heap size » WebLogic – Datasources

Database write activities are more resource intensive; if you find your Data Management process includes more write activities, then monitor the above statistics as well as database statistics. Then assess whether any of the following parameters requires adjustment. » Heap size » WebLogic – Datasources » FDMEE - Batch size » ODI » Array Fetch Size » Batch Update Size » Number of Sessions » Oracle Database » Sessions » Processes

For instructions on how to change the above parameters in the Oracle Hyperion Financial Data Quality Management, Enterprise Edition (FDMEE) – Tuning Guidelines document see:

http://www.oracle.com/technetwork/middleware/bi-foundation/fdmee-tuning-1112x-2349440.pdf

4 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

Test Hardware Configuration Specifications The test hardware configuration consisted of four physical servers with Windows Server 2008 R2 Enterprise Edition, hosting a single FDMEE server and ODI agent. All machines have 64-bit processors. Hyperthreading was enabled on all the machines doubling the number of virtual CPUs (vCPUs) as physical cores. TABLE 2 – TEST HARDWARE SPECIFICATIONS

Server

Processor

Memory

Function

Foundation Services

Intel Xeon X5670

72 GB*

Workspace, Foundation Services, Weblogic Admin Server

144 GB*

FDMEE Web Server, ODI

144 GB*

HFM, Planning, Essbase Server

256 GB*

Oracle 11g R2 RDBMS

12 cores (24 vCPUs) @2.93 GHz FDMEE Web Server

Intel Xeon X5675 12 cores (24 vCPUs) @3.07 GHz

HFM, Planning, Essbase Server

Intel Xeon X5675

DB Server

Intel Xeon E5-2690

12 cores (24 vCPUs) @3.07 Ghz

16 cores (32 vCPUs) @2.9 GHz

* While these servers have large memory and CPU capacities, the results of the tests show only a small portion of this was required to run successfully.

Configuration Tuning EPM version 11.1.2.4 was used for testing. In some cases it may be necessary to alter the default settings for your environment, to meet the needs based on user volume and hardware specifications. The following changes were made to the tuning settings in the test configuration: Tuned Settings for Test Configuration FDMEE Server » Batch Size - 30000 » Batch Timeout in Minutes - 30 ODI Server » OracleDIAgent - Maximum number of sessions - 1000 » Data Server – Array Fetch Size – 30000 » Data Server – Batch Update Size - 30000 WebLogic » Aif_datasources - 1500 » Odimasterrepository - 500 Registry Heap » -Xms= 6144m, -Xmx = 6144m Oracle DB » Processes - 2000 » Sessions – 3040 » Open Cursors - 5000

5 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

Default Settings FDMEE Server » Batch Size - 1000 » Batch Timeout in Minutes - 30 ODI Server » OracleDIAgent – Maximum number of sessions - 1000 » Data Server – Array Fetch Size – 30 » Data Server – Batch Update Size - 30 WebLogic » Aif_datasources - 100 » Odimasterrepository - 50 Registry Heap » -Xms= 4096, -Xmx= 4096

Test scenarios Single User Volume File Load: » Various sample file sizes were loaded from a single user, using the Data Load Rule option from the Workflow Tasks Menu: 6KB, 20KB, 50KB, 100KB, 500KB, 1,000KB, 2,000KB » User Trial Balance Report for current location with rules, Create PDF, Offline –generating 748 pages. » Loading 1, 3, 6 and 12 months of data from Oracle EBS Ledger. Single user tests were manually executed from a Windows 7 Professional client machine with Microsoft Internet Explorer 9.

Multi-User User File Load: » Various user loads 5, 10, 20 and 50 users importing a 6KB file from the Data Load Rule option on the Workflow Tasks Menu. Client loads for the multi-user tests were simulated using Oracle’s load testing tool, Oracle Application Testing Suite (OATS). Two components of OATS were employed. Open Script allows users to record user actions (HTTP requests) to simulate virtual users accessing the application simultaneously. It also allows for parameter substitutions. The Oracle Load Test component creates a simulation of multiple users, or a scenario, where you can manipulate a variety of parameters such as think time and user ramp up rate. Oracle Application Testing Suite is an effective way to baseline the performance of an initial configuration, and then using that baseline as a comparison as the configuration/system matures.

For more information on Oracle Application Testing Suite, see: http://www.oracle.com/technetwork/oem/apptest/etest-101273.html

Batch load and Data Load Workbench import tests were not performed during the multi-user testing. If users perform these activities the resource usage pattern will look different than the results presented here.

6 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

FDMEE Test Data Details Location: File type is Fixed, Target application is Oracle Hyperion Financial Management (HFM). Import Format: 14 mapping rows. Data Load Mapping for Location: 211 rows of account mappings using LIKE, BETWEEN and EXPLICIT. » 140 LIKE » 13 BETWEEN » 58 EXPLICIT Note about Data Load Mappings – No Multi-Dimension mappings were used in the test system. The number of mappings and the type of mappings can greatly affect your performance. The order of mapping resource intensity from lowest to highest is: Like, Between, Multi-Dimension, In and Explicit. The target Oracle Hyperion Financial Management (HFM) application contains: 1,352 Accounts, 1,219 Entities

TABLE 3 – VOLUME FILE LOAD, ROW COUNT

File Rows

TDATASEG Row Count After Load

File Size

6K

3,278

540 KB

20K

10,963

1,823 KB

50K

27,065

4,496 KB

100K

70,789

9,522 KB

500K

353,332

47,513 KB

1M

707,032

95,076 KB

2M

1,414,064

190,151 KB

This table contains the details of the files used to run the single user, for varying volume sizes. It also contains the row count from the TDATASEG table after the load is complete. Input files used were fixed width Trial Balance Reports.

The Oracle E-Business Suite (EBS) Financials source system is located in a data center separate from the test configuration.

7 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

Results Results of the tests described above include some sample response times and metrics for CPU utilization, memory and datasource connections.

Single User Test Results

TABLE 4 – TEST CONFIGURATION - SAMPLE RESOURCE USAGE – SINGLE USER

User Activity

aif_datasource connections used

odiMasterRepository connections used

Heap Memory used - MB

Load a 20k file, 1 period, replace method, Data Load Rule

3

3

500-700

Load a 500k file, 1 period, replace method, Data Load Rule

3

3

600-800

Load 20k file, 1 period, online, replace method, Data Load Workbench, import

5

3

500-600

Run Base Trial Balance report, producing 748 pages in PDF format, online

6

1

300-400

Run Base Trial Balance report, producing 748 pages in PDF format, offline

2

1

1,000-2,000

This table shows a datasource and heap memory usage for five sample user activities.

CPU Utilization for a single user activity will have a CPU spike, which in the test environment ranged from 40-50% of a single CPU. The spike on the FDMEE server ranges from 5-15 seconds in duration after which the CPU activity starts to rise on the database server. In the test environment, the CPU spike on the database server typically lasted for 10-15 seconds. The size and duration of the spike varies with the amount of data you are loading. Datasource utilization varies based on the user activity that is executing. You should note that any activities where the method selected is “online” require more datasource connections as noted above in the table.

TABLE 5 – TEST CONFIGURATION - SAMPLE RESPONSE TIMES – SINGLE USER

User Activity

Average Response Time, Sec.*

Load 20k file for one period, offline, using replace method through Data Load Workbench, import only

15

Run Base Trial Balance report, producing 105 pages in PDF format, online/offline

6

Run Base Trial Balance report, producing 748 pages in PDF format, online/offline

25

* Average response time is calculated by taking the average of 5 response times for this activity.

8 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

FIGURE 1 – TEST CONFIGURATION - SAMPLE RESPONSE TIMES – SINGLE USER – VARYING FILE SIZE

Response Time - Single User Import from File - Export to HFM 0:00 24:00 21:00

20:34

M 18:00 M 15:00 : 12:00 S 9:00 S

10:44 5:33

6:00 3:00

0:32

0:41

1:15

20k

50k

100k 500k File Row Size

0:00

1M

2M

Data Load Rule - Load file, 1 period, Replace, Import from source, Export to target This figure represents a single-user executing File Import through the Data Load rule.

Response times remain under 2 minutes for a file size of 100k rows or less. Factors that contribute to these response times are available heap memory set in the Window registry and Batch Size as set in FDMEE System Settings. FIGURE 2 – TEST CONFIGURATION - SAMPLE RESPONSE TIMES – SINGLE USER – DATA LOAD FROM EBS

Response Time - SingleUser Import data from Oracle EBS GL

M M : S S

0:24:00 0:22:00 0:20:00 0:18:00 0:16:00 0:14:00 0:12:00 0:10:00 0:08:00 0:06:00 0:04:00 0:02:00 0:00:00

0:22:57 0:19:45

0:09:01 0:03:57

121,519

374,978

730,864

1,404,753

Rows loaded to TDATASEG table The single-user test graph for data import from Oracle EBS GL shows sample times to load x number of rows. The bars correspond to loading 1, 3, 6 and 12 months of data to the test system HFM application.

9 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

These are sample approximations only, due to the Ledger system location outside of the network segment where the test EPM system was located. These response times depend heavily on tuning modifications made to the Array Fetch Size and Batch Update Size set within ODI. Each bar corresponds to loading 1, 3, 6 and 12 months of data from the EBS GL.

FIGURE 3 – TEST CONFIGURATION - SAMPLE CPU UTILIZATION – SINGLE USER – DATA LOAD FROM EBS

HyS9aifWeb - % Processor Time 12 month data load from EBS 70 60 50 40 30 20 10 0

HyS9aifWeb - % Processor Time

This figure shows the sample CPU utilization for the web application on the FDMEE test server for data import from Oracle EBS GL for 12 months. The first CPU peak was a single month load before the 12 month test was executed.

CPU utilization for the FDMEE server during a single user, 12- month data load (1,404,753 rows) from Oracle EBS ranged between 20-40% of a single CPU. The number of CPU spikes correlate to the number of periods chosen to load from the source system. Each spike in the test system lasted for approximately 5 seconds.

10 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

Multi-User Test Results TABLE 6 - TEST CONFIGURATION - SAMPLE RESOURCE USAGE – 5, 10, 20, 50 USERS

Load a 6k file for one period, using replace method through Data Load Rule, 5 iterations each user

User Activity

5 users

10 users

20 users

50 users

aif_datasource connections used

4-7

3-7

7-10

10-15

odiMasterRepository connections used

4-8

4-12

4-19

10-20

% CPU Utilization

20-75

40-175

50-200

200-400

Heap Memory used - MB

Reached a high of 4,586 MB

Reached a high of 5,257 MB

Reached a high of 4,730 MB

Reached a high of 5,500 MB

The multi-user test load table for File Import through the Data Load rule shows the resource utilization at varying levels of virtual users. Heap memory usage may not be incremental based on the number of users, and is dependent on garbage collection schemes. » Note- 100% CPU utilization = 1 CPU, 200% denotes 2 CPU’s etc.

FIGURE 4 – TEST CONFIGURATION - SAMPLE RESPONSE TIMES – MULTI-USER

Response Time - Multi-User Import 6K file, Export to HFM 0:03:43

0:04:00 0:03:30 M M : S S

0:03:00 0:02:30 0:02:00 0:01:14

0:01:30 0:01:00

0:00:29

0:00:30

0:00:28

0:00:30

0:00:00 MM:SS Data Load Rule - Load 6K file, 1 period, Replace, Import from source, Export to target 1 user

5 users

10 users

20 users

50 users

The multi-user test graph for File Import through the Data Load rule shows the response times under 2 minutes up to 20 users.

11 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

Clustering – Load Balancing Clustering a configuration is another way to scale and extend your configuration to improve performance. If your server has become CPU bound, adding another server to the configuration and creating another FDMEE web app may be the method of choice. You can use the same method if you are using virtual machines, and your existing VM cannot be extended. Clustered configurations distribute workloads among multiple identical cluster member instances. This effectively multiplies the amount of resources available to the distributed process, and provides for seamless scalability and fail over for high availability. In order to achieve your performance goals for the environment, creating multiple instances of the FDMEE web app and load balancing them may be all that is required. For more information on Clustering and Load Balancing see:

Oracle® Enterprise Performance Management System - Deployment Options Guide: http://docs.oracle.com/cd/E57185_01/epm.1112/epm_deployment_options.pdf

Database Sizing Determine database space requirements by the amount of data to pass through the FDMEE system. For example in the test system, the Oracle database TDATASEG table contained 8.6 million rows and the TDATAMAPSEG contained 386,000+ rows. This row count represents repeatedly importing data files with 1-2 million rows as well as moving 12 months of data from an external ledger system to one target application. The Oracle Database tablespace was allocated 32GB of space and 92% is currently used. The test system Oracle database is configured with Automatic Memory Management and FDMEE and ODI were configured with a tablespace separate from all other components in the configuration. The table size example shown here may vary greatly from your system based on the mappings, source and target systems in your environment. Consult your DBA to tune your database to meet your configuration requirements.

Conclusion The primary objective for FDMEE is to integrate and validate data from varying sources and move the data to target systems. Reading and writing large data sets requires sizing an environment properly to ensure all users of the system have a uniform performance experience. Based on the test configuration and the tests outlined above the test system comfortably sustains a user population of up to 50 users all executing modest size write and read activities. It is important to bear in mind that the data presented here is a sample from one configuration, whose environmental infrastructure, network, hardware, etc., may vary widely from yours. It should be used as a reference point to compare to your configuration experiences. The tests included files and source data that varied enough to cover small and large application usage for FDMEE. The best way to identify the specific requirements of your system is to perform a load test on the environment with use cases that reflect actual user flow. Included in this document are additional references to documentation that are available to assist you with your sizing task.

12 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

Reference documents Oracle Hyperion Financial Management (HFM) Performance Report » Oracle Support Document 1994672.1 (Hyperion Financial Management (HFM) 11.1.2.4 Performance Report) can be found at: https://mosemp.us.oracle.com/epmos/faces/DocumentDisplay?id=1994672.1 Oracle® Hyperion Financial Management, Fusion Edition – Performance Tuning Guide » The tuning guide can be found at: http://www.oracleimg.com/technetwork/middleware/financialmanagement/overview/hfmperformancetuning-1934817.pdf Oracle Profiler » Oracle Jrockit Mission Control provides profiling capabilities for processes using Jrockit JVM which can be found at: http://www.oracle.com/technetwork/middleware/jrockit/overview/missioncontrol-whitepaper-june08-1130357.pdf?ssSourceSiteId=ocomen Oracle Database Tuning » Consult your DBA for tuning. Oracle Database Online Documentation 11g Release 2 (11.2) which can be found at: https://docs.oracle.com/cd/E11882_01/server.112/e41573/toc.htm For other Oracle Documentation » Oracle Documentation Library (http://www.oracle.com/technology/documentation/epm.html) on Oracle® Technology Network for other performance tuning or configuration guides.

13 | ORACLE HYPERION FINANCIAL DATA QUALITY MANAGEMENT, ENTERPRISE EDITION – SIZING GUIDE

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