Oracle BI EE Architecture Deploymentv3

An Oracle White Paper May 2011

Oracle BI EE Architectural Deployment: Capacity Planning


Introduction ..................................................................................................................... 3 Oracle BI EE Components .............................................................................................. 4 Oracle BI EE Server Environment ................................................................................... 4 BI Sizing Assumptions .............................................................................................. 4 1) Small Size Oracle BI EE implementation .............................................................. 6 2) Medium Size Oracle BI EE implementation .......................................................... 6 3) Large Size Oracle BI EE implementation ............................................................. 8 Network Requirements .............................................................................................. 10 Clustering, Load Balancing, and Fail over in Oracle Business Intelligence ................... 10 Backup and Disaster Recovery .................................................................................. 10 Logical Partitioning, Virtualization & HW resources partitioning ................................. 11 Appendix A: Useful metrics to monitor .......................................................................... 12 Key BI Metrics......................................................................................................... 12 Operating System Server Resources Utilization Statistics...................................... 12 Network data........................................................................................................... 12 Database Server ..................................................................................................... 13 Web Servers and Application Server ...................................................................... 13 Appendix B: BI Sizing Spreadsheet .............................................................................. 15 11g Sizing Spreadsheet.......................................................................................... 15 Concurrent Users.................................................................................................... 15 Appendix C: Processing a Capacity Plan ...................................................................... 17 Locate and Resolve Over-Utilized Resources ........................................................ 17 Resolve High-Latency Transactions ....................................................................... 17 Address Under-Utilized Resources ......................................................................... 18 Final Analysis.......................................................................................................... 18 REFERENCE:......................................................................................................... 19

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Oracle BI EE Architectural Deployment: Capacity PlanningIntroductionThe objective of this paper is providing performance sizing information for Oracle Business Intelligence Enterprise Edition (OBIEE) 11g (11.1.1.5+). Business Intelligence (BI) Systems are usually complex and read intensive. Performance in a BI system is measured in a number of areas; the response time navigating from reports, to and from dashboards, and physical query response time. User-centric BI has moved information systems from the hands of developers into the hands of the masses making BI a mission critical system where reliability, availability and serviceability are the only consideration in capacity planning. In general there are two forms of capacity planning: Performance Sizing (Pre-configuration/Pre-Installation) Deployment (Post-configuration) Performance sizing or pre-configuration capacity planning, involves determining the hardware required to process a given workload. A reliable benchmark is used as the baseline for a given workload on a system. This produces performance statistics that display expected results of the workloads impact on a system on the same or similar hardware. Deployment capacity planning is a complex and ongoing performance study of hardware and software resource consumption on a deployed system. These studies are primarily established to provide capacity data to the system administrator, DBA, and other stakeholders about the utilization of the system. There are a number of factors that impacts performance in a BI system. Those areas include: Physical hardware Database Performance Network Database and BI model BI system configuration Application Server Performance Deployment architecture and topology

The performance test that BI sizing is based upon tries to represent a customer scenario where the user population is divided between administrative users and business users. The typical workload scenarios demonstrate 95% of business users viewing reports and navigating within dashboards. The remaining 5% of the concurrent users are categorized as administrative users or users performing application development. The mix of reports include varying business user roles utilizing a mix of dashboards, charts, tables, drill-downs, and pivot tables that return a number of rows (anywhere from 5-500) of aggregated data. Administrative users include users performing concurrent application development and ad-hoc reporting; i.e. navigating catalogs, creating new reports, modifying existing reports, and saving reports. Sizing will take into consideration the user population, concurrent users, users using formatted reports, and Scorecard. The primary purpose of this paper is to present the OBIEE 11g Sizing Spreadsheet from pre-installation capacity planning perspective. This paper will introduce topics that impacts performance with pointers to the BI documentation where more detailed information is available. Finally, the paper will provide

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architectural examples of small, medium, and large BI systems for the purpose of demonstrating how a BI System could be deployed.

Oracle BI EE ComponentsThe Oracle Business Intelligence components consist of: Oracle Business Intelligence Presentation Services o Ad-hoc query and reporting, highly interactive dashboards for accessing business intelligence and applications Oracle Business Intelligence Server o Common enterprise business model and abstraction layer Oracle Business Intelligence Publisher o Oracle Business Intelligence Publisher generates highly-formatted, pixel-perfect enterprise reports Oracle Business Intelligence Javahost o The Oracle Business Intelligence Javahost provides services to BI Presentation Services for Charts, Gauges and PDFs. Fusion Middleware Control o Fusion Middleware Control is the browser-based management tool used to manage, monitoring, and configure Oracle Business Intelligence components

Oracle BI EE Server EnvironmentHardware resources have an impact on the overall deployment and performance optimization and sizing of the Oracle BI EE environment. The following section discusses some of the key HW characteristics that should be correctly measured and sized: CPU/Cores Hardware vendors are required to list the following in the category of Number of CPUs: Chips Cores Cores/Chip For example: 1 Intel Xeon E5620, Quad-Core, 2.40 GHz configured as part of the Sun X2270 M2. A core is the equivalent to a CPU. Modern Server processors include 1 CPU that may include 2 or more cores. Multithreading Processors also have the ability to run multiple threads per core which results in performance gains. Clock Speed More powerful and modern CPUs support higher workloads. This correlates to the amount of memory in a system which increases the amount of memory linearly. As an example a machine with 2CPUs/4Core @ 2.8GHz and 16GB RAM would provide higher capacity and utilization that a dual processor system.BI Sizing Assumptions

This section contains BI Sizing assumptions to consider when using data based on the BI Sizing Spreadsheet. See Appendix B The Small, Medium, and Large Architectures are also based on this information.

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The users that place a load the OBIEE system are those who are actually performing processing. These users are termed concurrent users. The number of concurrent users is based on the total named user population and determining a percentage of concurrent users: Total named users This is the complete user population that will be utilizing the targeted hardware

Concurrent users This is the maximum percent of users in the total user population that will be active at any one time We do not calculate active users or users logged into the system not actively demanding system resources.

Deploying SSL will have a level of overhead on the overall performance Formatting of reports has overhead on the system verse executing HTML based reports only (i.e. Dashboards) In the case of single core chips, the recommendation is to deploy a minimum of 2 CPU's given the contention of all the OBI EE processes. For modern multi-core chips one CPU can be recommend, however, 1CPU should NOT be recommended for single-core chips Note: Multi-Core CPUs are replacing single and dual core CPUs in Server applications making the availability of those processors rare in newer Servers.

The hardware assumptions are based on capacity of the Oracle BI EE components only and NOT the database. Recommended sizing for Essbase can be found in Chapter 4 of the following documentation: http://download.oracle.com/docs/cd/E17236_01/epm.1112/epm_install_start_here_11121.pdf Upgrading the hardware of the Oracle BI EE environment will not necessarily make queries run faster. Good query performance generally assumes good DB design and/or aggregation strategies. Scaling scenarios are performed against a chipset verses the operating system environment. As an example for an Intel P4 we size similarly for both Windows and Linux. This sizing data represents Windows and Linux.

User concurrency varies over the lifecycle of the deployment and is impacted by many factors. As a BI environment becomes more mature the system can grow from being low named users with a high percentage of concurrent users to higher named users and lower concurrency yet demanding more hardware capacity. Initial sizing helps in determining what is required and how to process demand over time. To determine the BI capacity requirements, collect the following information: BI users (Reporting, Dashboards, etc) The number of BI users you expect to have, and when you expect them to use OBIEE.

Infrastructure, and Architecture complexity (SSL, BIP, etc) Assess the complexity of the processing that users will demand of BI and the design of the architecture and infrastructure.

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Capacity planning is an ongoing process. After deploying and implementing OBIEE the systems needs to be monitored to ensure the performance expectations are met.It is worth noting that sizing guidelines for the small, medium, and large implementation are for OBIEE components only and not for typical implementation which could include BI Applications or other Oracle technology.

1) Small Size Oracle BI EE implementation

The estimated hardware for a small sized Oracle Business Intelligence Suite Enterprise Edition implementation can be utilized for a wide range of concurrent users. For a typical implementation the estimated HW specifications required to support 100-200 total and 10-20 concurrent users could technically meet the needs required to support < 3000 total users at 10% concurrency resulting in < 300 concurrent users. A small sized system can be characterized as: x86 CPU 2-4 Cores with the recommended 2GB of RAM per Core < 1200 Concurrent Users

Figure 1: Example HW System Specs Description 1. Database Server: (Oracle 11g/IBM DB2/Microsoft SQL Server/Teradata database servers) 2. Oracle BI Server OS (ex: Oracle Enterprise Linux 5.5) a. Oracle BI Server b. Oracle BI Presentation Server c. Oracle BI Publisher d. Oracle WebLogic Server 3. Web Server (Oracle HTTP Server) 4. Identity Management Access Management Server

2) Medium Size Oracle BI EE implementation

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Due to the scalability and performant nature of OBIEE a medium sized implementation covers a wide range and overlaps with the small sized system and large sized systems in regards to the kind of hardware that can be used to accomplish the business need. While the HW specifications for a typical medium sized OBIEE implementation can support 1000-5000 total and 100-500 concurrent users, hardware sizing for medium sized implementations are characterized as systems between 1200 and 5000 concurrent users: x86 CPU 4-16 Cores with the recommended 2GB of RAM per Core 1200 5000 Concurrent Users BI Suites Components Example HW System Specs Description

Figure 2: Medium Configuration displaying clustered BI Server components

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1. Database Server: (Oracle 11g/IBM DB2/Microsoft SQL Server/Teradata database servers)- In a medium sized implementation database clustering and scalability is expected 2. Oracle BI Server OS (ex: Oracle Enterprise Linux 5.5) a. Oracle BI Server (OBIS+n) b. Oracle BI Presentation Server (OBIPS+n) c. Oracle BI Publisher d. Oracle WebLogic Server (WLS+n) 3. Web Server (Oracle HTTP Server + Load Balancer) 4. Identity Management Access Management Server

3) Large Size Oracle BI EE implementation

A large number of concurrent users can be deployed on the typical large sized Oracle BI EE system. The estimated HW for a large sized Oracle Business Intelligence Suite Enterprise Edition that is capable of supporting 50,000 or more total and 5000 or more concurrent users are as follows: x86 CPU 16+ Cores with the recommended 2GB of RAM per Core 5000+ Concurrent Users BI Suites Components

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Example HW System Specs Description

Figure 3: Example of Large implementation 1. Database Server: (Oracle 11g/IBM DB2/Microsoft SQL Server/Teradata database servers)- In a medium sized implementation database clustering and scalability is expected 2. Oracle BI Server OS (ex: Oracle Enterprise Linux 5.5) the overall BI implementation should be deployed in a highly available configuration. For a large configuration OBIEE is implemented into an environment where maximum availability architecture (MAA) best practices are in place. a. Oracle BI Server (OBIS+n) b. Oracle BI Presentation Server (OBIPS+n) c. Oracle BI Publisher d. Oracle WebLogic Server (WLS+n) 3. Web Server (Oracle HTTP Server + Load Balancer) 4. Identity Management Access Management Server9


Network RequirementsIt is recommended to deploy the BI servers on a dedicated subnet using > 100 MBPS (1Gbit if possible) to reduce latency between each server. 11g HTTP Response Size with Compression (KB)

Pages Dashboard with 3 Tables and 3 Charts

HTTP Response Size (Kbytes)

Compression ratio (%)

(each table has 5~10rows, 3~5 cols) Dashboard with 1 Table (25rows , 10 columns) Dashboard with 1 Large Table (300rows , 10 columns)

297.5 210

39 28.5

86 86

938

79

91

For the compression mentioned above the compression/decompression occurs between the client browser and HTTP server (usually Oracle HTTP Server (based on Apache 2.2)). The compression is performed by Apache 2.2 which has a compression module. Compression has minimal impact on the CPU of the HTTP server.

Clustering, Load Balancing, and Fail over in Oracle Business IntelligenceThis document does not cover methods used to attain and maintain a required capacity, utilization, and availability. In-depth documentation for Clustering and High Availability can be found in the following documents: Configuring Business Intelligence for High Availability: http://download.oracle.com/docs/cd/E21764_01/core.1111/e10106/bi.htm#sthref2545 http://download.oracle.com/docs/cd/E21764_01/bi.1111/e10541/highavail.htm#BABIFFCA Scaling Your Deployment: http://download.oracle.com/docs/cd/E21764_01/bi.1111/e10541/cluster.htm#BGBHFCJF Enterprise Deployment Guide for Oracle BI http://download.oracle.com/docs/cd/E21764_01/doc.1111/e15722/toc.htm Load Balancing HTTP Server http://download.oracle.com/docs/cd/E15523_01/core.1111/e12036/install.htm#CBHDDEFJ

Backup and Disaster RecoveryDatabase Data and Application Data10


Backup and Recovery of OBIEE Application data will include configuration data, Metadata repository, Web Catalog and other Application Configuration files. See: http://download.oracle.com/docs/cd/E21764_01/core.1111/e10105/br_intro.htm#CHDJBDDE

Logical Partitioning, Virtualization & HW resources partitioninghttp://www.oracle.com/us/technologies/virtualization/index.html

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Appendix A: Useful metrics to monitorThe OBIEE documentation contains key metrics and information about monitoring the BI performance and health: http://download.oracle.com/docs/cd/E21764_01/bi.1111/e10541/querycaching.htm#CHDEJBBEKey BI Metrics

o o o o o o o o o o

Request Processing Time (ms) SOA Request Processing Time (ms) Average Query Time (seconds) Active Sessions Requests (per minute) SOA Requests (per minute) Presentation Server Requests (per second) Server Queries (per second) Failed Queries Errors Reported (in the last hour)

Operating System Server Resources Utilization Statistics

o o

o o o

o

% Privileged Time The percentage of time the operating system was busy CPU data % Processor Time The percentage of time the processor was busy Available memory in Bytes The amount of free space in memory Memory data Page Faults per sec The number of page fault per sec. (Page faults are normal system occurrences that used to retrieve data from the disk. If the system needs certain code page and it is in memory, a logical I/O occurs. The data is read from the memory the transaction that needs data is processed. If the code page or data page is not in the memory, the system performs a physical I/O to read the needed page from the disk. This is accomplished through page faulting.) Pages/sec The number of actual pages being moved from disk to memory or back to disk. Only data pages are written back to disk when they are modified Code pages do not get modified

Network data

o o o

o

Current Network bandwidth The current size of the line e.g. 10 Mbps or Gbit User Activity Server Sessions The number of user sessions currently going on within the server Bytes Received/sec The number of bytes received by this system per second, averaged over the interval period Bytes Sent/sec The number of bytes sent by this system per second, averaged over time interval12


o

Bytes Total/sec The total number of bytes sent and received by this system per second, averaged over time interval. It comprises of the sum of Bytes Received/sec and Bytes Sent/sec

Database Server

Disk I/O data o % Disk Read Time The percentage of time that the disk was busy performing a read function o % Disk Write Time The percentage of time that the disk was busy performing a write function o % Disk Time The percentage of time that the disk was busy performing read or write functions o Avg. Disk Queue Length The actual disk queue for read and write operations o Disk sec/Read The average time (in milliseconds) a read operation takes. This time is important because prolonged read and write operation indicate an over utilized disk o Disk sec/Write The average time (in milliseconds) a write operation takes. This time is important because prolonged read and write operation indicate an over utilized disk Database Data o Buffer Cache Hit Ratio The percentage of time that a record was found in cache o Database User Connections The number of users connected to this database o Query/sec The number of transactions started for the database o Percent Log Used The percentage of the log that is used

Web Servers and Application Server

Web Servers o Request Throughput throughput requests per second and response times in seconds per request o Current Connections The number of current connections to the Web server o Connection Attempts/sec shows the number of attempts to connect the Web server o Anonymous Users count of users that established a connection with the Web Server since service started o Total Accesses information on the total number of hits on the Apache HTTP Server o Total Traffic information about the total bytes sent and received by the Apache HTTP Server o CPU Load information about the total CPU time consumed by the Apache HTTP Server http://download.oracle.com/docs/cd/E17904_01/core.1111/e10108/http.htm Application Servers o % Processor Time The percentage of processor time o Elapsed Time The time, in seconds, that the process instance has been running o I/O Data Operations13


The number of read and write operations generated by the process instance Request Throughput throughput requests per second and response times in seconds per request o Server Response Time Average response times and request rates http://download.oracle.com/docs/cd/E12840_01/wls/docs103/perform/ o

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Appendix B: BI Sizing Spreadsheet11g Sizing Spreadsheet

The 11g Sizing Spreadsheet as described in the BI Sizing Assumptions section of this paper.

Figure 4

Concurrent Users

The following table is based on the spreadsheet in figure 4. It is based on the minimal requirements. The total named users is set, SSL is not selected, Scorecard analysis is not considered, and user concurrency is determined to be 10%. The result is the Estimated CPU/CORE required.

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Appendix C: Processing a Capacity PlanThis document does not intend to address actions to resolve production Capacity planning for OBIEE but it does present a generic roadmap: 1. Resolve over-utilized resources. 2. Address high-latency transitions. 3. Address under-utilized resources. 4. Present a final analysis.Locate and Resolve Over-Utilized Resources

In the capacity planning processing over capacity or under utilization can occur when determining the sizing between small to medium and medium to large configurations. In all scenarios the Oracle expert services team is recommended to provide in depth analysis. During the process some hardware resources can be recognized as over-utilized. Resource over utilization causes performance issues by placing unnecessary burdens on the OS to manage resources which in the end impacts the BI Application performance. In this case it is important to determine the over-utilized resources and address how the problems can be resolved. Some factors include: How much the resource is over-utilized Criticality of the transactions or roles on the over-utilized resource Expense of adding additional resources

With the monitoring of OBIEE via FMW Control, OS management tools, and other management tools, some changes that might be considered include the following: Adding new resources to existing servers o RAM, CPU, etc

Adding new servers and assigning components to them o Scale out/cluster OBIEE Components

Changing application settings and usage profiles o Utilize capabilities within OBIEE via the common management framework

A trial and error process may be required to correct over utilization and repeating the process above until utilization is optimal.Resolve High-Latency Transactions

During the capacity planning process, system use, design and model design is usually an underappreciated aspect of the planning. When planning, it is worthy to note transactions with high latency to be able to determine the order in which these problems will be addressed. Factors that influence the priority of a particular latency issue might include the following: Significance of the transactions to the business How will users be impacted by high cost transactions and set plans to alleviate impact Pre-planning to counteract high-latency transactions can include acknowledging the importance of Report scheduling and user profiling/usage governance17


Resolution of high-latency transactions is a costly portion of capacity planning. Items that can impact latency include the following for potential changes:

Inquire about network bandwidth and the impact it may have on reducing transaction time Redistributing application components to other servers Changing application settings, such as BI caching

Address Under-Utilized Resources

Another key in capacity planning is preparing for the potential of resources that can be identified as under-utilized. The objective is to prepare for what could be deemed as excess resources that may or may not impact utilization or transaction latencies. In many deployments and capacity planning exercises the prospect of under-utilized resources is not the primary determining factor in the planning. Some items are crucial and impactful when considering the small to medium to large implementation without negative impact to the enterprise architecture some of those areas include: Security Availability and Elasticity to handle peak volumes Future growth and Planned growth Stability

To plan the optimization of resources at a site, the following should be noted: Engage Expert Services Recognize the fine line between a small, medium, and large configurations The potential for hardware reuse or optimal hardware use exist

To reduce and prevent under-utilized resources the direct path is to reduce the hardware sizing. In this case it would be difficult to determine if the overall performance would be impacted beyond an acceptable level.Final Analysis

Whether dealing with a workload based on simple queries with a small dataset to complex queries with enormous datasets, optimal results that start with results obtained from the OBIEE Performance, Scalability and Reliability (PSR) team and ends with Professional Services can provide a scenario where capacity planning helps with the following: Maximize availability Optimize utilization Minimize the Total Cost Of Ownership Maximize Return on Investment

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REFERENCE:

http://www.specbench.org/ http://oreilly.com/catalog/9780596518585 http://httpd.apache.org/docs/2.2/mod/mod_deflate.html http://www.spec.org/ http://download.oracle.com/docs/cd/E14571_01/bi.htm

Oracle BI EE Architectural Deploymnet Capacity Planning May 2011 Author: Contributing Authors: Oracle Corporation World Headquarters 500 Oracle Parkway Redwood Shores, CA 94065 U.S.A. Worldwide Inquiries: Phone: +1.650.506.7000 Fax: +1.650.506.7200 oracle.com

Copyright 2011, Oracle and/or its affiliates. All rights reserved. This document is provided for information purposes only and the contents hereof are subject to change without notice. This document is not warranted to be error-free, nor subject to any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or fitness for a particular purpose. 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 and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. AMD, Opteron, the AMD logo, and the AMD Opteron logo are trademarks or registered trademarks of Advanced Micro Devices. Intel and Intel Xeon are trademarks or registered trademarks of Intel Corporation. All SPARC trademarks are used under license and are trademarks or registered trademarks of SPARC International, Inc. UNIX is a registered trademark licensed through X/Open Company, Ltd. 1010

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