IBM Software IBM Power Systems Business Analytics. Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence

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1 IBM Software IBM Power Systems Business Analytics Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence

2 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence Contents 2 Disclaimer 2 Introduction 3 Overview of IBM Cognos BI IBM Cognos Platform Architecture IBM Cognos BI v10 Service Architecture 6 Cognos on Power Reference Architecture and Benefits Consolidated vs. Distributed Deployments - Distributed Deployments - Consolidated Deployments Example Architectures from Production Customer Environments - Single Power VM Deployment - Department Store Consolidated IBM Cognos BI Deployment - International CPG Company Consolidated BI Stack 12 IBM Power Systems Proven performance and scalability for Cognos BI IBM Cognos BI v on Windows 2008 and AIX Test case descriptions Tuning AIX for Optimal Cognos BI Application Performance - AIX tuning parameters for Cognos BI v8, v10.1 & v10.1 FP1 - AIX tuning parameters for Cognos BI v (RP1) 19 Conclusions 19 References Disclaimer Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here. The test data, test scenarios and test results presented in this document are for reference and informational purposes only. These results to do not form part of the product s specifications and are in no way a guarantee or warranty of performance on the part of IBM. The test results are not indicative of the actual hardware required for any specific solution. Results will vary based on customer-specific environments. Introduction IBM Power Systems servers are designed to run missioncritical applications in highly, virtualized, consolidated operating environments that offer the flexibility that analytics workloads need. IBM Power Systems are a leader in performance, energy efficiency, flexible virtualization features and reliability/availability/serviceability (RAS) capabilities. Companies deploying IBM Cognos Business Intelligence (BI) and other business analytics workloads can benefit from these superior features. The use of advanced virtualization features can help lower TCO, can provide flexibility in systems management, and can ensure business analysts and other BI end-users receive continued service without interruptions. 2

3 Business Analytics IBM Power System features provide a superior level of flexibility for managing performance for planned growth, unplanned peaks in use, and the need to scale. IBM Power Systems offer optional software feature called IBM PowerVM to achieve higher resource utilization rates through the dynamic allocation of processors and memory. IBM Power Systems also offers Capacity on Demand which allows quick access to dormant physical hardware resources (processors and memory) when more capacity is required. Using these features can enable uninterrupted service for business analysts, sales managers, and other end users who are dependent on Cognos Business Intelligence for their work. Overview of IBM Cognos Business Intelligence IBM Cognos Business Intelligence ensures every decisionmaker across the organization can easily find, analyze and share the information they need to make better, faster decisions. With the broadest set of capabilities in the market today Cognos BI delivers the full range of traditional BI capabilities including reporting, analysis, dashboarding and scorecarding, plus expanded capabilities including what-if analysis, realtime monitoring, statistical analysis and predictive analysis results. This full breadth of capabilities come together in a single unified workspace for business intelligence and analytics. This unified workspace delivers immense business value as it is easily accessible to everyone in the organization and allows users to have a complete perspective of their business from a single user interface. Users are able to progressively interact with their information without needing technical support provided by IT. They can quickly test hypotheses and bring in additional key information that will support decisions, by simply moving from viewing information in a report or dashboard to easily modifying, or creating new views and reports. Built-in collaboration is an integral part of Cognos BI, enabling accelerated alignment amongst decision makers allowing a company to make faster and improved decisions, and to outperform the competition. IBM Cognos Business Intelligence provides the following capabilities: Easily view, assemble, and personalize information Integrated search to find and modify existing content Explore all types of information from varying angles to assess the current business situation Analyze facts and anticipate tactical and strategic implications by shifting from viewing information to more advanced, predictive, or what-if analysis of information Collaborate to establish decision networks to share insights and to drive toward a collective intelligence Provide transparency and accountability to drive alignment and consensus Communicate and coordinate tasks to engage the right people at the right time Access information and take action anywhere, with disconnected, yet fully interactive reports, and full interactivity on mobile devices including native ipad application, iphone, Blackberry, Playbook and Android support. Integrate and link analytics in everyday work to business workflow and process Organizations need to make the most of a workforce that is increasingly driven to multi-task, network, and collaborate. IBM Cognos BI delivers analytics that everyone in the organization can use to answer key business questions. 3

4 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence IBM Cognos Platform IBM Cognos BI is underpinned by the proven Cognos Platform, which delivers cost effective scale and performance on a purpose built, open, enterprise-class platform. The IBM Cognos Platform delivers the capabilities to manage business intelligence applications with centralized, web-based administration that provides a complete view of system activity as well as system metrics and thresholds so that organizations can resolve potential issues before there is a business impact. The IBM Cognos Platform is built on a web-based serviceoriented-architecture (SOA) that is designed for scalability, availability, and openness. This n-tiered architecture is made up of three server tiers: Web tier Application tier Data tier Dispatcher Report Server Gateway Dispatcher Report Server Dispatcher Content Manager The web tier The application tier The data tier The tiers are based on business function and can be deployed in a wide range of topologies from being fully consolidated to a physically distributed install separated by networks and firewalls depending on business requirements. Reliability and scalability were key considerations when designing the IBM Cognos Platform. Services in the application tier operate on a peer-to-peer basis, which means that no service is more important and that there are loose service linkages. Any service of the same type, on any machine in an IBM Cognos Platform configuration, can satisfy an incoming request, which results in complete fault tolerance. The dispatching (or routing) of requests is done in an optimal way, with automatic load balancing built into the system. Figure 1: IBM Cognos BI 3-tier architecture. The IBM Cognos Platform provides optimized access to all data sources, including relational data sources and online analytical processing (OLAP), with a single query service. In addition, this query service understands and takes advantage of the data source strength by using a combination of open standards such as SQL99, native SQL, and native MDX to optimize data retrieval for all these different data providers. The IBM Cognos BI user interfaces are accessed through the web tier. Figure 1 shows a high level topology of the three-tier IBM Cognos BI architecture; understanding the Cognos BI architecture is important before learning the various options for how Cognos BI servers can be deployed. 4

5 Business Analytics There are many options for deploying Cognos BI server components and application services permitting you to align your server and service topology to match both your business requirements and application performance requirements. Cognos BI services can scale either vertically or horizontally with the ability of a single instance to effectively utilize hardware resources in a single instance or distribute load across multiple software instances and multiple logical partitions (LPAR s) or physical servers. Presentation Service Event Service Statistics Service Scheduling and Job Service Search Service... IBM Cognos BUS SOAP, XML IBM Cognos DISPATCHER(s) CM Cache CAM AAA Service Content Manager Service Graphics Service Query Service Report Service... JNI JNI JAVA.exe CAM AAA Server Graphics Server V5 Data Server Report Server CAM_LPSvr.exe Java.exe Relational Data Access (JDB C) BIBUSTKServerMain.exe Java.exe New Service in v10 Data Source Interfaces Java (JVM) C++ Process TM1 SAP/BW Oracle Essbase DB2 DMR Relational Figure 2: Service architecture for Cognos BI v10 5

6 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence IBM Cognos Business Intelligence v10 Service Architecture The application tier of Cognos BI is made up of various loosely coupled services that can be grouped to support specific processing roles depending upon the design of the BI application. For example, the IBM Cognos Content Manager can be installed so that it is separate from BI Report Servers and Report Servers can be grouped to provide processing for a specific application requirement such as batch versus interactive requests or to isolate the processing for a specific data source, package, or group of users. Use of IBM Power Systems permits both the horizontal and vertical scaling of Cognos BI services in a single consolidated platform, thereby reducing total cost of ownership through lower administrative and environmental costs and improved hardware utilization. Generally, it is recommended that services be deployed in two separate groupings based on server role Content Manager Server and Report Server. These are also the two groupings available within the installation wizard for IBM Cognos BI. Installing the Content Manager services into a separate location permits the greatest level of vertical scalability for Content Manager and reduces possible contention for server resources between Content Manager and the other application tier services. The Report Server installation will contain all services other than Content Manager. A more granular distribution of services can be achieved after installation by disabling undesired services within Cognos Configuration. Grouping all services together for a Report Server deployment reduces the latency of communications between application tier services and is the most commonly deployed and tested configuration for Cognos BI services. All discussion of scalability within this document will refer to these two configurations Content Manager and Report Server. IBM Power Systems for IBM Cognos BI Reference Architecture and Benefits IBM Power Systems are a superior platform to run IBM Cognos BI on due to leadership in system performance, energy efficiency, virtualization and availability. The various configurations of IBM Power Systems can provide a proven, high-performance platform for Cognos BI applications in either a distributed or consolidated server topology depending upon business or environmental requirements. Consolidated compared to distributed deployments The decision to deploy multiple instances of IBM Cognos BI server components can be driven by many different requirements; for example, performance, data source type or location, security, availability, geo-political boundaries, or organizational requirements all can play a factor when deciding how and where to install BI servers. IBM Power Systems provide the greatest flexibility to support those decision-driving requirements within either a single consolidated system or within physically distributed servers. Distributed deployments In a typical distributed server deployment, instances of Cognos BI Gateway, Content Manager, or Report Server can be deployed on physically separate servers. Servers are connected through local area network (LAN) connections or, in highly distributed examples, wide area network (WAN) connections. Physical I/O adapters are used for disk and network connectivity. 6

7 Business Analytics Advantages Dedicated server resources for each Cognos BI server Reduced latency can be achieved for WAN connected users by installing servers at remote locations New hardware can be added to the topology as when required Reliability through redundancy; no single point of failure if redundant Cognos services are configured on different systems Limitations Under-utilization of server resources; server resources are disconnected from one another and therefore some processing capacity will always be under-utilized High server maintenance and admin cost High data center footprint, cooling costs, and power consumption Possible Cognos BI server availability impacts due to scheduled or unscheduled server downtime Cognos BI server performance and scalability is limited by system architecture & available resources; provisioning time for additional capacity is much higher Distributing Cognos BI server components across multiple computers is often advantageous or even required in order to meet business requirements or performance goals. For example, it may be necessary to completely segregate processing for sensitive information like human resource or medical data in order to comply with an organization s security standards. Other deployments may require a server topology that is distributed across a wide area network in order to provide acceptable performance for users or data sources that are remotely located due to organizational boundaries or acquisitions. Consolidated Deployments In a consolidated deployment of IBM Cognos BI on IBM Power Systems, Gateways, Content Manager, and Report Servers can be distributed over native or IBM PowerVM LPARs; each running IBM AIX or Linux operating systems. A consolidated configuration for Cognos BI servers on IBM Power Systems provides much more flexibility in the ability to scale either vertically or horizontally in order to meet the processing requirements for various BI applications. Multiple instances of Cognos server components can be installed within a single LPAR, across multiple LPARs on a single IBM Power System, or across multiple IBM Power Systems in a combination of consolidated and distributed functions. Data sources can be deployed within an LPAR on the same IBM Power System, and Virtual I/O adapters can provide enhanced performance and manageability for storage and network I/O based on IBM PowerVM virtualization. Designed to provide these advantages Lower total cost of ownership (TCO) Server consolidation can result in higher resource utilization; all resources can be easily made directly available for any Cognos BI server Lower server maintenance and admin cost Lower data center footprint, power consumption, and cooling cost Flexible capacity PowerVM helps achieve higher scalability during peak use by increasing resource utilization rates through the dynamic allocation of processors and memory to Cognos BI LPARs Capacity on Demand allows quick access to dormant physical hardware resources when more capacity is required. Storage can be extended dynamically 7

8 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence Proven performance and scalability Multiple LPARs can communicate via Virtual LAN which is much faster than Ethernet based LAN Workloads can be virtually separated (e.g. Executives, batch, mobile, etc) New Cognos BI environments with special requirements can be deployed quickly (e.g. acquisitions, highly sensitive financial information, etc.) Scale up/out ratio can easily be changed Proven performance for IBM Cognos BI v10 High availability and reliability Live Partition Mobility (LPM) can be used to migrate a running LPAR during scheduled server maintenance Easy to setup redundant Cognos BI server instances through PowerVM Potentially lower TCO Modular deployments increases flexibility A consolidated installation of Cognos BI on IBM Power Systems can leverage IBM PowerVM to provide a highly scalable, high performance platform for BI applications. Power Systems environments offer virtualization capabilities with PowerVM. IBM PowerVM extends the capabilities of Power Systems with the ability to manage a flexible and dynamic IT infrastructure through the use of partitions, mobility and virtualized system resources. PowerVM offers a powerful set of virtualization features that can aid Cognos BI by providing end users with the best possible performance and reliability, more efficient use of system resources to save IT costs, dynamic systems management as new Cognos BI users and applications come onboard, and smarter systems maintenance that does not impact user experience. Using the recommended deployment model in Power Systems environments can provide advantages for BI end users and IT staff. Two commonly used PowerVM features that are useful to Cognos BI environments are dynamic logical partitions (LPARs) and live partition mobility (LPM). Power Systems provide an easy way to activate dormant processor and memory resources within your system without taking your system or Cognos BI software down. Whether your need is temporary or permanent, this feature can help boost your resources during your peak times. When deploying the Cognos BI on Power reference architecture, each Cognos BI server is deployed in its own partition. This is a good practice because each unique Cognos server requires varying amounts of system resources, such as processors and memory, at varying times. Running the servers in their own LPARs allows more fine-tuning of the system resources that each server requires. Sharing resources across the partitions can optimize the use of available processors, contributing to better control of IT costs. Processor resources can also be dynamically allocated to the partitions as they need them without manual IT administration. The primary benefit to Cognos BI software is to maximize throughput and reduce response times experienced by BI end users as the underlying Cognos BI servers have access to the maximum amount of resources when they need them. This can prevent or minimize any negative performance impacts during planned or unplanned peak use. 8

9 Business Analytics The recommended deployment model shows how to scale out and scale up Cognos BI on Power Systems by adding more system resources to existing partitions and adding more Cognos BI server instances in new partitions. When growth requires scaling up, adding more partitions to an existing system with available resources is easier and more timely compared with non-virtualized environments, especially when growth happens unexpectedly. Growing smaller nonvirtualized deployments often requires the time-consuming process of justifying, ordering and installing new hardware. Contention for CPU and memory resources is often the result of the unexpected need to scale due to new users or applications. There are many Power platform features that can benefit Cognos BI in this area: Capacity on Demand, and Active Memory Sharing. Live Partition Mobility can also make it easier to perform backups and planned maintenance without reducing availability to users Live Partition Mobility (LPM) can minimize or eliminate planned downtime resulting in uninterrupted service for BI end users. Systems administrators can use LPM to move one or more Cognos BI partitions to another physical IBM Power System before performing a hardware upgrade without impacting users. Cognos BI servers remain active and running during and after the move with little to no affect on BI performance. When the upgrade is complete, the partition can be moved back to the original system. When BI usage grows and threatens to constrain system resources, one or more LPARs can be moved using LPM to another IBM Power System where available resources exist. This allows flexibility to balance Cognos BI servers across a set of systems. LPM is also useful to move a Cognos BI test environment to a production system during a cutover to production, or to upgrade a Cognos BI environment from older Power hardware to a new IBM POWER7 processor model. IBM PowerVM offers other features that can benefit Cognos BI environments. Active Memory Sharing with memory pools enables sharing memory across multiple partitions. The memory can be dynamically shifted to the partitions when they need it. Storage virtualization can be a cost-effective way to optimize storage resources. IBM Cognos Business Intelligence has supported IBM POWER Systems and previous System p models for many releases. Cognos BI can be installed and is supported in AIX or Linux logical partitions. Cognos BI is not supported on the IBM i operating system. However, Cognos BI software prerequisites can be installed on IBM i partitions and Cognos BI can connect to IBM DB2 on IBM i as a supported data source. For more information related to supported software versions for IBM Cognos BI v10.1.1, please refer to the Supported Environments page which can be found in the Support section of IBM.com ibm.com/support/docview.wss?uid=swg An IBM Redbook is available that describes best practices for leveraging PowerVM virtualization features in Cognos BI deployments: Exploiting IBM PowerVM Virtualization Features with IBM Cognos 8 Business Intelligence. You can read the full details of how Cognos BI can exploit PowerVM features in an IBM Redbooks* publication provided in the References section. More information related to deploying and optimizing Cognos BI and AIX on Power Systems can be found in the white paper Cognos 8 Business Intelligence (BI) on IBM AIX best practices: Optimizing and scaling Cognos 8 BI on IBM AIX. 9

10 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence Web Gateway Report Server Report Server (Executives) Content Manager DB2 Content Store HTTP Load Balancer Enterprise Data Warehouse Cognos Clients Web Gateway Report Server Report Server (Batch) Content Manager DB2 Content Store Figure 3: Department Store example IBM Power Systems BI server topology Example architectures from production customer environments The following sections provide you with architecture examples from customer production environments Single Power VM deployment Deploying the entire Cognos BI stack including all 3 tiers on a single PowerVM is beneficial for quick deployments as the entire Cognos BI environment is self contained. This deployment method is used by customers that want to create new development environments quickly and in some cases even deploy production environments for special projects that don t require large scale or fail over scenarios. The advantage of this deployment method for development environments is that it is easy to deploy and development teams can have their own environments to accelerate development. Department store consolidated IBM Cognos BI deployment Benefits Consolidate multiple Cognos BI environments with other applications Flexibility of scaling up and out Ease of deployment Performance In this scenario the various tiers of a Cognos BI deployment are separated using IBM PowerVM but consolidated on one or a few Power Systems and deployed along with other applications. 10

11 Business Analytics The benefits of such a deployment is that it is a very flexible architecture for production systems as the Cognos BI tiers can be scaled out and up dynamically and at the same time is very cost effective. As scalability requirements change more CPU or memory can be allocated to scale up and additional Cognos BI services can be added to scale out. For example a customer has a requirement for an application to produce a large number of batch reports, a new Cognos BI dispatcher PowerVM can be deployed that exclusively handles this batch load using package routing. This is a good example how such a deployment can easily scale out. In another case the amount of data consumed by the BI application Dynamic Query Mode suddenly and dramatically increases which means that we need to provide the Dynamic Query cache with more memory. In this case we can easily scale up by providing the partition with the Dynamic Query cache with more memory and also more CPU. Detailed technical information about Dynamic Query Mode can be found on: ibm.com/developerworks/data/library/cognos/ infrastructure/cognos_specific/page529.html?ca=drs- An example is a retail customer that needs to provide business intelligence dashboards to more than 2000 merchandisers and executive. As shown in the diagram they deployed the Cognos BI web gateways, report servers and content managers on a single Power 795 System alongside existing applications. This allowed them to consolidate multiple BI environments into a single system and provides them with the ability to easily scale out and up at the same time. For example dedicated Report Servers for batch reporting and executives were deployed using package routing so that these particular workloads can consistently meet the service level agreements. The customer not only benefited from better and more consistent performance but also optimized their infrastructure cost. Web Gateway Report Server Report Server (Executives) Content Manager DB2 Content Store Information Server (ETL) HTTP Load Balancer Cognos Clients Web Gateway Report Server Report Server (Executives) Content Manager DB2 Content Store InfoSphere Warehouse (DB2) Figure 4: Consumer Package Goods IBM Power Systems BI server topology 11

12 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence International CPG company consolidated BI stack Benefits Consolidate entire BI Stack for lower TCO Easily deploy project based environments Modular architecture provides flexibility Performance This deployment option is similar to the previous deployment option except that the entire business intelligence stack including data warehouse and ETL are deployed on PowerVM instances in a single Power System. The advantage of this approach are the additional benefits of using the Power Hypervisor Ethernet connection which connects the ETL, data warehouse and Cognos BI using the faster virtual LAN. A major consumer packaging company implemented IBM Cognos BI, IBM InfoSphere Warehouse and IBM Information Server on a single IBM Power 785 System. Cognos BI is deployed in a similar way as in the previous sections by deploying the Cognos BI tiers in separate PowerVM instances but in addition also deploying IBM InfoSphere Warehouse and IBM Information Server in PowerVMs. By consolidating the entire business intelligence stack they were able to reduce infrastructure cost significantly and provide maximum performance and reliability. IBM Power Systems proven performance and scalability for IBM Cognos BI The combination of IBM POWER7 systems and IBM Cognos BI version provides a proven, high performance and highly scalable platform for business intelligence applications. Internal comparisons of IBM Cognos BI application performance between similarly configured IBM POWER6 and IBM POWER7 systems showed significant performance advantages for IBM POWER7 servers: up to 41% performance improvement for workloads made up of light-weight BI use cases 1 up to 26% performance improvements for mixed workloads (heavy or complex BI requests 2 blended with light-weight use cases) up to 35% faster cube builds with TM1 (IBM Cognos in-memory OLAP) Beginning with version 8.4, IBM Cognos BI software has steadily provided optimizations that focus on optimizing performance for BI workloads on IBM Power systems. Based upon tests performed using IBM POWER 6 and Cognos BI v8.4, IBM provided tuning recommendations which have been observed to improve BI application performance by more than 10 times for real BI customer applications on IBM Power Systems with AIX. For example; an IBM customer had developed a Cognos BI application to distribute PDF based reports via ; as implemented and before optimization, this application was performing at a rate of 11 multi-page reports per minute. After simply applying recommended AIX tuning parameters the application performance improved to 150 multi-page PDF reports per minute. On average, most applications may see performance improve two or three fold by applying AIX level tuning. Further optimizations have been made with the release of IBM Cognos BI v , and subsequently Cognos BI v Services supporting Cognos Dynamic Query with installations of IBM Cognos BI version and newer can detect when they are started on AIX and will automatically tune settings for AIX thread and memory handling for the JVM in which Dynamic Query is installed. Also, as of Cognos BI v new AIX compiler based optimizations have been implemented and a new thread caching memory allocator (called TCMalloc) has been implemented for IBM Cognos BI C++ based components such as the Cognos BI reporting 12

13 Business Analytics Total Average Response Time (seconds) No TCM alloc or AIX Tuning AIX Tuning Only, No TCM alloc Cognos BI AIX Optimization TCM alloc Only, no AIX Tuning TCM alloc with AIX Tuning Figure 5: Performance impact of recommended AIX tuning and the new TCMalloc memory allocator included with Cognos BI v services BIBusTKServerMain. The accumulative effect resulting from applying AIX tuning parameters along with the optimizations included within Cognos BI v has been observed through testing and customer experience to range from a two to ten fold increase in performance depending on application design. Figure 5 provides a performance comparison using four different configurations of Cognos BI v and AIX. The average response time is the best (shortest time) when TCMalloc and AIX tuning is applied. 1. No AIX tuning and no use of the TCMalloc memory allocator 2. Recommended AIX tuning only and no use of TCMalloc 3. Use of TCMalloc only and no AIX tuning 4. Both the recommended AIX tuning and TCMalloc enabled With the addition of TCMalloc in Cognos BI v it is no longer necessary for AIX system administrators to manually tune AIX memory allocation parameters, however, AIX thread handling parameters will still provide a 5% to 10% improvement in performance. Cognos BI Optimization by Test Case Run HTML Multi-Fact Master Detail Reports Run PDF Multi-Fact Master Detail Reports Run HTML 2-prompt Basket Analysis Interactive HTML Analysis Sorting and Calcs Run PDF Ranking Dimensional Functions Interactive Analysis with Powercube OLAP Interactive Analysis with DB2 OLAP Run HTML Time Period Analysis Reports Run PDF 2-prompt Basket Analysis Run Simple HTML Reports View PDF Time Period Analysis Reports Typical BI Day Run TPA PDF Reports Run PDF Banded PDF Reports Run HTML Reports with 2D Charts Run HTML Report OLAP Slicer Run a 2 page PDF Reports View a Simple PDF Reports Simple Portal Navigation Percent Improvement (%) Figure 6: Cognos BI v optimization benefits by test case 13

14 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence Performance of any BI application is largely dependant upon application and data source design, data source performance, and environmental performance. In order to provide a comprehensive view into the potential performance impact of optimizations made in Cognos BI v10.1.1, a broad range of BI test cases were used. Figure 6 provides a view into the performance improvements for the twenty different test cases used to validate AIX optimizations in Cognos BI v These test cases were selected to show the impact on performance for applications that utilize the Cognos BI server resources in different ways; the simple report views in HTML and PDF tend to place more load on the Content Manager service, interactive analysis tasks can place load across a variety of services, and test cases such as the Multi-fact Master Detail reports will stress the Cognos BI Report Services. Also included in these tests is the standard Typical BI Day suite of tests which represents a blending of use cases to mimic the processing load of a typical business intelligence application (according to third party research). The results below show the greatest benefit from Cognos BI v optimizations being enjoyed by test cases which place the most processing load on a Cognos BI server. Given the superior processing and I/O performance of IBM POWER 7 systems, greater performance benefits are often seen at higher levels of application load. IBM Cognos BI v on Windows 2008 and AIX 7.1 With IBM s ongoing focus on Cognos BI optimization in version , IBM Power Systems and AIX have become the proven choice as a highly scalable and high performance platform for business intelligence applications. Testing performed by IBM Labs show the performance of IBM Cognos BI v to be at least on par and generally better by 14% to 46% when compared to Microsoft Windows 2008 Server. Testing was performed using a variety of test cases selected to match the different ways that a BI application can utilize IBM Cognos BI services and system resources. The test systems used similar server configurations, (CPU sockets, cores, RAM), and current processor generation. The Windows 2008 Server was tested using a server configured with Intel Nehalem 4x8 core sockets running at 2.0GHz and 256GB RAM. The AIX environment was tested using an IBM POWER 7 System with 4x8 core sockets running at 3.55 GHz. In the AIX tests, only 31 cores were actually available for use by Cognos BI servers as one core was reserved for use by IBM PowerVM. Figure 7 provides the server topology used during performance testing. The Intel Nehalem and IBM Power processor architectures utilize cores that run at differing clock rates. The fastest available Nehalem-EX uses cores that run at a clock rate of 2.26 GHz; Intel based systems with this configuration were not available for testing in our labs. Given that some IBM Cognos BI test cases benefit from faster processor clock rates and some benefit from more highly threaded configurations; the results shown in figure 8, below, also include a column which contains total average response times for Intel improved by 10%. It should also be noted that the IBM POWER7 system used for AIX testing was configured with less RAM (244GB vs 256GB), and that one less processor core was available for Cognos BI services on the AIX system. 14

15 Business Analytics Web tier IBM Cognos ISAPI Gateway Application tier Report Server Content Manager Cubes Windows 2008 Server Intel Nehalem 4 socket/32 core 2.0 GHz 256 GB Memory VS Report Server Content Manager Cubes AIX Power 7 4 socket/31 core 3.55 GHz 244 GB Memory Data tier Authentication Content Store Reporting Data Sources TM1 LDAP Server DB2 Figure 7: Server topology for Windows 2008 vs AIX 7.1 comparisons 15

16 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence IBM Cognos BI v Performance windows 2008 vs AIX 7.1 Total Average Response Time (seconds) Windows 2008 Windows 2008 Adjusted AIX 7.1 Windows 2008 AIX 7.1 Test Case Total Average Response Time Adjusted Total Average Response Time Total Average Response Time % Difference Adjusted % Difference 1: Typical BI Day (Interactive & Batch) % 37.46% 2: Interactive Business Insight Use % 26.50% 3: Typical BI Day (Interactive Only) % 11.81% 4: 3D Charting % -9.90% 5: Large PDF Reporting % 21.69% 6: 50/50 Large PDF & Small HTML % 4.68% 7: Viewing Saved PDF % 40.44% 8: Light-weight HTML Reporting % 21.96% 9: Dynamic Query on TM1 Master Detail % 25.80% Figure 8: Cognos BI v test results 16

17 Business Analytics Test case descriptions Typical BI Day (Interactive & Batch) A blend of both interactive and batch processing requests meant to mimic a typical BI application based upon market feedback and customer experience. 250 concurrent users Interactive Business Insight Use A variety of Business Insight Dashboards with varying number of widgets as well as interactive user gestures within the Business Insight UI such as viewing reports, adding of widgets, prompts, and sliders. 250 concurrent users Typical BI Day (Interactive) The traditional suite of tests used by IBM to mimic an interactive BI workload typical of most BI customer applications. The Typical BI Day is a blend of use case which vary in complexity and system processing load including viewing saved reports, running reports in various output formats, relational, OLAP, and DMR data sources, normal user navigation gestures, and heavy-weight or complex analytical functions. 250 concurrent users 3D Charting A series of reports varying in the number and complexity of highly formatted 3D charts. 250 concurrent users Large PDF Reporting Reports that render a large number of PDF pages and places a heavy and slow moving load on the system. These reports are designed to exercise the local cache functionality of Cognos BI v concurrent users 50/50 Large PDF & Small HTML A combination of large PDF rendered reports of many pages and a single page, fast moving HTML rendered report. This test demonstrates the ability of the environment to context switch from fast moving objects to slower I/O intensive gestures. 250 concurrent users Viewing Saved PDF This is a fast moving test case with heavy impact on Cognos Content Manager. This test mimics the load generated by multiple users viewing saved output; a Java intensive test case. 250 concurrent users Light-weight HTML Reporting This test case mimics the running of small, banded HTML reports by multiple users. This is a very fast running test case with very little data returned by queries for this report. 250 concurrent users Dynamic Query on TM1 Master Detail This replicates the concurrent execution of Multi-fact Master Detail reports against an IBM TM cube. These reports are general very processor intensive on Cognos Report Servers. 120 concurrent users 17

18 Best practices and advantages of IBM Power Systems for running IBM Cognos Business Intelligence Tuning AIX for Optimal Cognos BI Application Performance Further information related to tuning AIX for IBM Cognos BI can be found in the original document; Cognos 8 Business Intelligence (BI) on IBM AIX best practices: Optimizing and scaling Cognos 8 BI on IBM AIX (see References). The two main areas to consider when tuning AIX for an IBM Cognos BI application are Memory Management & Thread Handling. In version of IBM Cognos BI, memory allocation settings are no longer required as the product has implemented TCMalloc, a new memory allocator that is installed by default. In versions older than including IBM Cognos BI v8.4, v8.4.1, v10.1, and v , it is still beneficial to set parameters related to memory allocation. All versions will also benefit from tuning thread handling parameters. The following are the recommended settings for AIX parameters to support Cognos BI applications: AIX tuning parameters for Cognos BI v8, v10.1 & v10.1 FP1 AIXTHREAD_MINKTHREADS = 32 AIXTHREAD_MNRATIO = 1:1 AIXTHREAD_MUTEX_FAST = ON MALLOCTYPE=buckets MALLOCMULTIHEAP=heaps:n (where n=2 times Num of CPUs) It should be noted that while use of MALLOCMUTIHEAP will benefit the performance of Cognos BI applications, care should be taken to monitor memory requirements for large reports. MALLOCMULTIHEAP works by allocating multiple heaps of RAM rather than a single heap. The Cognos Report Server threads partition the total physical heap. In a 32-bit application the total physical heap is 2GB. With the Cognos BIBusTKServerMain (classic Report Service) still being 32-bit, and generally using 4 threads, this means that an application might potentially end up with no single report able to consume more than 500 MB of RAM. AIX tuning parameters for Cognos BI v (RP1) Memory allocation parameters NOT required AIXTHREAD_MINKTHREADS = 32 AIXTHREAD_MNRATIO = 1:1 AIXTHREAD_MUTEX_FAST = ON AIXTHREAD_SCOPE = S SPINLOOPTIME = 4000 YIELDLOOPTIME = 20 18

19 Business Analytics Conclusions IBM Power Systems provide a proven, high performance and highly scalable platform for IBM Cognos BI applications. Leveraging PowerVM and Capacity on Demand can enable flexible scalability and high availability for Cognos BI applications. Contention for CPU and memory resources is often the result of the unexpected need to scale due to new users or applications. There are many Power platform features that can benefit Cognos BI in this area: Capacity on Demand, and Active Memory Sharing. Live Partition Mobility can also make it easier to perform backups and planned maintenance without reducing availability to users. References IBM Power Systems performance and energy efficiency performance benchmarks: ibm.com/systems/power/ PowerVM ibm.com/systems/power/software/virtualization Best-practices whitepaper: Deploying Cognos 8 Business Intelligence in an IBM Power virtualized environment ibm.com/partnerworld/page/pw_com_deploy_cognos Cognos 8 Business Intelligence (BI) on IBM AIX best practices: Optimizing and scaling Cognos 8 BI on IBM AIX ibm.com/partnerworld/page/whitepaper/aix/v6r1_cognos/ methods IBM Redbooks publications: Exploiting IBM PowerVM Virtualization Features with IBM Cognos 8 Business Intelligence (SG ) ibm.com/redbooks/redbooks.nsf/redpieceabstracts/ sg html?open 19

20 Copyright IBM Corporation 2011 IBM Corporation Software Group Route 100 Somers, NY U.S.A. Produced in the United States of America December 2011 All Rights Reserved IBM, the IBM logo, and AIX, Cognos, DB2, POWER6, POWER7 and Power Systems are trademarks or registered trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at While every attempt has been made to ensure that the information in this document is accurate and complete, some typographical errors or technical inaccuracies may exist. IBM does not accept responsibility for any kind of loss resulting from the use of information contained in this document. The information contained in this document is subject to change without notice. Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both. UNIX is a registered trademark of The Open Group in the United States and other countries. Java and all Java-based trademarks and logos are trademarks of Sun Microsystems, Inc. in the United States, other countries, or both. 1 Light weight test cases include executing and viewing HTML and PDF based reports and portal navigation 2 Heavy or complex BI requests include executing large and highly formatted PDF reports, locally processed calculations, interactive analysis activities, and complex queries. Please Recycle YTW03209-CAEN-00