Meeting Your Scalability Needs with IBM DB2 Universal Database Enterprise - Extended Edition for Windows NT

Transcription

1 IBM White Paper: IBM DB2 Universal Database on Windows NT Clusters Meeting Your Scalability Needs with IBM DB2 Universal Database Enterprise Extended Edition for Windows NT Is your decision support system not returning queries fast enough for your users? Has your data mart "maxed out" on your SMP system? Wouldn't it be great to just add another server to easily increase your system's capacity and power? Wouldn't it be great to be able to do this with low cost, standard highvolume components, and shrinkwrap software? That solution is closer than you think.

2 Trademarks and Service Marks The following terms are trademarks of the IBM Corporation in the United States or other countries or both: ADSTAR AS/400 CICS DB2 DB2 Client Application Enablers DB2 Connect DB2 Extenders DB2 Universal Database Distributed Relational Database Architecture DRDA IBM OS/2 Net.Data Netfinity S/390 Encina is a registered trademark of Transarc Corporation. Microsoft, Windows, and Windows NT are trademarks or registered trademarks of Microsoft Corporation. Compaq and ProLiant are trademarks or registered trademarks of Compaq Computer Corporation. Dolphin and CluStar are trademarks of Dolphin Interconnect Solutions, Inc. Dell and PowerEdge are trademarks of Dell Computer Corporation. GigaNet and clan are trademarks of GigaNet, Inc. Intel is a trademark of Intel Corporation. Java and JDBC are trademarks of Sun Microsystems, Incorporated. Tandem and ServerNet are registered trademarks or trademarks of Tandem Computers Incorporated in the United States and/or other countries. All other product or service names mentioned herein are trademarks or registered trademarks of their respective owners. April, IBM Corporation IBM DB2 Universal Database Enterprise Extended Edition

3 Introduction Today's competitive business environment is forcing companies to extract as much useful information as possible from the large volumes of data that they keep. Business Intelligence is a term often used to describe the type of I/T applications that transform data into information that helps companies make strategic business decisions. Parallel database technology is often a key component of these new applications. This technology enables scalable performance on large databases by breaking the processing into separate execution components that can be run concurrently on multiple processors. Elapsed times for queries can be drastically reduced by processing the individual queries in parallel. Parallel databases support a scalable growth path to easily add more processing power or disk to an existing system. DB2 Universal Database Enterprise Extended Edition (DB2 UDB EEE) was designed to support the very large databases that Business Intelligence applications often require. DB2 UDB EEE incorporates a highly scalable sharednothing software architecture, which allows it to exploit: symmetric multiprocessor (SMP) systems clusters of SMP systems massively parallel processor (MPP) systems This paper provides an overview of the DB2 UDB EEE product as it relates to the Windows NT environment. DB2 UDB EEE Architecture DB2 UDB EEE employs a sharednothing software architecture in which DB2 server instances run on several machines without the need to directly share memory or disk access. This architecture enables support for very large databases by dividing the database into partitions that can be stored and managed on separate servers of a sharednothing hardware system. By searching the database in parallel, elapsed times for queries can be dramatically reduced. The individual machines need to be able to communicate with each other over a highspeed, low latency network, often referred to as a system area network or SAN. In particular, DB2 UDB EEE supports Intelbased NT clusters. Several server platforms are available that can provide enterpriseclass cluster solutions, including IBM Netfinity servers, Compaq ProLiant servers, and Dell PowerEdge clusters. These servers, connected with interconnects, such as Dolphin CluStar, GigaNet clan, and Tandem Servernet interconnect, IBM DB2 Universal Database Enterprise Extended Edition 1

4 provide an example of a hardware environment that is ideally suited for DB2 UDB EEE while remaining capable of providing high availability and reliability. Multiple clustered systems (nodes) communicate over the highspeed interconnect and operate in parallel. Note that the individual systems (nodes) can be either uniprocessor systems or symmetrical multiprocessor (SMP) systems. In either case, each system (node) will have its own memory and access its own disks, but will share a scalable interconnect that always ensures pointtopoint connectivity across the system. This highly scalable design eliminates bottlenecks and enables customer configurations that can consist of tens to hundreds of nodes. For providing increased capacity and query performance requirements as your data and number of users grow, plug in a new server into the SAN and reconfigure DB2 to take advantage of the new server node. Parallel query processing in DB2 UDB EEE is achieved by executing tasks in parallel, with each task assigned to work on its own partition of the data. For example, a 6 uniprocessor cluster would enable a table scan to execute as 6 separate table scans operating on 6 separate database partitions. On a 4way SMP cluster configuration, there would typically be 4 database partitions, which would enable a table scan to execute across all servers concurrently. Parallel query execution within the SMP node is performed by creating separate execution tasks and executing these tasks in parallel, using the multiple processors of the SMP. The answer will be consolidated and returned to the user, who does not require any knowledge of these database partitions or parallel processing. From the end user s perspective, DB2 UDB EEE operates the same as a traditional (nonclustered) database, although performance will be drastically improved. DB2 UDB EEE, by default, uses TCP/IP to communicate between partitions of the cluster system. Messages and data are exchanged via an efficient buffer mechanism, which minimizes the number of communication calls required. With the introduction of the Virtual Interface (VI) Architecture, a specification that defines an industrystandard architecture for communication within clusters of servers and workstations, DB2 UDB EEE on NT can communicate in a distributed messaging environment using a lowlatency, highspeed system area network (SAN). The VI Architecture provides a reliable infrastructure for distributed message passing with low overhead, which in turn can provide better application availability. Because of its unique partitioning architecture and VI architecture support, DB2 UDB EEE can operate on standard highvolume servers and highspeed network fabrics. The new interconnect fabrics, including Dolphin CluStar, GigaNet clan, and Tandem ServerNet technology, that support the VI Architecture are able to provide high bandwidth for transferring many messages, low latency for fast pointtopoint delivery, and fault tolerance for ensuring that messages reach their destination. A demonstration of DB2 UDB EEE on Windows NT using betalevel support for the VI Architecture was given to developers at Intel s Developer Forum. DB2 UDB EEE demonstrated IBM DB2 Universal Database Enterprise Extended Edition 2

5 nearlinear scalability on a 6node cluster when the same query was run against one, two, three and six partitions of the same data. For more information regarding this demonstration, visit the following URLs: and Data Partitioning A crucial factor in attaining the performance advantages of a parallel environment is being able to intelligently distribute the data across the various database partitions. DB2 UDB EEE supports intelligent database partitioning, in that it evenly distributes and remembers the location of each data row. In the context of a large database, DB2 UDB EEE database partitioning makes database administration easier than a nonpartitioned database of the same size. Tools are provided that efficiently manage the large tables that occur in large databases. The design of DB2 UDB EEE ensures that database design decisions are separated from loadbalancing decisions. The partition map is an industryunique feature that enables DB2 UDB EEE to easily manage data placement. DB2 UDB EEE provides an advanced hashing algorithm to map each row in the database to a specific database partition. The hashing algorithm is applied to a column (or set of columns) in the table known as the partitioning key, resulting in a value between 0 and The partition map defines a specific database partition for each of the possible 4,096 values. DB2 UDB EEE employs a flexible topology for data storage to achieve a high degree of parallelism and performance. A database is set up to have a certain number of database partitions a subset of a database containing its own user data, indexes, transaction logs and configuration files. Within a database, administrators define a nodegroup a named set of database partitions across which data is partitioned. Nodegroups can span all or some of the database partitions created for the database. Within the nodegroup, tablespaces are defined that identify one or more containers (files or devices) into which table data and indexes will be stored. By specifying more than one container per tablespace in each database partition, I/O parallelism can be employed by the data manager for enhanced performance benefits. Partitioning Advantages The DB2 UDB EEE database partitioning architecture provides the following advantages: Data is distributed across multiple database partitions, thereby enabling databases scaling into the terabytes. DB2 UDB EEE is aware of the partitioning scheme in the data definition language (DDL), data manipulation SQL, and at run time. Its partitioning methodology can be viewed also as a load balancing tool (by changing the partition key and partition map, the number of rows in any database partition can be adjusted). The DB2 UDB EEE optimizer takes advantage of partitioning knowledge to evaluate the costs of different operations and thus choose the optimal execution strategy for a given SQL statement. Distribution of the data is easily done by hashing the value of the partitioning key, while the partition map provides knowledge of row location. IBM DB2 Universal Database Enterprise Extended Edition 3

6 In the event that there is data skew after the initial distribution, DB2 UDB EEE utilities can automatically analyze and correct the skew. DB2 UDB EEE can automatically create a new partition map to evenly distribute the currently skewed data by changing the partition assignments for some new subset of the 4096 hashing values. Affected data rows are automatically moved to their newly assigned database partition. Incremental database growth is supported by adding additional partitions to the database (along with more processing power), changing the partition map to include these new database partitions, and automatically redistributing the data. DB2 UDB EEE utilities provide this capability, allowing for a welldefined growth path. More data can be placed in partitions that have faster processing ability, thereby enabling load balancing on nodes of different processing power in a sharednothing configuration. The DB2 UDB EEE partition map is used to assign proportionally more data to those partitions with more processing power. Applications can call an API to determine the location of a row, and can then route the transaction directly to the node where the row is located. This API can also be used by transaction processing applications, such as IBM CICS, Encina, or Microsoft Transaction Server (MTS), to route transactions to the appropriate node and thus improve performance. The application view of a table is separated from the physical placement of data in support of proper database design principles. Function Shipping DB2 UDB EEE further utilizes the benefits of the sharednothing architecture by implementing a function shipping process flow model. Function shipping means that relational operators are executed on the system node containing the data whenever possible. This minimizes network traffic by filtering out unimportant data and achieves excellent parallelism. Function shipping also provides significant advantages when performing INSERT, UPDATE, or DELETE statements, since index maintenance, locking, and logging will be distributed across multiple database partitions. Function shipping is a superior design alternative to what is known as I/O shipping, which involves increased network traffic and decreased efficiency as data is sent from all nodes in the system to the node executing the task. For an example of function shipping, let's assume an EMPLOYEE table is partitioned across multiple nodes. The following SQL statement is executed: SELECT EMP_NO FROM EMPLOYEE WHERE SALARY > The coordinator node (the node of the system receiving the request) issues a request to each database partition in the group to select its subset of rows that meet the condition of having a SALARY value over Each database partition in the group then returns its answer set to the coordinating node for final processing. Because each database partition does the initial extraction from its own part of the EMPLOYEE table, no central lock manager is needed. Only a global deadlock detector, checking at regular IBM DB2 Universal Database Enterprise Extended Edition 4

7 intervals, is needed. Instead of having thousands of lock requests sent between systems, a quick and efficient deadlock detection takes place at userdefined intervals. Parallel Query Processing Interquery Parallelism: Interquery parallelism allows multiple queries to execute concurrently, resulting in a significant increase in throughput. DB2 UDB EEE incorporates advanced concurrency management mechanisms and workload balancing techniques to allow for extremely high throughput by utilizing all of the available resources. Intraquery Parallelism: Intraquery parallelism refers to the processing of parts of a single query at the same time using either intrapartition parallelism or interpartition parallelism or both, resulting in dramatic query response time improvements. Intrapartition parallelism refers to the ability to take an individual task such as scan, sort, merge, or join and generate multiple identical tasks operating on different pieces of data. This speeds up a task within a particular partition. Interpartition parallelism refers to the ability to break up a query into multiple parts across multiple partitions of a partitioned database. The query is performed in parallel across the partitions. DB2 UDB EEE generates a parallel execution strategy for all SQL statements using a costbased relational database optimizer. In the diagram below, a single query is broken down into its component parts utilizing both intrapartition and interpartition parallelism techniques. The query is decomposed into two subqueries that execute on separate partitions (interpartition parallellism). The circles represent parallel tasks, for example, parallel scans, within each partition (intrapartition parallelism). The parallel execution strategies in DB2 UDB EEE are executed asynchronously. Coordinator involvement is restricted to initializing slave tasks and to collecting final result sets. Specifically, in a multijoin query, there is no coordinator involvement between joins all processing is driven by the dataflow between slave tasks. This is sometimes referred to as pipeline parallelism or vertical parallelism. Pipeline parallelism is a form of parallel processing which allows the components of a query, such as scans, sorts, joins, etc. to overlap the processing and pass partial results to the next operation in the plan. Unlike some vendors, DB2 UDB EEE integrates advanced pipeline parallelism with its partition parallelism to reduce elapsed time for queries. IBM DB2 Universal Database Enterprise Extended Edition 5

8 Workload Balancing Because DB2 UDB EEE supports both interquery and intraquery parallelism, individual queries from multiple users can be processed concurrently, with each individual query processed in parallel across multiple processors. This results in a significant reduction in response time and a vast increase in throughput. DB2 UDB EEE provides the unique ability to distribute the query coordinator workload either manually or automatically across nodes. An administrator may assign a dedicated coordinator node with no data on it, or may choose to spread the users across all nodes on the system. This means that an administrator has control over the workload placement on the system. To even further automate workload balancing, a transaction manager, such as IBM CICS, Encina, or Microsoft Transaction Server, can be used to balance the workload on a per query basis. The DB2 UDB EEE query governor can also assist in balancing workload. The query governor acts according to a set of rules that are defined by the system administrator. For example, a rule may indicate that an application is using too much resource. In this situation, the governor may lower the application s priority (or force it off the system). The configuration rules can be changed while queries are running, and the governor will dynamically reflect these changes. Governor rules can also be set according to time of day. Other examples of using the governor include: Set CPU restrictions from 9:00 AM to 5:00 PM for everyone as a baseline Allow no queries to run for more than an hour as a baseline Slow down a subset of applications, as they are a lower priority Allow users doing performance tuning to get higher priority during lunch hours Increase the priority of an important application so it always completes quickly Provide a high priority for the first ten seconds of each transaction, ensuring a high priority and more consistent response time for short transactions in a mixed workload environment. Query Optimization The strength of the DB2 UDB EEE optimizer ensures high performance for complex queries on very large databases. IBM is recognized as an industry leader in optimization technology and has incorporated years of parallel research technology into DB2 UDB EEE. The optimization component of DB2 UDB EEE is responsible for generating the parallel query execution strategies for all SQL statements. DB2 UDB EEE can generate the optimal parallel plan rather than having the best serial plan simply executed in parallel. The generation of a parallel execution strategy for a given SQL statement is automatic, and is transparent to client applications. An application program does not have to be recompiled to exploit parallel execution. When the application program is bound to DB2 UDB EEE, the appropriate parallel execution strategy is generated and, if required, stored. While it is impossible to describe all the parallel execution strategies in this paper, the full power of parallel processing is also utilized for other SQL constructs, such as outer joins, subqueries, set operations (Union, Difference, Intersect), and UPDATE, INSERT and DELETE operations. IBM DB2 Universal Database Enterprise Extended Edition 6

9 In addition to understanding the parallel nature of the environment, the optimizer has a full query rewrite capability to ensure that even poorly written SQL performs optimally an important feature when pointandclick query tools are used to generate the query to be run. The optimizer also plays a key role in support of the SQL that can be issued. In a Business Intelligence environment, DB2 UDB EEE provides support for the advanced SQL capabilities typical to OnLine Analytical Processing (OLAP) applications: CUBE and ROLLUP clauses for queries. ROLLUP is an extension to the GROUP BY clause, and produces a result set that contains subtotal rows in addition to the "regular" grouped rows normally returned for a GROUP BY clause. CUBE produces a result set that contains all the rows of a ROLLUP aggregation and, in addition, contains Rollup Example: Shaded rows represent subtotal rows. The dashes show that the data is aggregated for all values in that column. SELECT MONTH(SALES_DATE), REGION, SALES_MGR, SUM(SALES) FROM SALES WHERE YEAR(SALES_DATE) = 1996 GROUP BY ROLLUP (MONTH(SALES_DATE), REGION, SALES_MGR) "crosstabulation" rows. CUBE produces rows with aggregate data for each dimension or column in the GROUP BY clause. MONTH REGION SALES_MGR SUM(SALES) Performance Numerous April Central Chow other performance April Central Smith features have been April April Central NorthWest Smith implemented in DB2 UDB EEE. It is possible to April NorthWest define multiple bufferpools April within a database and May Central Chow assign different tables or May Central May NorthWest Smith indexes to each, thereby May NorthWest maintaining certain tables May in memory for longer periods of time. With the support for the 4gigabyte Memory Tuning feature of Windows NT Server, Enterprise Edition, a larger memory space can be addressed and exploited. For managing the database bufferpool more effectively, DB2 UDB EEE provides asynchronous page cleaners that move dirty or updated pages to disk, thereby freeing up pages in the bufferpool for new data to be processed. These page cleaners will only operate when there is low activity on the system, to minimize impact to an operational system. In terms of I/O performance, sequential prefetch and index prefetch will preread data pages into the bufferpool in advance of when the data manager needs to process it, thereby reducing the wait time for I/O. As well, the big block I/O feature batches the reading and writing of multiple pages in one I/O call, which reduces the overhead of numerous smaller I/O calls to the operating system. DB2 UDB EEE incorporates a new indexing technique called dynamic bitmap index ANDing, which takes advantage of existing indexes on a large table to search for qualifying rows based on criteria in the query. For each index on the table, dynamically built bitmap representations of the qualifying rows are AND ed together to get all qualifying rows without having to directly scan the large table. IBM DB2 Universal Database Enterprise Extended Edition 7

10 DB2 UDB EEE also incorporates a new join technique for use with Star Schema databases those with a very large fact table with attributes that match other dimension tables. Queries in this environment typically involve joining dimension tables (for example, time, location, product type, company division) with the fact table (for example, sales transactions). If a bad plan for the query is generated, it can be very costly for the whole system. The DB2 optimizer can recognize this structure and will apply techniques using indexes and bitmaps to return the results with minimal I/O to the fact table. Database Administration Tools DB2 Contol Center The Control Center is available for performing administration tasks such as configuring, backing up and recovering data, managing directories, scheduling jobs, and managing media, all from a graphical interface. It also aids in managing database objects; for example: create and drop a database create, alter, and drop a tablespace or table create, alter, and drop an index create nodegroups backup and recover a database partition or tablespace partition define replication sources and subscriptions for data to be replicated between systems Each database partition server can be collectively managed centrally from the Contol Center. From the Control Center, several other useful tools can be launched: The Command Center is used for interactively entering commands and SQL statements, displaying results, and viewing the plan graphically through the Visual Explain tool. Visual Explain enables comprehensive tuning ability for complex parallel queries. The Script Center supports the creation and scheduling of scripts containing SQL, DB2 commands or operating system commands The Journal provides the status and information pertaining to all the jobs that are pending execution, executing, or that have completed. Recovery history, the alerts log and the message log can also be viewed. The Alert Center provides monitoring for early warnings of potential problems, and supports automation of actions to correct problems once discovered Data Load DB2 UDB EEE provides the ability to efficiently load large volumes of data into the database. The DB2 UDB EEE Autoloader is used to split table input according to partition key values, pipe the data to the appropriate partition, and simultaneously load data into each partition of the table. The Autoloader bypasses the transaction logging mechanism, which also decreases the time spent to load the data. Data can also be loaded into database tables using the IMPORT utility of DB2 UDB EEE which loads data by performing INSERT operations a logged operation. DB2 UDB EEE provides an enhanced INSERT where rows are batched before being sent to the destination node. This new INSERT is available to most application programs that use SQL INSERT and coordinate restart points using COMMIT. It is implemented as an option at program preparation (BIND) time. Most programs can use this option without any modification. Backup and Recovery DB2 UDB EEE provides a granular and parallel backup and restore utility. A backup can be taken in parallel across all of the database partitions, or against only a subset of the partitions. The degree of parallelism achieved during backup and restore of a IBM DB2 Universal Database Enterprise Extended Edition 8

11 database is determined by the number of backup devices available. This parallel capability results in a linear reduction in backup time, while the granular management allows an administrator the choice to back up only a subset of the data. Backup can be done online, meaning that users can continue to update the system while backups are taking place. DB2 UDB EEE provides similar granular management and parallelism of the restore. At restore time, it is necessary to ensure that the database partition that is being restored is in a consistent state with respect to the rest of the nodes in the system. This can be achieved by either restoring all of the database partitions using backup images that are known to be consistent, or by restoring a single database partition and rolling the logs forward to a point in time where the database state is consistent across all database partitions. DB2 UDB EEE interfaces with the IBM ADSTAR Distributed Storage Manager (ADSM) product, which manages backup jobs and media from multiple PC servers. The ADSM interface keeps track of backups and their associated logs. Thus, ADSM enhances the manageability of DB2 UDB EEE. Data Redistribution Utility The Redistribute utility is used to move data between database partitions when a new server is added to a nodegroup and/or when the data distribution across servers is not uniform (because of the skew in the data values in the partitioning key column). The Redistribute utility can be used to achieve a uniform distribution of data. Redistribute is an "online" operation: neither the database system nor the database needs to be shut down. Database administrators can specify what data should be moved and where it should be moved to. For example, suppose a nodegroup consists of 10 partitions (numbered 1 to 10) and two partitions (numbered 15 and 16) are added. The Redistribute utility can move some of the data to take advantage of the new partitions. For example, data can be moved from each of partitions 1 to 5 to partition 15, and data from partitions 6 to 10 can be moved to partition 16, to achieve a uniform distribution of data across all partitions in the nodegroup. Index Creation Index creation is performed in parallel across database partitions. A local index is created for each partition of the table. DB2 UDB EEE supports the creation of unique indexes, where the key columns include the partitioning key columns, or nonunique indexes. At each database partition, parallelism can also be employed when creating indexes by parallelizing I/O operations. Table Reorganization The Reorganization utility (REORG) executes in parallel across all of the nodes that contain a table partition for a given table. REORG reclusters the rows of a table on disk in order according to a specified index. Clustering of each individual table partition provides enhanced index scan performance. REORG can also employ I/O parallelism when data is spread across multiple containers. High Availability High availability is supported by the use of Microsoft Cluster Server (MSCS) software, which is available in Microsoft Windows NT Server, Enterprise Edition. The MSCS software provides transparent takeover of the disk and communications resources of the failed node. System nodes can be paired together, and each pair has access to shared disks (disks connected to two nodes). If one of the nodes in a pair fails, the other node can take over and the system continues to operate (an activeactive failover scenario). IBM DB2 Universal Database Enterprise Extended Edition 9

12 While this method provides quick takeover of a failed node, there may be an impact on performance due to an increased load on the takeover node. An alternative is to have the paired node remain idle until the takeover is required, thereby preserving the overall system performance (an activepassive failover scenario). This illustration shows nodes A and B using MSCS for activeactive failover. All DB2 resources switch to the surviving node. Nodes C and D are set up in a similar fashion. Other Product Features DB2 UDB EEE offers other functional capabilities as required to build extensible applications for emerging markets while bridging to existing lineofbusiness systems. Builtin Replication: DB2 UDB EEE supports data replication from other DB2 servers on distributed LAN systems and on host systems into DB2 UDB EEE. When used with other hostbased replication software, data from nonrelational data sources can also be replicated to DB2 UDB EEE. Replication provides another means for populating your data mart or data warehouse data from operational, lineofbusiness systems. Host Connectivity: DB2 UDB EEE provides builtin support for application access to DB2 host data on S/390 and AS/400 platforms. This support is provided through the integration of Distributed Relational Database Architecture (DRDA). As well, hostbased systems can query DB2 UDB EEE databases. ObjectRelational: DB2 UDB EEE fully supports SQL3 object extensions in the parallel environment for building more extensible applications that can include more than traditional alphanumerical data. This includes support for large objects to store up to 2GB data objects, userdefined functions for defining serverside methods to operate on data, userdefined data types to extend the types available, and table functions for returning virtual table data from other data sources. OLE automation is also supported, for allowing OLEenabled data sources to appear as a DB2 table. Network Computing: DB2 UDB EEE can be a data server for webbased applications. This includes serverside Java support for userdefined functions and stored procedures, JDBC support for building browserbased Java applets or application, and Net.Data to enable delivery of dynamic content to webbased applications. IBM DB2 Universal Database Enterprise Extended Edition 10

13 Summary IBM's ability to provide relational database technology exploiting a looselycoupled parallel processing environment, such as Windows NT clusters with highspeed interconnects, makes DB2 Universal Database Enterprise Extended Edition an ideal choice for today's missioncritical business applications on standard Intelbased servers. DB2 UDB EEE was designed to meet the scalability, availability, and processing requirements needed to run today's applications. DB2 Universal Database is the industry's first easytouse, multimedia, webenabled database, scaling from Intel to UNIX platforms, and from uniprocessor to SMP to MPP/cluster computing environments. For further information, please contact your local DB2 sales representative or visit the IBM Data Management Home Page at Visit the following sites to learn more about various interconnect solutions: Dolphin CluStar technology can be found at: GigaNet clan technology can be found at: Tandem ServerNet technology can be found at: Information regarding enterpriseclass Intelbased servers and clusters IBM Netfinity server information is located at: Compaq ProLiant and E2000 platform architecture can be found at: Dell PowerEdge cluster information is available at: Other white papers discussing clustering can be found at: For more information regarding the Intel Developer Forum demonstration, visit the following web pages: IBM DB2 Universal Database Enterprise Extended Edition 11