Oracle RMS - Performance
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This technical white paper summarizes performance test results for Oracle Retail Merchandising System 13.1.1 running on an Oracle Real Application Clusters (RAC) database with 1 to 4 nodes. Both online and batch workloads were tested. For online transactions, response times were excellent across configurations and CPU utilization decreased as nodes were added. For batch workloads, run times improved by approximately 1.5 times when doubling the RAC nodes from 1 to 2 and from 2 to 4 nodes. The paper provides details on the test environment, methodology, and analysis of the scaling results.
Oracle RMS - Performance
- 1. Performance brief for Oracle Retail Merchandising System 13.1.1 on HP ProLiant BL460c G6 and EVA6400 Using Oracle Database 11gR1 RAC on Linux Technical white paper Table of contents Executive summary............................................................................................................................... 2 Introduction ......................................................................................................................................... 2 Test topology....................................................................................................................................... 2 Test methodology................................................................................................................................. 4 Test business processes......................................................................................................................... 5 Online processes ............................................................................................................................. 5 Batch processes ............................................................................................................................... 5 Test results .......................................................................................................................................... 6 Test analysis summary .......................................................................................................................... 6 Online ............................................................................................................................................ 6 Batch .............................................................................................................................................. 6 Appendix A – Benchmark environment ................................................................................................... 9 For more information .......................................................................................................................... 10
- 2. Executive summary Oracle® Retail Merchandising System (RMS) load tests for both batch and online are run on an Oracle Real Application Clusters (RAC) database in an HP BladeSystem environment. As nodes are added to the RAC database, run times are reduced for the batch workloads and CPU utilization is reduced for equal numbers of online users. Online response times are excellent for all configurations with little variation as RAC nodes are added to the configuration. For a batch workload, the performance increase in going from 1 to 2 and 2 to 4 nodes is typically around 1½ times. For a consistent online workload, CPU utilization goes down to 55 – 60%. This white paper describes only the relative performance of RMS 13.1.1 as RAC nodes are added to the database. Detailed test results are available in a performance report available from the HP solutions alliance engineer for Oracle Retail. Refer to the URL in the For more information section of this brief. This paper describes testing completed in April 2010. Introduction In April 2010, the HP solution alliance engineering team for Oracle completed a performance test using the Oracle Retail Merchandising System (RMS) 13.1.1 Benchmark Kit on Oracle Database 11gR1 Real Application Clusters (RAC). The performance test measured the online and batch performance of the RMS application in multiple RAC configurations to determine the horizontal scalability of RMS 13.1 on HP ProLiant BL460c G6 servers running Oracle Enterprise Linux (OEL) release 5 update 2. The online tests consisted of RMS functionality that represents a day in the life of an RMS user. Tests included twelve workflows spanning numerous functional areas such as cost adjustments, organizational hierarchy, deals, items, mass return transfers, orders, return to vendors, suppliers and transfers. The batch tests included two workflows; one file-based batch process, sales upload, and the other table-based batch process, replenishment. These test results can be used to understand RMS 13.1.1 scaling out on an Oracle RAC database. The environment was set up for RAC scalability testing only. For a highly available environment, another application server could be added to eliminate that single point of failure. A load balancer could also be utilized to distribute online requests between the application servers. Test topology Oracle Retail Merchandising System 13.1.1 was run on HP BladeSystem ProLiant servers with an HP StorageWorks 6400 Enterprise Virtual Array for storage as shown in Figure 1. 2
- 3. Figure 1. Architectural diagram of test bed 3
- 4. The RMS database was run on 1, 2, 3 and 4 RAC nodes (with host names rac1, rac2, rac3, and rac4) running Oracle Database 11.1.0.7 on ProLiant BL460c G6 blade servers with Oracle Enterprise Linux 5 update 2 (OEL 5u2) within a c7000 blade enclosure. Each BL460c server was populated with a single quad-core 2.93GHz Intel® Xeon® processor and 24 GB of memory. For greater loads, these blade servers can be configured with two quad-core processors and up to 192 GB of memory. A Virtual Connect Flex-10 Ethernet module provided a 10GbE private interconnect between the nodes as well as a 1GbE connection outside of the enclosure and public network to the application server. For 10GbE data center environments, the Flex-10 modules allows up to 10Gb for the uplink outside the enclosure. For a baseline comparison, the RMS database was also run on a non-RAC database with host name rac0 on one of the BL460c G6 blade servers. A Virtual Connect server profile for each database server was created and assigned as required to the blade servers. For online tests, a ProLiant BL685c G1 blade server with 4 dual-core 2.6GHz AMD Opteron™ processors and 64 GB of memory running OEL 5u2 in the c7000 enclosure served as the application server running Oracle Application Server 10.1.2.3. Online user transactions were generated by HP LoadRunner 9.50 running on a ProLiant DL380 G3 with Microsoft® Windows® Server 2003 connected to the c7000 enclosure through an HP ProCurve 2848 switch. All disk storage was provided by an HP StorageWorks 6400 Enterprise Virtual Array with dual HSV400 controllers and 48 300GB 15K RPM SAS drives in 4 enclosures. Each of the blade servers utilized two fiber channel interfaces with each connected to a separate Virtual Connect 4Gb Fibre Channel (VC-FC) module. Two fibre channel interfaces from each of the VC-FC modules were attached to the HP StorageWorks SAN 4/16 switch and the 4 ports from each of the HSV400 controllers were connected to the SAN switch for maximum storage throughput. All of the blade servers used Virtual Connect fibre channel technology to boot from EVA LUNs. All database files resided in Oracle Automatic Storage Management (ASM) managed EVA LUNs. Details of the environment can be found in Appendix A. Test methodology The online workload test was conducted using HP LoadRunner software to simulate concurrent users within the Oracle Retail Merchandising System. The test execution consisted of 30 minutes of user ramp up followed by 1 hour of steady state. Measurements were recorded across both the application and database servers during the tests. The Sales Upload and Replenishment batch workloads were executed via a custom test harness script running on node rac1. The script controlled process execution, data preparation, file movement and statistics gathering. To test performance of a single RAC node, an Oracle database service was created to run against a single instance of a 2 node RAC cluster and tnsnames.ora designated this service for the RMS database. All system performance information was gathered at 15 second intervals by HP Performance Agent 5.00. 4
- 5. Test business processes Online processes The online workload spanned numerous functional areas within RMS. Online tests were run to simulate the work of 600 simultaneous users. The online transactions that make up each functional area for the online load test are described below. Cost Adjustment Create an average cost adjustment for an item. Warehouse Create a warehouse within the organizational hierarchy. Deals Search for an approved supplier deal. Item Creation Create and approve a one-level item with multiple suppliers, stores, multiple UDAs and various seasons. Item Creation 2 Create and approve a two-level item with differentiators, multiple suppliers and a location list of stores. Mass Return Transfer Create a mass return transfer for an item at all stores. Order Creation Create and approve a one-level item with multiple suppliers, stores, multiple UDAs and various seasons. Order Creation 2 Create an order for a parent item and item differentiators and distribute to two locations. Return to Vendor Create a return to vendor for a particular item and location. Stores Create a store within the organizational hierarchy. Supplier Create a new supplier within the merchandising system. Transfer Create a manual requisition transfer of a single item between two locations. Batch processes The Point of Sales Upload (posupld) module processes sales and return details from an external point of sale system. The sales/return transactions are validated against Oracle Retail item/store relations to ensure the sale is valid, but this validation process can be eliminated if the sales that are being passed in are screened by sales auditing (Oracle Retail Sales Audit). Sales audit was turned off for the testing of this program. Three different runs with uploads from 250, 500, and 1000 files were executed for the non-RAC and each RAC configuration. Replenishment allows the customer to automate the ordering process for items by monitoring inventory conditions and creating orders and/or transfers based on predefined replenishment parameters. The replenishment workload consists of a series of batch modules, some of which require pre- and post- processing as indicated: rplatupd (pre, post) Replenishment Attribute Update rilmaint (post) Replenishment Item Location Maintenance ociroq (pre) Recommended Order Quantity reqext (post) Replenishment Quantity Extract rplext (pre, post) Vendor Replenishment Extraction rplbld Replenishment Order Build rplapprv (pre) Automatic Replenishment Order Approval Including pre and post processing, there are fifteen separate modules. Three different runs with 1.34 million, 2.7 million, and 5.4 million item/locations were executed for the non-RAC and each RAC configuration. 5
- 6. Test results Detailed test results are available from the HP solutions alliance engineer for Oracle Retail. Refer to the URL in the For more information section of this brief. Test analysis summary Online Online response times were excellent for all configurations with little variation as RAC nodes were added to the configuration. Since 600 users were run in all configurations rather than running the maximum number of users that could be accommodated, a comparison of CPU utilization on the database servers is the best way to compare the scaling of RMS online across RAC nodes. Since each connection uses some memory, a comparison of memory utilization is also useful to see how much memory utilization is reduced on each node as more nodes are added. Figure 2 shows the reduction in CPU and memory utilization as RAC nodes are added to the configuration. Using CPU as a measure of scaling, we see 1.8x scaling when increasing from 1 to 2 RAC nodes and 1.7x scaling when increasing from 2 to 4 RAC nodes. Figure 2. Comparison of online scaling in non-RAC and 1- to 4-node RAC configurations RMS 13.1 Online Scaling on RAC non-RAC %CPU/GB 1 RAC node 2 RAC nodes 3 RAC nodes 4 RAC nodes Avg CPU util (%) Peak Mem (GB) Batch A graphic comparison of batch run times for largest loads (1000 posupld files, 5.4 million replenishment items/locations) in Figure 3 shows the relative performance increase as more nodes are added to the RAC cluster. 6
- 7. Figure 3. Comparison of batch scaling in non-RAC and 1- to 4-node RAC configurations RMS 13.1 Batch Scaling on RAC non-RAC Elapsed time 1 RAC node 2 RAC nodes 3 RAC nodes 4 RAC nodes Replenishment POS Upload POS upload scaling from 1 to 2 RAC nodes was 1.14x and from 2 to 4 RAC nodes was 1.54x. Overall replenishment scaling from 1 to 2 RAC nodes was 1.55x. Scaling from 2 to 4 RAC nodes was 1.54x. Some replenishment modules ran slower as RAC nodes were added. By tuning the test to have just those modules run against a single RAC node while the other modules ran across all RAC nodes, overall horizontal scaling for replenishment was improved. Scaling of individual replenishment module run times are shown in Figure 4. 7
- 8. Figure 4. Comparison of individual replenishment module scaling in non-RAC and 1- to 4-node RAC configurations. Modules that completed in less than ten seconds not included. RMS 13 Replenishment Module Scaling on RAC Elapsed time rplatupd rilmaint ociroq reqext rplext rplbld 0 1 2 3 4 Number of RAC nodes (0=non-RAC) 8
- 9. Appendix A – Benchmark environment Database Servers Four HP ProLiant BL460c blade servers were used as database and batch servers. Each system was configured as follows: Processor: One quad-core 2.93GHz Xeon 5570 with hyper-threading enabled Memory: 24 GB Network: Embedded NC532i Dual Port Flex-10 10GbE Multifunction Server Adapter Storage HBA: QLogic QMH2462 4Gb FC HBA Cluster Interconnect: 10GbE with jumbo frames Operating System: Oracle Enterprise Linux Release 5 Update 2 – 64-bit Storage HP StorageWorks 6400 Enterprise Virtual Array 2 x HSV400 controllers 48 x 300GB 15K RPM SAS drives in 4 drive bays Application Server One HP ProLiant BL685c G1 blade server was used as the applications server for all online tests. It was configured as follows: Processor: Four dual-core 2.6GHz AMD Opteron 8218 Memory: 64 GB Network: Embedded NC373i Multifunction Gigabit Server Adapter Operating System: Oracle Enterprise Linux Release 5 Update 2 – 64-bit Software Versions Oracle Retail Merchandising System 13.1.1 Oracle Database 11gR1 11.1.0.7 with patches: 7697360 7378322 7036284 7272646 Oracle Application Server and Developer Suite 10gR2 10.1.2.3 Oracle Application Server Forms and Reports Services 10g 10.1.2.0.2 with patch: 7379122 HP LoadRunner 9.5 HP Performance Agent 5.0 Oracle Cluster File System OCFS2 1.2.9 9
- 10. For more information For more information regarding this performance test including detailed test results, contact the HP Solutions Alliance engineer for Oracle Retail at http://hporacle.com/go/contacts. Follow the Global Alliance and Technical Contacts link. For information regarding an HP server solution for your Oracle Retail environment, contact the sales representative for your region listed at http://hporacle.com/go/contacts. Select your region on the map. Information about the HP BladeSystem can be found at http://www.hp.com/go/blades. To help us improve our documents, please provide feedback at http://h20219.www2.hp.com/ActiveAnswers/us/en/solutions/technical_tools_feedback.html. © Copyright 2010 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. The only warranties for HP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HP shall not be liable for technical or editorial errors or omissions contained herein. Microsoft and Windows are U.S. registered trademarks of Microsoft Corporation. AMD Opteron is a trademark of Advanced Micro Devices, Inc. Intel and Xeon are trademarks of Intel Corporation in the U.S. and other countries. Oracle is a registered trademark of Oracle Corporation and/or its affiliates. 4AA2-3897ENW, Created September 2010