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• Enterprise Manager will not start on WebLogic after ADF install

  - by retrodev

  I just built a WebLogic 10.3.6 cluster with EM and JRF checked in the domain extensions. Next I installed ADR 11.1.1.7 by first installing ADR 11.1.1.6, then patching the environment and running upgradeADF in wlst. All seems well except I cannot start EM. The application transitions to STATE_ADMIN, but then fails with the exception below. Any advice would be appreciated. <[ACTIVE] ExecuteThread: '6' for queue: 'weblogic.kernel.Default (self-tuning)' < < <1372081430346 java.lang.RuntimeException: com.sun.faces.config.ConfigurationException: CONFIGURATION FAILED! null at com.sun.faces.config.ConfigureListener.contextInitialized(ConfigureListener.java:293) at weblogic.servlet.internal.EventsManager$FireContextListenerAction.run(EventsManager.java:481) at weblogic.security.acl.internal.AuthenticatedSubject.doAs(AuthenticatedSubject.java:321) at weblogic.security.service.SecurityManager.runAs(SecurityManager.java:120) at weblogic.servlet.internal.EventsManager.notifyContextCreatedEvent(EventsManager.java:181) at weblogic.servlet.internal.WebAppServletContext.preloadResources(WebAppServletContext.java:1870) at weblogic.servlet.internal.WebAppServletContext.start(WebAppServletContext.java:3155) at weblogic.servlet.internal.WebAppModule.startContexts(WebAppModule.java:1518) at weblogic.servlet.internal.WebAppModule.start(WebAppModule.java:487) at weblogic.application.internal.flow.ModuleStateDriver$3.next(ModuleStateDriver.java:427) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.flow.ModuleStateDriver.start(ModuleStateDriver.java:119) at weblogic.application.internal.flow.ScopedModuleDriver.start(ScopedModuleDriver.java:201) at weblogic.application.internal.flow.ModuleListenerInvoker.start(ModuleListenerInvoker.java:249) at weblogic.application.internal.flow.ModuleStateDriver$3.next(ModuleStateDriver.java:427) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.flow.ModuleStateDriver.start(ModuleStateDriver.java:119) at weblogic.application.internal.flow.StartModulesFlow.activate(StartModulesFlow.java:28) at weblogic.application.internal.BaseDeployment$2.next(BaseDeployment.java:672) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.BaseDeployment.activate(BaseDeployment.java:212) at weblogic.application.internal.EarDeployment.activate(EarDeployment.java:59) at weblogic.application.internal.DeploymentStateChecker.activate(DeploymentStateChecker.java:161) at weblogic.deploy.internal.targetserver.AppContainerInvoker.activate(AppContainerInvoker.java:79) at weblogic.deploy.internal.targetserver.operations.AbstractOperation.activate(AbstractOperation.java:569) at weblogic.deploy.internal.targetserver.operations.ActivateOperation.activateDeployment(ActivateOperation.java:150) at weblogic.deploy.internal.targetserver.operations.ActivateOperation.doCommit(ActivateOperation.java:116) at weblogic.deploy.internal.targetserver.operations.StartOperation.doCommit(StartOperation.java:149) at weblogic.deploy.internal.targetserver.operations.AbstractOperation.commit(AbstractOperation.java:323) at weblogic.deploy.internal.targetserver.DeploymentManager.handleDeploymentCommit(DeploymentManager.java:844) at weblogic.deploy.internal.targetserver.DeploymentManager.activateDeploymentList(DeploymentManager.java:1249) at weblogic.deploy.internal.targetserver.DeploymentManager.handleCommit(DeploymentManager.java:440) at weblogic.deploy.internal.targetserver.DeploymentServiceDispatcher.commit(DeploymentServiceDispatcher.java:164) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer.doCommitCallback(DeploymentReceiverCallbackDeliverer.java:195) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer.access$100(DeploymentReceiverCallbackDeliverer.java:13) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer$2.run(DeploymentReceiverCallbackDeliverer.java:69) at weblogic.work.SelfTuningWorkManagerImpl$WorkAdapterImpl.run(SelfTuningWorkManagerImpl.java:545) at weblogic.work.ExecuteThread.execute(ExecuteThread.java:256) at weblogic.work.ExecuteThread.run(ExecuteThread.java:221) Caused By: com.sun.faces.config.ConfigurationException: CONFIGURATION FAILED! null at com.sun.faces.config.ConfigManager.initialize(ConfigManager.java:357) at com.sun.faces.config.ConfigureListener.contextInitialized(ConfigureListener.java:227) at weblogic.servlet.internal.EventsManager$FireContextListenerAction.run(EventsManager.java:481) at weblogic.security.acl.internal.AuthenticatedSubject.doAs(AuthenticatedSubject.java:321) at weblogic.security.service.SecurityManager.runAs(SecurityManager.java:120) at weblogic.servlet.internal.EventsManager.notifyContextCreatedEvent(EventsManager.java:181) at weblogic.servlet.internal.WebAppServletContext.preloadResources(WebAppServletContext.java:1870) at weblogic.servlet.internal.WebAppServletContext.start(WebAppServletContext.java:3155) at weblogic.servlet.internal.WebAppModule.startContexts(WebAppModule.java:1518) at weblogic.servlet.internal.WebAppModule.start(WebAppModule.java:487) at weblogic.application.internal.flow.ModuleStateDriver$3.next(ModuleStateDriver.java:427) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.flow.ModuleStateDriver.start(ModuleStateDriver.java:119) at weblogic.application.internal.flow.ScopedModuleDriver.start(ScopedModuleDriver.java:201) at weblogic.application.internal.flow.ModuleListenerInvoker.start(ModuleListenerInvoker.java:249) at weblogic.application.internal.flow.ModuleStateDriver$3.next(ModuleStateDriver.java:427) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.flow.ModuleStateDriver.start(ModuleStateDriver.java:119) at weblogic.application.internal.flow.StartModulesFlow.activate(StartModulesFlow.java:28) at weblogic.application.internal.BaseDeployment$2.next(BaseDeployment.java:672) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.BaseDeployment.activate(BaseDeployment.java:212) at weblogic.application.internal.EarDeployment.activate(EarDeployment.java:59) at weblogic.application.internal.DeploymentStateChecker.activate(DeploymentStateChecker.java:161) at weblogic.deploy.internal.targetserver.AppContainerInvoker.activate(AppContainerInvoker.java:79) at weblogic.deploy.internal.targetserver.operations.AbstractOperation.activate(AbstractOperation.java:569) at weblogic.deploy.internal.targetserver.operations.ActivateOperation.activateDeployment(ActivateOperation.java:150) at weblogic.deploy.internal.targetserver.operations.ActivateOperation.doCommit(ActivateOperation.java:116) at weblogic.deploy.internal.targetserver.operations.StartOperation.doCommit(StartOperation.java:149) at weblogic.deploy.internal.targetserver.operations.AbstractOperation.commit(AbstractOperation.java:323) at weblogic.deploy.internal.targetserver.DeploymentManager.handleDeploymentCommit(DeploymentManager.java:844) at weblogic.deploy.internal.targetserver.DeploymentManager.activateDeploymentList(DeploymentManager.java:1249) at weblogic.deploy.internal.targetserver.DeploymentManager.handleCommit(DeploymentManager.java:440) at weblogic.deploy.internal.targetserver.DeploymentServiceDispatcher.commit(DeploymentServiceDispatcher.java:164) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer.doCommitCallback(DeploymentReceiverCallbackDeliverer.java:195) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer.access$100(DeploymentReceiverCallbackDeliverer.java:13) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer$2.run(DeploymentReceiverCallbackDeliverer.java:69) at weblogic.work.SelfTuningWorkManagerImpl$WorkAdapterImpl.run(SelfTuningWorkManagerImpl.java:545) at weblogic.work.ExecuteThread.execute(ExecuteThread.java:256) at weblogic.work.ExecuteThread.run(ExecuteThread.java:221) Caused By: java.lang.NullPointerException at oracle.adfinternal.view.faces.unified.renderkit.UnifiedRenderKit.(UnifiedRenderKit.java:129) at oracle.adfinternal.view.faces.unified.renderkit.UnifiedRenderKit.createRenderKit(UnifiedRenderKit.java:111) at oracle.adfinternal.view.faces.unified.renderkit.UnifiedRenderKitFactory.getRenderKit(UnifiedRenderKitFactory.java:59) at org.apache.myfaces.trinidadinternal.renderkit.CoreRenderKitFactory.getRenderKit(CoreRenderKitFactory.java:55) at com.sun.faces.config.processor.RenderKitConfigProcessor.addRenderKits(RenderKitConfigProcessor.java:240) at com.sun.faces.config.processor.RenderKitConfigProcessor.process(RenderKitConfigProcessor.java:159) at com.sun.faces.config.processor.AbstractConfigProcessor.invokeNext(AbstractConfigProcessor.java:114) at com.sun.faces.config.processor.ManagedBeanConfigProcessor.process(ManagedBeanConfigProcessor.java:270) at com.sun.faces.config.processor.AbstractConfigProcessor.invokeNext(AbstractConfigProcessor.java:114) at com.sun.faces.config.processor.ValidatorConfigProcessor.process(ValidatorConfigProcessor.java:120) at com.sun.faces.config.processor.AbstractConfigProcessor.invokeNext(AbstractConfigProcessor.java:114) at com.sun.faces.config.processor.ConverterConfigProcessor.process(ConverterConfigProcessor.java:126) at com.sun.faces.config.processor.AbstractConfigProcessor.invokeNext(AbstractConfigProcessor.java:114) at com.sun.faces.config.processor.ComponentConfigProcessor.process(ComponentConfigProcessor.java:117) at com.sun.faces.config.processor.AbstractConfigProcessor.invokeNext(AbstractConfigProcessor.java:114) at com.sun.faces.config.processor.ApplicationConfigProcessor.process(ApplicationConfigProcessor.java:341) at com.sun.faces.config.processor.AbstractConfigProcessor.invokeNext(AbstractConfigProcessor.java:114) at com.sun.faces.config.processor.LifecycleConfigProcessor.process(LifecycleConfigProcessor.java:116) at com.sun.faces.config.processor.AbstractConfigProcessor.invokeNext(AbstractConfigProcessor.java:114) at com.sun.faces.config.processor.FactoryConfigProcessor.process(FactoryConfigProcessor.java:216) at com.sun.faces.config.ConfigManager.initialize(ConfigManager.java:338) at com.sun.faces.config.ConfigureListener.contextInitialized(ConfigureListener.java:227) at weblogic.servlet.internal.EventsManager$FireContextListenerAction.run(EventsManager.java:481) at weblogic.security.acl.internal.AuthenticatedSubject.doAs(AuthenticatedSubject.java:321) at weblogic.security.service.SecurityManager.runAs(SecurityManager.java:120) at weblogic.servlet.internal.EventsManager.notifyContextCreatedEvent(EventsManager.java:181) at weblogic.servlet.internal.WebAppServletContext.preloadResources(WebAppServletContext.java:1870) at weblogic.servlet.internal.WebAppServletContext.start(WebAppServletContext.java:3155) at weblogic.servlet.internal.WebAppModule.startContexts(WebAppModule.java:1518) at weblogic.servlet.internal.WebAppModule.start(WebAppModule.java:487) at weblogic.application.internal.flow.ModuleStateDriver$3.next(ModuleStateDriver.java:427) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.flow.ModuleStateDriver.start(ModuleStateDriver.java:119) at weblogic.application.internal.flow.ScopedModuleDriver.start(ScopedModuleDriver.java:201) at weblogic.application.internal.flow.ModuleListenerInvoker.start(ModuleListenerInvoker.java:249) at weblogic.application.internal.flow.ModuleStateDriver$3.next(ModuleStateDriver.java:427) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.flow.ModuleStateDriver.start(ModuleStateDriver.java:119) at weblogic.application.internal.flow.StartModulesFlow.activate(StartModulesFlow.java:28) at weblogic.application.internal.BaseDeployment$2.next(BaseDeployment.java:672) at weblogic.application.utils.StateMachineDriver.nextState(StateMachineDriver.java:52) at weblogic.application.internal.BaseDeployment.activate(BaseDeployment.java:212) at weblogic.application.internal.EarDeployment.activate(EarDeployment.java:59) at weblogic.application.internal.DeploymentStateChecker.activate(DeploymentStateChecker.java:161) at weblogic.deploy.internal.targetserver.AppContainerInvoker.activate(AppContainerInvoker.java:79) at weblogic.deploy.internal.targetserver.operations.AbstractOperation.activate(AbstractOperation.java:569) at weblogic.deploy.internal.targetserver.operations.ActivateOperation.activateDeployment(ActivateOperation.java:150) at weblogic.deploy.internal.targetserver.operations.ActivateOperation.doCommit(ActivateOperation.java:116) at weblogic.deploy.internal.targetserver.operations.StartOperation.doCommit(StartOperation.java:149) at weblogic.deploy.internal.targetserver.operations.AbstractOperation.commit(AbstractOperation.java:323) at weblogic.deploy.internal.targetserver.DeploymentManager.handleDeploymentCommit(DeploymentManager.java:844) at weblogic.deploy.internal.targetserver.DeploymentManager.activateDeploymentList(DeploymentManager.java:1249) at weblogic.deploy.internal.targetserver.DeploymentManager.handleCommit(DeploymentManager.java:440) at weblogic.deploy.internal.targetserver.DeploymentServiceDispatcher.commit(DeploymentServiceDispatcher.java:164) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer.doCommitCallback(DeploymentReceiverCallbackDeliverer.java:195) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer.access$100(DeploymentReceiverCallbackDeliverer.java:13) at weblogic.deploy.service.internal.targetserver.DeploymentReceiverCallbackDeliverer$2.run(DeploymentReceiverCallbackDeliverer.java:69) at weblogic.work.SelfTuningWorkManagerImpl$WorkAdapterImpl.run(SelfTuningWorkManagerImpl.java:545) at weblogic.work.ExecuteThread.execute(ExecuteThread.java:256) at weblogic.work.ExecuteThread.run(ExecuteThread.java:221)

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• Oracle BI and XS Energy Drinks – Don’t Miss the Amway Presentation!

  - by Maria Forney

  Amway is a global leader in the direct sales industry with $10.9B in annual sales in more than 100 countries and territories. The company has implemented a global BI framework that provides accurate, consistent, and timely insights to support global, regional and local analytical research, business planning, performance measurement and assessment. Oracle BI EE is used by 1500 employees across Amway sales, marketing, finance, and supply chain business units as well as Amway affiliates in Europe, Russia, South Africa, Japan, Australia, Latin America, Malaysia, Vietnam, and Indonesia. Last week, I spoke with Lead Data Analyst with Amway Global Sales, Dan Arganbright, and IT Manager with Amway BI Competency Center, Mike Olson, about their upcoming presentation at Oracle OpenWorld in San Francisco. Scheduled during a prime speaking slot on Monday, October 1 at 12:15pm in Moscone West, 2007, Dan and Mike will discuss their experience building Amway’s Distributor Consulting solution, powered by Oracle BI EE. You can find more information here. As background, Amway offers people an opportunity to own their own businesses and consumers exclusive products in health and wellness, beauty and home care.  The Amway internal Sales organization is charged with consulting leadership-level Distributors to help them with data insights and ultimately grow their business. Until recently, this was a resource-intense process of gathering and formatting data. In some markets, it took over 40 hours to collect the data and produce the analysis needed for one consultation session. Amway began its global BI journey in 2006 and since then the company has migrated from having multiple technology providers and integration points to an integrated strategic vendor approach. Today, the company has standardized on Oracle technology for BI.  Amway has achieved cost savings through the retirement of redundant technology platforms. In addition, Mike’s organization has led the charge to align disparate BI organizations into a BI Competency Center.  The following diagram highlights the simplicity of the standardized architecture of Amway today. Dubbed Distributor Consulting, Amway has developed a BI solution using the Oracle technology stack to help Distributor leaders grow their businesses. The Distributor Consulting solution provides over 40 metrics for Sales staff to provide data-driven insights on the Distributors and organizations they support.  Using Oracle BI EE, Exadata, and Oracle Data Integrator, Amway provides customized and personalized business intelligence, and the Oracle BI EE dashboards were developed by the Amway Sales organization, which demonstrates business empowerment of the technology. Amway is also leveraging the power of BI to drive business growth in all of its markets.  A new set of Distributor Segmentation metrics are enabling a better understanding of distributor behaviors. A Global Scorecard that Amway developed provides key metrics at a market and global level for executive-level discussions. Product Analysis teams can now highlight repeat purchase rates, product penetration and the success of CRM campaigns. In the words of Dan and Mike, the addition of Exadata 11 months ago has been “a game changer.”  Amway has been able to dramatically reduce complexity, improve performance and increase business productivity and cost savings. For example, the number of indexes on the global data warehouse was reduced from more than 1,000 to less than 20.  Pulling data for the highest level distributors or the largest markets in the company now can be done in minutes instead of hours.  As a result, IT has shifted from performance tuning and keeping the system operational to higher-value business-focused activities. •       “The distributors that have been introduced to the BI reports have found them extremely helpful. Because they have never had this kind of information before, when they were presented with the reports, they wanted to take action immediately!”  -     Sales Development Manager in Latin America Without giving away more, the Amway case study presentation will be one of the unique customer sessions at OpenWorld this year. Speakers Dan Arganbright and Mike Olson have planned an interactive and entertaining session on Monday October 1 at 12:15pm in Moscone West, 2007. I’ll see you there!

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• Oracle BI and XS Energy Drinks – Don’t Miss the Amway Presentation!

  - by Michelle Kimihira

  By Maria Forney Amway is a global leader in the direct sales industry with $10.9B in annual sales in more than 100 countries and territories. The company has implemented a global BI framework that provides accurate, consistent, and timely insights to support global, regional and local analytical research, business planning, performance measurement and assessment. Oracle BI EE is used by 1500 employees across Amway sales, marketing, finance, and supply chain business units as well as Amway affiliates in Europe, Russia, South Africa, Japan, Australia, Latin America, Malaysia, Vietnam, and Indonesia. Last week, I spoke with Lead Data Analyst with Amway Global Sales, Dan Arganbright, and IT Manager with Amway BI Competency Center, Mike Olson, about their upcoming presentation at Oracle OpenWorld in San Francisco. Scheduled during a prime speaking slot on Monday, October 1 at 12:15pm in Moscone West, 2007, Dan and Mike will discuss their experience building Amway’s Distributor Consulting solution, powered by Oracle BI EE. You can find more information here. As background, Amway offers people an opportunity to own their own businesses and consumers exclusive products in health and wellness, beauty and home care.  The Amway internal Sales organization is charged with consulting leadership-level Distributors to help them with data insights and ultimately grow their business. Until recently, this was a resource-intense process of gathering and formatting data. In some markets, it took over 40 hours to collect the data and produce the analysis needed for one consultation session. Amway began its global BI journey in 2006 and since then the company has migrated from having multiple technology providers and integration points to an integrated strategic vendor approach. Today, the company has standardized on Oracle technology for BI.  Amway has achieved cost savings through the retirement of redundant technology platforms. In addition, Mike’s organization has led the charge to align disparate BI organizations into a BI Competency Center.  The following diagram highlights the simplicity of the standardized architecture of Amway today. Dubbed Distributor Consulting, Amway has developed a BI solution using the Oracle technology stack to help Distributor leaders grow their businesses. The Distributor Consulting solution provides over 40 metrics for Sales staff to provide data-driven insights on the Distributors and organizations they support.  Using Oracle BI EE, Exadata, and Oracle Data Integrator, Amway provides customized and personalized business intelligence, and the Oracle BI EE dashboards were developed by the Amway Sales organization, which demonstrates business empowerment of the technology. Amway is also leveraging the power of BI to drive business growth in all of its markets.  A new set of Distributor Segmentation metrics are enabling a better understanding of distributor behaviors. A Global Scorecard that Amway developed provides key metrics at a market and global level for executive-level discussions. Product Analysis teams can now highlight repeat purchase rates, product penetration and the success of CRM campaigns. In the words of Dan and Mike, the addition of Exadata 11 months ago has been “a game changer.”  Amway has been able to dramatically reduce complexity, improve performance and increase business productivity and cost savings. For example, the number of indexes on the global data warehouse was reduced from more than 1,000 to less than 20.  Pulling data for the highest level distributors or the largest markets in the company now can be done in minutes instead of hours.  As a result, IT has shifted from performance tuning and keeping the system operational to higher-value business-focused activities. •       “The distributors that have been introduced to the BI reports have found them extremely helpful. Because they have never had this kind of information before, when they were presented with the reports, they wanted to take action immediately!”  -     Sales Development Manager in Latin America Without giving away more, the Amway case study presentation will be one of the unique customer sessions at OpenWorld this year. Speakers Dan Arganbright and Mike Olson have planned an interactive and entertaining session on Monday October 1 at 12:15pm in Moscone West, 2007. I’ll see you there!

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• Join our Marketing Intelligence Team in Dublin!

  - by jessica.ebbelaar

  Do you want to work with the brightest minds in the industry? Want to be part of a global team that’s changing the way the world does business? Then Oracle is the place for YOU. Join now as a Marketing Intelligence Representative. You will have the opportunity to develop within the role through working alongside the Business Development, Sales and Marketing teams within Oracle. The Marketing Intelligence Group is viewed as a true talent pool for the Business Development and Sales Teams. Oracle offers a structured training programme for Marketing Intelligence Representatives and Business Development Consultants including our approved sales certified training methodology along with regular product training. Miriam started her career as a Marketing Intelligence Representative six years ago, and shares what she has learned and how her career is progressing. My Career Path at Oracle: June 2005 – October 2005: Profiler in the Marketing Intelligence Team November 2005 - October 2006: Team Leader for MIT November 2006 - February 2008: Business Development Consultant Iberia March 2008 - December 2010: Lead Management Specialist Currently: Sales Program Manager for Iberia & Benelux What did you learn from your role in the Market Intelligence Team Being a Profiler helped me to understand how an organisation works, from the beginning to the end. It is like being in University but being paid! The three key things I learnt in this role are: Knowledge of customers: You are on the phone with over 70 customers daily. Not only does this give you an overview of the IT infrastructure of the customers companies but also how to manage their questions and rejections. Essentially you are learning how to convert their pain and complaints into business opportunities. Knowledge of Oracle: As a Profiler you get an excellent overview of how Oracle works internally, from Marketing to Sales, without forgetting the Operations Team. Knowledge about yourself: As a Profiler I learnt how to work outside of my comfort zone, there is a new challenge almost every day but Oracle are there to support you every step of the way. Oracle really invests in developing the MIT Team and as a Profiler you can expect product and sales training on a monthly basis. How did you progress from MIT to Business Development Group (BDG)? I made sure that my manager knew from the very beginning that I was keen to progress at Oracle and I was set very clear objectives to help me reach my goal.  My manager was very supportive and ensured I received all the training I needed. After I became a Team Leader of Profiling, I moved to an Iberia BDG position. How you feel your experience in MI has helped you in your current role? I truly believe that the MI position gives you a great overview of Oracle and this has really helped me in my current position.  I am the Sales Program Manager for IBERIA & Benelux and in my campaigns I need to target the right companies and the right job specs.  My time in the Market Intelligence team really helped me to understand how to focus and target my campaigns so I know I don’t miss any business opportunities! How would you sum up your Oracle experience? Oracle is a big organisation with big opportunities. With the right skills and with the great training programs that Oracle offer, the only limit is you! If you have any questions related to this article feel free to contact [email protected] You can find all our job opportunities via http://campus.oracle.com. Tags van Technorati: Marketing Intelligence,Benelux,Iberia,Profiler,Business Development,Sales Representatives,BDG,Business Development Group,opportunities,Oracle

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• Guest blog: A Closer Look at Oracle Price Analytics by Will Hutchinson

  - by Takin Babaei

  Overview:  Price Analytics helps companies understand how much of each sale goes into discounts, special terms, and allowances. This visibility lets sales management see the panoply of discounts and start seeing whether each discount drives desired behavior. In Price Analytics monitors parts of the quote-to-order process, tracking quotes, including the whole price waterfall and seeing which result in orders. The “price waterfall” shows all discounts between list price and “pocket price”. Pocket price is the final price the vendor puts in its pocket after all discounts are taken. The value proposition: Based on benchmarks from leading consultancies and companies I have talked to, where they have studied the effects of discounting and started enforcing what many of them call “discount discipline”, they find they can increase the pocket price by 0.8-3%. Yes, in today’s zero or negative inflation environment, one can, through better monitoring of discounts, collect what amounts to a price rise of a few percent. We are not talking about selling more product, merely about collecting a higher pocket price without decreasing quantities sold. Higher prices fall straight to the bottom line. The best reference I have ever found for understanding this phenomenon comes from an article from the September-October 1992 issue of Harvard Business Review called “Managing Price, Gaining Profit” by Michael Marn and Robert Rosiello of McKinsey & Co. They describe the outsized impact price management has on bottom line performance compared to selling more product or cutting variable or fixed costs. Price Analytics manages what Marn and Rosiello call “transaction pricing”, namely the prices of a given transaction, as opposed to what is on the price list or pricing according to the value received. They make the point that if the vendor does not manage the price waterfall, customers will, to the vendor’s detriment. It also discusses its findings that in companies it studied, there was no correlation between discount levels and any indication of customer value. I urge you to read this article. What Price Analytics does: Price analytics looks at quotes the company issues and tracks them until either the quote is accepted or rejected or it expires. There are prebuilt adapters for EBS and Siebel as well as a universal adapter. The target audience includes pricing analysts, product managers, sales managers, and VP’s of sales, marketing, finance, and sales operations. It tracks how effective discounts have been, the win rate on quotes, how well pricing policies have been followed, customer and product profitability, and customer performance against commitments. It has the concept of price waterfall, the deal lifecycle, and price segmentation built into the product. These help product and sales managers understand their pricing and its effectiveness on driving revenue and profit. They also help understand how terms are adhered to during negotiations. They also help people understand what segments exist and how well they are adhered to. To help your company increase its profits and revenues, I urge you to look at this product. If you have questions, please contact me. Will HutchinsonMaster Principal Sales Consultant – Analytics, Oracle Corp. Will Hutchinson has worked in the business intelligence and data warehousing for over 25 years. He started building data warehouses in 1986 at Metaphor, advancing to running Metaphor UK’s sales consulting area. He also worked in A.T. Kearney’s business intelligence practice for over four years, running projects and providing training to new consultants in the IT practice. He also worked at Informatica and then Siebel, before coming to Oracle with the Siebel acquisition. He became Master Principal Sales Consultant in 2009. He has worked on developing ROI and TCO models for business intelligence for over ten years. Mr. Hutchinson has a BS degree in Chemical Engineering from Princeton University and an MBA in Finance from the University of Chicago.

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• Four Easy Ways to Save a Rocky CRM Relationship

  - by Divya Malik

   Today, I am pleased to introduce our guest blogger Luke Christianson. Luke is  an Application Sales rep based out of Minneapolis, MN.  You can find him on LinkedIn and follow him on Twitter. In any relationship, sooner or later, the excitement fades away.  The honeymoon period gives way to the old routines you had, before you committed to each other and you eventually begin doing things apart from one another.  I’m not talking about a marriage…  Well, I guess I am.Commitment to a CRM tool and building a deep and lasting relationship is not much different than the basics of a traditional love story.  After your controlled CRM pilot program, and maybe the National Sales Meeting where you couldn’t escape those three wonderful letters, CRM, you will soon find that if you haven’t designed an environment where it’s going to enable your reps to make more money, the relationship is doomed.   . If you’re currently in a dysfunctional CRM relationship, here are 4 simple tips to re-engaging users and getting that spark back. Shadow a Sales Rep:   Chances are you can find out exactly what is preventing your sales reps from using the application by simply watching how they go about their day.  Sales reps are driven by money, not by additional administrative duties.  Your system needs to be setup so that they can get the information they need quickly, facilitate making key updates and run their business out of one easy-to-use application.  Increase your sales team’s productivity by 5% automatically:    Cancel the weekly forecast calls with your reps and require them update their opportunities in CRM.  Something else that I’ve seen work extremely well, is when you do Monthly or Quarterly reviews, do not let your sales reps bring anything into the room with them; no spreadsheets, notebooks, or computers.  Everything they need to tell you should be able to be put into CRM and fully accessible by the Sales Manager at any time.  Tool time:      Make sure the tools that you have selected meet both your short-term goals and your long term goals.   You need tools that can adapt like your business does.  You probably can’t wait two months for an update to a picklist value or for the addition of a simple workflow rule.  Do you feel the tools that are in place can create the experience you want for your users? and finally, if all else fails... Keep It Simple, Stupid:     Do you really need to require 15 fields to create an Opportunity?  Do you need to clutter the interface with different reports that don’t add daily value?  Most CRM systems on the market today are flexible enough today that your admin could clean up most of the unnecessary interface ‘noise’ in a few hours.  If they're not, see #3. Every strong relationship can be tedious at times, you’ll fight and eventually make amends, you may even threaten to upgrade to a newer model…  But be patient and think about what you want to achieve and you’ll find a partner for life.

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• Everytime user types , in my text box i want it to become ',' or help me do it using a parameter

  - by MyHeadHurts

  I am using a vb.net textbox to become part of my IN sql statement in my program I tryed to use a parameter and it didn't work here is my code TextBox1.Text = "'Cruises','Caribbean and Mexico','CentralSouth America', 'Europe','Far East','France','Italy','London/UK','Middle East/Africa','South Pacific','Spain/Portugal','USA/Canada'" the default value of my textbox although the user can edit the textbox, but they would need to type the ',' which i would rather them just type , . and my other code is If RadioButtonList1.SelectedValue = "Sales" And CheckBox1.Checked = False Then 'saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, dbo.B605SaleAsOfAdvancedMaster.AsOFSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, dbo.B605SaleAsOfAdvancedMaster.YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, dbo.B604SalesAsOfAdvanced.Sales AS CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =" & DropDownList1.SelectedValue & ") AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) order by B605SaleAsOfAdvancedMaster.SDESCR" saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, dbo.B605SaleAsOfAdvancedMaster.AsOFSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, dbo.B605SaleAsOfAdvancedMaster.YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, dbo.B604SalesAsOfAdvanced.Sales AS CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =@Dyyyy) AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) and dbo.B605SaleAsOfAdvancedMaster.SDESCR in ('Cruises','Caribbean and Mexico','CentralSouth America', 'Europe','Far East','France','Italy','London/UK','Middle East/Africa','South Pacific','Spain/Portugal','USA/Canada') order by B605SaleAsOfAdvancedMaster.SDESCR" Label2.Text = "Sales" ElseIf RadioButtonList1.SelectedValue = "NetSales" And CheckBox1.Checked = False Then saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, (ISNULL(dbo.B605SaleAsOfAdvancedMaster.AsOFNET,0) + (ISNULL(dbo.B605SaleAsOfAdvancedMaster.AsOFOther,0))) as AsofSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, (ISNULL(dbo.B605SaleAsOfAdvancedMaster.YENET,0) + (ISNULL(dbo.B605SaleAsOfAdvancedMaster.YEOther,0))) as YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, (ISNULL(dbo.B604SalesAsOfAdvanced.netSales,0) + (ISNULL(dbo.B604SalesAsOfAdvanced.OtherSales,0))) as CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =@Dyyyy) AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) and dbo.B605SaleAsOfAdvancedMaster.SDESCR in ('Cruises','Caribbean and Mexico','CentralSouth America', 'Europe','Far East','France','Italy','London/UK','Middle East/Africa','South Pacific','Spain/Portugal','USA/Canada') order by B605SaleAsOfAdvancedMaster.SDESCR" Label2.Text = "Net Sales" ElseIf RadioButtonList1.SelectedValue = "INSSales" And CheckBox1.Checked = False Then saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, ISNULL(dbo.B605SaleAsOfAdvancedMaster.AsOFINS,0)as AsofSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, ISNULL(dbo.B605SaleAsOfAdvancedMaster.YEINS,0) as YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, ISNULL(dbo.B604SalesAsOfAdvanced.INSSales,0) as CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =@Dyyyy) AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) and dbo.B605SaleAsOfAdvancedMaster.SDESCR in ('Cruises','Caribbean and Mexico','CentralSouth America', 'Europe','Far East','France','Italy','London/UK','Middle East/Africa','South Pacific','Spain/Portugal','USA/Canada') order by B605SaleAsOfAdvancedMaster.SDESCR" Label2.Text = "Insurance Sales" ElseIf RadioButtonList1.SelectedValue = "CXSales" And CheckBox1.Checked = False Then saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, ISNULL(dbo.B605SaleAsOfAdvancedMaster.AsOFCX,0)as AsofSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, ISNULL(dbo.B605SaleAsOfAdvancedMaster.YECX,0) as YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, ISNULL(dbo.B604SalesAsOfAdvanced.CXSales,0) as CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =@Dyyyy) AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) and dbo.B605SaleAsOfAdvancedMaster.SDESCR in ('Cruises','Caribbean and Mexico','CentralSouth America', 'Europe','Far East','France','Italy','London/UK','Middle East/Africa','South Pacific','Spain/Portugal','USA/Canada') order by B605SaleAsOfAdvancedMaster.SDESCR" Label2.Text = "Canceled Sales" ElseIf RadioButtonList1.SelectedValue = "Sales" And CheckBox1.Checked = True Then saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, dbo.B605SaleAsOfAdvancedMaster.AsOFSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, dbo.B605SaleAsOfAdvancedMaster.YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, dbo.B604SalesAsOfAdvanced.Sales AS CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =@Dyyyy) AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) and dbo.B605SaleAsOfAdvancedMaster.SDESCR in (" & TextBox1.Text & ") order by B605SaleAsOfAdvancedMaster.SDESCR" Label2.Text = "Sales" ElseIf RadioButtonList1.SelectedValue = "NetSales" And CheckBox1.Checked = True Then saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, (ISNULL(dbo.B605SaleAsOfAdvancedMaster.AsOFNET,0) + (ISNULL(dbo.B605SaleAsOfAdvancedMaster.AsOFOther,0))) as AsofSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, (ISNULL(dbo.B605SaleAsOfAdvancedMaster.YENET,0) + (ISNULL(dbo.B605SaleAsOfAdvancedMaster.YEOther,0))) as YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, (ISNULL(dbo.B604SalesAsOfAdvanced.netSales,0) + (ISNULL(dbo.B604SalesAsOfAdvanced.OtherSales,0))) as CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =@Dyyyy) AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) and dbo.B605SaleAsOfAdvancedMaster.SDESCR in (" & TextBox1.Text & ") order by B605SaleAsOfAdvancedMaster.SDESCR" Label2.Text = "Net Sales" ElseIf RadioButtonList1.SelectedValue = "INSSales" And CheckBox1.Checked = True Then saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, ISNULL(dbo.B605SaleAsOfAdvancedMaster.AsOFINS,0)as AsofSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, ISNULL(dbo.B605SaleAsOfAdvancedMaster.YEINS,0) as YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, ISNULL(dbo.B604SalesAsOfAdvanced.INSSales,0) as CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =@Dyyyy) AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) and dbo.B605SaleAsOfAdvancedMaster.SDESCR in (" & TextBox1.Text & ") order by B605SaleAsOfAdvancedMaster.SDESCR" Label2.Text = "Insurance Sales" ElseIf RadioButtonList1.SelectedValue = "CXSales" And CheckBox1.Checked = True Then saocmd1.CommandText = "SELECT dbo.B605SaleAsOfAdvancedMaster.SDESCR, dbo.B605SaleAsOfAdvancedMaster.DYYYY, ISNULL(dbo.B605SaleAsOfAdvancedMaster.AsOFCX,0)as AsofSales, dbo.B605SaleAsOfAdvancedMaster.ASOFPAX, ISNULL(dbo.B605SaleAsOfAdvancedMaster.YECX,0) as YESales, dbo.B605SaleAsOfAdvancedMaster.YEPAX, ISNULL(dbo.B604SalesAsOfAdvanced.CXSales,0) as CurrentSales, dbo.B604SalesAsOfAdvanced.PAX AS CurrentPAX FROM B604SalesAsOfAdvanced INNER JOIN B605SaleAsOfAdvancedMaster ON dbo.B605SaleAsOfAdvancedMaster.SDESCR = B604SalesAsOfAdvanced.SDESCR WHERE (B605SaleAsOfAdvancedMaster.DYYYY =@Dyyyy) AND (B604SalesAsOfAdvanced.DYYYY = (DatePart(year, GetDate()) +1)) and dbo.B605SaleAsOfAdvancedMaster.SDESCR in (" & TextBox1.Text & ") order by B605SaleAsOfAdvancedMaster.SDESCR" Label2.Text = "Canceled Sales" End If Basically what is happening is, if a certain radio button is selected and the user didn't click the checkbox the default regions are included and they are hardcoded because the query runs much faster. if the user did click the checkbox then the textbox where they type the specific regions shows up and it will run the query that includes the dbo.B605SaleAsOfAdvancedMaster.SDESCR in (" & TextBox1.Text & ") If you can somehow do this using parameters and not with the textbox1.text in the query it will run much faster for me thanks for your help

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• Heaps of Trouble?

  - by Paul White NZ

  If you’re not already a regular reader of Brad Schulz’s blog, you’re missing out on some great material.  In his latest entry, he is tasked with optimizing a query run against tables that have no indexes at all.  The problem is, predictably, that performance is not very good.  The catch is that we are not allowed to create any indexes (or even new statistics) as part of our optimization efforts. In this post, I’m going to look at the problem from a slightly different angle, and present an alternative solution to the one Brad found.  Inevitably, there’s going to be some overlap between our entries, and while you don’t necessarily need to read Brad’s post before this one, I do strongly recommend that you read it at some stage; he covers some important points that I won’t cover again here. The Example We’ll use data from the AdventureWorks database, copied to temporary unindexed tables.  A script to create these structures is shown below: CREATE TABLE #Custs ( CustomerID INTEGER NOT NULL, TerritoryID INTEGER NULL, CustomerType NCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, ); GO CREATE TABLE #Prods ( ProductMainID INTEGER NOT NULL, ProductSubID INTEGER NOT NULL, ProductSubSubID INTEGER NOT NULL, Name NVARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, ); GO CREATE TABLE #OrdHeader ( SalesOrderID INTEGER NOT NULL, OrderDate DATETIME NOT NULL, SalesOrderNumber NVARCHAR(25) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, CustomerID INTEGER NOT NULL, ); GO CREATE TABLE #OrdDetail ( SalesOrderID INTEGER NOT NULL, OrderQty SMALLINT NOT NULL, LineTotal NUMERIC(38,6) NOT NULL, ProductMainID INTEGER NOT NULL, ProductSubID INTEGER NOT NULL, ProductSubSubID INTEGER NOT NULL, ); GO INSERT #Custs ( CustomerID, TerritoryID, CustomerType ) SELECT C.CustomerID, C.TerritoryID, C.CustomerType FROM AdventureWorks.Sales.Customer C WITH (TABLOCK); GO INSERT #Prods ( ProductMainID, ProductSubID, ProductSubSubID, Name ) SELECT P.ProductID, P.ProductID, P.ProductID, P.Name FROM AdventureWorks.Production.Product P WITH (TABLOCK); GO INSERT #OrdHeader ( SalesOrderID, OrderDate, SalesOrderNumber, CustomerID ) SELECT H.SalesOrderID, H.OrderDate, H.SalesOrderNumber, H.CustomerID FROM AdventureWorks.Sales.SalesOrderHeader H WITH (TABLOCK); GO INSERT #OrdDetail ( SalesOrderID, OrderQty, LineTotal, ProductMainID, ProductSubID, ProductSubSubID ) SELECT D.SalesOrderID, D.OrderQty, D.LineTotal, D.ProductID, D.ProductID, D.ProductID FROM AdventureWorks.Sales.SalesOrderDetail D WITH (TABLOCK); The query itself is a simple join of the four tables: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #Prods P JOIN #OrdDetail D ON P.ProductMainID = D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID JOIN #OrdHeader H ON D.SalesOrderID = H.SalesOrderID JOIN #Custs C ON H.CustomerID = C.CustomerID ORDER BY P.ProductMainID ASC OPTION (RECOMPILE, MAXDOP 1); Remember that these tables have no indexes at all, and only the single-column sampled statistics SQL Server automatically creates (assuming default settings).  The estimated query plan produced for the test query looks like this (click to enlarge): The Problem The problem here is one of cardinality estimation – the number of rows SQL Server expects to find at each step of the plan.  The lack of indexes and useful statistical information means that SQL Server does not have the information it needs to make a good estimate.  Every join in the plan shown above estimates that it will produce just a single row as output.  Brad covers the factors that lead to the low estimates in his post. In reality, the join between the #Prods and #OrdDetail tables will produce 121,317 rows.  It should not surprise you that this has rather dire consequences for the remainder of the query plan.  In particular, it makes a nonsense of the optimizer’s decision to use Nested Loops to join to the two remaining tables.  Instead of scanning the #OrdHeader and #Custs tables once (as it expected), it has to perform 121,317 full scans of each.  The query takes somewhere in the region of twenty minutes to run to completion on my development machine. A Solution At this point, you may be thinking the same thing I was: if we really are stuck with no indexes, the best we can do is to use hash joins everywhere. We can force the exclusive use of hash joins in several ways, the two most common being join and query hints.  A join hint means writing the query using the INNER HASH JOIN syntax; using a query hint involves adding OPTION (HASH JOIN) at the bottom of the query.  The difference is that using join hints also forces the order of the join, whereas the query hint gives the optimizer freedom to reorder the joins at its discretion. Adding the OPTION (HASH JOIN) hint results in this estimated plan: That produces the correct output in around seven seconds, which is quite an improvement!  As a purely practical matter, and given the rigid rules of the environment we find ourselves in, we might leave things there.  (We can improve the hashing solution a bit – I’ll come back to that later on). Faster Nested Loops It might surprise you to hear that we can beat the performance of the hash join solution shown above using nested loops joins exclusively, and without breaking the rules we have been set. The key to this part is to realize that a condition like (A = B) can be expressed as (A <= B) AND (A >= B).  Armed with this tremendous new insight, we can rewrite the join predicates like so: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #OrdDetail D JOIN #OrdHeader H ON D.SalesOrderID >= H.SalesOrderID AND D.SalesOrderID <= H.SalesOrderID JOIN #Custs C ON H.CustomerID >= C.CustomerID AND H.CustomerID <= C.CustomerID JOIN #Prods P ON P.ProductMainID >= D.ProductMainID AND P.ProductMainID <= D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID ORDER BY D.ProductMainID OPTION (RECOMPILE, LOOP JOIN, MAXDOP 1, FORCE ORDER); I’ve also added LOOP JOIN and FORCE ORDER query hints to ensure that only nested loops joins are used, and that the tables are joined in the order they appear.  The new estimated execution plan is: This new query runs in under 2 seconds. Why Is It Faster? The main reason for the improvement is the appearance of the eager Index Spools, which are also known as index-on-the-fly spools.  If you read my Inside The Optimiser series you might be interested to know that the rule responsible is called JoinToIndexOnTheFly. An eager index spool consumes all rows from the table it sits above, and builds a index suitable for the join to seek on.  Taking the index spool above the #Custs table as an example, it reads all the CustomerID and TerritoryID values with a single scan of the table, and builds an index keyed on CustomerID.  The term ‘eager’ means that the spool consumes all of its input rows when it starts up.  The index is built in a work table in tempdb, has no associated statistics, and only exists until the query finishes executing. The result is that each unindexed table is only scanned once, and just for the columns necessary to build the temporary index.  From that point on, every execution of the inner side of the join is answered by a seek on the temporary index – not the base table. A second optimization is that the sort on ProductMainID (required by the ORDER BY clause) is performed early, on just the rows coming from the #OrdDetail table.  The optimizer has a good estimate for the number of rows it needs to sort at that stage – it is just the cardinality of the table itself.  The accuracy of the estimate there is important because it helps determine the memory grant given to the sort operation.  Nested loops join preserves the order of rows on its outer input, so sorting early is safe.  (Hash joins do not preserve order in this way, of course). The extra lazy spool on the #Prods branch is a further optimization that avoids executing the seek on the temporary index if the value being joined (the ‘outer reference’) hasn’t changed from the last row received on the outer input.  It takes advantage of the fact that rows are still sorted on ProductMainID, so if duplicates exist, they will arrive at the join operator one after the other. The optimizer is quite conservative about introducing index spools into a plan, because creating and dropping a temporary index is a relatively expensive operation.  It’s presence in a plan is often an indication that a useful index is missing. I want to stress that I rewrote the query in this way primarily as an educational exercise – I can’t imagine having to do something so horrible to a production system. Improving the Hash Join I promised I would return to the solution that uses hash joins.  You might be puzzled that SQL Server can create three new indexes (and perform all those nested loops iterations) faster than it can perform three hash joins.  The answer, again, is down to the poor information available to the optimizer.  Let’s look at the hash join plan again: Two of the hash joins have single-row estimates on their build inputs.  SQL Server fixes the amount of memory available for the hash table based on this cardinality estimate, so at run time the hash join very quickly runs out of memory. This results in the join spilling hash buckets to disk, and any rows from the probe input that hash to the spilled buckets also get written to disk.  The join process then continues, and may again run out of memory.  This is a recursive process, which may eventually result in SQL Server resorting to a bailout join algorithm, which is guaranteed to complete eventually, but may be very slow.  The data sizes in the example tables are not large enough to force a hash bailout, but it does result in multiple levels of hash recursion.  You can see this for yourself by tracing the Hash Warning event using the Profiler tool. The final sort in the plan also suffers from a similar problem: it receives very little memory and has to perform multiple sort passes, saving intermediate runs to disk (the Sort Warnings Profiler event can be used to confirm this).  Notice also that because hash joins don’t preserve sort order, the sort cannot be pushed down the plan toward the #OrdDetail table, as in the nested loops plan. Ok, so now we understand the problems, what can we do to fix it?  We can address the hash spilling by forcing a different order for the joins: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #Prods P JOIN #Custs C JOIN #OrdHeader H ON H.CustomerID = C.CustomerID JOIN #OrdDetail D ON D.SalesOrderID = H.SalesOrderID ON P.ProductMainID = D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID ORDER BY D.ProductMainID OPTION (MAXDOP 1, HASH JOIN, FORCE ORDER); With this plan, each of the inputs to the hash joins has a good estimate, and no hash recursion occurs.  The final sort still suffers from the one-row estimate problem, and we get a single-pass sort warning as it writes rows to disk.  Even so, the query runs to completion in three or four seconds.  That’s around half the time of the previous hashing solution, but still not as fast as the nested loops trickery. Final Thoughts SQL Server’s optimizer makes cost-based decisions, so it is vital to provide it with accurate information.  We can’t really blame the performance problems highlighted here on anything other than the decision to use completely unindexed tables, and not to allow the creation of additional statistics. I should probably stress that the nested loops solution shown above is not one I would normally contemplate in the real world.  It’s there primarily for its educational and entertainment value.  I might perhaps use it to demonstrate to the sceptical that SQL Server itself is crying out for an index. Be sure to read Brad’s original post for more details.  My grateful thanks to him for granting permission to reuse some of his material. Paul White Email: [email protected] Twitter: @PaulWhiteNZ

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• My Ubuntu 12.10 will not start

  - by Adam Sales

  I'll boot my computer, then it'll get going, go to a purple screen and then my monitor goes to sleep, i've restarted it several times, and tried to get it to boot, no matter what it keeps going to the black screen. I've tried reinstalling ubuntu, i've even tried both 64 bit, and 32 bit. i have not once got it to a normal boot successfully either.It just won't run in normal boot, so i'm resorted to using safe mode, please help me, idk what to do.

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• Apache 2.2.21 installation on Linux 6 but got error while accessing in browser

  - by JRanjan

  I am very new to linux. I have install apache 2.2.21 on linux 6 platform. While i am using ./apachectl start or ./apachectl -k start command it shows that apache is started. But while i am trying to to access apache default page in any browser using " http://:8080 " it shows page cannot be displayed. Can any one help me on this issue ??????? Plz its urgent.. I am also enclosing the error_log file as below: error_log file [Thu Nov 24 08:57:23 2011] [notice] Apache/2.2.21 (Unix) DAV/2 configured -- resuming normal operations [Fri Nov 25 01:45:58 2011] [notice] caught SIGTERM, shutting down [Fri Nov 25 01:46:12 2011] [notice] Digest: generating secret for digest authentication ... [Fri Nov 25 01:46:12 2011] [notice] Digest: done [Fri Nov 25 01:46:13 2011] [notice] Apache/2.2.21 (Unix) DAV/2 configured -- resuming normal operations [Fri Nov 25 01:54:58 2011] [notice] caught SIGTERM, shutting down [Fri Nov 25 01:55:10 2011] [notice] Digest: generating secret for digest authentication ... [Fri Nov 25 01:55:10 2011] [notice] Digest: done [Fri Nov 25 01:55:11 2011] [notice] Apache/2.2.21 (Unix) DAV/2 configured -- resuming normal operations [Fri Nov 25 01:58:10 2011] [notice] caught SIGTERM, shutting down [Fri Nov 25 01:59:41 2011] [notice] Digest: generating secret for digest authentication ... [Fri Nov 25 01:59:41 2011] [notice] Digest: done [Fri Nov 25 01:59:42 2011] [notice] Apache/2.2.21 (Unix) DAV/2 configured -- resuming normal operations [Fri Nov 25 03:23:14 2011] [notice] caught SIGTERM, shutting down [Fri Nov 25 03:27:36 2011] [notice] Digest: generating secret for digest authentication ... [Fri Nov 25 03:27:36 2011] [notice] Digest: done [Fri Nov 25 03:27:37 2011] [notice] Apache/2.2.21 (Unix) DAV/2 configured -- resuming normal operations [Fri Nov 25 08:52:27 2011] [notice] caught SIGTERM, shutting down [Fri Nov 25 08:52:43 2011] [notice] Digest: generating secret for digest authentication ... [Fri Nov 25 08:52:43 2011] [notice] Digest: done [Fri Nov 25 08:52:44 2011] [notice] Apache/2.2.21 (Unix) DAV/2 configured -- resuming normal operations [Fri Nov 25 09:21:39 2011] [notice] caught SIGTERM, shutting down [Fri Nov 25 09:21:57 2011] [notice] Digest: generating secret for digest authentication ... [Fri Nov 25 09:21:57 2011] [notice] Digest: done [Fri Nov 25 09:21:58 2011] [notice] Apache/2.2.21 (Unix) DAV/2 configured -- resuming normal operations [Mon Nov 28 01:06:58 2011] [notice] caught SIGTERM, shutting down [Mon Nov 28 01:07:58 2011] [notice] Digest: generating secret for digest authentication ... [Mon Nov 28 01:07:58 2011] [notice] Digest: done [Mon Nov 28 01:07:59 2011] [notice] Apache/2.2.21 (Unix) DAV/2 configured -- resuming normal operations

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• Using OpenGL drawing operations in an object-oriented setting?

  - by Lion Kabob

  I've been plowing through basic shaders and whatnot for an application I'm writing, and I've been having trouble figuring out a high-level organization for the drawing calls. I'm thinking of having a singleton class which implements a number of basic drawing operations, taking data from "user" classes and passing that to the appropriate opengl calls. I'm wondering how people do this when writing their own applications, as the internet is chock full of basic "Your first shader" tutorials, but very little on suggested organization of drawing code. My particular environment is targeted at iPad/OpenGL ES 2.0, but I think the question stands for most environments.

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• How to plan my web based project before starting code ?

  - by Arsheep

  Me and my friend started working together as partners , we have decided to make Kick-as* website after website. We have the ideas written down like 100's of them (yes we are choosing best and easy among them first). My friend does the layout design and arranging things , and my part is coding and server management. The little problem i am facing is lack of experience in planing a project. What i do is, I just start the code straight away and along with code I make DB, like when i need a table i make it. I know this is very bad approach for a medium sized project. Here at stackoverflow i saw lots of experienced coders. Need to learn a lot from you guys :) . So can you plese help me on how to plan a project and what coding standard/structure/frameworks to be used (I do PHP code). Thanks in advance.

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• How to plan mine web based project before starting code ?

  - by Arsheep

  Me and mine friend started working together as partners , we have decided to make Kick-as* website after website. We have the ideas written down like 100's of them (yes we are choosing best and easy among them first). Mine friend do the layout design and arranging things , and mine part is coding and server management. The little problem i am facing is lack of experience in planing a project .What i do is , i just start the code straight away and along with code I make DB , Like when i need a table i make it. I know this is very bad approach for a medium sized project. Here at stackoverflow i saw lots of experienced coders . Need to learn a lot from you guys :) . So can you plese help me on how to plan a project and what coding standard/structure/frameworks to be used (I do PHP code). Thanks in advance.

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• What is the optimal number of threads for performing IO operations in java?

  - by marc

  In Goetz's "Java Concurrency in Practice", in a footnote on page 101, he writes "For computational problems like this that do not I/O and access no shared data, Ncpu or Ncpu+1 threads yield optimal throughput; more threads do not help, and may in fact degrade performance..." My question is, when performing I/O operations such as file writing, file reading, file deleting, etc, are there guidelines for the number of threads to use to achieve maximum performance? I understand this will be just a guide number, since disk speeds and a host of other factors play into this. Still, I'm wondering: can 20 threads write 1000 separate files to disk faster than 4 threads can on a 4-cpu machine?

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• How to fit more operations to tab bar + navigation bar?

  - by Henry

  I want to use Tabview for my whole app. However in certain view, I have more operations than I can fit in the navigator bar. So I thought of using Toolbar but toolbar should be located at the bottom, right? Toolbar looks weird to be on top of the tabview, and hiding tabview for one view doesn't really make sense. I guess I can go with more buttons in the main view, but any other alternatives? What can one use to add more operation(s) to tabview? Thanks

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• Can Graphical Operations be combined in Qt or any other library ?

  - by Sunny

  Hi, Here is a Scenario, A series of operations that I will call for painting, QPainter p(this); 1). p.fillRect(0,0,320,240, RED_COLOR) 2) p.drawLine(0,0,100,100, BLUE_COLOR) 3) p.fillRect(0,0,320,240, YELLOW_COLOR) Now I want that painter should not draw first FillRect Function. It should not draw line. It should only perform last operation. Is there any way to achive this optimization in Qt. Is this type of drawing/painting optimizations are supported by any library?

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• Query Execution Plan - When is the Where clause executed?

  - by Alex

  I have a query like this (created by LINQ): SELECT [t0].[Id], [t0].[CreationDate], [t0].[CreatorId] FROM [dbo].[DataFTS]('test', 100) AS [t0] WHERE [t0].[CreatorId] = 1 ORDER BY [t0].[RANK] DataFTS is a full-text search table valued function. The query execution plan looks like this: SELECT (0%) - Sort (23%) - Nested Loops (Inner Join) (1%) - Sort (Top N Sort) (25%) - Stream Aggregate (0%) - Stream Aggregate (0%) - Compute Scalar (0%) - Table Valued Function (FullTextMatch) (13%) | | - Clustered Index Seek (38%) Does this mean that the WHERE clause ([CreatorId] = 1) is executed prior to the TVF ( full text search) or after the full text search? Thank you.

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• Python code to do csv file row entries comparison operations and count the number of times row value

  - by Venomancer

  have an excel based CSV file with two columns (or rows, Pythonically) that I am working on. What I need to do is to perform some operations so that I can compare the two data entries in each 'row'. To be more precise, one column has constant numbers all the way down, whereas the other column has varying values. So I need to count the number of times the varying column data entry values crosses the constant value on the other column. For example, fro the csv file i have two columns: Varying Column; Constant Column 24 25 26 25 crossed 27 25 26 25 25.5 25 23 25 crossed 26 25 crossed Thus, the varying column data entries have crossed 25 three times. I need to generate a code that can count the number of the crosses. Please do help out, Thanks.

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• What is the difference between bit shifting and arithmetical operations?

  - by Espuz

  int aNumber; aNumber = aValue / 2; aNumber = aValue >> 1; aNumber = aValue * 2; aNumber = aValue << 1; aNumber = aValue / 4; aNumber = aValue >> 2; aNumber = aValue * 8; aNumber = aValue << 4; // etc. Whats is the "best" way to do operations? When is better to use bit shifting?

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• Change $mailTo variable based on select input value (array)

  - by Dirty Bird Design

  I have the following select list: <form action="mail.php" method="POST"> <select name="foo" id="foo"> <option value="sales">Sales</option> <option value="salesAssist">Sales Assist</option> <option value="billing">Billing</option> <option value="billingAssist">Billing Assist</option> </select> </form> I need to route the $mailTo variable depending on which option they select, Sales and Sales Assist go to [email protected], while Billing and Billing Assist go to [email protected] PHP pseudeo code! <? php $_POST['foo'] if inArray(sales, salesAssist) foo="[email protected]"; else if inArray(billing, billingAssist) foo="[email protected]"; mailTo="foo" ?> I know there is nothing correct about the above, but you can see what I am trying to do, change a variable's value based on the selected value. I don't want to do this with JS, would rather learn more PHP here. Thank you.

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• Why isn't INT more efficient than UNIQUEIDENTIFIER (according to the execution plan)?

  - by ck

  I have a parent table and child table where the columns that join them together are the UNIQUEIDENTIFIER type. The child table has a clustered index on the column that joins it to the parent table (its PK, which is also clustered). I have created a copy of both of these tables but changed the relationship columns to be INTs instead, have rebuilt the indexes so that they are essentially the same structure and can be queried in the same way. When I query for a known 20 records from the parent table, pulling in all the related records from the child tables, I get identical query costs across both, i.e. 50/50 cost for the batches. If this is true, then my giant project to change all of the tables like this appears to be pointless, other than speeding up inserts. Can anyone provide any light on the situation? EDIT: The question is not about which is more efficient, but why is the query execution plan showing both queries as having the same cost?

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• More CPU cores may not always lead to better performance – MAXDOP and query memory distribution in spotlight

  - by sqlworkshops

  More hardware normally delivers better performance, but there are exceptions where it can hinder performance. Understanding these exceptions and working around it is a major part of SQL Server performance tuning.   When a memory allocating query executes in parallel, SQL Server distributes memory to each task that is executing part of the query in parallel. In our example the sort operator that executes in parallel divides the memory across all tasks assuming even distribution of rows. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union.   In reality, how often are column values evenly distributed, think about an example; are employees working for your company distributed evenly across all the Zip codes or mainly concentrated in the headquarters? What happens when you sort result set based on Zip codes? Do all products in the catalog sell equally or are few products hot selling items?   One of my customers tested the below example on a 24 core server with various MAXDOP settings and here are the results:MAXDOP 1: CPU time = 1185 ms, elapsed time = 1188 msMAXDOP 4: CPU time = 1981 ms, elapsed time = 1568 msMAXDOP 8: CPU time = 1918 ms, elapsed time = 1619 msMAXDOP 12: CPU time = 2367 ms, elapsed time = 2258 msMAXDOP 16: CPU time = 2540 ms, elapsed time = 2579 msMAXDOP 20: CPU time = 2470 ms, elapsed time = 2534 msMAXDOP 0: CPU time = 2809 ms, elapsed time = 2721 ms - all 24 cores.In the above test, when the data was evenly distributed, the elapsed time of parallel query was always lower than serial query.   Why does the query get slower and slower with more CPU cores / higher MAXDOP? Maybe you can answer this question after reading the article; let me know: [email protected].   Well you get the point, let’s see an example.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script.   Let’s update the Employees table with 49 out of 50 employees located in Zip code 2001. update Employees set Zip = EmployeeID / 400 + 1 where EmployeeID % 50 = 1 update Employees set Zip = 2001 where EmployeeID % 50 != 1 go update statistics Employees with fullscan go   Let’s create the temporary table #FireDrill with all possible Zip codes. drop table #FireDrill go create table #FireDrill (Zip int primary key) insert into #FireDrill select distinct Zip from Employees update statistics #FireDrill with fullscan go  Let’s execute the query serially with MAXDOP 1. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --First serially with MAXDOP 1 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 1) goThe query took 1011 ms to complete.   The execution plan shows the 77816 KB of memory was granted while the estimated rows were 799624.  No Sort Warnings in SQL Server Profiler.  Now let’s execute the query in parallel with MAXDOP 0. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --In parallel with MAXDOP 0 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 0) go The query took 1912 ms to complete.  The execution plan shows the 79360 KB of memory was granted while the estimated rows were 799624.  The estimated number of rows between serial and parallel plan are the same. The parallel plan has slightly more memory granted due to additional overhead. Sort properties shows the rows are unevenly distributed over the 4 threads.   Sort Warnings in SQL Server Profiler.   Intermediate Summary: The reason for the higher duration with parallel plan was sort spill. This is due to uneven distribution of employees over Zip codes, especially concentration of 49 out of 50 employees in Zip code 2001. Now let’s update the Employees table and distribute employees evenly across all Zip codes.   update Employees set Zip = EmployeeID / 400 + 1 go update statistics Employees with fullscan go  Let’s execute the query serially with MAXDOP 1. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --Serially with MAXDOP 1 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 1) go   The query took 751 ms to complete.  The execution plan shows the 77816 KB of memory was granted while the estimated rows were 784707.  No Sort Warnings in SQL Server Profiler.   Now let’s execute the query in parallel with MAXDOP 0. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --In parallel with MAXDOP 0 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 0) go The query took 661 ms to complete.  The execution plan shows the 79360 KB of memory was granted while the estimated rows were 784707.  Sort properties shows the rows are evenly distributed over the 4 threads. No Sort Warnings in SQL Server Profiler.    Intermediate Summary: When employees were distributed unevenly, concentrated on 1 Zip code, parallel sort spilled while serial sort performed well without spilling to tempdb. When the employees were distributed evenly across all Zip codes, parallel sort and serial sort did not spill to tempdb. This shows uneven data distribution may affect the performance of some parallel queries negatively. For detailed discussion of memory allocation, refer to webcasts available at www.sqlworkshops.com/webcasts.     Some of you might conclude from the above execution times that parallel query is not faster even when there is no spill. Below you can see when we are joining limited amount of Zip codes, parallel query will be fasted since it can use Bitmap Filtering.   Let’s update the Employees table with 49 out of 50 employees located in Zip code 2001. update Employees set Zip = EmployeeID / 400 + 1 where EmployeeID % 50 = 1 update Employees set Zip = 2001 where EmployeeID % 50 != 1 go update statistics Employees with fullscan go  Let’s create the temporary table #FireDrill with limited Zip codes. drop table #FireDrill go create table #FireDrill (Zip int primary key) insert into #FireDrill select distinct Zip       from Employees where Zip between 1800 and 2001 update statistics #FireDrill with fullscan go  Let’s execute the query serially with MAXDOP 1. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --Serially with MAXDOP 1 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 1) go The query took 989 ms to complete.  The execution plan shows the 77816 KB of memory was granted while the estimated rows were 785594. No Sort Warnings in SQL Server Profiler.  Now let’s execute the query in parallel with MAXDOP 0. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --In parallel with MAXDOP 0 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 0) go The query took 1799 ms to complete.  The execution plan shows the 79360 KB of memory was granted while the estimated rows were 785594.  Sort Warnings in SQL Server Profiler.    The estimated number of rows between serial and parallel plan are the same. The parallel plan has slightly more memory granted due to additional overhead.  Intermediate Summary: The reason for the higher duration with parallel plan even with limited amount of Zip codes was sort spill. This is due to uneven distribution of employees over Zip codes, especially concentration of 49 out of 50 employees in Zip code 2001.   Now let’s update the Employees table and distribute employees evenly across all Zip codes. update Employees set Zip = EmployeeID / 400 + 1 go update statistics Employees with fullscan go Let’s execute the query serially with MAXDOP 1. --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --Serially with MAXDOP 1 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 1) go The query took 250  ms to complete.  The execution plan shows the 9016 KB of memory was granted while the estimated rows were 79973.8.  No Sort Warnings in SQL Server Profiler.  Now let’s execute the query in parallel with MAXDOP 0.  --Example provided by www.sqlworkshops.com --Execute query with uneven Zip code distribution --In parallel with MAXDOP 0 set statistics time on go declare @EmployeeID int, @EmployeeName varchar(48),@zip int select @EmployeeName = e.EmployeeName, @zip = e.Zip from Employees e       inner join #FireDrill fd on (e.Zip = fd.Zip)       order by e.Zip option (maxdop 0) go The query took 85 ms to complete.  The execution plan shows the 13152 KB of memory was granted while the estimated rows were 784707.  No Sort Warnings in SQL Server Profiler.    Here you see, parallel query is much faster than serial query since SQL Server is using Bitmap Filtering to eliminate rows before the hash join.   Parallel queries are very good for performance, but in some cases it can hinder performance. If one identifies the reason for these hindrances, then it is possible to get the best out of parallelism. I covered many aspects of monitoring and tuning parallel queries in webcasts (www.sqlworkshops.com/webcasts) and articles (www.sqlworkshops.com/articles). I suggest you to watch the webcasts and read the articles to better understand how to identify and tune parallel query performance issues.   Summary: One has to avoid sort spill over tempdb and the chances of spills are higher when a query executes in parallel with uneven data distribution. Parallel query brings its own advantage, reduced elapsed time and reduced work with Bitmap Filtering. So it is important to understand how to avoid spills over tempdb and when to execute a query in parallel.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.   Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan  

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• MERGE Bug with Filtered Indexes

  - by Paul White

  A MERGE statement can fail, and incorrectly report a unique key violation when: The target table uses a unique filtered index; and No key column of the filtered index is updated; and A column from the filtering condition is updated; and Transient key violations are possible Example Tables Say we have two tables, one that is the target of a MERGE statement, and another that contains updates to be applied to the target.  The target table contains three columns, an integer primary key, a single character alternate key, and a status code column.  A filtered unique index exists on the alternate key, but is only enforced where the status code is ‘a’: CREATE TABLE #Target ( pk integer NOT NULL, ak character(1) NOT NULL, status_code character(1) NOT NULL,   PRIMARY KEY (pk) );   CREATE UNIQUE INDEX uq1 ON #Target (ak) INCLUDE (status_code) WHERE status_code = 'a'; The changes table contains just an integer primary key (to identify the target row to change) and the new status code: CREATE TABLE #Changes ( pk integer NOT NULL, status_code character(1) NOT NULL,   PRIMARY KEY (pk) ); Sample Data The sample data for the example is: INSERT #Target (pk, ak, status_code) VALUES (1, 'A', 'a'), (2, 'B', 'a'), (3, 'C', 'a'), (4, 'A', 'd');   INSERT #Changes (pk, status_code) VALUES (1, 'd'), (4, 'a');          Target                     Changes +-----------------------+    +------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦ ¦  1 ¦ A  ¦ a           ¦    ¦  1 ¦ d           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+ ¦  4 ¦ A  ¦ d           ¦ +-----------------------+ The target table’s alternate key (ak) column is unique, for rows where status_code = ‘a’.  Applying the changes to the target will change row 1 from status ‘a’ to status ‘d’, and row 4 from status ‘d’ to status ‘a’.  The result of applying all the changes will still satisfy the filtered unique index, because the ‘A’ in row 1 will be deleted from the index and the ‘A’ in row 4 will be added. Merge Test One Let’s now execute a MERGE statement to apply the changes: MERGE #Target AS t USING #Changes AS c ON c.pk = t.pk WHEN MATCHED AND c.status_code <> t.status_code THEN UPDATE SET status_code = c.status_code; The MERGE changes the two target rows as expected.  The updated target table now contains: +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦ ¦  1 ¦ A  ¦ d           ¦ <—changed from ‘a’ ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ a           ¦ <—changed from ‘d’ +-----------------------+ Merge Test Two Now let’s repopulate the changes table to reverse the updates we just performed: TRUNCATE TABLE #Changes;   INSERT #Changes (pk, status_code) VALUES (1, 'a'), (4, 'd'); This will change row 1 back to status ‘a’ and row 4 back to status ‘d’.  As a reminder, the current state of the tables is:          Target                        Changes +-----------------------+    +------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦ ¦  1 ¦ A  ¦ d           ¦    ¦  1 ¦ a           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ d           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+ ¦  4 ¦ A  ¦ a           ¦ +-----------------------+ We execute the same MERGE statement: MERGE #Target AS t USING #Changes AS c ON c.pk = t.pk WHEN MATCHED AND c.status_code <> t.status_code THEN UPDATE SET status_code = c.status_code; However this time we receive the following message: Msg 2601, Level 14, State 1, Line 1 Cannot insert duplicate key row in object 'dbo.#Target' with unique index 'uq1'. The duplicate key value is (A). The statement has been terminated. Applying the changes using UPDATE Let’s now rewrite the MERGE to use UPDATE instead: UPDATE t SET status_code = c.status_code FROM #Target AS t JOIN #Changes AS c ON t.pk = c.pk WHERE c.status_code <> t.status_code; This query succeeds where the MERGE failed.  The two rows are updated as expected: +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦ ¦  1 ¦ A  ¦ a           ¦ <—changed back to ‘a’ ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ d           ¦ <—changed back to ‘d’ +-----------------------+ What went wrong with the MERGE? In this test, the MERGE query execution happens to apply the changes in the order of the ‘pk’ column. In test one, this was not a problem: row 1 is removed from the unique filtered index by changing status_code from ‘a’ to ‘d’ before row 4 is added.  At no point does the table contain two rows where ak = ‘A’ and status_code = ‘a’. In test two, however, the first change was to change row 1 from status ‘d’ to status ‘a’.  This change means there would be two rows in the filtered unique index where ak = ‘A’ (both row 1 and row 4 meet the index filtering criteria ‘status_code = a’). The storage engine does not allow the query processor to violate a unique key (unless IGNORE_DUP_KEY is ON, but that is a different story, and doesn’t apply to MERGE in any case).  This strict rule applies regardless of the fact that if all changes were applied, there would be no unique key violation (row 4 would eventually be changed from ‘a’ to ‘d’, removing it from the filtered unique index, and resolving the key violation). Why it went wrong The query optimizer usually detects when this sort of temporary uniqueness violation could occur, and builds a plan that avoids the issue.  I wrote about this a couple of years ago in my post Beware Sneaky Reads with Unique Indexes (you can read more about the details on pages 495-497 of Microsoft SQL Server 2008 Internals or in Craig Freedman’s blog post on maintaining unique indexes).  To summarize though, the optimizer introduces Split, Filter, Sort, and Collapse operators into the query plan to: Split each row update into delete followed by an inserts Filter out rows that would not change the index (due to the filter on the index, or a non-updating update) Sort the resulting stream by index key, with deletes before inserts Collapse delete/insert pairs on the same index key back into an update The effect of all this is that only net changes are applied to an index (as one or more insert, update, and/or delete operations).  In this case, the net effect is a single update of the filtered unique index: changing the row for ak = ‘A’ from pk = 4 to pk = 1.  In case that is less than 100% clear, let’s look at the operation in test two again:          Target                     Changes                   Result +-----------------------+    +------------------+    +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦    ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦    ¦----+----+-------------¦ ¦  1 ¦ A  ¦ d           ¦    ¦  1 ¦ d           ¦    ¦  1 ¦ A  ¦ a           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ a           ¦    ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+    ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ a           ¦                            ¦  4 ¦ A  ¦ d           ¦ +-----------------------+                            +-----------------------+ From the filtered index’s point of view (filtered for status_code = ‘a’ and shown in nonclustered index key order) the overall effect of the query is:   Before           After +---------+    +---------+ ¦ pk ¦ ak ¦    ¦ pk ¦ ak ¦ ¦----+----¦    ¦----+----¦ ¦  4 ¦ A  ¦    ¦  1 ¦ A  ¦ ¦  2 ¦ B  ¦    ¦  2 ¦ B  ¦ ¦  3 ¦ C  ¦    ¦  3 ¦ C  ¦ +---------+    +---------+ The single net change there is a change of pk from 4 to 1 for the nonclustered index entry ak = ‘A’.  This is the magic performed by the split, sort, and collapse.  Notice in particular how the original changes to the index key (on the ‘ak’ column) have been transformed into an update of a non-key column (pk is included in the nonclustered index).  By not updating any nonclustered index keys, we are guaranteed to avoid transient key violations. The Execution Plans The estimated MERGE execution plan that produces the incorrect key-violation error looks like this (click to enlarge in a new window): The successful UPDATE execution plan is (click to enlarge in a new window): The MERGE execution plan is a narrow (per-row) update.  The single Clustered Index Merge operator maintains both the clustered index and the filtered nonclustered index.  The UPDATE plan is a wide (per-index) update.  The clustered index is maintained first, then the Split, Filter, Sort, Collapse sequence is applied before the nonclustered index is separately maintained. There is always a wide update plan for any query that modifies the database. The narrow form is a performance optimization where the number of rows is expected to be relatively small, and is not available for all operations.  One of the operations that should disallow a narrow plan is maintaining a unique index where intermediate key violations could occur. Workarounds The MERGE can be made to work (producing a wide update plan with split, sort, and collapse) by: Adding all columns referenced in the filtered index’s WHERE clause to the index key (INCLUDE is not sufficient); or Executing the query with trace flag 8790 set e.g. OPTION (QUERYTRACEON 8790). Undocumented trace flag 8790 forces a wide update plan for any data-changing query (remember that a wide update plan is always possible).  Either change will produce a successfully-executing wide update plan for the MERGE that failed previously. Conclusion The optimizer fails to spot the possibility of transient unique key violations with MERGE under the conditions listed at the start of this post.  It incorrectly chooses a narrow plan for the MERGE, which cannot provide the protection of a split/sort/collapse sequence for the nonclustered index maintenance. The MERGE plan may fail at execution time depending on the order in which rows are processed, and the distribution of data in the database.  Worse, a previously solid MERGE query may suddenly start to fail unpredictably if a filtered unique index is added to the merge target table at any point. Connect bug filed here Tests performed on SQL Server 2012 SP1 CUI (build 11.0.3321) x64 Developer Edition © 2012 Paul White – All Rights Reserved Twitter: @SQL_Kiwi Email: [email protected]

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• What is a ‘best practice’ backup plan for a website?

  - by HollerTrain

  I have a website which is very large and has a large user-base. I am trying to think of a 'best practice' way to create a back up or mirror website, so if something happens on domain.com, I can quickly point the site to backup.domain.com via 401 redirect. This would give me time to troubleshoot domain.com while everyone is viewing backup.domain.com and not knowing the difference. Is my method the ideal method, or have you enacted better methods to creating a backup site? I don't want to have the site go down and then get yelled at every minute while I'm trying to fix it. Ideally I would just 'flip the switch' and it would redirect the user to a backup. Any insight would be greatly appreciated.

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• Dell Management Packs in System Center Operations Manager 2007 R2?

  - by bwerks

  Hey all, I recently set up SCOM in a small business network environment. The root management server is a Dell Poweredge 2950, and I'd like to use SCOM to monitor it using Dell's management packs. I've imported the management packs into the SCOM deployment and followed Dell's installation instructions, but it doesn't seem to be fully working yet. Currently, the Diagram views in the Dell tree (Monitoring tab) seem to show me the server's place in the network topology, so it seems that at least part of it is working. However, none of the reports under "Performance and Power Monitoring Views" provide any information. When clicking on one of them (Power Consumption (Watts), for instance), the display area is blank and there is a tooltip visible that reads "No performance counter is selected. To select a counter, place a check mark in the Show column in legend below." However, in the legend, there's nothing there for me to check. I've installed OpenManage 6.2 on the server as per the Dell documentation, but I don't know what else I could have done that I missed. Does this sound like a familiar problem to anyone?

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