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  • Week in Geek: USDA Chooses Microsoft for Cloud Services Edition

    - by Asian Angel
    This week we learned how to create geeky LED holiday lights with old bottles, dig deeper in Windows Defrag via the command prompt, use Google Chrome’s drag/drop feature to upload files easier, find great gift recommendations by looking through the How-To Geek holiday gift guide, and have fun adding Merry Christmas fonts to our computers. Photo by ntr23. Random Geek Links It has been a busy week, so we have extra news link goodness with information that is good for you to know. USDA making the move to Microsoft The U.S. Department of Agriculture has announced that it has chosen Microsoft to host things like e-mail, instant messaging, and collaboration through the software giant’s Business Productivity Online Suite. Google says it was cut off from USDA project bid Google is claiming that it was not given a chance to bid on a cloud-computing project for the U.S. Department of Agriculture, for which the contract was awarded to rival Microsoft. Apache is being forced into a Java Fork When Oracle rolled over Apache and Google’s objections to its Java plans in December, the scene was set for Apache to leave and, eventually, force a Java code fork. Tumblr explains daylong outage After experiencing an outage that started on Sunday afternoon and stretched through most of the day yesterday, Tumblr has explained what happened. Google demos Chrome OS, launches pilot program During a press briefing this week in San Francisco, Google launched the Chrome application store and demonstrated Chrome OS, its browser-centric netbook operating system. Don’t expect Spotify in U.S. this holiday season As of last week, Spotify had yet to sign a single licensing deal with a major label, after spending more than a year negotiating, multiple music sources told CNET. December 2010 Patch Tuesday will come with most bulletins ever According to the Microsoft Security Response Center, Microsoft will issue 17 Security Bulletins addressing 40 vulnerabilities on Tuesday, December 14. It will also host a webcast to address customer questions the following day. Hacker plants back door in Symbian firmware Indian hacker Atul Alex has had a look at the firmware for Symbian S60 smartphones and come up with a back door for it. PC quarantines raise tough complexities The concept of quarantining PCs to prevent widespread infection is “interesting, but difficult to implement, with far too many problems”, said security experts. Symantec: DDoS attacks hard to defend It has surfaced that the distributed denial of service (DDoS) attacks on Visa and MasterCard Web sites on Wednesday were carried out by a toolkit known as low orbit ion cannon (LOIC). Web Sockets and the risks of unfinished standards Enthusiasm for a promising new standard called Web Sockets has quickly cooled in some quarters as a potential security problem led some browser makers to hastily postpone support. Internet Explorer 9 to get tracking protection Microsoft is making changes to Internet Explorer 9’s security features that will better enable users to keep sites from tracking their activity across browsing sessions. NASA sold PCs with sensitive data NASA failed to remove sensitive data from computers that it sold, according to an audit report released this week. Cybercrooks create fake Amazon receipts The bad guys have created yet another online scam, this one involving fake Amazon receipts. World of Warcraft character move fees waived Until December 22, Blizzard will allow free realm transfers from 25 highly populated servers to alleviate log-in queues or performance issues. (The free transfers are one-way and one-time only.) SpaceX Dragon reaches orbit atop a Falcon with a fiery tail The Space Exploration Technologies corporation has become the first nongovernmental entity to put a vehicle into low Earth orbit. Geek Video of the Week If birds have wings, then why are the Angry Birds using slingshots? Photo by Dorkly Bits. Wait… Birds have Wings, Why are the Angry Ones Using Slingshots? Sysadmin Geek Tips How To Setup Email Alerts on Linux Using Gmail or SMTP Linux machines may require administrative intervention in countless ways, but without manually logging into them how would you know about it? Here’s how to setup emails to get notified when your machines want some tender love and attention. Random TinyHacker Links Red Panda Webcam Support Firefox and the Knoxville Zoo’s Red Panda program. Christmas Icons (Icons we like) Superb set of holiday icons by lgp85 at deviantArt. Download the .zip and use as .png or convert to .ico at Convertico.com or with tiny app Imagicon. Super User Questions Enjoy reading the great answers to this week’s popular questions from Super User Useful USB boot disks? DVD/CD burning .zip: is it more reliable, faster, longer lasting to burn a zip of files rather than the files as a folder? What are other ways to backup my files if I do not have an external drive? Anti virus what is the difference between these all? How can I block all Facebook elements/content? How-To Geek Weekly Article Recap Have you had a busy week between work and preparing for the holidays? Get caught up on your HTG reading with our hottest articles of the week. 20 Windows Keyboard Shortcuts You Might Not Know The 50 Best Registry Hacks that Make Windows Better LCD? LED? Plasma? The How-To Geek Guide to HDTV Technology HTG Explains: Which Linux File System Should You Choose? How to Use and Customize Google Chrome Web Apps One Year Ago on How-To Geek This week’s batch of retro geeky goodness is all about customizing Windows 7. ClassicShell Adds Classic Start Menu and Explorer Features to Windows 7 Get an Aero-Styled Classic Start Menu in Windows 7 Customize the Windows 7 Logon Screen Get the Classic Style Network Activity Indicator Back in Windows 7 How To Enable Check Boxes for Items In Windows 7 The Geek Note We would like you to join us in welcoming Jason Fitzpatrick to the writing staff here at How-To Geek. He started with us this past week, so take some time to read through his articles about the Wii, Kindle, & PlayStation 2 Peripherals and leave a friendly comment to say “Hi”! Got a great tip to share? Make sure to send it in to us at [email protected]. Photo by real00. Latest Features How-To Geek ETC The 50 Best Registry Hacks that Make Windows Better The How-To Geek Holiday Gift Guide (Geeky Stuff We Like) LCD? LED? Plasma? The How-To Geek Guide to HDTV Technology The How-To Geek Guide to Learning Photoshop, Part 8: Filters Improve Digital Photography by Calibrating Your Monitor Our Favorite Tech: What We’re Thankful For at How-To Geek Settle into Orbit with the Voyage Theme for Chrome and Iron Awesome Safari Compass Icons Set Escape from the Exploding Planet Wallpaper Move Your Tumblr Blog to WordPress Pytask is an Easy to Use To-Do List Manager for Your Ubuntu System Snowy Christmas House Personas Theme for Firefox

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  • TFS 2010 Basic Concepts

    - by jehan
    v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Here, I’m going to discuss some key Architectural changes and concepts that have taken place in TFS 2010 when compared to TFS 2008. In TFS 2010 Installation, First you need to do the Installation and then you have to configure the Installation Feature from the available features. This is bit similar to SharePoint Installation, where you will first do the Installation and then configure the SharePoint Farms. 1) Installation Features available in TFS2010: a) Basic: It is the most compact TFS installation possible. It will install and configure Source Control, Work Item tracking and Build Services only. (SharePoint and Reporting Integration will not be possible). b) Standard Single Server: This is suitable for Single Server deployment of TFS. It will install and configure Windows SharePoint Services for you and will use the default instance of SQL Server. c) Advanced: It is suitable, if you want use Remote Servers for SQL Server Databases, SharePoint Products and Technologies and SQL Server Reporting Services. d) Application Tier Only: If you want to configure high availability for Team Foundation Server in a Load Balanced Environment (NLB) or you want to move Team Foundation Server from one server to other or you want to restore TFS. e) Upgrade: If you want to upgrade from a prior version of TFS. Note: One more important thing to know here about  TFS 2010 Basic is that,  it can be installed on Client Operations Systems(Windows 7 and Windows Vista SP3), Where as  earlier you cannot Install previous version of TFS (2008 and 2005) on client OS. 2) Team Project Collections: Connect to TFS dialog box in TFS 2008:  In TFS 2008, the TFS Server contains a set of Team Projects and each project may or may not be independent of other projects and every checkin gets a ever increasing  changeset ID  irrespective of the team project in which it is checked in and the same applies to work items  also, who also gets unique Work Item Ids.The main problem with this approach was that there are certain things which were impossible to do; those were required as per the Application Development Process. a)      If something has gone wrong in one team project and now you want to restore it back to earlier state where it was working properly then it requires you to restore the Database of Team Foundation Server from the backup you have taken as per your Maintenance plans and because of this the other team projects may lose out on the work which is not backed up. b)       Your company had a merge with some other company and now you have two TFS servers. One TFS Server which you are working on and other TFS server which other company was working and now after the merge you want to integrate the team projects from two TFS servers into one, which is almost impossible to achieve in TFS 2008. Though you can create the Team Projects in one server manually (In Source Control) which you want to integrate from the other TFS Server, but will lose out on History of Change Sets and Work items and others which are very important. There were few more issues of this sort, which were difficult to resolve in TFS 2008. To resolve issues related to above kind of scenarios which were mainly related TFS Maintenance, Integration, migration and Security,  Microsoft has come up with Team Project Collections concept in TFS 2010.This concept is similar to SharePoint Site Collections and if you are familiar with SharePoint Architecture, then it will help you to understand TFS 2010 Architecture easily. Connect to TFS dialog box in TFS 2010: In above dialog box as you can see there are two Team Project Collections, each team project can contain any number of team projects as you can see on right side it shows the two Team Projects in Team Project Collection (Default Collection) which I have chosen. Note: You can connect to only one Team project Collection at a time using an instance of  TFS Team Explorer. How does it work? To introduce Team Project Collections, changes have been done in reorganization of TFS databases. TFS 2008 was composed of 5-7 databases partitioned by subsystem (each for Version Control, Work Item Tracking, Build, Integration, Project Management...) New TFS 2010 database architecture: TFS_Config: It’s the root database and it contains centralized TFS configuration data, including the list of all team projects exist in TFS server. TFS_Warehouse: The data warehouse contains all the reporting data of served by this server (farm). TFS_* : This contains individual team project collection data. This database contains all the operational data of team project collection regardless of subsystem.In additional to this, you will have databases for SharePoint and Report Server. 3) TFS Farms:  As TFS 2010 is more flexible to configure as multiple Application tiers and multiple Database tiers, so it will be more appropriate to call as TFS Farm if you going for multi server installation of TFS. NLB support for TFS application tiers – With TFS 2010: you can configure multiple TFS application tier machines to serve the same set of Team Project Collections. The primary purpose of NLB support is to enable a cleaner and more complete high availability than in TFS 2008. Even if any application tier in the farm fails then farm will automatically continue to work with hardly any indication to end users of a problem. SQL data tiers: With 2010 you can configure many SQL Servers. Each Database can be configured to be on any SQL Server because each Team Project Collection is an independent database. This feature can also be used to load balance databases across SQL Servers.These new capabilities will significantly change the way enterprises manage their TFS installations in the future. With Team Project Collections and TFS farms, you can create a single, arbitrarily large TFS installation. You can grow it incrementally by adding ATs and SQL Servers as needed.

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  • Basics of Join Predicate Pushdown in Oracle

    - by Maria Colgan
    Happy New Year to all of our readers! We hope you all had a great holiday season. We start the new year by continuing our series on Optimizer transformations. This time it is the turn of Predicate Pushdown. I would like to thank Rafi Ahmed for the content of this blog.Normally, a view cannot be joined with an index-based nested loop (i.e., index access) join, since a view, in contrast with a base table, does not have an index defined on it. A view can only be joined with other tables using three methods: hash, nested loop, and sort-merge joins. Introduction The join predicate pushdown (JPPD) transformation allows a view to be joined with index-based nested-loop join method, which may provide a more optimal alternative. In the join predicate pushdown transformation, the view remains a separate query block, but it contains the join predicate, which is pushed down from its containing query block into the view. The view thus becomes correlated and must be evaluated for each row of the outer query block. These pushed-down join predicates, once inside the view, open up new index access paths on the base tables inside the view; this allows the view to be joined with index-based nested-loop join method, thereby enabling the optimizer to select an efficient execution plan. The join predicate pushdown transformation is not always optimal. The join predicate pushed-down view becomes correlated and it must be evaluated for each outer row; if there is a large number of outer rows, the cost of evaluating the view multiple times may make the nested-loop join suboptimal, and therefore joining the view with hash or sort-merge join method may be more efficient. The decision whether to push down join predicates into a view is determined by evaluating the costs of the outer query with and without the join predicate pushdown transformation under Oracle's cost-based query transformation framework. The join predicate pushdown transformation applies to both non-mergeable views and mergeable views and to pre-defined and inline views as well as to views generated internally by the optimizer during various transformations. The following shows the types of views on which join predicate pushdown is currently supported. UNION ALL/UNION view Outer-joined view Anti-joined view Semi-joined view DISTINCT view GROUP-BY view Examples Consider query A, which has an outer-joined view V. The view cannot be merged, as it contains two tables, and the join between these two tables must be performed before the join between the view and the outer table T4. A: SELECT T4.unique1, V.unique3 FROM T_4K T4,            (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3) VWHERE T4.unique3 = V.hundred(+) AND       T4.ten = V.ten(+) AND       T4.thousand = 5; The following shows the non-default plan for query A generated by disabling join predicate pushdown. When query A undergoes join predicate pushdown, it yields query B. Note that query B is expressed in a non-standard SQL and shows an internal representation of the query. B: SELECT T4.unique1, V.unique3 FROM T_4K T4,           (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3             AND T4.unique3 = V.hundred(+)             AND T4.ten = V.ten(+)) V WHERE T4.thousand = 5; The execution plan for query B is shown below. In the execution plan BX, note the keyword 'VIEW PUSHED PREDICATE' indicates that the view has undergone the join predicate pushdown transformation. The join predicates (shown here in red) have been moved into the view V; these join predicates open up index access paths thereby enabling index-based nested-loop join of the view. With join predicate pushdown, the cost of query A has come down from 62 to 32.  As mentioned earlier, the join predicate pushdown transformation is cost-based, and a join predicate pushed-down plan is selected only when it reduces the overall cost. Consider another example of a query C, which contains a view with the UNION ALL set operator.C: SELECT R.unique1, V.unique3 FROM T_5K R,            (SELECT T1.unique3, T2.unique1+T1.unique1             FROM T_5K T1, T_10K T2             WHERE T1.unique1 = T2.unique1             UNION ALL             SELECT T1.unique3, T2.unique2             FROM G_4K T1, T_10K T2             WHERE T1.unique1 = T2.unique1) V WHERE R.unique3 = V.unique3 and R.thousand < 1; The execution plan of query C is shown below. In the above, 'VIEW UNION ALL PUSHED PREDICATE' indicates that the UNION ALL view has undergone the join predicate pushdown transformation. As can be seen, here the join predicate has been replicated and pushed inside every branch of the UNION ALL view. The join predicates (shown here in red) open up index access paths thereby enabling index-based nested loop join of the view. Consider query D as an example of join predicate pushdown into a distinct view. We have the following cardinalities of the tables involved in query D: Sales (1,016,271), Customers (50,000), and Costs (787,766).  D: SELECT C.cust_last_name, C.cust_city FROM customers C,            (SELECT DISTINCT S.cust_id             FROM sales S, costs CT             WHERE S.prod_id = CT.prod_id and CT.unit_price > 70) V WHERE C.cust_state_province = 'CA' and C.cust_id = V.cust_id; The execution plan of query D is shown below. As shown in XD, when query D undergoes join predicate pushdown transformation, the expensive DISTINCT operator is removed and the join is converted into a semi-join; this is possible, since all the SELECT list items of the view participate in an equi-join with the outer tables. Under similar conditions, when a group-by view undergoes join predicate pushdown transformation, the expensive group-by operator can also be removed. With the join predicate pushdown transformation, the elapsed time of query D came down from 63 seconds to 5 seconds. Since distinct and group-by views are mergeable views, the cost-based transformation framework also compares the cost of merging the view with that of join predicate pushdown in selecting the most optimal execution plan. Summary We have tried to illustrate the basic ideas behind join predicate pushdown on different types of views by showing example queries that are quite simple. Oracle can handle far more complex queries and other types of views not shown here in the examples. Again many thanks to Rafi Ahmed for the content of this blog post.

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  • Multi-tenant ASP.NET MVC - Views

    - by zowens
    Part I – Introduction Part II – Foundation Part III – Controllers   So far we have covered the basic premise of tenants and how they will be delegated. Now comes a big issue with multi-tenancy, the views. In some applications, you will not have to override views for each tenant. However, one of my requirements is to add extra views (and controller actions) along with overriding views from the core structure. This presents a bit of a problem in locating views for each tenant request. I have chosen quite an opinionated approach at the present but will coming back to the “views” issue in a later post. What’s the deal? The path I’ve chosen is to use precompiled Spark views. I really love Spark View Engine and was planning on using it in my project anyways. However, I ran across a really neat aspect of the source when I was having a look under the hood. There’s an easy way to hook in embedded views from your project. There are solutions that provide this, but they implement a special Virtual Path Provider. While I think this is a great solution, I would rather just have Spark take care of the view resolution. The magic actually happens during the compilation of the views into a bin-deployable DLL. After the views are compiled, the are simply pulled out of the views DLL. Each tenant has its own views DLL that just has “.Views” appended after the assembly name as a convention. The list of reasons for this approach are quite long. The primary motivation is performance. I’ve had quite a few performance issues in the past and I would like to increase my application’s performance in any way that I can. My customized build of Spark removes insignificant whitespace from the HTML output so I can some some bandwidth and load time without having to deal with whitespace removal at runtime.   How to setup Tenants for the Host In the source, I’ve provided a single tenant as a sample (Sample1). This will serve as a template for subsequent tenants in your application. The first step is to add a “PostBuildStep” installer into the project. I’ve defined one in the source that will eventually change as we focus more on the construction of dependency containers. The next step is to tell the project to run the installer and copy the DLL output to a folder in the host that will pick up as a tenant. Here’s the code that will achieve it (this belongs in Post-build event command line field in the Build Events tab of settings) %systemroot%\Microsoft.NET\Framework\v4.0.30319\installutil "$(TargetPath)" copy /Y "$(TargetDir)$(TargetName)*.dll" "$(SolutionDir)Web\Tenants\" copy /Y "$(TargetDir)$(TargetName)*.pdb" "$(SolutionDir)Web\Tenants\" The DLLs with a name starting with the target assembly name will be copied to the “Tenants” folder in the web project. This means something like MultiTenancy.Tenants.Sample1.dll and MultiTenancy.Tenants.Sample1.Views.dll will both be copied along with the debug symbols. This is probably the simplest way to go about this, but it is a tad inflexible. For example, what if you have dependencies? The preferred method would probably be to use IL Merge to merge your dependencies with your target DLL. This would have to be added in the build events. Another way to achieve that would be to simply bypass Visual Studio events and use MSBuild.   I also got a question about how I was setting up the controller factory. Here’s the basics on how I’m setting up tenants inside the host (Global.asax) protected void Application_Start() { RegisterRoutes(RouteTable.Routes); // create a container just to pull in tenants var topContainer = new Container(); topContainer.Configure(config => { config.Scan(scanner => { scanner.AssembliesFromPath(Path.Combine(Server.MapPath("~/"), "Tenants")); scanner.AddAllTypesOf<IApplicationTenant>(); }); }); // create selectors var tenantSelector = new DefaultTenantSelector(topContainer.GetAllInstances<IApplicationTenant>()); var containerSelector = new TenantContainerResolver(tenantSelector); // clear view engines, we don't want anything other than spark ViewEngines.Engines.Clear(); // set view engine ViewEngines.Engines.Add(new TenantViewEngine(tenantSelector)); // set controller factory ControllerBuilder.Current.SetControllerFactory(new ContainerControllerFactory(containerSelector)); } The code to setup the tenants isn’t actually that hard. I’m utilizing assembly scanners in StructureMap as a simple way to pull in DLLs that are not in the AppDomain. Remember that there is a dependency on the host in the tenants and a tenant cannot simply be referenced by a host because of circular dependencies.   Tenant View Engine TenantViewEngine is a simple delegator to the tenant’s specified view engine. You might have noticed that a tenant has to define a view engine. public interface IApplicationTenant { .... IViewEngine ViewEngine { get; } } The trick comes in specifying the view engine on the tenant side. Here’s some of the code that will pull views from the DLL. protected virtual IViewEngine DetermineViewEngine() { var factory = new SparkViewFactory(); var file = GetType().Assembly.CodeBase.Without("file:///").Replace(".dll", ".Views.dll").Replace('/', '\\'); var assembly = Assembly.LoadFile(file); factory.Engine.LoadBatchCompilation(assembly); return factory; } This code resides in an abstract Tenant where the fields are setup in the constructor. This method (inside the abstract class) will load the Views assembly and load the compilation into Spark’s “Descriptors” that will be used to determine views. There is some trickery on determining the file location… but it works just fine.   Up Next There’s just a few big things left such as StructureMap configuring controllers with a convention instead of specifying types directly with container construction and content resolution. I will also try to find a way to use the Web Forms View Engine in a multi-tenant way we achieved with the Spark View Engine without using a virtual path provider. I will probably not use the Web Forms View Engine personally, but I’m sure some people would prefer using WebForms because of the maturity of the engine. As always, I love to take questions by email or on twitter. Suggestions are always welcome as well! (Oh, and here’s another link to the source code).

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  • Customize Team Build 2010 – Part 13: Get control over the Build Output

    In the series the following parts have been published Part 1: Introduction Part 2: Add arguments and variables Part 3: Use more complex arguments Part 4: Create your own activity Part 5: Increase AssemblyVersion Part 6: Use custom type for an argument Part 7: How is the custom assembly found Part 8: Send information to the build log Part 9: Impersonate activities (run under other credentials) Part 10: Include Version Number in the Build Number Part 11: Speed up opening my build process template Part 12: How to debug my custom activities Part 13: Get control over the Build Output Part 14: Execute a PowerShell script Part 15: Fail a build based on the exit code of a console application In the part 8, I have explained how you can add informational messages, warnings or errors to the build output. If you want to integrate with other lines of text to the build output, you need to do more. This post will show you how you can add extra steps, additional information and hyperlinks to the build output. UPDATE 13-12-2010: Thanks to Jason Pricket, it is now also possible to not show every activity in the build log. This is really useful when you are doing for-loops in your template. To see how you can do that, check out Jason's blog: http://blogs.msdn.com/b/jpricket/archive/2010/12/09/tfs-2010-making-your-build-log-less-noisy.aspx Add an hyperlink to the end of the build output Lets start with a simple example of how you can adjust the build output. In this case we are going to add at the end of the build output an hyperlink where a user can click on to for example start the deployment to the test environment. In part 4 you can find information how you can create a custom activity To add information to the build output, you need the BuildDetail. This value is a variable in your xaml and is thus easily transferable to you custom activity. Besides the BuildDetail the user has also to specify the text and the url that has to be added to the end of the build output. The following code segment shows you how you can achieve this.     [BuildActivity(HostEnvironmentOption.All)]    public sealed class AddHyperlinkToBuildOutput : CodeActivity    {        [RequiredArgument]        public InArgument<IBuildDetail> BuildDetail { get; set; }         [RequiredArgument]        public InArgument<string> DisplayText { get; set; }         [RequiredArgument]        public InArgument<string> Url { get; set; }         protected override void Execute(CodeActivityContext context)        {            // Obtain the runtime value of the input arguments                        IBuildDetail buildDetail = context.GetValue(this.BuildDetail);            string displayText = context.GetValue(this.DisplayText);            string url = context.GetValue(this.Url);             // Add the hyperlink            buildDetail.Information.AddExternalLink(displayText, new Uri(url));            buildDetail.Information.Save();        }    } If you add this activity to somewhere in your build process template (within the scope Run on Agent), you will get the following build output Add an line of text to the build output The next challenge is to add this kind of output not only to the end of the build output but at the step that is currently executing. To be able to do this, you need the current node in the build output. The following code shows you how you can achieve this. First you need to get the current activity tracking, which you can get with the following line of code             IActivityTracking currentTracking = context.GetExtension<IBuildLoggingExtension>().GetActivityTracking(context); Then you can create a new node and set its type to Activity Tracking Node (so copy it from the current node) and do nice things with the node.             IBuildInformationNode childNode = currentTracking.Node.Children.CreateNode();            childNode.Type = currentTracking.Node.Type;            childNode.Fields.Add("DisplayText", "This text is displayed."); You can also add a build step to display progress             IBuildStep buildStep = childNode.Children.AddBuildStep("Custom Build Step", "This is my custom build step");            buildStep.FinishTime = DateTime.Now.AddSeconds(10);            buildStep.Status = BuildStepStatus.Succeeded; Or you can add an hyperlink to the node             childNode.Children.AddExternalLink("My link", new Uri(http://www.ewaldhofman.nl)); When you combine this together you get the following result in the build output   You can download the full solution at BuildProcess.zip. It will include the sources of every part and will continue to evolve.

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  • Customize Team Build 2010 – Part 13: Get control over the Build Output

    In the series the following parts have been published Part 1: Introduction Part 2: Add arguments and variables Part 3: Use more complex arguments Part 4: Create your own activity Part 5: Increase AssemblyVersion Part 6: Use custom type for an argument Part 7: How is the custom assembly found Part 8: Send information to the build log Part 9: Impersonate activities (run under other credentials) Part 10: Include Version Number in the Build Number Part 11: Speed up opening my build process template Part 12: How to debug my custom activities Part 13: Get control over the Build Output Part 14: Execute a PowerShell script Part 15: Fail a build based on the exit code of a console application     In the part 8, I have explained how you can add informational messages, warnings or errors to the build output. If you want to integrate with other lines of text to the build output, you need to do more. This post will show you how you can add extra steps, additional information and hyperlinks to the build output. Add an hyperlink to the end of the build output Lets start with a simple example of how you can adjust the build output. In this case we are going to add at the end of the build output an hyperlink where a user can click on to for example start the deployment to the test environment. In part 4 you can find information how you can create a custom activity To add information to the build output, you need the BuildDetail. This value is a variable in your xaml and is thus easily transferable to you custom activity. Besides the BuildDetail the user has also to specify the text and the url that has to be added to the end of the build output. The following code segment shows you how you can achieve this.     [BuildActivity(HostEnvironmentOption.All)]    public sealed class AddHyperlinkToBuildOutput : CodeActivity    {        [RequiredArgument]        public InArgument<IBuildDetail> BuildDetail { get; set; }         [RequiredArgument]        public InArgument<string> DisplayText { get; set; }         [RequiredArgument]        public InArgument<string> Url { get; set; }         protected override void Execute(CodeActivityContext context)        {            // Obtain the runtime value of the input arguments                        IBuildDetail buildDetail = context.GetValue(this.BuildDetail);            string displayText = context.GetValue(this.DisplayText);            string url = context.GetValue(this.Url);             // Add the hyperlink            buildDetail.Information.AddExternalLink(displayText, new Uri(url));            buildDetail.Information.Save();        }    } If you add this activity to somewhere in your build process template (within the scope Run on Agent), you will get the following build output Add an line of text to the build output The next challenge is to add this kind of output not only to the end of the build output but at the step that is currently executing. To be able to do this, you need the current node in the build output. The following code shows you how you can achieve this. First you need to get the current activity tracking, which you can get with the following line of code             IActivityTracking currentTracking = context.GetExtension<IBuildLoggingExtension>().GetActivityTracking(context); Then you can create a new node and set its type to Activity Tracking Node (so copy it from the current node) and do nice things with the node.             IBuildInformationNode childNode = currentTracking.Node.Children.CreateNode();            childNode.Type = currentTracking.Node.Type;            childNode.Fields.Add("DisplayText", "This text is displayed."); You can also add a build step to display progress             IBuildStep buildStep = childNode.Children.AddBuildStep("Custom Build Step", "This is my custom build step");            buildStep.FinishTime = DateTime.Now.AddSeconds(10);            buildStep.Status = BuildStepStatus.Succeeded; Or you can add an hyperlink to the node             childNode.Children.AddExternalLink("My link", new Uri(http://www.ewaldhofman.nl)); When you combine this together you get the following result in the build output     You can download the full solution at BuildProcess.zip. It will include the sources of every part and will continue to evolve.

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  • Using SQL Source Control with Fortress or Vault &ndash; Part 2

    - by AjarnMark
    In Part 1, I started talking about using Red-Gate’s newest version of SQL Source Control and how I really like it as a viable method to source control your database development.  It looks like this is going to turn into a little series where I will explain how we have done things in the past, and how life is different with SQL Source Control.  I will also explain some of my philosophy and methodology around deployment with these tools.  But for now, let’s talk about some of the good and the bad of the tool itself. More Kudos and Features I mentioned previously how impressed I was with the responsiveness of Red-Gate’s team.  I have been having an ongoing email conversation with Gyorgy Pocsi, and as I have run into problems or requested things behave a little differently, it has not been more than a day or two before a new Build is ready for me to download and test.  Quite impressive! I’m sure much of the requests I put in were already in the plans, so I can’t really take credit for them, but throughout this conversation, Red-Gate has implemented several features that were not in the first Early Access version.  Those include: Honoring the Fortress configuration option to require Work Item (Bug) IDs on check-ins. Adding the check-in comment text as a comment to the Work Item. Adding the list of checked-in files, along with the Fortress links for automatic History and DIFF view Updating the status of a Work Item on check-in (e.g. setting the item to Complete or, in our case “Dev-Complete”) Support for the Fortress 2.0 API, and not just the Vault Pro 5.1 API.  (See later notes regarding support for Fortress 2.0). These were all features that I felt we really needed to have in-place before I could honestly consider converting my team to using SQL Source Control on a regular basis.  Now that I have those, my only excuse is not wanting to switch boats on the team mid-stream.  So when we wrap up our current release in a few weeks, we will make the jump.  In the meantime, I will continue to bang on it to make sure it is stable.  It passed one test for stability when I did a test load of one of our larger database schemas into Fortress with SQL Source Control.  That database has about 150 tables, 200 User-Defined Functions and nearly 900 Stored Procedures.  The initial load to source control went smoothly and took just a brief amount of time. Warnings Remember that this IS still in pre-release stage and while I have not had any problems after that first hiccup I wrote about last time, you still need to treat it with a healthy respect.  As I understand it, the RTM is targeted for February.  There are a couple more features that I hope make it into the final release version, but if not, they’ll probably be coming soon thereafter.  Those are: A Browse feature to let me lookup the Work Item ID instead of having to remember it or look back in my Item details.  This is just a matter of convenience. I normally have my Work Item list open anyway, so I can easily look it up, but hey, why not make it even easier. A multi-line comment area.  The current space for writing check-in comments is a single-line text box.  I would like to have a multi-line space as I sometimes write lengthy commentary.  But I recognize that it is a struggle to get most developers to put in more than the word “fixed” as their comment, so this meets the need of the majority as-is, and it’s not a show-stopper for us. Merge.  SQL Source Control currently does not have a Merge feature.  If two or more people make changes to the same database object, you will get a warning of the conflict and have to choose which one wins (and then manually edit to include the others’ changes).  I think it unlikely you will run into actual conflicts in Stored Procedures and Functions, but you might with Views or Tables.  This will be nice to have, but I’m not losing any sleep over it.  And I have multiple tools at my disposal to do merges manually, so really not a show-stopper for us. Automation has its limits.  As cool as this automation is, it has its limits and there are some changes that you will be better off scripting yourself.  For example, if you are refactoring table definitions, and want to change a column name, you can write that as a quick sp_rename command and preserve the data within that column.  But because this tool is looking just at a before and after picture, it cannot tell that you just renamed a column.  To the tool, it looks like you dropped one column and added another.  This is not a knock against Red-Gate.  All automated scripting tools have this issue, unless the are actively monitoring your every step to know exactly what you are doing.  This means that when you go to Deploy your changes, SQL Compare will script the change as a column drop and add, or will attempt to rebuild the entire table.  Unfortunately, neither of these approaches will preserve the existing data in that column the way an sp_rename will, and so you are better off scripting that change yourself.  Thankfully, SQL Compare will produce warnings about the potential loss of data before it does the actual synchronization and give you a chance to intercept the script and do it yourself. Also, please note that the current official word is that SQL Source Control supports Vault Professional 5.1 and later.  Vault Professional is the new name for what was previously known as Fortress.  (You can read about the name change on SourceGear’s site.)  The last version of Fortress was 2.x, and the API for Fortress 2.x is different from the API for Vault Pro.  At my company, we are currently running Fortress 2.0, with plans to upgrade to Vault Pro early next year.  Gyorgy was able to come up with a work-around for me to be able to use SQL Source Control with Fortress 2.0, even though it is not officially supported.  If you are using Fortress 2.0 and want to use SQL Source Control, be aware that this is not officially supported, but it is working for us, and you can probably get the work-around instructions from Red-Gate if you’re really, really nice to them. Upcoming Topics Some of the other topics I will likely cover in this series over the next few weeks are: How we used to do source control back in the old days (a few weeks ago) before SQL Source Control was available to Vault users What happens when you restore a database that is linked to source control Handling multiple development branches of source code Concurrent Development practices and handling Conflicts Deployment Tips and Best Practices A recap after using the tool for a while

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  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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  • Combination of Operating Mode and Commit Strategy

    - by Kevin Yang
    If you want to populate a source into multiple targets, you may also want to ensure that every row from the source affects all targets uniformly (or separately). Let’s consider the Example Mapping below. If a row from SOURCE causes different changes in multiple targets (TARGET_1, TARGET_2 and TARGET_3), for example, it can be successfully inserted into TARGET_1 and TARGET_3, but failed to be inserted into TARGET_2, and the current Mapping Property TLO (target load order) is “TARGET_1 -> TARGET_2 -> TARGET_3”. What should Oracle Warehouse Builder do, in order to commit the appropriate data to all affected targets at the same time? If it doesn’t behave as you intended, the data could become inaccurate and possibly unusable.                                               Example Mapping In OWB, we can use Mapping Configuration Commit Strategies and Operating Modes together to achieve this kind of requirements. Below we will explore the combination of these two features and how they affect the results in the target tables Before going to the example, let’s review some of the terms we will be using (Details can be found in white paper Oracle® Warehouse Builder Data Modeling, ETL, and Data Quality Guide11g Release 2): Operating Modes: Set-Based Mode: Warehouse Builder generates a single SQL statement that processes all data and performs all operations. Row-Based Mode: Warehouse Builder generates statements that process data row by row. The select statement is in a SQL cursor. All subsequent statements are PL/SQL. Row-Based (Target Only) Mode: Warehouse Builder generates a cursor select statement and attempts to include as many operations as possible in the cursor. For each target, Warehouse Builder inserts each row into the target separately. Commit Strategies: Automatic: Warehouse Builder loads and then automatically commits data based on the mapping design. If the mapping has multiple targets, Warehouse Builder commits and rolls back each target separately and independently of other targets. Use the automatic commit when the consequences of multiple targets being loaded unequally are not great or are irrelevant. Automatic correlated: It is a specialized type of automatic commit that applies to PL/SQL mappings with multiple targets only. Warehouse Builder considers all targets collectively and commits or rolls back data uniformly across all targets. Use the correlated commit when it is important to ensure that every row in the source affects all affected targets uniformly. Manual: select manual commit control for PL/SQL mappings when you want to interject complex business logic, perform validations, or run other mappings before committing data. Combination of the commit strategy and operating mode To understand the effects of each combination of operating mode and commit strategy, I’ll illustrate using the following example Mapping. Firstly we insert 100 rows into the SOURCE table and make sure that the 99th row and 100th row have the same ID value. And then we create a unique key constraint on ID column for TARGET_2 table. So while running the example mapping, OWB tries to load all 100 rows to each of the targets. But the mapping should fail to load the 100th row to TARGET_2, because it will violate the unique key constraint of table TARGET_2. With different combinations of Commit Strategy and Operating Mode, here are the results ¦ Set-based/ Correlated Commit: Configuration of Example mapping:                                                     Result:                                                      What’s happening: A single error anywhere in the mapping triggers the rollback of all data. OWB encounters the error inserting into Target_2, it reports an error for the table and does not load the row. OWB rolls back all the rows inserted into Target_1 and does not attempt to load rows to Target_3. No rows are added to any of the target tables. ¦ Row-based/ Correlated Commit: Configuration of Example mapping:                                                   Result:                                                  What’s happening: OWB evaluates each row separately and loads it to all three targets. Loading continues in this way until OWB encounters an error loading row 100th to Target_2. OWB reports the error and does not load the row. It rolls back the row 100th previously inserted into Target_1 and does not attempt to load row 100 to Target_3. Then, if there are remaining rows, OWB will continue loading them, resuming with loading rows to Target_1. The mapping completes with 99 rows inserted into each target. ¦ Set-based/ Automatic Commit: Configuration of Example mapping: Result: What’s happening: When OWB encounters the error inserting into Target_2, it does not load any rows and reports an error for the table. It does, however, continue to insert rows into Target_3 and does not roll back the rows previously inserted into Target_1. The mapping completes with one error message for Target_2, no rows inserted into Target_2, and 100 rows inserted into Target_1 and Target_3 separately. ¦ Row-based/Automatic Commit: Configuration of Example mapping: Result: What’s happening: OWB evaluates each row separately for loading into the targets. Loading continues in this way until OWB encounters an error loading row 100 to Target_2 and reports the error. OWB does not roll back row 100th from Target_1, does insert it into Target_3. If there are remaining rows, it will continue to load them. The mapping completes with 99 rows inserted into Target_2 and 100 rows inserted into each of the other targets. Note: Automatic Correlated commit is not applicable for row-based (target only). If you design a mapping with the row-based (target only) and correlated commit combination, OWB runs the mapping but does not perform the correlated commit. In set-based mode, correlated commit may impact the size of your rollback segments. Space for rollback segments may be a concern when you merge data (insert/update or update/insert). Correlated commit operates transparently with PL/SQL bulk processing code. The correlated commit strategy is not available for mappings run in any mode that are configured for Partition Exchange Loading or that include a Queue, Match Merge, or Table Function operator. If you want to practice in your own environment, you can follow the steps: 1. Import the MDL file: commit_operating_mode.mdl 2. Fix the location for oracle module ORCL and deploy all tables under it. 3. Insert sample records into SOURCE table, using below plsql code: begin     for i in 1..99     loop         insert into source values(i, 'col_'||i);     end loop;     insert into source values(99, 'col_99'); end; 4. Configure MAPPING_1 to any combinations of operating mode and commit strategy you want to test. And make sure feature TLO of mapping is open. 5. Deploy Mapping “MAPPING_1”. 6. Run the mapping and check the result.

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  • How to archive data from a table to a local or remote database in SQL 2005 and SQL 2008

    - by simonsabin
    Often you have the need to archive data from a table. This leads to a number of challenges 1. How can you do it without impacting users 2. How can I make it transactionally consistent, i.e. the data I put in the archive is the data I remove from the main table 3. How can I get it to perform well Points 1 is very much tied to point 3. If it doesn't perform well then the delete of data is going to cause lots of locks and thus potentially blocking. For points 1 and 3 refer to my previous posts DELETE-TOP-x-rows-avoiding-a-table-scan and UPDATE-and-DELETE-TOP-and-ORDER-BY---Part2. In essence you need to be removing small chunks of data from your table and you want to do that avoiding a table scan. So that deals with the delete approach but archiving is about inserting that data somewhere else. Well in SQL 2008 they introduced a new feature INSERT over DML (Data Manipulation Language, i.e. SQL statements that change data), or composable DML. The ability to nest DML statements within themselves, so you can past the results of an insert to an update to a merge. I've mentioned this before here SQL-Server-2008---MERGE-and-optimistic-concurrency. This feature is currently limited to being able to consume the results of a DML statement in an INSERT statement. There are many restrictions which you can find here http://msdn.microsoft.com/en-us/library/ms177564.aspx look for the section "Inserting Data Returned From an OUTPUT Clause Into a Table" Even with the restrictions what we can do is consume the OUTPUT from a DELETE and INSERT the results into a table in another database. Note that in BOL it refers to not being able to use a remote table, remote means a table on another SQL instance. To show this working use this SQL to setup two databases foo and fooArchive create database foo go --create the source table fred in database foo select * into foo..fred from sys.objects go create database fooArchive go if object_id('fredarchive',DB_ID('fooArchive')) is null begin     select getdate() ArchiveDate,* into fooArchive..FredArchive from sys.objects where 1=2       end go And then we can use this simple statement to archive the data insert into fooArchive..FredArchive select getdate(),d.* from (delete top (1)         from foo..Fred         output deleted.*) d         go In this statement the delete can be any delete statement you wish so if you are deleting by ids or a range of values then you can do that. Refer to the DELETE-TOP-x-rows-avoiding-a-table-scan post to ensure that your delete is going to perform. The last thing you want to do is to perform 100 deletes each with 5000 records for each of those deletes to do a table scan. For a solution that works for SQL2005 or if you want to archive to a different server then you can use linked servers or SSIS. This example shows how to do it with linked servers. [ONARC-LAP03] is the source server. begin transaction insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*') d commit transaction and to prove the transactions work try, you should get the same number of records before and after. select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive   begin transaction insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*') d rollback transaction   select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive The transactions are very important with this solution. Look what happens when you don't have transactions and an error occurs   select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive   insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*                     raiserror (''Oh doo doo'',15,15)') d                     select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive Before running this think what the result would be. I got it wrong. What seems to happen is that the remote query is executed as a transaction, the error causes that to rollback. However the results have already been sent to the client and so get inserted into the

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  • SSIS: Deploying OLAP cubes using C# script tasks and AMO

    - by DrJohn
    As part of the continuing series on Building dynamic OLAP data marts on-the-fly, this blog entry will focus on how to automate the deployment of OLAP cubes using SQL Server Integration Services (SSIS) and Analysis Services Management Objects (AMO). OLAP cube deployment is usually done using the Analysis Services Deployment Wizard. However, this option was dismissed for a variety of reasons. Firstly, invoking external processes from SSIS is fraught with problems as (a) it is not always possible to ensure SSIS waits for the external program to terminate; (b) we cannot log the outcome properly and (c) it is not always possible to control the server's configuration to ensure the executable works correctly. Another reason for rejecting the Deployment Wizard is that it requires the 'answers' to be written into four XML files. These XML files record the three things we need to change: the name of the server, the name of the OLAP database and the connection string to the data mart. Although it would be reasonably straight forward to change the content of the XML files programmatically, this adds another set of complication and level of obscurity to the overall process. When I first investigated the possibility of using C# to deploy a cube, I was surprised to find that there are no other blog entries about the topic. I can only assume everyone else is happy with the Deployment Wizard! SSIS "forgets" assembly references If you build your script task from scratch, you will have to remember how to overcome one of the major annoyances of working with SSIS script tasks: the forgetful nature of SSIS when it comes to assembly references. Basically, you can go through the process of adding an assembly reference using the Add Reference dialog, but when you close the script window, SSIS "forgets" the assembly reference so the script will not compile. After repeating the operation several times, you will find that SSIS only remembers the assembly reference when you specifically press the Save All icon in the script window. This problem is not unique to the AMO assembly and has certainly been a "feature" since SQL Server 2005, so I am not amazed it is still present in SQL Server 2008 R2! Sample Package So let's take a look at the sample SSIS package I have provided which can be downloaded from here: DeployOlapCubeExample.zip  Below is a screenshot after a successful run. Connection Managers The package has three connection managers: AsDatabaseDefinitionFile is a file connection manager pointing to the .asdatabase file you wish to deploy. Note that this can be found in the bin directory of you OLAP database project once you have clicked the "Build" button in Visual Studio TargetOlapServerCS is an Analysis Services connection manager which identifies both the deployment server and the target database name. SourceDataMart is an OLEDB connection manager pointing to the data mart which is to act as the source of data for your cube. This will be used to replace the connection string found in your .asdatabase file Once you have configured the connection managers, the sample should run and deploy your OLAP database in a few seconds. Of course, in a production environment, these connection managers would be associated with package configurations or set at runtime. When you run the sample, you should see that the script logs its activity to the output screen (see screenshot above). If you configure logging for the package, then these messages will also appear in your SSIS logging. Sample Code Walkthrough Next let's walk through the code. The first step is to parse the connection string provided by the TargetOlapServerCS connection manager and obtain the name of both the target OLAP server and also the name of the OLAP database. Note that the target database does not have to exist to be referenced in an AS connection manager, so I am using this as a convenient way to define both properties. We now connect to the server and check for the existence of the OLAP database. If it exists, we drop the database so we can re-deploy. svr.Connect(olapServerName); if (svr.Connected) { // Drop the OLAP database if it already exists Database db = svr.Databases.FindByName(olapDatabaseName); if (db != null) { db.Drop(); } // rest of script } Next we start building the XMLA command that will actually perform the deployment. Basically this is a small chuck of XML which we need to wrap around the large .asdatabase file generated by the Visual Studio build process. // Start generating the main part of the XMLA command XmlDocument xmlaCommand = new XmlDocument(); xmlaCommand.LoadXml(string.Format("<Batch Transaction='false' xmlns='http://schemas.microsoft.com/analysisservices/2003/engine'><Alter AllowCreate='true' ObjectExpansion='ExpandFull'><Object><DatabaseID>{0}</DatabaseID></Object><ObjectDefinition/></Alter></Batch>", olapDatabaseName));  Next we need to merge two XML files which we can do by simply using setting the InnerXml property of the ObjectDefinition node as follows: // load OLAP Database definition from .asdatabase file identified by connection manager XmlDocument olapCubeDef = new XmlDocument(); olapCubeDef.Load(Dts.Connections["AsDatabaseDefinitionFile"].ConnectionString); // merge the two XML files by obtain a reference to the ObjectDefinition node oaRootNode.InnerXml = olapCubeDef.InnerXml;   One hurdle I had to overcome was removing detritus from the .asdabase file left by the Visual Studio build. Through an iterative process, I found I needed to remove several nodes as they caused the deployment to fail. The XMLA error message read "Cannot set read-only node: CreatedTimestamp" or similar. In comparing the XMLA generated with by the Deployment Wizard with that generated by my code, these read-only nodes were missing, so clearly I just needed to strip them out. This was easily achieved using XPath to find the relevant XML nodes, of which I show one example below: foreach (XmlNode node in rootNode.SelectNodes("//ns1:CreatedTimestamp", nsManager)) { node.ParentNode.RemoveChild(node); } Now we need to change the database name in both the ID and Name nodes using code such as: XmlNode databaseID = xmlaCommand.SelectSingleNode("//ns1:Database/ns1:ID", nsManager); if (databaseID != null) databaseID.InnerText = olapDatabaseName; Finally we need to change the connection string to point at the relevant data mart. Again this is easily achieved using XPath to search for the relevant nodes and then replace the content of the node with the new name or connection string. XmlNode connectionStringNode = xmlaCommand.SelectSingleNode("//ns1:DataSources/ns1:DataSource/ns1:ConnectionString", nsManager); if (connectionStringNode != null) { connectionStringNode.InnerText = Dts.Connections["SourceDataMart"].ConnectionString; } Finally we need to perform the deployment using the Execute XMLA command and check the returned XmlaResultCollection for errors before setting the Dts.TaskResult. XmlaResultCollection oResults = svr.Execute(xmlaCommand.InnerXml);  // check for errors during deployment foreach (Microsoft.AnalysisServices.XmlaResult oResult in oResults) { foreach (Microsoft.AnalysisServices.XmlaMessage oMessage in oResult.Messages) { if ((oMessage.GetType().Name == "XmlaError")) { FireError(oMessage.Description); HadError = true; } } } If you are not familiar with XML programming, all this may all seem a bit daunting, but perceiver as the sample code is pretty short. If you would like the script to process the OLAP database, simply uncomment the lines in the vicinity of Process method. Of course, you can extend the script to perform your own custom processing and to even synchronize the database to a front-end server. Personally, I like to keep the deployment and processing separate as the code can become overly complex for support staff.If you want to know more, come see my session at the forthcoming SQLBits conference.

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  • Fun with Aggregates

    - by Paul White
    There are interesting things to be learned from even the simplest queries.  For example, imagine you are given the task of writing a query to list AdventureWorks product names where the product has at least one entry in the transaction history table, but fewer than ten. One possible query to meet that specification is: SELECT p.Name FROM Production.Product AS p JOIN Production.TransactionHistory AS th ON p.ProductID = th.ProductID GROUP BY p.ProductID, p.Name HAVING COUNT_BIG(*) < 10; That query correctly returns 23 rows (execution plan and data sample shown below): The execution plan looks a bit different from the written form of the query: the base tables are accessed in reverse order, and the aggregation is performed before the join.  The general idea is to read all rows from the history table, compute the count of rows grouped by ProductID, merge join the results to the Product table on ProductID, and finally filter to only return rows where the count is less than ten. This ‘fully-optimized’ plan has an estimated cost of around 0.33 units.  The reason for the quote marks there is that this plan is not quite as optimal as it could be – surely it would make sense to push the Filter down past the join too?  To answer that, let’s look at some other ways to formulate this query.  This being SQL, there are any number of ways to write logically-equivalent query specifications, so we’ll just look at a couple of interesting ones.  The first query is an attempt to reverse-engineer T-SQL from the optimized query plan shown above.  It joins the result of pre-aggregating the history table to the Product table before filtering: SELECT p.Name FROM ( SELECT th.ProductID, cnt = COUNT_BIG(*) FROM Production.TransactionHistory AS th GROUP BY th.ProductID ) AS q1 JOIN Production.Product AS p ON p.ProductID = q1.ProductID WHERE q1.cnt < 10; Perhaps a little surprisingly, we get a slightly different execution plan: The results are the same (23 rows) but this time the Filter is pushed below the join!  The optimizer chooses nested loops for the join, because the cardinality estimate for rows passing the Filter is a bit low (estimate 1 versus 23 actual), though you can force a merge join with a hint and the Filter still appears below the join.  In yet another variation, the < 10 predicate can be ‘manually pushed’ by specifying it in a HAVING clause in the “q1” sub-query instead of in the WHERE clause as written above. The reason this predicate can be pushed past the join in this query form, but not in the original formulation is simply an optimizer limitation – it does make efforts (primarily during the simplification phase) to encourage logically-equivalent query specifications to produce the same execution plan, but the implementation is not completely comprehensive. Moving on to a second example, the following query specification results from phrasing the requirement as “list the products where there exists fewer than ten correlated rows in the history table”: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) < 10 ); Unfortunately, this query produces an incorrect result (86 rows): The problem is that it lists products with no history rows, though the reasons are interesting.  The COUNT_BIG(*) in the EXISTS clause is a scalar aggregate (meaning there is no GROUP BY clause) and scalar aggregates always produce a value, even when the input is an empty set.  In the case of the COUNT aggregate, the result of aggregating the empty set is zero (the other standard aggregates produce a NULL).  To make the point really clear, let’s look at product 709, which happens to be one for which no history rows exist: -- Scalar aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709;   -- Vector aggregate SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = 709 GROUP BY th.ProductID; The estimated execution plans for these two statements are almost identical: You might expect the Stream Aggregate to have a Group By for the second statement, but this is not the case.  The query includes an equality comparison to a constant value (709), so all qualified rows are guaranteed to have the same value for ProductID and the Group By is optimized away. In fact there are some minor differences between the two plans (the first is auto-parameterized and qualifies for trivial plan, whereas the second is not auto-parameterized and requires cost-based optimization), but there is nothing to indicate that one is a scalar aggregate and the other is a vector aggregate.  This is something I would like to see exposed in show plan so I suggested it on Connect.  Anyway, the results of running the two queries show the difference at runtime: The scalar aggregate (no GROUP BY) returns a result of zero, whereas the vector aggregate (with a GROUP BY clause) returns nothing at all.  Returning to our EXISTS query, we could ‘fix’ it by changing the HAVING clause to reject rows where the scalar aggregate returns zero: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID HAVING COUNT_BIG(*) BETWEEN 1 AND 9 ); The query now returns the correct 23 rows: Unfortunately, the execution plan is less efficient now – it has an estimated cost of 0.78 compared to 0.33 for the earlier plans.  Let’s try adding a redundant GROUP BY instead of changing the HAVING clause: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY th.ProductID HAVING COUNT_BIG(*) < 10 ); Not only do we now get correct results (23 rows), this is the execution plan: I like to compare that plan to quantum physics: if you don’t find it shocking, you haven’t understood it properly :)  The simple addition of a redundant GROUP BY has resulted in the EXISTS form of the query being transformed into exactly the same optimal plan we found earlier.  What’s more, in SQL Server 2008 and later, we can replace the odd-looking GROUP BY with an explicit GROUP BY on the empty set: SELECT p.Name FROM Production.Product AS p WHERE EXISTS ( SELECT * FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ); I offer that as an alternative because some people find it more intuitive (and it perhaps has more geek value too).  Whichever way you prefer, it’s rather satisfying to note that the result of the sub-query does not exist for a particular correlated value where a vector aggregate is used (the scalar COUNT aggregate always returns a value, even if zero, so it always ‘EXISTS’ regardless which ProductID is logically being evaluated). The following query forms also produce the optimal plan and correct results, so long as a vector aggregate is used (you can probably find more equivalent query forms): WHERE Clause SELECT p.Name FROM Production.Product AS p WHERE ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) < 10; APPLY SELECT p.Name FROM Production.Product AS p CROSS APPLY ( SELECT NULL FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () HAVING COUNT_BIG(*) < 10 ) AS ca (dummy); FROM Clause SELECT q1.Name FROM ( SELECT p.Name, cnt = ( SELECT COUNT_BIG(*) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID GROUP BY () ) FROM Production.Product AS p ) AS q1 WHERE q1.cnt < 10; This last example uses SUM(1) instead of COUNT and does not require a vector aggregate…you should be able to work out why :) SELECT q.Name FROM ( SELECT p.Name, cnt = ( SELECT SUM(1) FROM Production.TransactionHistory AS th WHERE th.ProductID = p.ProductID ) FROM Production.Product AS p ) AS q WHERE q.cnt < 10; The semantics of SQL aggregates are rather odd in places.  It definitely pays to get to know the rules, and to be careful to check whether your queries are using scalar or vector aggregates.  As we have seen, query plans do not show in which ‘mode’ an aggregate is running and getting it wrong can cause poor performance, wrong results, or both. © 2012 Paul White Twitter: @SQL_Kiwi email: [email protected]

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  • Google Analytics on Android

    - by pjv
    There is a specific and official analytics SDK for native Android apps (note that I'm not talking about webpages in apps on a phone). This library basically sends pages and events to Google Analytics and you can view your analytics in exactly the same dashboard as for websites. Since my background is apps rather than websites, and since a lot of the Google Analytics terminology seems particularly inapplicable to a native app, I need some pointers. Please discuss my remarks, provide some clarification where you think I'm off-track, and above all share good experiences! 1. Page Views Pages mostly can match different Activities (and Dialogs) being displayed. Activities can be visible behind non-full-screen Activities however, though only the top-level Activity can be interacted. This sort-off clashes with a "(page) view". You'd also want at least one page view for each visit and therefore put one page view tracker in the Application class. However this does not constitute a window or sorts. Usually an Activity will open at the same time, so the time spent on that page will have been 0. This will influence your "time spent" statistics. How are these counted anyway? Moreover, there is a loose coupling between the Activities, by means of Intents. A user can, much like on any website, step in at any Activity, although usually this then concerns resuming the application where he left off. This makes that the hierarchy of Activities usually is very flat. And since there are no url's involved. What meaning would using slashes in page titles have, such as "/Home"? All pages would appear on an equal level in the reports, so no content drilldown. Non-unique page views seem to be counted as some kind of indicator of successfulness: how often does the visitor revisit the page. When the user rotates the screen however usually an Activity resumes again, thus making it a new page view. This happens a lot. Maybe a well-thought-through placement of the call might solve this, or placing several, I'm not sure. How to deal with Page Views? 2. Events I'd say there are two sorts: A user event Something that happened, usually as an indirect consequence of the above. The latter particularly is giving me headaches. First of all, many events aren't written in code any more, but pieced logically together by means of Intents. This means that there is no place to put the analytics call. You'd either have to give up this advantage and start doing it the old-fashioned way in favor of good analytics, or, just be missing some events. Secondly, as a developer you're not so much interested in when a user clicks a button, but if the action that should have been performed really was performed and what the result was. There seems to be no clear way to get resulting data into Google Analytics (what's up with the integers? I want to put in Strings!). The same that applies to the flat pages hierarchy, also goes for the event categories. You could do "vertical" categories (topically, that is), but some code is shared "horizontally" and the tracking will be equally shared. Just as with the Intents mechanism, inheritance makes it hard for you to put the tracking in the right places at all times. And I can't really imagine "horizontal" categories. Unless you start making really small categories, such as all the items form the same menu in one category, I have a hard time grasping the concept. Finally, how do you deal with cancelling? Usually you both have an explicit cancel mechanism by ways of a button, as well as the implicit cancel when the "back"-button is pressed to leave the activity and there were no changes. The latter also applies to "saves", when the back button is pressed and there ARE changes. How are you consequently going to catch all these if not by doing all the "back"-button work yourself? How to deal with events? 3. Goals For goal types I have choice of: URL Destination, Time on Site, and Pages/Visit. Most apps don't have a funnel that leads the user to some "registration done" or "order placed" page. Apps have either already been bought (in which case you want to stimulate the user to love your app, so that he might bring on new buyers) or are paid for by in-app ads. So URL Destination is not a very important goal. Time on Site also seems troublesome. First, I have some doubt on how this would be measured. Second, I don't necessarily want my user to spend a lot of time in my already paid app, just be active and content. Equivalently, why not mention how frequent a user uses your app? Regarding Pages/Visit I already mentioned how screen orientation changes blow up the page view numbers. In an app I'd be most interested in events/visit to measure the user's involvement/activity. If he's intensively using the app then he must be loving it right? Furthermore, I also have some small funnels (that do not lead to conversion though) that I want to see streamlined. In my mind those funnels would end in events rather than page views but that seems not to be possible. I could also measure clickthroughs on in-app ads, but then I'd need to track those as Page Views rather than Events, in view of "URL Destination". What are smart goals for apps and how can you fit them on top of Analytics? 4. Optimisation Is there a smart way to manually do what "Website Optimiser" does for websites? Most importantly, how would I track different landing page designs? 5. Traffic Sources Referrals deal with installation time referrals, if you're smart enough to get them included. But perhaps I'd also want to get some data which third-party app sends users to my app to perform some actions (this app interoperability is possible via Intents). Many of the terminologies related to "Traffic Sources" seem totally meaningless and there is no possibility of connecting in AdSense. What are smart uses of this data? 6. Visitors Of the "Browser capabilities", "Network Properties" and "Mobile" tabs, many things are pointless as they have no influence on / relation with my mostly offline app that won't use flash anyway. Only if you drill down far enough, can you get to OS versions, which do matter a lot. I even forgot where you could check what exact Android devices visited. What are smart uses of this data? How can you make the relevant info more prominent? 7. Other No in-page analytics. I have to register my app as a web-url (What!?)?

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  • Different Not Automatically Implies Better

    - by Alois Kraus
    Originally posted on: http://geekswithblogs.net/akraus1/archive/2013/11/05/154556.aspxRecently I was digging deeper why some WCF hosted workflow application did consume quite a lot of memory although it did basically only load a xaml workflow. The first tool of choice is Process Explorer or even better Process Hacker (has more options and the best feature copy&paste does work). The three most important numbers of a process with regards to memory are Working Set, Private Working Set and Private Bytes. Working set is the currently consumed physical memory (parts can be shared between processes e.g. loaded dlls which are read only) Private Working Set is the physical memory needed by this process which is not shareable Private Bytes is the number of non shareable which is only visible in the current process (e.g. all new, malloc, VirtualAlloc calls do create private bytes) When you have a bigger workflow it can consume under 64 bit easily 500MB for a 1-2 MB xaml file. This does not look very scalable. Under 64 bit the issue is excessive private bytes consumption and not the managed heap. The picture is quite different for 32 bit which looks a bit strange but it seems that the hosted VB compiler is a lot less memory hungry under 32 bit. I did try to repro the issue with a medium sized xaml file (400KB) which does contain 1000 variables and 1000 if which can be represented by C# code like this: string Var1; string Var2; ... string Var1000; if (!String.IsNullOrEmpty(Var1) ) { Console.WriteLine(“Var1”); } if (!String.IsNullOrEmpty(Var2) ) { Console.WriteLine(“Var2”); } ....   Since WF is based on VB.NET expressions you are bound to the hosted VB.NET compiler which does result in (x64) 140 MB of private bytes which is ca. 140 KB for each if clause which is quite a lot if you think about the actually present functionality. But there is hope. .NET 4.5 does allow now C# expressions for WF which is a major step forward for all C# lovers. I did create some simple patcher to “cross compile” my xaml to C# expressions. Lets look at the result: C# Expressions VB Expressions x86 x86 On my home machine I have only 32 bit which gives you quite exactly half of the memory consumption under 64 bit. C# expressions are 10 times more memory hungry than VB.NET expressions! I wanted to do more with less memory but instead it did consume a magnitude more memory. That is surprising to say the least. The workflow does initialize in about the same time under x64 and x86 where the VB code does it in 2s whereas the C# version needs 18s. Also nearly ten times slower. That is a too high price to pay for any bigger sized xaml workflow to convert from VB.NET to C# expressions. If I do reduce the number of expressions to 500 then it does need 400MB which is about half of the memory. It seems that the cost per if does rise linear with the number of total expressions in a xaml workflow.  Expression Language Cost per IF Startup Time C# 1000 Ifs x64 1,5 MB 18s C# 500 Ifs x64 750 KB 9s VB 1000 Ifs x64 140 KB 2s VB 500 Ifs x64 70 KB 1s Now we can directly compare two MS implementations. It is clear that the VB.NET compiler uses the same underlying structure but it has much higher offset compared to the highly inefficient C# expression compiler. I have filed a connect bug here with a harsher wording about recent advances in memory consumption. The funniest thing is that one MS employee did give an Azure AppFabric demo around early 2011 which was so slow that he needed to investigate with xperf. He was after startup time and the call stacks with regards to VB.NET expression compilation were remarkably similar. In fact I only found this post by googling for parts of my call stacks. … “C# expressions will be coming soon to WF, and that will have different performance characteristics than VB” … What did he know Jan 2011 what I did no know until today? ;-). He knew that C# expression will come but that they will not be automatically have better footprint. It is about time to fix that. In its current state C# expressions are not usable for bigger workflows. That also explains the headline for today. You can cheat startup time by prestarting workflows so that the demo looks nice and snappy but it does hurt scalability a lot since you do need much more memory than necessary. I did find the stacks by enabling virtual allocation tracking within XPerf which is still the best tool out there. But first you need to look at your process to check where the memory is hiding: For the C# Expression compiler you do not need xperf. You can directly dump the managed heap and check with a profiler of your choice. But if the allocations are happening on the Private Data ( VirtualAlloc ) you can find it with xperf. There is a nice video on channel 9 explaining VirtualAlloc tracking it in greater detail. If your data allocations are on the Heap it does mean that the C/C++ runtime did create a heap for you where all malloc, new calls do allocate from it. You can enable heap tracing with xperf and full call stack support as well which is doable via xperf like it is shown also on channel 9. Or you can use WPRUI directly: To make “Heap Usage” it work you need to set for your executable the tracing flags (before you start it). For example devenv.exe HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Windows NT\CurrentVersion\Image File Execution Options\devenv.exe DWORD TracingFlags 1 Do not forget to disable it after you did complete profiling the process or it will impact the startup time quite a lot. You can with xperf attach directly to a running process and collect heap allocation information from a gone wild process. Very handy if you need to find out what a process was doing which has arrived in a funny state. “VirtualAlloc usage” does work without explicitly enabling stuff for a specific process and is always on machine wide. I had issues on my Windows 7 machines with the call stack collection and the latest Windows 8.1 Performance Toolkit. I was told that WPA from Windows 8.0 should work fine but I do not want to downgrade.

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  • ?12c database ????Adaptive Execution Plans ????????

    - by Liu Maclean(???)
    12c R1 ????SQL??????- Adaptive Execution Plans ????????,???????optimizer ??????(runtime)???????????????, ????????????????????? SQL???????? ????????????, ?????????????????????????????????????????????????????????????adaptive plan ????????????????????????????????????,?????subplan???????????????????? ??????, ???????? ???????????????,?????????, ?????? ???????????????”???”????, ???????????????????buffer ???????  ????????????,?????,??????????????????? ???optimizer ?????????????????????????,?????????????????????????????????????????plan???? ??12C?????????????, ???????????????????,?????? ???????????? ????????????2???: Dynamic Plans????: ???????????????????????;??????,???optimizer??????????subplans??????????????, ???????????????????,?????????????? Reoptimization????: ?Dynamic Plans????,Reoptimization??????????????????????Reoptimization??,?????????????????????????,??reoptimization????? OPTIMIZER_ADAPTIVE_REPORTING_ONLY ???? report-only????????????????TRUE,?????????report-only????,???????????????,??????????????? Dynamic Plans ??????????????,????????????????????????, ?????????????,???????????,????????????????????????????????????????? ?????????????final plan??????????????default plan, ??final plan?default plan???????,????????????? subplan ???????????????,???????????????????????? ??????,???????statistics collector ?buffer???????????statistics collector?????????????????,???????????????????????????? ?????????????????????????????????????????,??????????,?????????????? ???????????,???????buffer???? ???????????????,?????????????????????????????,??????buffer,??????final plan? ????????,???????????????????????,????????????????? ?V$SQL??????IS_RESOLVED_DYNAMIC_PLAN??????????final plan???default plan? ??????dynamic plan ???????SQL PLAN directives?????? declare cursor PLAN_DIRECTIVE_IDS is select directive_id from DBA_SQL_PLAN_DIRECTIVES; begin for z in PLAN_DIRECTIVE_IDS loop DBMS_SPD.DROP_SQL_PLAN_DIRECTIVE(z.directive_id); end loop; end; / explain plan for select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; select * from table(dbms_xplan.display()); Plan hash value: 1255158658 www.askmaclean.com ------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 4 | 128 | 7 (0)| 00:00:01 | | 1 | NESTED LOOPS | | | | | | | 2 | NESTED LOOPS | | 4 | 128 | 7 (0)| 00:00:01 | |* 3 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 (0)| 00:00:01 | |* 4 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK | 1 | | 0 (0)| 00:00:01 | | 5 | TABLE ACCESS BY INDEX ROWID| PRODUCT_INFORMATION | 1 | 20 | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("O"."UNIT_PRICE"=15 AND "QUANTITY">1) 4 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") alter session set events '10053 trace name context forever,level 1'; OR alter session set events 'trace[SQL_Plan_Directive] disk highest'; select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; ---------------------------------------------------------------+-----------------------------------+ | Id | Operation | Name | Rows | Bytes | Cost | Time | ---------------------------------------------------------------+-----------------------------------+ | 0 | SELECT STATEMENT | | | | 7 | | | 1 | HASH JOIN | | 4 | 128 | 7 | 00:00:01 | | 2 | NESTED LOOPS | | | | | | | 3 | NESTED LOOPS | | 4 | 128 | 7 | 00:00:01 | | 4 | STATISTICS COLLECTOR | | | | | | | 5 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 | 00:00:01 | | 6 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK| 1 | | 0 | | | 7 | TABLE ACCESS BY INDEX ROWID | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | | 8 | TABLE ACCESS FULL | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | ---------------------------------------------------------------+-----------------------------------+ Predicate Information: ---------------------- 1 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") 5 - filter(("O"."UNIT_PRICE"=15 AND "QUANTITY">1)) 6 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") ===================================== SPD: BEGIN context at statement level ===================================== Stmt: ******* UNPARSED QUERY IS ******* SELECT /*+ OPT_ESTIMATE (@"SEL$1" JOIN ("P"@"SEL$1" "O"@"SEL$1") ROWS=13.000000 ) OPT_ESTIMATE (@"SEL$1" TABLE "O"@"SEL$1" ROWS=13.000000 ) */ "P"."PRODUCT_NAME" "PRODUCT_NAME" FROM "OE"."ORDER_ITEMS" "O","OE"."PRODUCT_INFORMATION" "P" WHERE "O"."UNIT_PRICE"=15 AND "O"."QUANTITY">1 AND "P"."PRODUCT_ID"="O"."PRODUCT_ID" Objects referenced in the statement PRODUCT_INFORMATION[P] 92194, type = 1 ORDER_ITEMS[O] 92197, type = 1 Objects in the hash table Hash table Object 92197, type = 1, ownerid = 6573730143572393221: No Dynamic Sampling Directives for the object Hash table Object 92194, type = 1, ownerid = 17822962561575639002: No Dynamic Sampling Directives for the object Return code in qosdInitDirCtx: ENBLD =================================== SPD: END context at statement level =================================== ======================================= SPD: BEGIN context at query block level ======================================= Query Block SEL$1 (#0) Return code in qosdSetupDirCtx4QB: NOCTX ===================================== SPD: END context at query block level ===================================== SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Inserted felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: qosdCreateFindingSingTab retCode = CREATED, fid = 2896834833840853267 SPD: qosdCreateDirCmp retCode = CREATED, fid = 2896834833840853267 SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SKIP_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Modified felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 5618517328604016300 SPD: Modified felem, fid=5618517328604016300, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 1142802697078608149 SPD: Modified felem, fid=1142802697078608149, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 2, objcnt = 2, obItr = 0, objid = 92194, objtyp = 1, vecsize = 0, obItr = 1, objid = 92197, objtyp = 1, vecsize = 0, fid = 1437680122701058051 SPD: Modified felem, fid=1437680122701058051, ftype = 1, freason = 2, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO select * from table(dbms_xplan.display_cursor(format=>'report')) ; ????report????adaptive plan Adaptive plan: ------------- This cursor has an adaptive plan, but adaptive plans are enabled for reporting mode only.  The plan that would be executed if adaptive plans were enabled is displayed below. ------------------------------------------------------------------------------------------ | Id  | Operation          | Name                | Rows  | Bytes | Cost (%CPU)| Time     | ------------------------------------------------------------------------------------------ |   0 | SELECT STATEMENT   |                     |       |       |     7 (100)|          | |*  1 |  HASH JOIN         |                     |     4 |   128 |     7   (0)| 00:00:01 | |*  2 |   TABLE ACCESS FULL| ORDER_ITEMS         |     4 |    48 |     3   (0)| 00:00:01 | |   3 |   TABLE ACCESS FULL| PRODUCT_INFORMATION |     1 |    20 |     1   (0)| 00:00:01 | ------------------------------------------------------------------------------------------ SQL> select SQL_ID,IS_RESOLVED_DYNAMIC_PLAN,sql_text from v$SQL WHERE SQL_TEXT like '%MALCEAN%' and sql_text not like '%like%'; SQL_ID IS -------------------------- -- SQL_TEXT -------------------------------------------------------------------------------- 6ydj1bn1bng17 Y select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id ???? explain plan for ????default plan, ??????optimizer???final plan,??V$SQL.IS_RESOLVED_DYNAMIC_PLAN???Y,????????????? DBA_SQL_PLAN_DIRECTIVES?????????????SQL PLAN DIRECTIVES, ???12c? ???MMON?????DML ???column usage??????????,????SMON??? MMON????SGA??PLAN DIRECTIVES??? ?????DBMS_SPD.flush_sql_plan_directive???? select directive_id,type,reason from DBA_SQL_PLAN_DIRECTIVES / DIRECTIVE_ID TYPE REASON ----------------------------------- -------------------------------- ----------------------------- 10321283028317893030 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 4757086536465754886 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 16085268038103121260 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE SQL> set pages 9999 SQL> set lines 300 SQL> col state format a5 SQL> col subobject_name format a11 SQL> col col_name format a11 SQL> col object_name format a13 SQL> select d.directive_id, o.object_type, o.object_name, o.subobject_name col_name, d.type, d.state, d.reason 2 from dba_sql_plan_directives d, dba_sql_plan_dir_objects o 3 where d.DIRECTIVE_ID=o.DIRECTIVE_ID 4 and o.object_name in ('ORDER_ITEMS') 5 order by d.directive_id; DIRECTIVE_ID OBJECT_TYPE OBJECT_NAME COL_NAME TYPE STATE REASON ------------ ------------ ------------- ----------- -------------------------------- ----- ------------------------------------- --- 1.8156E+19 COLUMN ORDER_ITEMS UNIT_PRICE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 TABLE ORDER_ITEMS DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 COLUMN ORDER_ITEMS QUANTITY DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE DBA_SQL_PLAN_DIRECTIVES????? _BASE_OPT_DIRECTIVE ? _BASE_OPT_FINDING SELECT d.dir_own#, d.dir_id, d.f_id, decode(type, 1, 'DYNAMIC_SAMPLING', 'UNKNOWN'), decode(state, 1, 'NEW', 2, 'MISSING_STATS', 3, 'HAS_STATS', 4, 'CANDIDATE', 5, 'PERMANENT', 6, 'DISABLED', 'UNKNOWN'), decode(bitand(flags, 1), 1, 'YES', 'NO'), cast(d.created as timestamp), cast(d.last_modified as timestamp), -- Please see QOSD_DAYS_TO_UPDATE and QOSD_PLUS_SECONDS for more details -- about 6.5 cast(d.last_used as timestamp) - NUMTODSINTERVAL(6.5, 'day') FROM sys.opt_directive$ d ??dbms_spd??? SQL PLAN DIRECTIVES, SQL PLAN DIRECTIVES???retention ???53?: Package: DBMS_SPD This package provides subprograms for managing Sql Plan Directives(SPD). SPD are objects generated automatically by Oracle server. For example, if server detects that the single table cardinality estimated by optimizer is off from the actual number of rows returned when accessing the table, it will automatically create a directive to do dynamic sampling for the table. When any Sql statement referencing the table is compiled, optimizer will perform dynamic sampling for the table to get more accurate estimate. Notes: DBMSL_SPD is a invoker-rights package. The invoker requires ADMINISTER SQL MANAGEMENT OBJECT privilege for executing most of the subprograms of this package. Also the subprograms commit the current transaction (if any), perform the operation and commit it again. DBA view dba_sql_plan_directives shows all the directives created in the system and the view dba_sql_plan_dir_objects displays the objects that are included in the directives. -- Default value for SPD_RETENTION_WEEKS SPD_RETENTION_WEEKS_DEFAULT CONSTANT varchar2(4) := '53'; | STATE : NEW : Newly created directive. | : MISSING_STATS : The directive objects do not | have relevant stats. | : HAS_STATS : The objects have stats. | : PERMANENT : A permanent directive. Server | evaluated effectiveness and these | directives are useful. | | AUTO_DROP : YES : Directive will be dropped | automatically if not | used for SPD_RETENTION_WEEKS. | This is the default behavior. | NO : Directive will not be dropped | automatically. Procedure: flush_sql_plan_directive This procedure allows manually flushing the Sql Plan directives that are automatically recorded in SGA memory while executing sql statements. The information recorded in SGA are periodically flushed by oracle background processes. This procedure just provides a way to flush the information manually. ????”_optimizer_dynamic_plans”(enable dynamic plans)????????,???TRUE??DYNAMIC PLAN? ???FALSE???????????? ????,Dynamic Plan????????????Nested Loop?Hash Join???case ,????????Nested loop???????????HASH JOIN,?HASH JOIN????????????????? ????????subplan?????,???? pass?? ?join method???,?????STATISTICS COLLECTOR???cardinality?,???????HASH JOIN?????Nested Loop,????????????subplan?????access path; ???????Sales??????????????????,????HASH JOIN,??SUBPLAN??customers?????????;?????Nested Loop,???????cust_id?????Range Scan+Access by Rowid? Cardinality feedback Cardinality feedback????????11.2????,????????re-optimization???;  ???????????,Cardinality feedback?????????????????????????? ???????????????????,?????????????????,??????????Cardinality feedback????????????? ????????????????????????? ??????????????Cardinality feedback ??: ????????,???????????,??????????,????????????????selectivity ??? ????????????: ??????,?????????????????????????????????,??????????????????? ????????????????????????????????????????,?????????????????????????? ?????????,???????????????,?????????? ??????????Cardinality ????,??????join Cardinality ????????? Cardinality feedback???????cursor?,?Cursor???aged out????? SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ---------------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem | ---------------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | 20 | | | | |* 1 | HASH JOIN | | 1 | 4 | 13 |00:00:00.01 | 24 | 20 | 2061K| 2061K| 429K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 4 | 13 |00:00:00.01 | 7 | 6 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 1 | 288 |00:00:00.01 | 17 | 14 | | | | ---------------------------------------------------------------------------------------------------------------------------------------- SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | | | | |* 1 | HASH JOIN | | 1 | 13 | 13 |00:00:00.01 | 24 | 2061K| 2061K| 413K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 13 | 13 |00:00:00.01 | 7 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 288 | 288 |00:00:00.01 | 17 | | | | ------------------------------------------------------------------------------------------------------------------------------- Note ----- - statistics feedback used for this statement SQL> select count(*) from v$SQL where SQL_ID='cz0hg2zkvd10y'; COUNT(*) ---------- 2 SQL>select sql_ID,USE_FEEDBACK_STATS FROM V$SQL_SHARED_CURSOR where USE_FEEDBACK_STATS ='Y'; SQL_ID U ------------- - cz0hg2zkvd10y Y ????????Cardinality feedback????,???????????????????????????,????????????order_items???????? ????2??????plan hash value??(??????????),?????2????child cursor??????gather_plan_statistics???actual : A-ROWS  estimate :E-ROWS????????? Automatic Re-optimization ???dynamic plan, Re-optimization???????????????  ?  ??????????????? ????????????????????????????????  ???????????,??????????????, ???????????????????? ???????????  Re-optimization??, ????????????????????? Re-optimization????dynamic plan??????????  dynamic plan????????????????????, ???????????????????? ????,??????????join order ??????????????,?????????????join order????? ??????,????????Re-optimization, ??Re-optimization ??????????????????? ?Oracle database 12c?,join statistics?????????????????????,??????????????????????Re-optimization???????????adaptive cursor sharing????? ????????????????,???????????? ????? ???????statistics collectors ????????????????????Re-optimization??????2?????????????,???????????????? ??????????????Re-optimization?????,?????????????????????? ???v$SQL??????IS_REOPTIMIZABLE?????????????????????Re-optimization,??????????Re-optimization???,?????Re-optimization ,???????reporting????? IS_REOPTIMIZABLE VARCHAR2(1) This columns shows whether the next execution matching this child cursor will trigger a reoptimization. The values are:   Y: If the next execution will trigger a reoptimization R: If the child cursor contains reoptimization information, but will not trigger reoptimization because the cursor was compiled in reporting mode N: If the child cursor has no reoptimization information ??1: select plan_table_output from table (dbms_xplan.display_cursor('gwf99gfnm0t7g',NULL,'ALLSTATS LAST')); SQL_ID  gwf99gfnm0t7g, child number 0 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 1906736282 ------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation             | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT      |                     |      1 |        |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   1 |  NESTED LOOPS         |                     |      1 |      1 |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   2 |   MERGE JOIN CARTESIAN|                     |      1 |      4 |   9135 |00:00:00.02 |      34 |     15 |       |       |          | |*  3 |    TABLE ACCESS FULL  | PRODUCT_INFORMATION |      1 |      1 |     87 |00:00:00.01 |      33 |     14 |       |       |          | |   4 |    BUFFER SORT        |                     |     87 |    105 |   9135 |00:00:00.01 |       1 |      1 |  4096 |  4096 | 4096  (0)| |   5 |     INDEX FULL SCAN   | ORDER_PK            |      1 |    105 |    105 |00:00:00.01 |       1 |      1 |       |       |          | |*  6 |   INDEX UNIQUE SCAN   | ORDER_ITEMS_UK      |   9135 |      1 |    269 |00:00:00.01 |    1302 |      3 |       |       |          | ------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    6 - access("O"."ORDER_ID"="ORDER_ID" AND "P"."PRODUCT_ID"="O"."PRODUCT_ID") SQL_ID  gwf99gfnm0t7g, child number 1 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 35479787 -------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation              | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | -------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT       |                     |      1 |        |    269 |00:00:00.01 |      63 |      3 |       |       |          | |   1 |  NESTED LOOPS          |                     |      1 |    269 |    269 |00:00:00.01 |      63 |      3 |       |       |          | |*  2 |   HASH JOIN            |                     |      1 |    313 |    269 |00:00:00.01 |      42 |      3 |  1321K|  1321K| 1234K (0)| |*  3 |    TABLE ACCESS FULL   | PRODUCT_INFORMATION |      1 |     87 |     87 |00:00:00.01 |      16 |      0 |       |       |          | |   4 |    INDEX FAST FULL SCAN| ORDER_ITEMS_UK      |      1 |    665 |    665 |00:00:00.01 |      26 |      3 |       |       |          | |*  5 |   INDEX UNIQUE SCAN    | ORDER_PK            |    269 |      1 |    269 |00:00:00.01 |      21 |      0 |       |       |          | -------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    2 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID")    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    5 - access("O"."ORDER_ID"="ORDER_ID") Note -----    - statistics feedback used for this statement    SQL> select IS_REOPTIMIZABLE,child_number FROM V$SQL  A where A.SQL_ID='gwf99gfnm0t7g'; IS CHILD_NUMBER -- ------------ Y             0 N             1    1* select child_number,other_xml From v$SQL_PLAN  where SQL_ID='gwf99gfnm0t7g' and other_xml is not nul SQL> / CHILD_NUMBER OTHER_XML ------------ --------------------------------------------------------------------------------            1 <other_xml><info type="cardinality_feedback">yes</info><info type="db_version">1              2.1.0.1</info><info type="parse_schema"><![CDATA["OE"]]></info><info type="plan_              hash">35479787</info><info type="plan_hash_2">3382491761</info><outline_data><hi              nt><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]></hint><hint><![CDATA[OPTIMIZER_FEATUR              ES_ENABLE('12.1.0.1')]]></hint><hint><![CDATA[DB_VERSION('12.1.0.1')]]></hint><h              int><![CDATA[ALL_ROWS]]></hint><hint><![CDATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></              hint><hint><![CDATA[MERGE(@"SEL$2")]]></hint><hint><![CDATA[OUTLINE(@"SEL$1")]]>              </hint><hint><![CDATA[OUTLINE(@"SEL$2")]]></hint><hint><![CDATA[FULL(@"SEL$F5BB7              4E1" "P"@"SEL$2")]]></hint><hint><![CDATA[INDEX_FFS(@"SEL$F5BB74E1" "O"@"SEL$2"              ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PRODUCT_ID"))]]></hint><hint><![CDATA[I              NDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA[              LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$2" "O"@"SEL$1")]]></hint><hint><![C              DATA[USE_HASH(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint><hint><![CDATA[USE_NL(@"SEL$              F5BB74E1" "O"@"SEL$1")]]></hint></outline_data></other_xml>            0 <other_xml><info type="db_version">12.1.0.1</info><info type="parse_schema"><![C              DATA["OE"]]></info><info type="plan_hash">1906736282</info><info type="plan_hash              _2">2579473118</info><outline_data><hint><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]>              </hint><hint><![CDATA[OPTIMIZER_FEATURES_ENABLE('12.1.0.1')]]></hint><hint><![CD              ATA[DB_VERSION('12.1.0.1')]]></hint><hint><![CDATA[ALL_ROWS]]></hint><hint><![CD              ATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></hint><hint><![CDATA[MERGE(@"SEL$2")]]></hi              nt><hint><![CDATA[OUTLINE(@"SEL$1")]]></hint><hint><![CDATA[OUTLINE(@"SEL$2")]]>              </hint><hint><![CDATA[FULL(@"SEL$F5BB74E1" "P"@"SEL$2")]]></hint><hint><![CDATA[              INDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA              [INDEX(@"SEL$F5BB74E1" "O"@"SEL$2" ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PROD              UCT_ID"))]]></hint><hint><![CDATA[LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$1              " "O"@"SEL$2")]]></hint><hint><![CDATA[USE_MERGE_CARTESIAN(@"SEL$F5BB74E1" "O"@"              SEL$1")]]></hint><hint><![CDATA[USE_NL(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint></o              utline_data></other_xml> ??2: SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 0 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 -------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | -------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | 14 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 8 | 29 |00:00:00.01 | 17 | 14 | -------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OWNER OBJECT_NAME COL_NAME OBJECT TYPE STATE REASON ----------------------- ----- ------------- ----------- ------ ---------------- ----- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; ELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 1 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 ----------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | ----------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 29 | 29 |00:00:00.01 | 17 | ----------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) Note ----- - cardinality feedback used for this statement SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' b74nw722wjvy3 1 select /*+g N ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' SELECT /*+gather_plan_statistics*/ CUST_EMAIL FROM CUSTOMERS WHERE CUST_STATE_PROVINCE='MA' AND COUNTRY_ID='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID 3tk6hj3nkcs2u, child number 0 ------------------------------------- Select /*+gather_plan_statistics*/ cust_email From customers Where cust_state_province='MA' And country_id='US' Plan hash value: 1683234692 ------------------------------------------------------------------------------- |Id | Operation | Name | Starts|E-Rows|A-Rows| A-Time |Buffers| ------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 2 |00:00:00.01| 16 | |*1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 2| 2 |00:00:00.01| 16 | ----------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='MA' AND "COUNTRY_ID"='US')) Note ----- - dynamic sampling used for this statement (level=2) - 1 Sql Plan Directive used for this statement EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OW OBJECT_NA COL_NAME OBJECT TYPE STATE REASON ------------------- -- --------- ---------- ------- --------------- ------------- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE

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  • Outlook 2011 Contact Import from CSV with Notes containing new lines / cr / lf

    - by Paul Hargreaves
    I'm trying to import several thousand contacts into Outlook 2011 for Mac. Everything is working well except the Notes field as I cannot figure out how to get new lines / carriage returns into it. There is no documentation for the exact format that Outlook supports. After searching the web and experimenting I have tried: Creating a single contact in Outlook with Notes containing several lines of text. I then export the contact to a csv, deleting the contact in Outlook, then re-import. All lines in Notes merge together :-/ Following tips I found such as containing new lines around quotes. e.g. http://creativyst.com/Doc/Articles/CSV/CSV01.htm (search for line-break) Switching the CSV format from DOS to Unix, experimenting using manually injected ctrl-characters such as ^M etc. I would include an example export/import but unfortunately the the new breaks included do not work well in a SU code block.

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  • Windows Can't Find SepSysPlant.exe?

    - by Stevoni
    In the last two days I've suddenly started receiving the following error message: "Windows cannot find'C:\WINDOWS\sepsysplant.exe'. Make sure you typed the name correctly, and try again.To Search for a file, click the start." It comes and goes with no apparent association with any running applications. I only have a bare minimum of programs installed as this is a work machine (XP Pro SP3) and the Symantec virus scan (today's definitions) were unable to find anything. After a quick Google search I found 4 results all of which were asking the question or stating the existence of the file and the Yahoo search resulted with nothing. Anyone know what's causing this a way of tracking down what it is?

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  • Resolving “ssl handshake failure” error in PostgresQL

    - by Mitch
    I would like to connect to my Postgres 8.3 database using SSL from my XP client using OpenSSL. This works fine without SSL. When I try it with SSL (no client certificate), I get the error: error:140790E5:SSL routines:SSL23_WRITE:ssl handshake failure I have followed the instructions in the Postgres manual for SSL including creating a self-signed certificate. In my pg_hba.conf there is a line: host dbname loginname 123.45.67.89/32 md5 The version of OpenSSL on the server is 0.9.8g and on the client is 0.9.8j. I'd appreciate any suggestions for tracking down the problem. Edit: The uncommented lines from postgresql.conf are: data_directory = '/var/ebs0/postgres/main' hba_file = '/etc/postgresql/8.3/main/pg_hba.conf' ident_file = '/etc/postgresql/8.3/main/pg_ident.conf' external_pid_file = '/var/run/postgresql/8.3-main.pid' listen_addresses = '*' port = 5432 max_connections = 100 unix_socket_directory = '/var/run/postgresql' ssl = true shared_buffers = 24MB

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  • Networking with Windows 7

    - by Alix Axel
    I got several computers connected to my home wireless network and I want to make use of some of the features of Windows 7 for home networks but I can't seem to get them working: How do I keep files and folders in sync between specific computers? I'm not talking about Live Sync. How can I stream to Windows Media Player from another computer? I would appreciate if someone could provide me some links / solutions that address my needs. Thanks! To anyone who thinks this question is a duplicate and wants to close it please bare in mind the following: I'm not looking for additional software, I know I can use Live Sync, Dropbox and so on but I'm asking this: how do I configure Windows 7 to sync files between my home network - no Internet required! This has something to do with shared folders and offline files in Windows 7, but I can't get it to work. PS: Please merge with this question: http://superuser.com/questions/139763/networking-with-windows-7

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  • how can i figure out iis7 memory leak from this dump result?

    - by Cenk Erdem
    my application sometimes starts to eat too much memory in a few seconds then crashes, i used debugdiag to take a dump when this happened, in the analyse i see lots of memory allocations all of them has the same information and each of them allocates 128mb. they look like this: Address 0x00000000`aff41798 Allocation Time 06:56:06 since tracking started Allocation Size 128.00 MBytes Function Source Destination LeakTrack+186cf clr!CExecutionEngine::ClrVirtualAlloc+3c clr!ClrVirtualAlloc+3c clr!WKS::virtual_alloc+42 clr!WKS::gc_heap::get_segment+a2 clr!WKS::gc_heap::get_large_segment+204 clr!WKS::gc_heap::loh_get_new_seg+78 clr! ?? ::FNODOBFM::`string'+a008a clr!WKS::gc_heap::try_allocate_more_space+31b clr!WKS::gc_heap::allocate_more_space+26 clr!WKS::gc_heap::allocate_large_object+6a clr!WKS::GCHeap::Alloc+b5 clr!FramedAllocateString+b06 mscorlib_ni+39f5fd mscorlib_ni+389f83 System_Xml_ni+451adc System_Data_SqlXml_ni+2275d4 System_Data_SqlXml_ni+233f32 System_Data_SqlXml_ni+8ec28 System_Data_SqlXml_ni+8eb65 System_Web_ni+2882b2 System_Web_ni+2794b6 System_Web_ni+2794b6 0x7FF002474BC what can be wrong about my code? any suggestions?

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  • Log analyzer that calculates "time on page"?

    - by netvope
    I need to get an idea of the average "time on page" or "page view duration" for each page on my websites without client-side scripting (such as using onunload event handler). Is any of the free log analyzers capable of doing this? I looked at Webalizer, AWStats and Analog, but they don't seem to have such a function. The closest thing is "visits duration" in AWStats, but I'd like to see "page view duration" instead. I know that visitor tracking is inaccurate without client-side scripting, but I can bear with it. Google Analytics seems to provide a "time on page" metric without hooking the onunload event (but correct me if I'm wrong), so I believe this is possible.

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  • SGE: invoking qmake raises "critical error: can't resolve group"

    - by Pierre
    I'm new to SGE an I'm trying to run qmake with the simple following Makefile with our very new cluster: merge.txt: job1.txt job2.txt job3.txt ... cat $^ > $@ job1.txt: sleep 1 echo "Hello From " $@ > $@ sleep 1 job2.txt: sleep 2 echo "Hello From " $@ > $@ sleep 2 job3.txt: (...) the following command raises an error: qmake -l arch=lx24-amd64 -cwd -v PATH -- -j 4 sleep 1 dynamic mode sleep 2 dynamic mode sleep 3 dynamic mode sleep 4 dynamic mode critical error: can't resolve group qmake: *** [job3.txt] Error 1 critical error: can't resolve group qmake: *** [job2.txt] Error 1 critical error: can't resolve group qmake: *** [job1.txt] Error 1 critical error: can't resolve group what's wrong ?

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  • Custom forms in Sharepoint with MS SQL Server as Backend. Is it possible?

    - by Kaan
    We're evaluating using SharePoint 2010 as our project management tool. Specifically, the system needs to satisfy the following: Discussion groups Project management (simple issue tracking, no complex workflows or vcs integrations) News feed for the project(s) File sharing based on authorization/user-roles Custom homepage Custom forms using MS SQL Server as a backend and contents of old forms searchable from the user interface. Now, I think [1-5] is possible using SharePoint (Comments are always welcome :)). I'm not sure about [6]. Is it possible? For instance, can an admin or a user of the SharePoint portal, create a custom form (without any programming) that uses MS SQL Server as a backend and publish it to the portal so that other users can also perform data entry? If it can be done (be it with or without some programming), can users perform text search on form data using the SharePoint interface?

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  • How do you organise the cables in your racks?

    - by Tim
    I'm migrating my current half-size rack to a full-size rack and want to take the opportunity to reorganize and sort our spaghetti-hell of ethernet cables. What system do you use for organising your cables? Do you use any tracking software? Do you physically label the cables? What are you identifying when you label each end? Mac address? Port number? Asset number? What do you use to label them? I was looking at a hand held labeler, but the wrap around laser printer sheets might work. The Brady ID PAL seems good, but it's pricey. Ideas?

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  • Resolving “ssl handshake failure” error in PostgresQL

    - by Mitch
    I would like to connect to my Postgres 8.3 database using SSL from my XP client using OpenSSL. This works fine without SSL. When I try it with SSL (no client certificate), I get the error: error:140790E5:SSL routines:SSL23_WRITE:ssl handshake failure I have followed the instructions in the Postgres manual for SSL including creating a self-signed certificate. In my pg_hba.conf there is a line: host dbname loginname 123.45.67.89/32 md5 The version of OpenSSL on the server is 0.9.8g and on the client is 0.9.8j. I'd appreciate any suggestions for tracking down the problem. Edit: The uncommented lines from postgresql.conf are: data_directory = '/var/ebs0/postgres/main' hba_file = '/etc/postgresql/8.3/main/pg_hba.conf' ident_file = '/etc/postgresql/8.3/main/pg_ident.conf' external_pid_file = '/var/run/postgresql/8.3-main.pid' listen_addresses = '*' port = 5432 max_connections = 100 unix_socket_directory = '/var/run/postgresql' ssl = true shared_buffers = 24MB

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