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  • Rendering ASP.NET MVC Views to String

    - by Rick Strahl
    It's not uncommon in my applications that I require longish text output that does not have to be rendered into the HTTP output stream. The most common scenario I have for 'template driven' non-Web text is for emails of all sorts. Logon confirmations and verifications, email confirmations for things like orders, status updates or scheduler notifications - all of which require merged text output both within and sometimes outside of Web applications. On other occasions I also need to capture the output from certain views for logging purposes. Rather than creating text output in code, it's much nicer to use the rendering mechanism that ASP.NET MVC already provides by way of it's ViewEngines - using Razor or WebForms views - to render output to a string. This is nice because it uses the same familiar rendering mechanism that I already use for my HTTP output and it also solves the problem of where to store the templates for rendering this content in nothing more than perhaps a separate view folder. The good news is that ASP.NET MVC's rendering engine is much more modular than the full ASP.NET runtime engine which was a real pain in the butt to coerce into rendering output to string. With MVC the rendering engine has been separated out from core ASP.NET runtime, so it's actually a lot easier to get View output into a string. Getting View Output from within an MVC Application If you need to generate string output from an MVC and pass some model data to it, the process to capture this output is fairly straight forward and involves only a handful of lines of code. The catch is that this particular approach requires that you have an active ControllerContext that can be passed to the view. This means that the following approach is limited to access from within Controller methods. Here's a class that wraps the process and provides both instance and static methods to handle the rendering:/// <summary> /// Class that renders MVC views to a string using the /// standard MVC View Engine to render the view. /// /// Note: This class can only be used within MVC /// applications that have an active ControllerContext. /// </summary> public class ViewRenderer { /// <summary> /// Required Controller Context /// </summary> protected ControllerContext Context { get; set; } public ViewRenderer(ControllerContext controllerContext) { Context = controllerContext; } /// <summary> /// Renders a full MVC view to a string. Will render with the full MVC /// View engine including running _ViewStart and merging into _Layout /// </summary> /// <param name="viewPath"> /// The path to the view to render. Either in same controller, shared by /// name or as fully qualified ~/ path including extension /// </param> /// <param name="model">The model to render the view with</param> /// <returns>String of the rendered view or null on error</returns> public string RenderView(string viewPath, object model) { return RenderViewToStringInternal(viewPath, model, false); } /// <summary> /// Renders a partial MVC view to string. Use this method to render /// a partial view that doesn't merge with _Layout and doesn't fire /// _ViewStart. /// </summary> /// <param name="viewPath"> /// The path to the view to render. Either in same controller, shared by /// name or as fully qualified ~/ path including extension /// </param> /// <param name="model">The model to pass to the viewRenderer</param> /// <returns>String of the rendered view or null on error</returns> public string RenderPartialView(string viewPath, object model) { return RenderViewToStringInternal(viewPath, model, true); } public static string RenderView(string viewPath, object model, ControllerContext controllerContext) { ViewRenderer renderer = new ViewRenderer(controllerContext); return renderer.RenderView(viewPath, model); } public static string RenderPartialView(string viewPath, object model, ControllerContext controllerContext) { ViewRenderer renderer = new ViewRenderer(controllerContext); return renderer.RenderPartialView(viewPath, model); } protected string RenderViewToStringInternal(string viewPath, object model, bool partial = false) { // first find the ViewEngine for this view ViewEngineResult viewEngineResult = null; if (partial) viewEngineResult = ViewEngines.Engines.FindPartialView(Context, viewPath); else viewEngineResult = ViewEngines.Engines.FindView(Context, viewPath, null); if (viewEngineResult == null) throw new FileNotFoundException(Properties.Resources.ViewCouldNotBeFound); // get the view and attach the model to view data var view = viewEngineResult.View; Context.Controller.ViewData.Model = model; string result = null; using (var sw = new StringWriter()) { var ctx = new ViewContext(Context, view, Context.Controller.ViewData, Context.Controller.TempData, sw); view.Render(ctx, sw); result = sw.ToString(); } return result; } } The key is the RenderViewToStringInternal method. The method first tries to find the view to render based on its path which can either be in the current controller's view path or the shared view path using its simple name (PasswordRecovery) or alternately by its full virtual path (~/Views/Templates/PasswordRecovery.cshtml). This code should work both for Razor and WebForms views although I've only tried it with Razor Views. Note that WebForms Views might actually be better for plain text as Razor adds all sorts of white space into its output when there are code blocks in the template. The Web Forms engine provides more accurate rendering for raw text scenarios. Once a view engine is found the view to render can be retrieved. Views in MVC render based on data that comes off the controller like the ViewData which contains the model along with the actual ViewData and ViewBag. From the View and some of the Context data a ViewContext is created which is then used to render the view with. The View picks up the Model and other data from the ViewContext internally and processes the View the same it would be processed if it were to send its output into the HTTP output stream. The difference is that we can override the ViewContext's output stream which we provide and capture into a StringWriter(). After rendering completes the result holds the output string. If an error occurs the error behavior is similar what you see with regular MVC errors - you get a full yellow screen of death including the view error information with the line of error highlighted. It's your responsibility to handle the error - or let it bubble up to your regular Controller Error filter if you have one. To use the simple class you only need a single line of code if you call the static methods. Here's an example of some Controller code that is used to send a user notification to a customer via email in one of my applications:[HttpPost] public ActionResult ContactSeller(ContactSellerViewModel model) { InitializeViewModel(model); var entryBus = new busEntry(); var entry = entryBus.LoadByDisplayId(model.EntryId); if ( string.IsNullOrEmpty(model.Email) ) entryBus.ValidationErrors.Add("Email address can't be empty.","Email"); if ( string.IsNullOrEmpty(model.Message)) entryBus.ValidationErrors.Add("Message can't be empty.","Message"); model.EntryId = entry.DisplayId; model.EntryTitle = entry.Title; if (entryBus.ValidationErrors.Count > 0) { ErrorDisplay.AddMessages(entryBus.ValidationErrors); ErrorDisplay.ShowError("Please correct the following:"); } else { string message = ViewRenderer.RenderView("~/views/template/ContactSellerEmail.cshtml",model, ControllerContext); string title = entry.Title + " (" + entry.DisplayId + ") - " + App.Configuration.ApplicationName; AppUtils.SendEmail(title, message, model.Email, entry.User.Email, false, false)) } return View(model); } Simple! The view in this case is just a plain MVC view and in this case it's a very simple plain text email message (edited for brevity here) that is created and sent off:@model ContactSellerViewModel @{ Layout = null; }re: @Model.EntryTitle @Model.ListingUrl @Model.Message ** SECURITY ADVISORY - AVOID SCAMS ** Avoid: wiring money, cross-border deals, work-at-home ** Beware: cashier checks, money orders, escrow, shipping ** More Info: @(App.Configuration.ApplicationBaseUrl)scams.html Obviously this is a very simple view (I edited out more from this page to keep it brief) -  but other template views are much more complex HTML documents or long messages that are occasionally updated and they are a perfect fit for Razor rendering. It even works with nested partial views and _layout pages. Partial Rendering Notice that I'm rendering a full View here. In the view I explicitly set the Layout=null to avoid pulling in _layout.cshtml for this view. This can also be controlled externally by calling the RenderPartial method instead: string message = ViewRenderer.RenderPartialView("~/views/template/ContactSellerEmail.cshtml",model, ControllerContext); with this line of code no layout page (or _viewstart) will be loaded, so the output generated is just what's in the view. I find myself using Partials most of the time when rendering templates, since the target of templates usually tend to be emails or other HTML fragment like output, so the RenderPartialView() method is definitely useful to me. Rendering without a ControllerContext The preceding class is great when you're need template rendering from within MVC controller actions or anywhere where you have access to the request Controller. But if you don't have a controller context handy - maybe inside a utility function that is static, a non-Web application, or an operation that runs asynchronously in ASP.NET - which makes using the above code impossible. I haven't found a way to manually create a Controller context to provide the ViewContext() what it needs from outside of the MVC infrastructure. However, there are ways to accomplish this,  but they are a bit more complex. It's possible to host the RazorEngine on your own, which side steps all of the MVC framework and HTTP and just deals with the raw rendering engine. I wrote about this process in Hosting the Razor Engine in Non-Web Applications a long while back. It's quite a process to create a custom Razor engine and runtime, but it allows for all sorts of flexibility. There's also a RazorEngine CodePlex project that does something similar. I've been meaning to check out the latter but haven't gotten around to it since I have my own code to do this. The trick to hosting the RazorEngine to have it behave properly inside of an ASP.NET application and properly cache content so templates aren't constantly rebuild and reparsed. Anyway, in the same app as above I have one scenario where no ControllerContext is available: I have a background scheduler running inside of the app that fires on timed intervals. This process could be external but because it's lightweight we decided to fire it right inside of the ASP.NET app on a separate thread. In my app the code that renders these templates does something like this:var model = new SearchNotificationViewModel() { Entries = entries, Notification = notification, User = user }; // TODO: Need logging for errors sending string razorError = null; var result = AppUtils.RenderRazorTemplate("~/views/template/SearchNotificationTemplate.cshtml", model, razorError); which references a couple of helper functions that set up my RazorFolderHostContainer class:public static string RenderRazorTemplate(string virtualPath, object model,string errorMessage = null) { var razor = AppUtils.CreateRazorHost(); var path = virtualPath.Replace("~/", "").Replace("~", "").Replace("/", "\\"); var merged = razor.RenderTemplateToString(path, model); if (merged == null) errorMessage = razor.ErrorMessage; return merged; } /// <summary> /// Creates a RazorStringHostContainer and starts it /// Call .Stop() when you're done with it. /// /// This is a static instance /// </summary> /// <param name="virtualPath"></param> /// <param name="binBasePath"></param> /// <param name="forceLoad"></param> /// <returns></returns> public static RazorFolderHostContainer CreateRazorHost(string binBasePath = null, bool forceLoad = false) { if (binBasePath == null) { if (HttpContext.Current != null) binBasePath = HttpContext.Current.Server.MapPath("~/"); else binBasePath = AppDomain.CurrentDomain.BaseDirectory; } if (_RazorHost == null || forceLoad) { if (!binBasePath.EndsWith("\\")) binBasePath += "\\"; //var razor = new RazorStringHostContainer(); var razor = new RazorFolderHostContainer(); razor.TemplatePath = binBasePath; binBasePath += "bin\\"; razor.BaseBinaryFolder = binBasePath; razor.UseAppDomain = false; razor.ReferencedAssemblies.Add(binBasePath + "ClassifiedsBusiness.dll"); razor.ReferencedAssemblies.Add(binBasePath + "ClassifiedsWeb.dll"); razor.ReferencedAssemblies.Add(binBasePath + "Westwind.Utilities.dll"); razor.ReferencedAssemblies.Add(binBasePath + "Westwind.Web.dll"); razor.ReferencedAssemblies.Add(binBasePath + "Westwind.Web.Mvc.dll"); razor.ReferencedAssemblies.Add("System.Web.dll"); razor.ReferencedNamespaces.Add("System.Web"); razor.ReferencedNamespaces.Add("ClassifiedsBusiness"); razor.ReferencedNamespaces.Add("ClassifiedsWeb"); razor.ReferencedNamespaces.Add("Westwind.Web"); razor.ReferencedNamespaces.Add("Westwind.Utilities"); _RazorHost = razor; _RazorHost.Start(); //_RazorHost.Engine.Configuration.CompileToMemory = false; } return _RazorHost; } The RazorFolderHostContainer essentially is a full runtime that mimics a folder structure like a typical Web app does including caching semantics and compiling code only if code changes on disk. It maps a folder hierarchy to views using the ~/ path syntax. The host is then configured to add assemblies and namespaces. Unfortunately the engine is not exactly like MVC's Razor - the expression expansion and code execution are the same, but some of the support methods like sections, helpers etc. are not all there so templates have to be a bit simpler. There are other folder hosts provided as well to directly execute templates from strings (using RazorStringHostContainer). The following is an example of an HTML email template @inherits RazorHosting.RazorTemplateFolderHost <ClassifiedsWeb.SearchNotificationViewModel> <html> <head> <title>Search Notifications</title> <style> body { margin: 5px;font-family: Verdana, Arial; font-size: 10pt;} h3 { color: SteelBlue; } .entry-item { border-bottom: 1px solid grey; padding: 8px; margin-bottom: 5px; } </style> </head> <body> Hello @Model.User.Name,<br /> <p>Below are your Search Results for the search phrase:</p> <h3>@Model.Notification.SearchPhrase</h3> <small>since @TimeUtils.ShortDateString(Model.Notification.LastSearch)</small> <hr /> You can see that the syntax is a little different. Instead of the familiar @model header the raw Razor  @inherits tag is used to specify the template base class (which you can extend). I took a quick look through the feature set of RazorEngine on CodePlex (now Github I guess) and the template implementation they use is closer to MVC's razor but there are other differences. In the end don't expect exact behavior like MVC templates if you use an external Razor rendering engine. This is not what I would consider an ideal solution, but it works well enough for this project. My biggest concern is the overhead of hosting a second razor engine in a Web app and the fact that here the differences in template rendering between 'real' MVC Razor views and another RazorEngine really are noticeable. You win some, you lose some It's extremely nice to see that if you have a ControllerContext handy (which probably addresses 99% of Web app scenarios) rendering a view to string using the native MVC Razor engine is pretty simple. Kudos on making that happen - as it solves a problem I see in just about every Web application I work on. But it is a bummer that a ControllerContext is required to make this simple code work. It'd be really sweet if there was a way to render views without being so closely coupled to the ASP.NET or MVC infrastructure that requires a ControllerContext. Alternately it'd be nice to have a way for an MVC based application to create a minimal ControllerContext from scratch - maybe somebody's been down that path. I tried for a few hours to come up with a way to make that work but gave up in the soup of nested contexts (MVC/Controller/View/Http). I suspect going down this path would be similar to hosting the ASP.NET runtime requiring a WorkerRequest. Brrr…. The sad part is that it seems to me that a View should really not require much 'context' of any kind to render output to string. Yes there are a few things that clearly are required like paths to the virtual and possibly the disk paths to the root of the app, but beyond that view rendering should not require much. But, no such luck. For now custom RazorHosting seems to be the only way to make Razor rendering go outside of the MVC context… Resources Full ViewRenderer.cs source code from Westwind.Web.Mvc library Hosting the Razor Engine for Non-Web Applications RazorEngine on GitHub© Rick Strahl, West Wind Technologies, 2005-2012Posted in ASP.NET   ASP.NET  MVC   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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  • Secure wipe of a hard drive using WinPE.

    - by Derek Meier
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} The wiping of a hard drive is typically seen as fairly trivial.  There are tons of applications out there that will do it for you.  Point àClickàGlobal-Thermo Nuclear War. However, these applications are typically expensive or unreliable.  Plus, if you have a laptop or lack a secondary computer to put the hard drive into – how on earth do you wipe it quickly and easily while still conforming to a 7 pass rule (this means that every possible bit on the hard drive is set to 0 and then to 1 seven times in a row)?  Yes, one pass should be enough – as turning every bit from a 1 to a zero will wipe the data from existence.  But, we’re dealing with tinfoil hat wearing types here people.  DOD standards dictate at least 3 passes, and typically 7 is the preferred amount.  I’m not going to argue about data recovery.  I have been told to use 7 passes, and so I will.  So say we all! Quite some time ago I used to make a BartPE XP-based boot cd for the original purpose of securely wiping data.  I loved BartPE and integrated so many plugins into my builds that I could do pretty much anything directly from CD.  Reset passwords, uninstall security updates, wipe drives, chkdsk, remove spyware, install Windows, etc.  However, with the newer multi-core systems and new chipsets coming out from vendors, I found that BartPE was rather difficult to keep up to date.  I have since switched to WinPE 3.0 (Windows Preinstallation Environment). http://technet.microsoft.com/en-us/library/cc748933(WS.10).aspx  It is fairly simple to create your own CD, and I have made a few helpful scripts to easily integrate drivers and rebuild the ISO file for you.  I’ll cover making your own boot CD utilizing WinPE 3.0 in a later post – I can talk about WinPE forever and need to collect my thoughts!!  My wife loves talking about WinPE almost as much as talking about Doctor Who.  Wait, did I say loves?  Hmmmm, I may have meant loathes. The topic at hand?  Right. Wiping a drive! I must have drunk too much coffee this morning.  I like to use a simple batch script that calls a combination of diskpart.exe from Microsoft® and Sdelete.exe created by our friend Mark Russinovich. http://technet.microsoft.com/en-us/sysinternals/bb897443.aspx All of the following files are located within the same directory on my WinPE boot CD. Here are the contents of wipe_me.bat, script.txt and sdelete.reg. Wipe_me.bat:   @echo off echo. echo     I will completely wipe the local hard drives using echo     7 individual wipes. The data will NOT echo     be recoverable.  I will begin after you pause echo. echo Preparing to partition and format disk. Diskpart.exe /s "script.txt" REM I was annoyed by not having a completely automated script – and Sdelete wants you to accept the license agreement. So, I added a registry file to skip doing that. regedit /S sdelete.reg rem sdelete options selected are: -p (passes) -c (zero free space) -s (recurse through subdirectories, if any) -z (clean free space) [drive letter] sdelete.exe -p 7 -c -s -z c: echo. echo Pass seven complete. echo. echo Wiping complete. Pause exit script.txt: list disk select disk 0 clean create partition primary select partition 1 active format FS=NTFS LABEL="New Volume" QUICK assign letter=c exit *Notes: This script assumes one local hard drive – change the script as you see fit for your environment.  The clean command will overwrite the master boot record and any hidden sector information – so be careful!   sdelete.reg: Windows Registry Editor Version 5.00 [HKEY_CURRENT_USER\Software\Sysinternals\SDelete] "EulaAccepted"=dword:00000001   With a combination of WinPE, sdelete.exe and your friendly neighborhood text editor you can begin wiping drives as quickly and easily as possible!  I hope this helps, I get asked this a lot in my line of work. Best of luck, Derek

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  • SQL SERVER – Single Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28

    - by pinaldave
    In this post, let’s delve a bit more in depth regarding wait stats. The very first question: when do the wait stats occur? Here is the simple answer. When SQL Server is executing any task, and if for any reason it has to wait for resources to execute the task, this wait is recorded by SQL Server with the reason for the delay. Later on we can analyze these wait stats to understand the reason the task was delayed and maybe we can eliminate the wait for SQL Server. It is not always possible to remove the wait type 100%, but there are few suggestions that can help. Before we continue learning about wait types and wait stats, we need to understand three important milestones of the query life-cycle. Running - a query which is being executed on a CPU is called a running query. This query is responsible for CPU time. Runnable – a query which is ready to execute and waiting for its turn to run is called a runnable query. This query is responsible for Single Wait time. (In other words, the query is ready to run but CPU is servicing another query). Suspended – a query which is waiting due to any reason (to know the reason, we are learning wait stats) to be converted to runnable is suspended query. This query is responsible for wait time. (In other words, this is the time we are trying to reduce). In simple words, query execution time is a summation of the query Executing CPU Time (Running) + Query Wait Time (Suspended) + Query Single Wait Time (Runnable). Again, it may be possible a query goes to all these stats multiple times. Let us try to understand the whole thing with a simple analogy of a taxi and a passenger. Two friends, Tom and Danny, go to the mall together. When they leave the mall, they decide to take a taxi. Tom and Danny both stand in the line waiting for their turn to get into the taxi. This is the Signal Wait Time as they are ready to get into the taxi but the taxis are currently serving other customer and they have to wait for their turn. In other word they are in a runnable state. Now when it is their turn to get into the taxi, the taxi driver informs them he does not take credit cards and only cash is accepted. Neither Tom nor Danny have enough cash, they both cannot get into the vehicle. Tom waits outside in the queue and Danny goes to ATM to fetch the cash. During this time the taxi cannot wait, they have to let other passengers get into the taxi. As Tom and Danny both are outside in the queue, this is the Query Wait Time and they are in the suspended state. They cannot do anything till they get the cash. Once Danny gets the cash, they are both standing in the line again, creating one more Single Wait Time. This time when their turn comes they can pay the taxi driver in cash and reach their destination. The time taken for the taxi to get from the mall to the destination is running time (CPU time) and the taxi is running. I hope this analogy is bit clear with the wait stats. You can check the single wait stats using following query of Glenn Berry. -- Signal Waits for instance SELECT CAST(100.0 * SUM(signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%signal (cpu) waits], CAST(100.0 * SUM(wait_time_ms - signal_wait_time_ms) / SUM (wait_time_ms) AS NUMERIC(20,2)) AS [%resource waits] FROM sys.dm_os_wait_stats OPTION (RECOMPILE); Higher the single wait stats are not good for the system. Very high value indicates CPU pressure. In my experience, when systems are running smooth and without any glitch the single wait stat is lower than 20%. Again, this number can be debated (and it is from my experience and is not documented anywhere). In other words, lower is better and higher is not good for the system. In future articles we will discuss in detail the various wait types and wait stats and their resolution. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • AMD-V is not enable in virtualbox in amd APU

    - by shantanu
    I am running Dual core AMD E450 APU. When i tried to run a 64-bit OS that requires hardware virtualization using virtual-box it showed me an error "AMD-V is not enable". My AMD processor should provide AMD-V support. And i can find no option for AMD-V in BIOS. How can i solve this problem? How could i enable AMD-V for my APU? Thanks in advance lscpu :- Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian CPU(s): 2 On-line CPU(s) list: 0,1 Thread(s) per core: 1 Core(s) per socket: 2 Socket(s): 1 NUMA node(s): 1 Vendor ID: AuthenticAMD CPU family: 20 Model: 2 Stepping: 0 CPU MHz: 1650.000 BogoMIPS: 3291.72 Virtualization: AMD-V L1d cache: 32K L1i cache: 32K L2 cache: 512K NUMA node0 CPU(s): 0,1 EDITED:- Error of virtualBOX:- Failed to open a session for the virtual machine XXX. AMD-V is disabled in the BIOS. (VERR_SVM_DISABLED). Result Code: NS_ERROR_FAILURE (0x80004005) Component: Console Interface: IConsole {1968b7d3-e3bf-4ceb-99e0-cb7c913317bb}

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  • can anyone reccommend a Google SERP tracker?

    - by Haroldo
    I want to track my website's position in Google's search results for around 50 keywords/phrases and am looking to a nice webapp/windows app to automate this process? Ideally i want to see pretty javscript or flash line graphs for my keyword/position. I'm currently free-trialing: Raven Tools and Sheer SEO but am not particularly impressed with either... I guess my budget is up to £25-30/$30-40 per month for a decent bit of software ps. i've tried asking this on SuperUser but it seems a bit webdeveloper-y...

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  • Week in Geek: Facebook Valentine’s Day Scams Edition

    - by Asian Angel
    This week we learned how to get started with the Linux command-line text editor Nano, “speed up Start Menu searching, halt auto-rotating Android screens, & set up Dropbox-powered torrenting”, change the default application for Android tasks, find great gift recommendations for Valentine’s Day using the How-To Geek Valentine’s Day gift guide, had fun decorating our desktops with TRON and TRON Legacy theme items, and more Latest Features How-To Geek ETC Internet Explorer 9 RC Now Available: Here’s the Most Interesting New Stuff Here’s a Super Simple Trick to Defeating Fake Anti-Virus Malware How to Change the Default Application for Android Tasks Stop Believing TV’s Lies: The Real Truth About "Enhancing" Images The How-To Geek Valentine’s Day Gift Guide Inspire Geek Love with These Hilarious Geek Valentines Four Awesome TRON Legacy Themes for Chrome and Iron Anger is Illogical – Old School Style Instructional Video [Star Trek Mashup] Get the Old Microsoft Paint UI Back in Windows 7 Relax and Sleep Is a Soothing Sleep Timer Google Rolls Out Two-Factor Authentication Peaceful Early Morning by the Riverside Wallpaper

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  • Best way of learning Python + GUI when coming from .NET

    - by Oscar Mederos
    I've been developing applications in C# / VB.NET for about 3-4 years (.NET Framework v2.0, 3.5, 4). I have also developed some command-line applications or scripts in C, and Python under Linux. Sometimes I need to develop my applications in another languages, like Python, but the problem thing is that lots of those applications require a GUI. Maybe not a too complex one, but it does require some windows with buttons, text boxes, list boxes,... What books/tips/tutorials do you suggest me to start working with that language and be able to deploy my deliverables not only in .NET? Note: Learning python is not the big deal here, because I already know the basic of it. I just want to focus on the GUI. Maybe this question should be on UI instead of here? If so, please, migrate it :)

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  • SQL SERVER – T-SQL Script to Take Database Offline – Take Database Online

    - by pinaldave
    Blog reader Joyesh Mitra recently left a comment to one of my very old posts about SQL SERVER – 2005 Take Off Line or Detach Database, which I have written focusing on taking the database offline. However, I did not include how to bring the offline database to online in that post. The reason I did not write it was that I was thinking it was a very simple script that almost everyone knows. However, it seems to me that there is something I found advanced in this procedure that is not simple for other people. We all have different expertise and we all try to learn new things, so I do not see any reason as to not write about the script to take the database online. -- Create Test DB CREATE DATABASE [myDB] GO -- Take the Database Offline ALTER DATABASE [myDB] SET OFFLINE WITH ROLLBACK IMMEDIATE GO -- Take the Database Online ALTER DATABASE [myDB] SET ONLINE GO -- Clean up DROP DATABASE [myDB] GO Joyesh let me know if this answers your question. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, Readers Question, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Improving Partitioned Table Join Performance

    - by Paul White
    The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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  • SQL SERVER – Puzzle – Challenge – Error While Converting Money to Decimal

    - by pinaldave
    Earlier I wrote SQL SERVER – Challenge – Puzzle – Usage of FAST Hint and I did receive some good comments. Here is another question to tease your mind. Run following script and you will see that it will thrown an error. DECLARE @mymoney MONEY; SET @mymoney = 12345.67; SELECT CAST(@mymoney AS DECIMAL(5,2)) MoneyInt; GO The datatype of money is also visually look similar to the decimal, why it would throw following error: Msg 8115, Level 16, State 8, Line 3 Arithmetic overflow error converting money to data type numeric. Please leave a comment with explanation and I will post a your answer on this blog with due credit. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Error Messages, SQL Puzzle, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • SQL SERVER – Difference Between GETDATE and SYSDATETIME

    - by pinaldave
    Sometime something so simple skips our mind. I never knew the difference between GETDATE and SYSDATETIME. I just ran simple query as following and realized the difference. SELECT GETDATE() fn_GetDate, SYSDATETIME() fn_SysDateTime In case of GETDATE the precision is till miliseconds and in case of SYSDATETIME the precision is till nanoseconds. Now the questions is to you – did you know this? Be honest and please share your views. I already accepted that I did not know this in very first line. Reference: Pinal Dave (http://www.SQLAuthority.com), Filed under: Pinal Dave, SQL, SQL Authority, SQL DateTime, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • The best terminal emulator for a heavy terminal user?

    - by Noah Goodrich
    I spend a lot of time at the command-line during the workday and at home too since I run Ubuntu exclusively. I've been using the default gnome terminal but I've reached a point where I'd really like to get my terminal tricked out so that my common tasks are as easy as possible. Specifically, I find that I spend of lot of time browsing code in the terminal and working in config files. On my wish list would be: Ability to have multiple screens, tabs, windows (I don't have a preference at this point) that I can easily switch between. Color coding for everything Easy to modify the aesthetics of the terminal (is it vain to want my terminal to look nice?) such as transparency, borders, etc.

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  • Oracle President Mark Hurd Highlights How Data-driven HR Decisions Help Maximize Business Performance

    - by Scott Ewart
    HR Intelligence Can Help Companies Win the Race for Talent Today during a keynote at Taleo World 2012, Oracle President Mark Hurd outlined the ways that executives can use HR intelligence to help them make better business decisions, shape the future of their organizations and improve the bottom line. He highlighted that talent management is one of the top three focus areas for CEOs, and explained how HR intelligence can help drive decisions to meet business objectives. Hurd urged HR leaders to use data to make fact-based decisions about hiring, talent management and succession to drive strategic growth. To win the race for talent, Hurd explained that organizations need powerful technology that provides fact-based valuable insight that is needed to proactively manage talent, drive strategic initiatives that promote innovation, and enhance business performance. To view the full story and press release, click here.

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  • SQL SERVER – Disabled Index and Update Statistics

    - by pinaldave
    When we try to update the statistics, it throws an error as if the clustered index is disabled. Now let us enable the clustered index only and attempt to update the statistics of the table right after that. Have you ever come across the situation where a conversation never gets over and it continues even though original point of discussion has passed. I am facing the same situation in the case of Disabled Index. Here is the link to original conversations. SQL SERVER – Disable Clustered Index and Data Insert – Reader had a issue here with Disabled Index SQL SERVER – Understanding ALTER INDEX ALL REBUILD with Disabled Clustered Index – Reader asked the effect of Rebuilding Indexes The same reader asked me today – “I understood what the disabled indexes do; what is their effect on statistics. Is it true that even though indexes are disabled, they continue updating the statistics?“ The answer is very interesting: If you have disabled clustered index, you will be not able to update the statistics at all for any index. If you have enabled clustered index and disabled non clustered index when you update the statistics of the table, it automatically updates the statistics of the ALL (disabled and enabled – both) the indexes on the table. If you are not satisfied with the answer, let us go over a simple example. I have written necessary comments in the code itself to have a clear idea. USE tempdb GO -- Drop Table if Exists IF EXISTS (SELECT * FROM sys.objects WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[TableName]') AND type IN (N'U')) DROP TABLE [dbo].[TableName] GO -- Create Table CREATE TABLE [dbo].[TableName]( [ID] [int] NOT NULL, [FirstCol] [varchar](50) NULL ) GO -- Insert Some data INSERT INTO TableName SELECT 1, 'First' UNION ALL SELECT 2, 'Second' UNION ALL SELECT 3, 'Third' UNION ALL SELECT 4, 'Fourth' UNION ALL SELECT 5, 'Five' GO -- Create Clustered Index ALTER TABLE [TableName] ADD CONSTRAINT [PK_TableName] PRIMARY KEY CLUSTERED ([ID] ASC) GO -- Create Nonclustered Index CREATE UNIQUE NONCLUSTERED INDEX [IX_NonClustered_TableName] ON [dbo].[TableName] ([FirstCol] ASC) GO -- Check that all the indexes are enabled SELECT OBJECT_NAME(OBJECT_ID), Name, type_desc, is_disabled FROM sys.indexes WHERE OBJECT_NAME(OBJECT_ID) = 'TableName' GO Now let us update the statistics of the table and check the statistics update date. -- Update the stats of table UPDATE STATISTICS TableName WITH FULLSCAN GO -- Check Statistics Last Updated Datetime SELECT name AS index_name, STATS_DATE(OBJECT_ID, index_id) AS StatsUpdated FROM sys.indexes WHERE OBJECT_ID = OBJECT_ID('TableName') GO Now let us disable the indexes and check if they are disabled using sys.indexes. -- Disable Indexes -- Disable Nonclustered Index ALTER INDEX [IX_NonClustered_TableName] ON [dbo].[TableName] DISABLE GO -- Disable Clustered Index ALTER INDEX [PK_TableName] ON [dbo].[TableName] DISABLE GO -- Check that all the indexes are disabled SELECT OBJECT_NAME(OBJECT_ID), Name, type_desc, is_disabled FROM sys.indexes WHERE OBJECT_NAME(OBJECT_ID) = 'TableName' GO Let us try to update the statistics of the table. -- Update the stats of table UPDATE STATISTICS TableName WITH FULLSCAN GO /* -- Above operation should thrown following error Msg 1974, Level 16, State 1, Line 1 Cannot perform the specified operation on table 'TableName' because its clustered index 'PK_TableName' is disabled. */ When we try to update the statistics it throws an error as it clustered index is disabled. Now let us enable the clustered index only and attempt to update the statistics of the table right after that. -- Now let us rebuild clustered index only ALTER INDEX [PK_TableName] ON [dbo].[TableName] REBUILD GO -- Check that all the indexes status SELECT OBJECT_NAME(OBJECT_ID), Name, type_desc, is_disabled FROM sys.indexes WHERE OBJECT_NAME(OBJECT_ID) = 'TableName' GO -- Check Statistics Last Updated Datetime SELECT name AS index_name, STATS_DATE(OBJECT_ID, index_id) AS StatsUpdated FROM sys.indexes WHERE OBJECT_ID = OBJECT_ID('TableName') GO -- Update the stats of table UPDATE STATISTICS TableName WITH FULLSCAN GO -- Check Statistics Last Updated Datetime SELECT name AS index_name, STATS_DATE(OBJECT_ID, index_id) AS StatsUpdated FROM sys.indexes WHERE OBJECT_ID = OBJECT_ID('TableName') GO We can clearly see that even though the nonclustered index is disabled it is also updated. If you do not need a nonclustered index, I suggest you to drop it as keeping them disabled is an overhead on your system. This is because every time the statistics are updated for system all the statistics for disabled indexesare also updated. -- Clean up DROP TABLE [TableName] GO The complete script is given below for easy reference. USE tempdb GO -- Drop Table if Exists IF EXISTS (SELECT * FROM sys.objects WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[TableName]') AND type IN (N'U')) DROP TABLE [dbo].[TableName] GO -- Create Table CREATE TABLE [dbo].[TableName]( [ID] [int] NOT NULL, [FirstCol] [varchar](50) NULL ) GO -- Insert Some data INSERT INTO TableName SELECT 1, 'First' UNION ALL SELECT 2, 'Second' UNION ALL SELECT 3, 'Third' UNION ALL SELECT 4, 'Fourth' UNION ALL SELECT 5, 'Five' GO -- Create Clustered Index ALTER TABLE [TableName] ADD CONSTRAINT [PK_TableName] PRIMARY KEY CLUSTERED ([ID] ASC) GO -- Create Nonclustered Index CREATE UNIQUE NONCLUSTERED INDEX [IX_NonClustered_TableName] ON [dbo].[TableName] ([FirstCol] ASC) GO -- Check that all the indexes are enabled SELECT OBJECT_NAME(OBJECT_ID), Name, type_desc, is_disabled FROM sys.indexes WHERE OBJECT_NAME(OBJECT_ID) = 'TableName' GO -- Update the stats of table UPDATE STATISTICS TableName WITH FULLSCAN GO -- Check Statistics Last Updated Datetime SELECT name AS index_name, STATS_DATE(OBJECT_ID, index_id) AS StatsUpdated FROM sys.indexes WHERE OBJECT_ID = OBJECT_ID('TableName') GO -- Disable Indexes -- Disable Nonclustered Index ALTER INDEX [IX_NonClustered_TableName] ON [dbo].[TableName] DISABLE GO -- Disable Clustered Index ALTER INDEX [PK_TableName] ON [dbo].[TableName] DISABLE GO -- Check that all the indexes are disabled SELECT OBJECT_NAME(OBJECT_ID), Name, type_desc, is_disabled FROM sys.indexes WHERE OBJECT_NAME(OBJECT_ID) = 'TableName' GO -- Update the stats of table UPDATE STATISTICS TableName WITH FULLSCAN GO /* -- Above operation should thrown following error Msg 1974, Level 16, State 1, Line 1 Cannot perform the specified operation on table 'TableName' because its clustered index 'PK_TableName' is disabled. */ -- Now let us rebuild clustered index only ALTER INDEX [PK_TableName] ON [dbo].[TableName] REBUILD GO -- Check that all the indexes status SELECT OBJECT_NAME(OBJECT_ID), Name, type_desc, is_disabled FROM sys.indexes WHERE OBJECT_NAME(OBJECT_ID) = 'TableName' GO -- Check Statistics Last Updated Datetime SELECT name AS index_name, STATS_DATE(OBJECT_ID, index_id) AS StatsUpdated FROM sys.indexes WHERE OBJECT_ID = OBJECT_ID('TableName') GO -- Update the stats of table UPDATE STATISTICS TableName WITH FULLSCAN GO -- Check Statistics Last Updated Datetime SELECT name AS index_name, STATS_DATE(OBJECT_ID, index_id) AS StatsUpdated FROM sys.indexes WHERE OBJECT_ID = OBJECT_ID('TableName') GO -- Clean up DROP TABLE [TableName] GO Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Statistics

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  • Oracle OpenWorld Preview: Real World Perspectives from Oracle WebCenter Customers

    - by Christie Flanagan
    Normal 0 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;} If you frequent the Oracle WebCenter blog you’ve probably read a lot about the customer experience revolution over the last few months.  An important aspect of the customer experience revolution is the increasing role that peers play in influencing how others perceive a product, brand or solution, simply by sharing their own, real-world experiences.  Think about it, who do you trust more -- marketers and sales people pitching polished messages or peers with similar roles and similar challenges to the ones you face in your business every day? With this spirit in mind, this polished marketer personally invites you to hear directly from Oracle WebCenter customers about their real-life experiences during our customer panel sessions at Oracle OpenWorld next week.  If you’re currently using WebCenter, thinking about it, or just want to find out more about best practices in social business, next-generation portals, enterprise content management or web experience management, be sure to attend these sessions: CON8899 - Becoming a Social Business: Stories from the Front Lines of Change Wednesday, Oct 3, 11:45 AM - 12:45 PM - Moscone West - 3000Priscilla Hancock - Vice President/CIO, University of Louisville Kellie Christensen - Director of Information Technology, Banner EngineeringWhat does it really mean to be a social business? How can you change your organization to embrace social approaches? What pitfalls do you need to avoid? In this lively panel discussion, customer and industry thought leaders in social business explore these topics and more as they share their stories of the good, the bad, and the ugly that can happen when embracing social methods and technologies to improve business success. Using moderated questions and open Q&A from the audience, the panel discusses vital topics such as the critical factors for success, the major issues to avoid, how to gain senior executive support for social efforts, how to handle undesired behavior, and how to measure business impact. This session will take a thought-provoking look at becoming a social business from the inside. CON8900 - Building Next-Generation Portals: An Interactive Customer Panel DiscussionWednesday, Oct 3, 5:00 PM - 6:00 PM - Moscone West - 3000Roberts Wayne - Director, IT, Canadian Partnership Against CancerMike Beattie - VP Application Development, Aramark Uniform ServicesJohn Chen - Utilities Services Manager 6, Los Angeles Department of Water & PowerJörg Modlmayr - Head of Product Managment, Siemens AGSocial and collaborative technologies have changed how people interact, learn, and collaborate, and providing a modern, social Web presence is imperative to remain competitive in today’s market. Can your business benefit from a more collaborative and interactive portal environment for employees, customers, and partners? Attend this session to hear from Oracle WebCenter Portal customers as they share their strategies and best practices for providing users with a modern experience that adapts to their needs and includes personalized access to content in context. The panel also addresses how customers have benefited from creating next-generation portals by migrating from older portal technologies to Oracle WebCenter Portal. CON8898 - Land Mines, Potholes, and Dirt Roads: Navigating the Way to ECM NirvanaThursday, Oct 4, 12:45 PM - 1:45 PM - Moscone West - 3001Stephen Madsen - Senior Management Consultant, Alberta Agriculture and Rural DevelopmentHimanshu Parikh - Sr. Director, Enterprise Architecture & Middleware, Ross Stores, Inc.Ten years ago, people were predicting that by this time in history, we’d be some kind of utopian paperless society. As we all know, we're not there yet, but are we getting closer? What is keeping companies from driving down the road to enterprise content management bliss? Most people understand that using ECM as a central platform enables organizations to expedite document-centric processes, but most business processes in organizations are still heavily paper-based. Many of these processes could be automated and improved with an ECM platform infrastructure. In this panel discussion, you’ll hear from Oracle WebCenter customers that have already solved some of these challenges as they share their strategies for success and roads to avoid along your journey. CON8897 - Using Web Experience Management to Drive Online Marketing SuccessThursday, Oct 4, 2:15 PM - 3:15 PM - Moscone West - 3001Blane Nelson - Chief Architect, Ancestry.comMike Remedios - CIO, ArbonneCaitlin Scanlon - Product Manager, Monster WorldwideEvery year, the online channel becomes more imperative for driving organizational top-line revenue, but for many companies, mastering how to best market their products and services in a fast-evolving online world with high customer expectations for personalized experiences can be a complex proposition. Come to this panel discussion, and hear directly from customers on how they are succeeding today by using Web experience management to drive marketing success, using capabilities such as targeting and optimization, user-generated content, mobile site publishing, and site visitor personalization to deliver engaging online experiences. Your Handy Guide to WebCenter at Oracle OpenWorld Want a quick and easy guide to all the keynotes, demos, hands-on labs and WebCenter sessions you definitely don't want to miss at Oracle OpenWorld? Download this handy guide, Focus on WebCenter. More helpful links: * Oracle OpenWorld* Oracle Customer Experience Summit @ OpenWorld* Oracle OpenWorld on Facebook * Oracle OpenWorld on Twitter* Oracle OpenWorld on LinkedIn* Oracle OpenWorld Blog

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  • Chester Devs Presentation and source code &ndash; &lsquo;Event Store - an introduction to a DSD for event sourcing and notifications&rsquo;

    - by Liam Westley
    Originally posted on: http://geekswithblogs.net/twickers/archive/2013/11/11/chester-devs-presentation-and-source-code-ndash-lsquoevent-store.aspxThank you everyone at Chester Devs Thanks to Fran Hoey and all the people from Chester Devs. It was a hard drive up and back but the enthusiasm of the audience, with some great questions does make it worthwhile. Presentation and source code My presentation, source code, Event Store runners and text files containing the various command line parameters used for curl is now available on GitHub; https://github.com/westleyl/ChesterDevs-EventStore. Don’t worry if you don’t have a GitHub account, you don’t need one, you can just click on the Download Zip button on the right hand menu to download all the files as a single ZIP file.  If all you want is the PowerPoint presentation, go to https://github.com/westleyl/ChesterDevs-EventStore/blob/master/Powerpoint/Huddle-EventStore.pptx, and click on the View Raw button. Downloading and installing Event Store and Tools Download Event Store http://download.geteventstore.com – I unzipped these files into C:\EventStore\v2.0.1 Download Curl from http://curl.haxx.se/download.html – I downloaded Win64 Generic (with SSL) and unzipped these files into C:\curl version 7.31.0 Running the tools I used in my presentation Demonstration 1 (running Event Store) You can use one of my Event Store runner command files to run the single node version of Event Store, using default ports of 2213 for HTTP and 1113  for TCP, and with a wildcard HTTP pattern.  Both take a single command line parameter to specify the location of the data and log files.  The runners assume the single node executable is located in C:\EventStore\v2.0.1, and will placed data files and logs beneath C:\EventStore\Data, i.e. RunEventStore.cmd TestData1 This will create data files in C:\EventStore\Data\TestData1\Data and log files in C:\EventStore\Data\TestData1\logs. If, when running Event Store you may see the following message, [03288,15,06:23:00.622] Failed to start http server Access is denied You will either need to run Event Store in an administrator console window, or you can use the netsh command to create a firewall permission to allow HTTP listening (this will need to be run, once, in an administrator console window), netsh http add urlacl url=http://*:2213/ user=liam You can always delete this later by running the delete; netsh http delete urlacl url=http://*:2213/ If you want to confirm that everything is running OK, open the management console in a browser by navigating to http://127.0.0.1:2213. If at any point you are asked for a user name and password use the default of ‘admin’/‘changeit’. Demonstration 2 (reading and adding data, curl) In my second demonstration I used curl directly from the console to read streams, write events and then read back those events. On GitHub I have included is a set of curl commands, CurlCommandLine.txt, and a sample data file, SampleData.json, to load an event into a DDDNorth3 stream. As there is not much data in the Event Store at this point I used the $stats-127.0.0.1:2113 which is a stream containing performance statistics for Event Store and is updated every 30 seconds (default). Demonstration 3 (projections) On GitHub I have included a sample projection, Projection-ByRoom.txt, which will create streams based on the room on which a session was held on the DDDNorth3 agenda. Browse to the management console, http://127.0.0.1:2213.  Click on Projections, New Projection, give it a name, Sessions-ByRoom, and copy in the JavaScript in the Projection-ByRoom.txt file.  Select Continuous, tick Emit Enabled and then click on Post. It should run immediately. You may by challenged for the administration login for the management console, if so use the default user name and password; 'admin'/'changeit'. Demonstration 4 (C# client) The final demonstration was the Visual Studio 2012 project using the Event Store client – referenced directly as C:\EventStore\v2.0.1\EventStore.ClientAPI.dll, although you can switch this to the latest Event Store client NuGet package. The source code provides a console app for viewing projections with the projection manager (HTTP connection), as well as containing a full set of data for the entire DDDNorth3 agenda.  It also deals with the strategy for reading newest events backwards to older events and ignoring older events that have been superseded. Resources Event Store home page: http://www.geteventstore.com/ Event Store source code on GitHub: https://github.com/eventstore/eventstore Event Store documentation on GitHub: https://github.com/eventstore/eventstore/wiki (includes index to @RobAshton’s blog series on Event Store at https://github.com/eventstore/eventstore/wiki#rob-ashton---projections-series) Event Store forum in Google Groups: https://groups.google.com/forum/?fromgroups#!forum/event-store TopShelf Windows service wrapper is available on github: https://gist.github.com/trbngr/5083266

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  • Ask How-To Geek: Tiling Windows, iOS Remote Desktop, and Getting a Handle on Windows 7 Libraries

    - by Jason Fitzpatrick
    This week we’re taking a look at how to tile application windows in Windows 7, remote controlling your desktop from iOS devices, and understanding exactly what Windows 7 libraries are. Once a week we dip into our reader mailbag and help readers solve their problems, sharing the useful solutions with you in the process. Read on to see the fixes for this week’s reader dilemmas. Latest Features How-To Geek ETC How To Colorize Black and White Vintage Photographs in Photoshop How To Get SSH Command-Line Access to Windows 7 Using Cygwin The How-To Geek Video Guide to Using Windows 7 Speech Recognition How To Create Your Own Custom ASCII Art from Any Image How To Process Camera Raw Without Paying for Adobe Photoshop How Do You Block Annoying Text Message (SMS) Spam? Battlestar Galactica – Caprica Map of the 12 Colonies (Wallpaper Also Available) View Enlarged Versions of Thumbnail Images with Thumbnail Zoom for Firefox IntoNow Identifies Any TV Show by Sound Walk Score Calculates a Neighborhood’s Pedestrian Friendliness Factor Fantasy World at Twilight Wallpaper Hack a Wireless Doorbell into a Snail Mail Indicator

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  • AddThis - contains too many device filters error

    - by Yousef_Jadallah
    When using AddThis service with asp.net, some exceptions will throw like these: The string 'fb:like:layout' contains too many device filters. There can be only one. The string 'g:plusone:size' contains too many device filters. There can be only one. You can solve this by using "In line server code".   Step 1: Implement the following code in your code file:   Protected Function GetFacebookAttribute() As String Return String .Format( "{0}=" "{1}" ""...(read more)

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  • Real-Time Co-Authoring Feature now Available in Microsoft Office Web Apps

    - by Akemi Iwaya
    The lack of a collaboration feature in Microsoft’s Office Web Apps was a big disappointment for many people, but starting this week, that is no longer a problem. Microsoft has added an awesome new collaboration feature to their Office Web Apps that will help you and your co-workers be more productive than ever before no matter where you are working from now. Screenshot courtesy of the Office 365 Technology Blog. In addition to the new collaboration feature, new updates such as improved formatting controls, the ability to drag and drop cells, new picture cropping functionality, and more has been added to the Office Web Apps line-up. You can learn more about the new updates for each of the Office Web Apps and the new collaboration feature via the blog post linked below. Collaboration just got easier: Real-time co-authoring now available in Office Web Apps [via Ars Technica]     

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  • ADNOC talks about 50x increase in performance

    - by KLaker
    If you are still wondering about how Exadata can revolutionise your business then I would recommend watching this great video which was recorded at this year's OpenWorld. First a little background...The Abu Dhabi National Oil Company for Distribution (ADNOC) is an integrated energy company that was founded in 1973. ADNOC Distribution markets and distributes petroleum products and services within the United Arab Emirates and internationally. As one of the largest and most innovative government-owned petroleum companies in the Arab Gulf, ADNOC Distribution is renowned and respected for the exceptional quality and reliability of its products and services. Its five corporate divisions include more than 200 filling stations (a number that is growing at 8% annually), more than 150 convenience stores, 10 vehicle inspection stations, as well as wholesale and retail sales of bulk fuel, gas, oil, diesel, and lubricants. ADNOC selected Oracle Exadata Database Machine after extensive research because it provided them with a single platform that can run mixed workloads in a single unified machine: "We chose Oracle Exadata Database Machine because it.offered a fully integrated and highly engineered system that was ready to deploy. With our infrastructure running all the same technology, we can operate any type of Oracle Database without restrictions and be prepared for business growth," said Ali Abdul Aziz Al-Ali, IT division manager, ADNOC Distribution. ".....we could consolidate our transaction processing and business intelligence onto one platform. Competing solutions are just not capable of doing that." - Awad Ahmed Ali El-Sidiq, Senior Database Administrator, ADNOC Distribution In this new video Awad Ahmen Ali El Sidddig, Senior DBA at ADNOC, talks about the impact that Exadata has had on his team and the whole business. ADNOC is using our engineered systems to drive and manage all their workloads: from transaction systems to payments system to data warehouse to BI environment. A true Disk-to-Dashboard revolution using Engineered Systems. This engineered approach is delivering 50x improvement in performance with one queries running 100x faster! The IT has even revolutionised some of their data warehouse related processes with the help of Exadata and now jobs that were taking over 4 hours now run in a few minutes.  To watch the video click on the image below which will take you to our Oracle YouTube page: (if the above link does not work, click here: http://www.youtube.com/watch?v=zcRpxc6u5Ic) Now that queries are running 100x faster and jobs are completing in minutes not hours, what is next for the IT team at ADNOC? Like many of our customers ADNOC is now looking to take advantage of big data to help them better align their business operations with customer behaviour and customer insights. To help deliver this next level of insight the IT team is looking at the new features in Oracle Database 12c such as the new in-memory feature to deliver even more performance gains.  The great news is that Awad Ahmen Ali El Sidddig was awarded DBA of the Year - EMEA within our Data Warehouse Global Leaders programme and you can see the badge for this award pop-up at the start of video. Well done to everyone at ADNOC and thanks for spending the time with us at OOW to create this great video.

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  • DDD North 3 Presentation and source code &ndash; &lsquo;Event Store - an introduction to a DSD for event sourcing and notifications&rsquo;

    - by Liam Westley
    Originally posted on: http://geekswithblogs.net/twickers/archive/2013/10/15/ddd-north-3-presentation-and-source-code-ndash-lsquoevent-store.aspxThank you everyone at DDD North Thanks to all the people who helped organise the cracking conference that is DDD North 3, returning to Sunderland, and the great facilities at the University of Sunderland, and the fine drinks reception at Sunderland Software City.  The whole event wouldn’t be possible without the sponsors who ensured over 400 people were kept fed and watered so they could enjoy the impressive range of sessions. And lastly, a thank you to all those delegates who gave up their free time on a Saturday to spend a day dashing between lecture rooms, including a late change to my room which saw 40 people having to brave a journey between buildings in the fine drizzle. The enthusiasm from the delegates always helps recharge my geek batteries. Presentation and source code My presentation, source code, Event Store runners and text files containing the various command line parameters used for curl is now available on GitHub; https://github.com/westleyl/DDDNorth3-EventStore. Don’t worry if you don’t have a GitHub account, you don’t need one, you can just click on the Download Zip button on the right hand menu to download all the files as a single ZIP file.  If all you want is the PowerPoint presentation, go to https://github.com/westleyl/DDDNorth3-EventStore/blob/master/Powerpoint/DDDNorth-EventStore.pptx, and click on the View Raw button. Downloading and installing Event Store and Tools Download Event Store http://download.geteventstore.com – I unzipped these files into C:\EventStore\v2.0.1 Download Curl from http://curl.haxx.se/download.html – I downloaded Win64 Generic (with SSL) and unzipped these files into C:\curl version 7.31.0 Running the tools I used in my presentation Demonstration 1 (running Event Store) You can use one of my Event Store runner command files to run the single node version of Event Store, using default ports of 2213 for HTTP and 1113  for TCP, and with a wildcard HTTP pattern.  Both take a single command line parameter to specify the location of the data and log files.  The runners assume the single node executable is located in C:\EventStore\v2.0.1, and will placed data files and logs beneath C:\EventStore\Data, i.e. RunEventStore.cmd TestData1 This will create data files in C:\EventStore\Data\TestData1\Data and log files in C:\EventStore\Data\TestData1\logs. If, when running Event Store you may see the following message, [03288,15,06:23:00.622] Failed to start http server Access is denied You will either need to run Event Store in an administrator console window, or you can use the netsh command to create a firewall permission to allow HTTP listening (this will need to be run, once, in an administrator console window), netsh http add urlacl url=http://*:2213/ user=liam You can always delete this later by running the delete; netsh http delete urlacl url=http://*:2213/ If you want to confirm that everything is running OK, open the management console in a browser by navigating to http://127.0.0.1:2213. If at any point you are asked for a user name and password use the default of ‘admin’/‘changeit’.   Demonstration 2 (reading and adding data, curl) In my second demonstration I used curl directly from the console to read streams, write events and then read back those events. On GitHub I have included is a set of curl commands, CurlCommandLine.txt, and a sample data file, SampleData.json, to load an event into a DDDNorth3 stream. As there is not much data in the Event Store at this point I used the $stats-127.0.0.1:2113 which is a stream containing performance statistics for Event Store and is updated every 30 seconds (default). Demonstration 3 (projections) On GitHub I have included a sample projection, Projection-ByRoom.txt, which will create streams based on the room on which a session was held on the DDDNorth3 agenda. Browse to the management console, http://127.0.0.1:2213.  Click on Projections, New Projection, give it a name, Sessions-ByRoom, and copy in the JavaScript in the Projection-ByRoom.txt file.  Select Continuous, tick Emit Enabled and then click on Post. It should run immediately. You may by challenged for the administration login for the management console, if so use the default user name and password; 'admin'/'changeit'.   Demonstration 4 (C# client) The final demonstration was the Visual Studio 2012 project using the Event Store client – referenced directly as C:\EventStore\v2.0.1\EventStore.ClientAPI.dll, although you can switch this to the latest Event Store client NuGet package. The source code provides a console app for viewing projections with the projection manager (HTTP connection), as well as containing a full set of data for the entire DDDNorth3 agenda.  It also deals with the strategy for reading newest events backwards to older events and ignoring older events that have been superseded. Resources Event Store home page: http://www.geteventstore.com/ Event Store source code on GitHub: https://github.com/eventstore/eventstore Event Store documentation on GitHub: https://github.com/eventstore/eventstore/wiki (includes index to @RobAshton’s blog series on Event Store at https://github.com/eventstore/eventstore/wiki#rob-ashton---projections-series) Event Store forum in Google Groups: https://groups.google.com/forum/?fromgroups#!forum/event-store TopShelf Windows service wrapper is available on github: https://gist.github.com/trbngr/5083266

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  • WebLogic Server Performance and Tuning: Part I - Tuning JVM

    - by Gokhan Gungor
    Each WebLogic Server instance runs in its own dedicated Java Virtual Machine (JVM) which is their runtime environment. Every Admin Server in any domain executes within a JVM. The same also applies for Managed Servers. WebLogic Server can be used for a wide variety of applications and services which uses the same runtime environment and resources. Oracle WebLogic ships with 2 different JVM, HotSpot and JRocket but you can choose which JVM you want to use. JVM is designed to optimize itself however it also provides some startup options to make small changes. There are default values for its memory and garbage collection. In real world, you will not want to stick with the default values provided by the JVM rather want to customize these values based on your applications which can produce large gains in performance by making small changes with the JVM parameters. We can tell the garbage collector how to delete garbage and we can also tell JVM how much space to allocate for each generation (of java Objects) or for heap. Remember during the garbage collection no other process is executed within the JVM or runtime, which is called STOP THE WORLD which can affect the overall throughput. Each JVM has its own memory segment called Heap Memory which is the storage for java Objects. These objects can be grouped based on their age like young generation (recently created objects) or old generation (surviving objects that have lived to some extent), etc. A java object is considered garbage when it can no longer be reached from anywhere in the running program. Each generation has its own memory segment within the heap. When this segment gets full, garbage collector deletes all the objects that are marked as garbage to create space. When the old generation space gets full, the JVM performs a major collection to remove the unused objects and reclaim their space. A major garbage collect takes a significant amount of time and can affect system performance. When we create a managed server either on the same machine or on remote machine it gets its initial startup parameters from $DOMAIN_HOME/bin/setDomainEnv.sh/cmd file. By default two parameters are set:     Xms: The initial heapsize     Xmx: The max heapsize Try to set equal initial and max heapsize. The startup time can be a little longer but for long running applications it will provide a better performance. When we set -Xms512m -Xmx1024m, the physical heap size will be 512m. This means that there are pages of memory (in the state of the 512m) that the JVM does not explicitly control. It will be controlled by OS which could be reserve for the other tasks. In this case, it is an advantage if the JVM claims the entire memory at once and try not to spend time to extend when more memory is needed. Also you can use -XX:MaxPermSize (Maximum size of the permanent generation) option for Sun JVM. You should adjust the size accordingly if your application dynamically load and unload a lot of classes in order to optimize the performance. You can set the JVM options/heap size from the following places:     Through the Admin console, in the Server start tab     In the startManagedWeblogic script for the managed servers     $DOMAIN_HOME/bin/startManagedWebLogic.sh/cmd     JAVA_OPTIONS="-Xms1024m -Xmx1024m" ${JAVA_OPTIONS}     In the setDomainEnv script for the managed servers and admin server (domain wide)     USER_MEM_ARGS="-Xms1024m -Xmx1024m" When there is free memory available in the heap but it is too fragmented and not contiguously located to store the object or when there is actually insufficient memory we can get java.lang.OutOfMemoryError. We should create Thread Dump and analyze if that is possible in case of such error. The second option we can use to produce higher throughput is to garbage collection. We can roughly divide GC algorithms into 2 categories: parallel and concurrent. Parallel GC stops the execution of all the application and performs the full GC, this generally provides better throughput but also high latency using all the CPU resources during GC. Concurrent GC on the other hand, produces low latency but also low throughput since it performs GC while application executes. The JRockit JVM provides some useful command-line parameters that to control of its GC scheme like -XgcPrio command-line parameter which takes the following options; XgcPrio:pausetime (To minimize latency, parallel GC) XgcPrio:throughput (To minimize throughput, concurrent GC ) XgcPrio:deterministic (To guarantee maximum pause time, for real time systems) Sun JVM has similar parameters (like  -XX:UseParallelGC or -XX:+UseConcMarkSweepGC) to control its GC scheme. We can add -verbosegc -XX:+PrintGCDetails to monitor indications of a problem with garbage collection. Try configuring JVM’s of all managed servers to execute in -server mode to ensure that it is optimized for a server-side production environment.

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  • SQL SERVER – Solution to Puzzle – Simulate LEAD() and LAG() without Using SQL Server 2012 Analytic Function

    - by pinaldave
    Earlier I wrote a series on SQL Server Analytic Functions of SQL Server 2012. During the series to keep the learning maximum and having fun, we had few puzzles. One of the puzzle was simulating LEAD() and LAG() without using SQL Server 2012 Analytic Function. Please read the puzzle here first before reading the solution : Write T-SQL Self Join Without Using LEAD and LAG. When I was originally wrote the puzzle I had done small blunder and the question was a bit confusing which I corrected later on but wrote a follow up blog post on over here where I describe the give-away. Quick Recap: Generate following results without using SQL Server 2012 analytic functions. I had received so many valid answers. Some answers were similar to other and some were very innovative. Some answers were very adaptive and some did not work when I changed where condition. After selecting all the valid answer, I put them in table and ran RANDOM function on the same and selected winners. Here are the valid answers. No Joins and No Analytic Functions Excellent Solution by Geri Reshef – Winner of SQL Server Interview Questions and Answers (India | USA) WITH T1 AS (SELECT Row_Number() OVER(ORDER BY SalesOrderDetailID) N, s.SalesOrderID, s.SalesOrderDetailID, s.OrderQty FROM Sales.SalesOrderDetail s WHERE SalesOrderID IN (43670, 43669, 43667, 43663)) SELECT SalesOrderID,SalesOrderDetailID,OrderQty, CASE WHEN N%2=1 THEN MAX(CASE WHEN N%2=0 THEN SalesOrderDetailID END) OVER (Partition BY (N+1)/2) ELSE MAX(CASE WHEN N%2=1 THEN SalesOrderDetailID END) OVER (Partition BY N/2) END LeadVal, CASE WHEN N%2=1 THEN MAX(CASE WHEN N%2=0 THEN SalesOrderDetailID END) OVER (Partition BY N/2) ELSE MAX(CASE WHEN N%2=1 THEN SalesOrderDetailID END) OVER (Partition BY (N+1)/2) END LagVal FROM T1 ORDER BY SalesOrderID, SalesOrderDetailID, OrderQty; GO No Analytic Function and Early Bird Excellent Solution by DHall – Winner of Pluralsight 30 days Subscription -- a query to emulate LEAD() and LAG() ;WITH s AS ( SELECT 1 AS ldOffset, -- equiv to 2nd param of LEAD 1 AS lgOffset, -- equiv to 2nd param of LAG NULL AS ldDefVal, -- equiv to 3rd param of LEAD NULL AS lgDefVal, -- equiv to 3rd param of LAG ROW_NUMBER() OVER (ORDER BY SalesOrderDetailID) AS row, SalesOrderID, SalesOrderDetailID, OrderQty FROM Sales.SalesOrderDetail WHERE SalesOrderID IN (43670, 43669, 43667, 43663) ) SELECT s.SalesOrderID, s.SalesOrderDetailID, s.OrderQty, ISNULL( sLd.SalesOrderDetailID, s.ldDefVal) AS LeadValue, ISNULL( sLg.SalesOrderDetailID, s.lgDefVal) AS LagValue FROM s LEFT OUTER JOIN s AS sLd ON s.row = sLd.row - s.ldOffset LEFT OUTER JOIN s AS sLg ON s.row = sLg.row + s.lgOffset ORDER BY s.SalesOrderID, s.SalesOrderDetailID, s.OrderQty No Analytic Function and Partition By Excellent Solution by DHall – Winner of Pluralsight 30 days Subscription /* a query to emulate LEAD() and LAG() */ ;WITH s AS ( SELECT 1 AS LeadOffset, /* equiv to 2nd param of LEAD */ 1 AS LagOffset, /* equiv to 2nd param of LAG */ NULL AS LeadDefVal, /* equiv to 3rd param of LEAD */ NULL AS LagDefVal, /* equiv to 3rd param of LAG */ /* Try changing the values of the 4 integer values above to see their effect on the results */ /* The values given above of 0, 0, null and null behave the same as the default 2nd and 3rd parameters to LEAD() and LAG() */ ROW_NUMBER() OVER (ORDER BY SalesOrderDetailID) AS row, SalesOrderID, SalesOrderDetailID, OrderQty FROM Sales.SalesOrderDetail WHERE SalesOrderID IN (43670, 43669, 43667, 43663) ) SELECT s.SalesOrderID, s.SalesOrderDetailID, s.OrderQty, ISNULL( sLead.SalesOrderDetailID, s.LeadDefVal) AS LeadValue, ISNULL( sLag.SalesOrderDetailID, s.LagDefVal) AS LagValue FROM s LEFT OUTER JOIN s AS sLead ON s.row = sLead.row - s.LeadOffset /* Try commenting out this next line when LeadOffset != 0 */ AND s.SalesOrderID = sLead.SalesOrderID /* The additional join criteria on SalesOrderID above is equivalent to PARTITION BY SalesOrderID in the OVER clause of the LEAD() function */ LEFT OUTER JOIN s AS sLag ON s.row = sLag.row + s.LagOffset /* Try commenting out this next line when LagOffset != 0 */ AND s.SalesOrderID = sLag.SalesOrderID /* The additional join criteria on SalesOrderID above is equivalent to PARTITION BY SalesOrderID in the OVER clause of the LAG() function */ ORDER BY s.SalesOrderID, s.SalesOrderDetailID, s.OrderQty No Analytic Function and CTE Usage Excellent Solution by Pravin Patel - Winner of SQL Server Interview Questions and Answers (India | USA) --CTE based solution ; WITH cteMain AS ( SELECT SalesOrderID, SalesOrderDetailID, OrderQty, ROW_NUMBER() OVER (ORDER BY SalesOrderDetailID) AS sn FROM Sales.SalesOrderDetail WHERE SalesOrderID IN (43670, 43669, 43667, 43663) ) SELECT m.SalesOrderID, m.SalesOrderDetailID, m.OrderQty, sLead.SalesOrderDetailID AS leadvalue, sLeg.SalesOrderDetailID AS leagvalue FROM cteMain AS m LEFT OUTER JOIN cteMain AS sLead ON sLead.sn = m.sn+1 LEFT OUTER JOIN cteMain AS sLeg ON sLeg.sn = m.sn-1 ORDER BY m.SalesOrderID, m.SalesOrderDetailID, m.OrderQty No Analytic Function and Co-Related Subquery Usage Excellent Solution by Pravin Patel – Winner of SQL Server Interview Questions and Answers (India | USA) -- Co-Related subquery SELECT m.SalesOrderID, m.SalesOrderDetailID, m.OrderQty, ( SELECT MIN(SalesOrderDetailID) FROM Sales.SalesOrderDetail AS l WHERE l.SalesOrderID IN (43670, 43669, 43667, 43663) AND l.SalesOrderID >= m.SalesOrderID AND l.SalesOrderDetailID > m.SalesOrderDetailID ) AS lead, ( SELECT MAX(SalesOrderDetailID) FROM Sales.SalesOrderDetail AS l WHERE l.SalesOrderID IN (43670, 43669, 43667, 43663) AND l.SalesOrderID <= m.SalesOrderID AND l.SalesOrderDetailID < m.SalesOrderDetailID ) AS leag FROM Sales.SalesOrderDetail AS m WHERE m.SalesOrderID IN (43670, 43669, 43667, 43663) ORDER BY m.SalesOrderID, m.SalesOrderDetailID, m.OrderQty This was one of the most interesting Puzzle on this blog. Giveaway Winners will get following giveaways. Geri Reshef and Pravin Patel SQL Server Interview Questions and Answers (India | USA) DHall Pluralsight 30 days Subscription Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, Readers Contribution, Readers Question, SQL, SQL Authority, SQL Function, SQL Puzzle, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Quick 2D sight area calculation algorithm?

    - by Rogach
    I have a matrix of tiles, on some of that tiles there are objects. I want to calculate which tiles are visible to player, and which are not, and I need to do it quite efficiently (so it would compute fast enough even when I have a big matrices (100x100) and lots of objects). I tried to do it with Besenham's algorithm, but it was slow. Also, it gave me some errors: ----XXX- ----X**- ----XXX- -@------ -@------ -@------ ----XXX- ----X**- ----XXX- (raw version) (Besenham) (correct, since tunnel walls are still visible at distance) (@ is the player, X is obstacle, * is invisible, - is visible) I'm sure this can be done - after all, we have NetHack, Zangband, and they all dealt with this problem somehow :) What algorithm can you recommend for this? EDIT: Definition of visible (in my opinion): tile is visible when at least a part (e.g. corner) of the tile can be connected to center of player tile with a straight line which does not intersect any of obstacles.

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  • Developer’s Life – Every Developer is a Spiderman

    - by Pinal Dave
    I have to admit, Spiderman is my favorite superhero.  The most recent movie recently was released in theaters, so it has been at the front of my mind for some time. Spiderman was my favorite superhero even before the latest movie came out, but of course I took my whole family to see the movie as soon as I could!  Every one of us loved it, including my daughter.  We all left the movie thinking how great it would be to be Spiderman.  So, with that in mind, I started thinking about how we are like Spiderman in our everyday lives, especially developers. Let me list some of the reasons why I think every developer is a Spiderman. We have special powers, just like a superhero.  There is a reason that when there are problems or emergencies, we get called in, just like a superhero!  Our powers might not be the ability to swing through skyscrapers on a web, our powers are our debugging abilities, but there are still similarities! Spiderman never gives up.  He might not be the strongest superhero, and the ability to shoot web from your wrists is a pretty cool power, it’s not as impressive as being able to fly, or be invisible, or turn into a hulking green monster.  Developers are also human.  We have cool abilities, but our true strength lies in our willingness to work hard, find solutions, and go above and beyond to solve problems. Spiderman and developers have “spidey sense.”  This is sort of a joke in the comics and movies as well – that Spiderman can just tell when something is about to go wrong, or when a villain is just around the corner.  Developers also have a spidey sense about when a server is about to crash (usually at midnight on a Saturday). Spiderman makes a great superhero because he doesn’t look like one.  Clark Kent is probably fooling no one, hiding his superhero persona behind glasses.  But Peter Parker actually does blend in.  Great developers also blend in.  When they do their job right, no one knows they were there at all. “With great power comes great responsibility.”  There is a joke about developers (sometimes we even tell the jokes) about how if they are unhappy, the server or databases might mysteriously develop problems.  The truth is, very few developers would do something to harm a company’s computer system – they take their job very seriously.  It is a big responsibility. These are just a few of the reasons why I love Spiderman, why I love being a developer, and why I think developers are the greatest.  Let me know other reasons you love Spiderman and developers, or if you can shoot webs from your wrists – I might have a job for you. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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