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• upgrading from MVC4 to MVC5 pre-Release

  - by Jack M

  I have made that dreadful error of upgrading from MVC4 to MVC5 pre-release by updating the razor, and mvc webpage in my references I have System.Web.Mvc, System.Web.Webpages, System.Web.Webpages.Razor and System.Web.Razor as version v4.0.30319, when I run my application I get [A]System.Web.WebPages.Razor.Configuration.HostSection cannot be cast to [B]System.Web.WebPages.Razor.Configuration.HostSection. Type A originates from 'System.Web.WebPages.Razor, Version=2.0.0.0, Culture=neutral, PublicKeyToken=31bf3856ad364e35' in the context 'Default' at location 'C:\Windows\Microsoft.Net\assembly\GAC_MSIL\System.Web.WebPages.Razor\v4.0_2.0.0.0__31bf3856ad364e35\System.Web.WebPages.Razor.dll'. Type B originates from 'System.Web.WebPages.Razor, Version=3.0.0.0, Culture=neutral, PublicKeyToken=31bf3856ad364e35' in the context 'Default' at location 'C:\Windows\Microsoft.NET\Framework64\v4.0.30319\Temporary ASP.NET Files\membership\c70f06fe\9163b1ca\assembly\dl3\291c956e\73c25daa_cf74ce01\System.Web.WebPages.Razor.dll'. is this the same as http://www.asp.net/whitepapers/mvc4-release-notes Thanks Adding a stacktrace: [InvalidCastException: [A]System.Web.WebPages.Razor.Configuration.HostSection cannot be cast to [B]System.Web.WebPages.Razor.Configuration.HostSection. Type A originates from 'System.Web.WebPages.Razor, Version=2.0.0.0, Culture=neutral, PublicKeyToken=31bf3856ad364e35' in the context 'Default' at location 'C:\Windows\Microsoft.Net\assembly\GAC_MSIL\System.Web.WebPages.Razor\v4.0_2.0.0.0__31bf3856ad364e35\System.Web.WebPages.Razor.dll'. Type B originates from 'System.Web.WebPages.Razor, Version=3.0.0.0, Culture=neutral, PublicKeyToken=31bf3856ad364e35' in the context 'Default' at location 'C:\Windows\Microsoft.NET\Framework64\v4.0.30319\Temporary ASP.NET Files\c70f06fe\9163b1ca\assembly\dl3\291c956e\73c25daa_cf74ce01\System.Web.WebPages.Razor.dll'.] System.Web.WebPages.Razor.WebRazorHostFactory.CreateHostFromConfig(String virtualPath, String physicalPath) +193 System.Web.WebPages.Razor.RazorBuildProvider.GetHostFromConfig() +51 System.Web.WebPages.Razor.RazorBuildProvider.CreateHost() +24 System.Web.WebPages.Razor.RazorBuildProvider.get_Host() +34 System.Web.WebPages.Razor.RazorBuildProvider.EnsureGeneratedCode() +85 System.Web.WebPages.Razor.RazorBuildProvider.get_CodeCompilerType() +34 System.Web.Compilation.BuildProvider.GetCompilerTypeFromBuildProvider(BuildProvider buildProvider) +189 System.Web.Compilation.BuildProvidersCompiler.ProcessBuildProviders() +265 System.Web.Compilation.BuildProvidersCompiler.PerformBuild() +21 System.Web.Compilation.BuildManager.CompileWebFile(VirtualPath virtualPath) +580 System.Web.Compilation.BuildManager.GetVPathBuildResultInternal(VirtualPath virtualPath, Boolean noBuild, Boolean allowCrossApp, Boolean allowBuildInPrecompile, Boolean throwIfNotFound, Boolean ensureIsUpToDate) +571 System.Web.Compilation.BuildManager.GetVPathBuildResultWithNoAssert(HttpContext context, VirtualPath virtualPath, Boolean noBuild, Boolean allowCrossApp, Boolean allowBuildInPrecompile, Boolean throwIfNotFound, Boolean ensureIsUpToDate) +203 System.Web.Compilation.BuildManager.GetVirtualPathObjectFactory(VirtualPath virtualPath, HttpContext context, Boolean allowCrossApp, Boolean throwIfNotFound) +249 System.Web.Compilation.BuildManager.GetCompiledType(VirtualPath virtualPath) +17 System.Web.Mvc.BuildManagerCompiledView.Render(ViewContext viewContext, TextWriter writer) +90 System.Web.Mvc.ViewResultBase.ExecuteResult(ControllerContext context) +380 System.Web.Mvc.ControllerActionInvoker.InvokeActionResultFilterRecursive(IList`1 filters, Int32 filterIndex, ResultExecutingContext preContext, ControllerContext controllerContext, ActionResult actionResult) +109 System.Web.Mvc.ControllerActionInvoker.InvokeActionResultFilterRecursive(IList`1 filters, Int32 filterIndex, ResultExecutingContext preContext, ControllerContext controllerContext, ActionResult actionResult) +890 System.Web.Mvc.ControllerActionInvoker.InvokeActionResultWithFilters(ControllerContext controllerContext, IList`1 filters, ActionResult actionResult) +97 System.Web.Mvc.Async.<>c__DisplayClass1e.<BeginInvokeAction>b__1b(IAsyncResult asyncResult) +241 System.Web.Mvc.Controller.<BeginExecuteCore>b__1d(IAsyncResult asyncResult, ExecuteCoreState innerState) +29 System.Web.Mvc.Async.WrappedAsyncVoid`1.CallEndDelegate(IAsyncResult asyncResult) +111 System.Web.Mvc.Controller.EndExecuteCore(IAsyncResult asyncResult) +53 System.Web.Mvc.Async.WrappedAsyncVoid`1.CallEndDelegate(IAsyncResult asyncResult) +19 System.Web.Mvc.MvcHandler.<BeginProcessRequest>b__4(IAsyncResult asyncResult, ProcessRequestState innerState) +51 System.Web.Mvc.Async.WrappedAsyncVoid`1.CallEndDelegate(IAsyncResult asyncResult) +111 System.Web.CallHandlerExecutionStep.System.Web.HttpApplication.IExecutionStep.Execute() +606 System.Web.HttpApplication.ExecuteStep(IExecutionStep step, Boolean& completedSynchronously) +288

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• What's the different between ASP.NET AJAX pageLoad() and JavaScript window.onload?

  - by Amr ElGarhy

  I'm working with ASP.NET AJAX and want to understand the difference between these two snippets: function pageLoad(sender, eventArgs) { } and window.onload = function() { } Do they act the same? Or is one called before the other? Or will one be called automatically and the another not?

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• Employee Info Starter Kit - Visual Studio 2010 and .NET 4.0 Version (4.0.0) Available

  - by Mohammad Ashraful Alam

  Employee Info Starter Kit is a ASP.NET based web application, which includes very simple user requirements, where we can create, read, update and delete (crud) the employee info of a company. Based on just a database table, it explores and solves most of the major problems in web development architectural space.  This open source starter kit extensively uses major features available in latest Visual Studio, ASP.NET and Sql Server to make robust, scalable, secured and maintanable web applications quickly and easily. Since it's first release, this starter kit achieved a huge popularity in web developer community and includes 1,40,000+ download from project web site. Visual Studio 2010 and .NET 4.0 came up with lots of exciting features to make software developers life easier.  A new version (v4.0.0) of Employee Info Starter Kit is now available in both MSDN Code Gallery and CodePlex. Chckout the latest version of this starter kit to enjoy cool features available in Visual Studio 2010 and .NET 4.0. [ Release Notes ] Architectural Overview Simple 2 layer architecture (user interface and data access layer) with 1 optional cache layer ASP.NET Web Form based user interface Custom Entity Data Container implemented (with primitive C# types for data fields) Active Record Design Pattern based Data Access Layer, implemented in C# and Entity Framework 4.0 Sql Server Stored Procedure to perform actual CRUD operation Standard infrastructure (architecture, helper utility) for automated integration (bottom up manner) and unit testing Technology UtilizedProgramming Languages/Scripts Browser side: JavaScript Web server side: C# 4.0 Database server side: T-SQL .NET Framework Components .NET 4.0 Entity Framework .NET 4.0 Optional/Named Parameters .NET 4.0 Tuple .NET 3.0+ Extension Method .NET 3.0+ Lambda Expressions .NET 3.0+ Aanonymous Type .NET 3.0+ Query Expressions .NET 3.0+ Automatically Implemented Properties .NET 3.0+ LINQ .NET 2.0 + Partial Classes .NET 2.0 + Generic Type .NET 2.0 + Nullable Type   ASP.NET 3.5+ List View (TBD) ASP.NET 3.5+ Data Pager (TBD) ASP.NET 2.0+ Grid View ASP.NET 2.0+ Form View ASP.NET 2.0+ Skin ASP.NET 2.0+ Theme ASP.NET 2.0+ Master Page ASP.NET 2.0+ Object Data Source ASP.NET 1.0+ Role Based Security Visual Studio Features Visual Studio 2010 CodedUI Test Visual Studio 2010 Layer Diagram Visual Studio 2010 Sequence Diagram Visual Studio 2010 Directed Graph Visual Studio 2005+ Database Unit Test Visual Studio 2005+ Unit Test Visual Studio 2005+ Web Test Visual Studio 2005+ Load Test Sql Server Features Sql Server 2005 Stored Procedure Sql Server 2005 Xml type Sql Server 2005 Paging support

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• Making Sense of ASP.NET Paths

  - by Rick Strahl

  ASP.Net includes quite a plethora of properties to retrieve path information about the current request, control and application. There's a ton of information available about paths on the Request object, some of it appearing to overlap and some of it buried several levels down, and it can be confusing to find just the right path that you are looking for. To keep things straight I thought it a good idea to summarize the path options along with descriptions and example paths. I wrote a post about this a long time ago in 2004 and I find myself frequently going back to that page to quickly figure out which path I’m looking for in processing the current URL. Apparently a lot of people must be doing the same, because the original post is the second most visited even to this date on this blog to the tune of nearly 500 hits per day. So, I decided to update and expand a bit on the original post with a little more information and clarification based on the original comments. Request Object Paths Available Here's a list of the Path related properties on the Request object (and the Page object). Assume a path like http://www.west-wind.com/webstore/admin/paths.aspx for the paths below where webstore is the name of the virtual. .blackborder td { border-bottom: solid 1px silver; border-left: solid 1px silver; } Request Property Description and Value ApplicationPath Returns the web root-relative logical path to the virtual root of this app. /webstore/ PhysicalApplicationPath Returns local file system path of the virtual root for this app. c:\inetpub\wwwroot\webstore PhysicalPath Returns the local file system path to the current script or path. c:\inetpub\wwwroot\webstore\admin\paths.aspx Path FilePath CurrentExecutionFilePath All of these return the full root relative logical path to the script page including path and scriptname. CurrentExcecutionFilePath will return the ‘current’ request path after a Transfer/Execute call while FilePath will always return the original request’s path. /webstore/admin/paths.aspx AppRelativeCurrentExecutionFilePath Returns an ASP.NET root relative virtual path to the script or path for the current request. If in  a Transfer/Execute call the transferred Path is returned. ~/admin/paths.aspx PathInfo Returns any extra path following the script name. If no extra path is provided returns the root-relative path (returns text in red below). string.Empty if no PathInfo is available. /webstore/admin/paths.aspx/ExtraPathInfo RawUrl Returns the full root relative URL including querystring and extra path as a string. /webstore/admin/paths.aspx?sku=wwhelp40 Url Returns a fully qualified URL including querystring and extra path. Note this is a Uri instance rather than string. http://www.west-wind.com/webstore/admin/paths.aspx?sku=wwhelp40 UrlReferrer The fully qualified URL of the page that sent the request. This is also a Uri instance and this value is null if the page was directly accessed by typing into the address bar or using an HttpClient based Referrer client Http header. http://www.west-wind.com/webstore/default.aspx?Info Control.TemplateSourceDirectory Returns the logical path to the folder of the page, master or user control on which it is called. This is useful if you need to know the path only to a Page or control from within the control. For non-file controls this returns the Page path. /webstore/admin/ As you can see there’s a ton of information available there for each of the three common path formats: Physical Path is an OS type path that points to a path or file on disk. Logical Path is a Web path that is relative to the Web server’s root. It includes the virtual plus the application relative path. ~/ (Root-relative) Path is an ASP.NET specific path that includes ~/ to indicate the virtual root Web path. ASP.NET can convert virtual paths into either logical paths using Control.ResolveUrl(), or physical paths using Server.MapPath(). Root relative paths are useful for specifying portable URLs that don’t rely on relative directory structures and very useful from within control or component code. You should be able to get any necessary format from ASP.NET from just about any path or script using these mechanisms. ~/ Root Relative Paths and ResolveUrl() and ResolveClientUrl() ASP.NET supports root-relative virtual path syntax in most of its URL properties in Web Forms. So you can easily specify a root relative path in a control rather than a location relative path: <asp:Image runat="server" ID="imgHelp" ImageUrl="~/images/help.gif" /> ASP.NET internally resolves this URL by using ResolveUrl("~/images/help.gif") to arrive at the root-relative URL of /webstore/images/help.gif which uses the Request.ApplicationPath as the basepath to replace the ~. By convention any custom Web controls also should use ResolveUrl() on URL properties to provide the same functionality. In your own code you can use Page.ResolveUrl() or Control.ResolveUrl() to accomplish the same thing: string imgPath = this.ResolveUrl("~/images/help.gif"); imgHelp.ImageUrl = imgPath; Unfortunately ResolveUrl() is limited to WebForm pages, so if you’re in an HttpHandler or Module it’s not available. ASP.NET Mvc also has it’s own more generic version of ResolveUrl in Url.Decode: <script src="<%= Url.Content("~/scripts/new.js") %>" type="text/javascript"></script> which is part of the UrlHelper class. In ASP.NET MVC the above sort of syntax is actually even more crucial than in WebForms due to the fact that views are not referencing specific pages but rather are often path based which can lead to various variations on how a particular view is referenced. In a Module or Handler code Control.ResolveUrl() unfortunately is not available which in retrospect seems like an odd design choice – URL resolution really should happen on a Request basis not as part of the Page framework. Luckily you can also rely on the static VirtualPathUtility class: string path = VirtualPathUtility.ToAbsolute("~/admin/paths.aspx"); VirtualPathUtility also many other quite useful methods for dealing with paths and converting between the various kinds of paths supported. One thing to watch out for is that ToAbsolute() will throw an exception if a query string is provided and doesn’t work on fully qualified URLs. I wrote about this topic with a custom solution that works fully qualified URLs and query strings here (check comments for some interesting discussions too). Similar to ResolveUrl() is ResolveClientUrl() which creates a fully qualified HTTP path that includes the protocol and domain name. It’s rare that this full resolution is needed but can be useful in some scenarios. Mapping Virtual Paths to Physical Paths with Server.MapPath() If you need to map root relative or current folder relative URLs to physical URLs or you can use HttpContext.Current.Server.MapPath(). Inside of a Page you can do the following: string physicalPath = Server.MapPath("~/scripts/ww.jquery.js")); MapPath is pretty flexible and it understands both ASP.NET style virtual paths as well as plain relative paths, so the following also works. string physicalPath = Server.MapPath("scripts/silverlight.js"); as well as dot relative syntax: string physicalPath = Server.MapPath("../scripts/jquery.js"); Once you have the physical path you can perform standard System.IO Path and File operations on the file. Remember with physical paths and IO or copy operations you need to make sure you have permissions to access files and folders based on the Web server user account that is active (NETWORK SERVICE, ASPNET typically). Note the Server.MapPath will not map up beyond the virtual root of the application for security reasons. Server and Host Information Between these settings you can get all the information you may need to figure out where you are at and to build new Url if necessary. If you need to build a URL completely from scratch you can get access to information about the server you are accessing: Server Variable Function and Example SERVER_NAME The of the domain or IP Address wwww.west-wind.com or 127.0.0.1 SERVER_PORT The port that the request runs under. 80 SERVER_PORT_SECURE Determines whether https: was used. 0 or 1 APPL_MD_PATH ADSI DirectoryServices path to the virtual root directory. Note that LM typically doesn’t work for ADSI access so you should replace that with LOCALHOST or the machine’s NetBios name. /LM/W3SVC/1/ROOT/webstore Request.Url and Uri Parsing If you still need more control over the current request URL or  you need to create new URLs from an existing one, the current Request.Url Uri property offers a lot of control. Using the Uri class and UriBuilder makes it easy to retrieve parts of a URL and create new URLs based on existing URL. The UriBuilder class is the preferred way to create URLs – much preferable over creating URIs via string concatenation. Uri Property Function Scheme The URL scheme or protocol prefix. http or https Port The port if specifically specified. DnsSafeHost The domain name or local host NetBios machine name www.west-wind.com or rasnote LocalPath The full path of the URL including script name and extra PathInfo. /webstore/admin/paths.aspx Query The query string if any ?id=1 The Uri class itself is great for retrieving Uri parts, but most of the properties are read only if you need to modify a URL in order to change it you can use the UriBuilder class to load up an existing URL and modify it to create a new one. Here are a few common operations I’ve needed to do to get specific URLs: Convert the Request URL to an SSL/HTTPS link For example to take the current request URL and converted  it to a secure URL can be done like this: UriBuilder build = new UriBuilder(Request.Url); build.Scheme = "https"; build.Port = -1; // don't inject port Uri newUri = build.Uri; string newUrl = build.ToString(); Retrieve the fully qualified URL without a QueryString AFAIK, there’s no native routine to retrieve the current request URL without the query string. It’s easy to do with UriBuilder however: UriBuilder builder = newUriBuilder(Request.Url); builder.Query = ""; stringlogicalPathWithoutQuery = builder.ToString(); What else? I took a look through the old post’s comments and addressed as many of the questions and comments that came up in there. With a few small and silly exceptions this update post handles most of these. But I’m sure there are a more things that go in here. What else would be useful to put onto this post so it serves as a nice all in one place to go for path references? If you think of something leave a comment and I’ll try to update the post with it in the future.© Rick Strahl, West Wind Technologies, 2005-2010Posted in ASP.NET  

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• Parallelism in .NET – Part 3, Imperative Data Parallelism: Early Termination

  - by Reed

  Although simple data parallelism allows us to easily parallelize many of our iteration statements, there are cases that it does not handle well.  In my previous discussion, I focused on data parallelism with no shared state, and where every element is being processed exactly the same. Unfortunately, there are many common cases where this does not happen.  If we are dealing with a loop that requires early termination, extra care is required when parallelizing. Often, while processing in a loop, once a certain condition is met, it is no longer necessary to continue processing.  This may be a matter of finding a specific element within the collection, or reaching some error case.  The important distinction here is that, it is often impossible to know until runtime, what set of elements needs to be processed. In my initial discussion of data parallelism, I mentioned that this technique is a candidate when you can decompose the problem based on the data involved, and you wish to apply a single operation concurrently on all of the elements of a collection.  This covers many of the potential cases, but sometimes, after processing some of the elements, we need to stop processing. As an example, lets go back to our previous Parallel.ForEach example with contacting a customer.  However, this time, we’ll change the requirements slightly.  In this case, we’ll add an extra condition – if the store is unable to email the customer, we will exit gracefully.  The thinking here, of course, is that if the store is currently unable to email, the next time this operation runs, it will handle the same situation, so we can just skip our processing entirely.  The original, serial case, with this extra condition, might look something like the following: foreach(var customer in customers) { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { // Exit gracefully if we fail to email, since this // entire process can be repeated later without issue. if (theStore.EmailCustomer(customer) == false) break; customer.LastEmailContact = DateTime.Now; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Here, we’re processing our loop, but at any point, if we fail to send our email successfully, we just abandon this process, and assume that it will get handled correctly the next time our routine is run.  If we try to parallelize this using Parallel.ForEach, as we did previously, we’ll run into an error almost immediately: the break statement we’re using is only valid when enclosed within an iteration statement, such as foreach.  When we switch to Parallel.ForEach, we’re no longer within an iteration statement – we’re a delegate running in a method. This needs to be handled slightly differently when parallelized.  Instead of using the break statement, we need to utilize a new class in the Task Parallel Library: ParallelLoopState.  The ParallelLoopState class is intended to allow concurrently running loop bodies a way to interact with each other, and provides us with a way to break out of a loop.  In order to use this, we will use a different overload of Parallel.ForEach which takes an IEnumerable<T> and an Action<T, ParallelLoopState> instead of an Action<T>.  Using this, we can parallelize the above operation by doing: Parallel.ForEach(customers, (customer, parallelLoopState) => { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { // Exit gracefully if we fail to email, since this // entire process can be repeated later without issue. if (theStore.EmailCustomer(customer) == false) parallelLoopState.Break(); else customer.LastEmailContact = DateTime.Now; } }); There are a couple of important points here.  First, we didn’t actually instantiate the ParallelLoopState instance.  It was provided directly to us via the Parallel class.  All we needed to do was change our lambda expression to reflect that we want to use the loop state, and the Parallel class creates an instance for our use.  We also needed to change our logic slightly when we call Break().  Since Break() doesn’t stop the program flow within our block, we needed to add an else case to only set the property in customer when we succeeded.  This same technique can be used to break out of a Parallel.For loop. That being said, there is a huge difference between using ParallelLoopState to cause early termination and to use break in a standard iteration statement.  When dealing with a loop serially, break will immediately terminate the processing within the closest enclosing loop statement.  Calling ParallelLoopState.Break(), however, has a very different behavior. The issue is that, now, we’re no longer processing one element at a time.  If we break in one of our threads, there are other threads that will likely still be executing.  This leads to an important observation about termination of parallel code: Early termination in parallel routines is not immediate.  Code will continue to run after you request a termination. This may seem problematic at first, but it is something you just need to keep in mind while designing your routine.  ParallelLoopState.Break() should be thought of as a request.  We are telling the runtime that no elements that were in the collection past the element we’re currently processing need to be processed, and leaving it up to the runtime to decide how to handle this as gracefully as possible.  Although this may seem problematic at first, it is a good thing.  If the runtime tried to immediately stop processing, many of our elements would be partially processed.  It would be like putting a return statement in a random location throughout our loop body – which could have horrific consequences to our code’s maintainability. In order to understand and effectively write parallel routines, we, as developers, need a subtle, but profound shift in our thinking.  We can no longer think in terms of sequential processes, but rather need to think in terms of requests to the system that may be handled differently than we’d first expect.  This is more natural to developers who have dealt with asynchronous models previously, but is an important distinction when moving to concurrent programming models. As an example, I’ll discuss the Break() method.  ParallelLoopState.Break() functions in a way that may be unexpected at first.  When you call Break() from a loop body, the runtime will continue to process all elements of the collection that were found prior to the element that was being processed when the Break() method was called.  This is done to keep the behavior of the Break() method as close to the behavior of the break statement as possible. We can see the behavior in this simple code: var collection = Enumerable.Range(0, 20); var pResult = Parallel.ForEach(collection, (element, state) => { if (element > 10) { Console.WriteLine("Breaking on {0}", element); state.Break(); } Console.WriteLine(element); }); If we run this, we get a result that may seem unexpected at first: 0 2 1 5 6 3 4 10 Breaking on 11 11 Breaking on 12 12 9 Breaking on 13 13 7 8 Breaking on 15 15 What is occurring here is that we loop until we find the first element where the element is greater than 10.  In this case, this was found, the first time, when one of our threads reached element 11.  It requested that the loop stop by calling Break() at this point.  However, the loop continued processing until all of the elements less than 11 were completed, then terminated.  This means that it will guarantee that elements 9, 7, and 8 are completed before it stops processing.  You can see our other threads that were running each tried to break as well, but since Break() was called on the element with a value of 11, it decides which elements (0-10) must be processed. If this behavior is not desirable, there is another option.  Instead of calling ParallelLoopState.Break(), you can call ParallelLoopState.Stop().  The Stop() method requests that the runtime terminate as soon as possible , without guaranteeing that any other elements are processed.  Stop() will not stop the processing within an element, so elements already being processed will continue to be processed.  It will prevent new elements, even ones found earlier in the collection, from being processed.  Also, when Stop() is called, the ParallelLoopState’s IsStopped property will return true.  This lets longer running processes poll for this value, and return after performing any necessary cleanup. The basic rule of thumb for choosing between Break() and Stop() is the following. Use ParallelLoopState.Stop() when possible, since it terminates more quickly.  This is particularly useful in situations where you are searching for an element or a condition in the collection.  Once you’ve found it, you do not need to do any other processing, so Stop() is more appropriate. Use ParallelLoopState.Break() if you need to more closely match the behavior of the C# break statement. Both methods behave differently than our C# break statement.  Unfortunately, when parallelizing a routine, more thought and care needs to be put into every aspect of your routine than you may otherwise expect.  This is due to my second observation: Parallelizing a routine will almost always change its behavior. This sounds crazy at first, but it’s a concept that’s so simple its easy to forget.  We’re purposely telling the system to process more than one thing at the same time, which means that the sequence in which things get processed is no longer deterministic.  It is easy to change the behavior of your routine in very subtle ways by introducing parallelism.  Often, the changes are not avoidable, even if they don’t have any adverse side effects.  This leads to my final observation for this post: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

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• Issues integrating NCover with CC.NET, .NET framework 4.0 and MsTest

  - by Nikhil

  I'm implementing continuous integration with CruiseControl.NET, .NET 4.0, NCover and MsTest. On the build server I'm unable to run code coverage from the Ncover explorer or NCover console. When I run where vstesthost.exe from the Ncover console it returns the Visual Studio 9.0 path and does not seem to pick up .net framework 4.0. I've followed instructions from this MSTest: Measuring Test Quality With NCover post with slight modifications for .net framework 4.0, without any success. My CC.NET script looks like this <exec> <executable>C:\Program Files (x86)\NCover\NCover.Console.exe</executable> <baseDirectory>$(project_root)\</baseDirectory> <buildArgs>"C:\Program Files (x86)\**Microsoft Visual Studio 10.0**\Common7\IDE\MSTest.exe" /testcontainer:...\...\UnitTests.dll /resultsfile:TestResults.trx //xml D:\_Projects\....\Temp_Coverage.xml //pm vstesthost.exe</buildArgs> <buildTimeoutSeconds>$(ncover.timeout)</buildTimeoutSeconds> </exec> Has anyone come across similar issue. Any help would be much appreciated.

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• Parallelism in .NET – Part 7, Some Differences between PLINQ and LINQ to Objects

  - by Reed

  In my previous post on Declarative Data Parallelism, I mentioned that PLINQ extends LINQ to Objects to support parallel operations.  Although nearly all of the same operations are supported, there are some differences between PLINQ and LINQ to Objects.  By introducing Parallelism to our declarative model, we add some extra complexity.  This, in turn, adds some extra requirements that must be addressed. In order to illustrate the main differences, and why they exist, let’s begin by discussing some differences in how the two technologies operate, and look at the underlying types involved in LINQ to Objects and PLINQ . LINQ to Objects is mainly built upon a single class: Enumerable.  The Enumerable class is a static class that defines a large set of extension methods, nearly all of which work upon an IEnumerable<T>.  Many of these methods return a new IEnumerable<T>, allowing the methods to be chained together into a fluent style interface.  This is what allows us to write statements that chain together, and lead to the nice declarative programming model of LINQ: double min = collection .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Other LINQ variants work in a similar fashion.  For example, most data-oriented LINQ providers are built upon an implementation of IQueryable<T>, which allows the database provider to turn a LINQ statement into an underlying SQL query, to be performed directly on the remote database. PLINQ is similar, but instead of being built upon the Enumerable class, most of PLINQ is built upon a new static class: ParallelEnumerable.  When using PLINQ, you typically begin with any collection which implements IEnumerable<T>, and convert it to a new type using an extension method defined on ParallelEnumerable: AsParallel().  This method takes any IEnumerable<T>, and converts it into a ParallelQuery<T>, the core class for PLINQ.  There is a similar ParallelQuery class for working with non-generic IEnumerable implementations. This brings us to our first subtle, but important difference between PLINQ and LINQ – PLINQ always works upon specific types, which must be explicitly created. Typically, the type you’ll use with PLINQ is ParallelQuery<T>, but it can sometimes be a ParallelQuery or an OrderedParallelQuery<T>.  Instead of dealing with an interface, implemented by an unknown class, we’re dealing with a specific class type.  This works seamlessly from a usage standpoint – ParallelQuery<T> implements IEnumerable<T>, so you can always “switch back” to an IEnumerable<T>.  The difference only arises at the beginning of our parallelization.  When we’re using LINQ, and we want to process a normal collection via PLINQ, we need to explicitly convert the collection into a ParallelQuery<T> by calling AsParallel().  There is an important consideration here – AsParallel() does not need to be called on your specific collection, but rather any IEnumerable<T>.  This allows you to place it anywhere in the chain of methods involved in a LINQ statement, not just at the beginning.  This can be useful if you have an operation which will not parallelize well or is not thread safe.  For example, the following is perfectly valid, and similar to our previous examples: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); However, if SomeOperation() is not thread safe, we could just as easily do: double min = collection .Select(item => item.SomeOperation()) .AsParallel() .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); In this case, we’re using standard LINQ to Objects for the Select(…) method, then converting the results of that map routine to a ParallelQuery<T>, and processing our filter (the Where method) and our aggregation (the Min method) in parallel. PLINQ also provides us with a way to convert a ParallelQuery<T> back into a standard IEnumerable<T>, forcing sequential processing via standard LINQ to Objects.  If SomeOperation() was thread-safe, but PerformComputation() was not thread-safe, we would need to handle this by using the AsEnumerable() method: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .AsEnumerable() .Min(item => item.PerformComputation()); Here, we’re converting our collection into a ParallelQuery<T>, doing our map operation (the Select(…) method) and our filtering in parallel, then converting the collection back into a standard IEnumerable<T>, which causes our aggregation via Min() to be performed sequentially. This could also be written as two statements, as well, which would allow us to use the language integrated syntax for the first portion: var tempCollection = from item in collection.AsParallel() let e = item.SomeOperation() where (e.SomeProperty > 6 && e.SomeProperty < 24) select e; double min = tempCollection.AsEnumerable().Min(item => item.PerformComputation()); This allows us to use the standard LINQ style language integrated query syntax, but control whether it’s performed in parallel or serial by adding AsParallel() and AsEnumerable() appropriately. The second important difference between PLINQ and LINQ deals with order preservation.  PLINQ, by default, does not preserve the order of of source collection. This is by design.  In order to process a collection in parallel, the system needs to naturally deal with multiple elements at the same time.  Maintaining the original ordering of the sequence adds overhead, which is, in many cases, unnecessary.  Therefore, by default, the system is allowed to completely change the order of your sequence during processing.  If you are doing a standard query operation, this is usually not an issue.  However, there are times when keeping a specific ordering in place is important.  If this is required, you can explicitly request the ordering be preserved throughout all operations done on a ParallelQuery<T> by using the AsOrdered() extension method.  This will cause our sequence ordering to be preserved. For example, suppose we wanted to take a collection, perform an expensive operation which converts it to a new type, and display the first 100 elements.  In LINQ to Objects, our code might look something like: // Using IEnumerable<SourceClass> collection IEnumerable<ResultClass> results = collection .Select(e => e.CreateResult()) .Take(100); If we just converted this to a parallel query naively, like so: IEnumerable<ResultClass> results = collection .AsParallel() .Select(e => e.CreateResult()) .Take(100); We could very easily get a very different, and non-reproducable, set of results, since the ordering of elements in the input collection is not preserved.  To get the same results as our original query, we need to use: IEnumerable<ResultClass> results = collection .AsParallel() .AsOrdered() .Select(e => e.CreateResult()) .Take(100); This requests that PLINQ process our sequence in a way that verifies that our resulting collection is ordered as if it were processed serially.  This will cause our query to run slower, since there is overhead involved in maintaining the ordering.  However, in this case, it is required, since the ordering is required for correctness. PLINQ is incredibly useful.  It allows us to easily take nearly any LINQ to Objects query and run it in parallel, using the same methods and syntax we’ve used previously.  There are some important differences in operation that must be considered, however – it is not a free pass to parallelize everything.  When using PLINQ in order to parallelize your routines declaratively, the same guideline I mentioned before still applies: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

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• Parallelism in .NET – Part 9, Configuration in PLINQ and TPL

  - by Reed

  Parallel LINQ and the Task Parallel Library contain many options for configuration.  Although the default configuration options are often ideal, there are times when customizing the behavior is desirable.  Both frameworks provide full configuration support. When working with Data Parallelism, there is one primary configuration option we often need to control – the number of threads we want the system to use when parallelizing our routine.  By default, PLINQ and the TPL both use the ThreadPool to schedule tasks.  Given the major improvements in the ThreadPool in CLR 4, this default behavior is often ideal.  However, there are times that the default behavior is not appropriate.  For example, if you are working on multiple threads simultaneously, and want to schedule parallel operations from within both threads, you might want to consider restricting each parallel operation to using a subset of the processing cores of the system.  Not doing this might over-parallelize your routine, which leads to inefficiencies from having too many context switches. In the Task Parallel Library, configuration is handled via the ParallelOptions class.  All of the methods of the Parallel class have an overload which accepts a ParallelOptions argument. We configure the Parallel class by setting the ParallelOptions.MaxDegreeOfParallelism property.  For example, let’s revisit one of the simple data parallel examples from Part 2: Parallel.For(0, pixelData.GetUpperBound(0), row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Here, we’re looping through an image, and calling a method on each pixel in the image.  If this was being done on a separate thread, and we knew another thread within our system was going to be doing a similar operation, we likely would want to restrict this to using half of the cores on the system.  This could be accomplished easily by doing: var options = new ParallelOptions(); options.MaxDegreeOfParallelism = Math.Max(Environment.ProcessorCount / 2, 1); Parallel.For(0, pixelData.GetUpperBound(0), options, row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); Now, we’re restricting this routine to using no more than half the cores in our system.  Note that I included a check to prevent a single core system from supplying zero; without this check, we’d potentially cause an exception.  I also did not hard code a specific value for the MaxDegreeOfParallelism property.  One of our goals when parallelizing a routine is allowing it to scale on better hardware.  Specifying a hard-coded value would contradict that goal. Parallel LINQ also supports configuration, and in fact, has quite a few more options for configuring the system.  The main configuration option we most often need is the same as our TPL option: we need to supply the maximum number of processing threads.  In PLINQ, this is done via a new extension method on ParallelQuery<T>: ParallelEnumerable.WithDegreeOfParallelism. Let’s revisit our declarative data parallelism sample from Part 6: double min = collection.AsParallel().Min(item => item.PerformComputation()); Here, we’re performing a computation on each element in the collection, and saving the minimum value of this operation.  If we wanted to restrict this to a limited number of threads, we would add our new extension method: int maxThreads = Math.Max(Environment.ProcessorCount / 2, 1); double min = collection .AsParallel() .WithDegreeOfParallelism(maxThreads) .Min(item => item.PerformComputation()); This automatically restricts the PLINQ query to half of the threads on the system. PLINQ provides some additional configuration options.  By default, PLINQ will occasionally revert to processing a query in parallel.  This occurs because many queries, if parallelized, typically actually cause an overall slowdown compared to a serial processing equivalent.  By analyzing the “shape” of the query, PLINQ often decides to run a query serially instead of in parallel.  This can occur for (taken from MSDN): Queries that contain a Select, indexed Where, indexed SelectMany, or ElementAt clause after an ordering or filtering operator that has removed or rearranged original indices. Queries that contain a Take, TakeWhile, Skip, SkipWhile operator and where indices in the source sequence are not in the original order. Queries that contain Zip or SequenceEquals, unless one of the data sources has an originally ordered index and the other data source is indexable (i.e. an array or IList(T)). Queries that contain Concat, unless it is applied to indexable data sources. Queries that contain Reverse, unless applied to an indexable data source. If the specific query follows these rules, PLINQ will run the query on a single thread.  However, none of these rules look at the specific work being done in the delegates, only at the “shape” of the query.  There are cases where running in parallel may still be beneficial, even if the shape is one where it typically parallelizes poorly.  In these cases, you can override the default behavior by using the WithExecutionMode extension method.  This would be done like so: var reversed = collection .AsParallel() .WithExecutionMode(ParallelExecutionMode.ForceParallelism) .Select(i => i.PerformComputation()) .Reverse(); Here, the default behavior would be to not parallelize the query unless collection implemented IList<T>.  We can force this to run in parallel by adding the WithExecutionMode extension method in the method chain. Finally, PLINQ has the ability to configure how results are returned.  When a query is filtering or selecting an input collection, the results will need to be streamed back into a single IEnumerable<T> result.  For example, the method above returns a new, reversed collection.  In this case, the processing of the collection will be done in parallel, but the results need to be streamed back to the caller serially, so they can be enumerated on a single thread. This streaming introduces overhead.  IEnumerable<T> isn’t designed with thread safety in mind, so the system needs to handle merging the parallel processes back into a single stream, which introduces synchronization issues.  There are two extremes of how this could be accomplished, but both extremes have disadvantages. The system could watch each thread, and whenever a thread produces a result, take that result and send it back to the caller.  This would mean that the calling thread would have access to the data as soon as data is available, which is the benefit of this approach.  However, it also means that every item is introducing synchronization overhead, since each item needs to be merged individually. On the other extreme, the system could wait until all of the results from all of the threads were ready, then push all of the results back to the calling thread in one shot.  The advantage here is that the least amount of synchronization is added to the system, which means the query will, on a whole, run the fastest.  However, the calling thread will have to wait for all elements to be processed, so this could introduce a long delay between when a parallel query begins and when results are returned. The default behavior in PLINQ is actually between these two extremes.  By default, PLINQ maintains an internal buffer, and chooses an optimal buffer size to maintain.  Query results are accumulated into the buffer, then returned in the IEnumerable<T> result in chunks.  This provides reasonably fast access to the results, as well as good overall throughput, in most scenarios. However, if we know the nature of our algorithm, we may decide we would prefer one of the other extremes.  This can be done by using the WithMergeOptions extension method.  For example, if we know that our PerformComputation() routine is very slow, but also variable in runtime, we may want to retrieve results as they are available, with no bufferring.  This can be done by changing our above routine to: var reversed = collection .AsParallel() .WithExecutionMode(ParallelExecutionMode.ForceParallelism) .WithMergeOptions(ParallelMergeOptions.NotBuffered) .Select(i => i.PerformComputation()) .Reverse(); On the other hand, if are already on a background thread, and we want to allow the system to maximize its speed, we might want to allow the system to fully buffer the results: var reversed = collection .AsParallel() .WithExecutionMode(ParallelExecutionMode.ForceParallelism) .WithMergeOptions(ParallelMergeOptions.FullyBuffered) .Select(i => i.PerformComputation()) .Reverse(); Notice, also, that you can specify multiple configuration options in a parallel query.  By chaining these extension methods together, we generate a query that will always run in parallel, and will always complete before making the results available in our IEnumerable<T>.

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• Parallelism in .NET – Part 2, Simple Imperative Data Parallelism

  - by Reed

  In my discussion of Decomposition of the problem space, I mentioned that Data Decomposition is often the simplest abstraction to use when trying to parallelize a routine.  If a problem can be decomposed based off the data, we will often want to use what MSDN refers to as Data Parallelism as our strategy for implementing our routine.  The Task Parallel Library in .NET 4 makes implementing Data Parallelism, for most cases, very simple. Data Parallelism is the main technique we use to parallelize a routine which can be decomposed based off data.  Data Parallelism refers to taking a single collection of data, and having a single operation be performed concurrently on elements in the collection.  One side note here: Data Parallelism is also sometimes referred to as the Loop Parallelism Pattern or Loop-level Parallelism.  In general, for this series, I will try to use the terminology used in the MSDN Documentation for the Task Parallel Library.  This should make it easier to investigate these topics in more detail. Once we’ve determined we have a problem that, potentially, can be decomposed based on data, implementation using Data Parallelism in the TPL is quite simple.  Let’s take our example from the Data Decomposition discussion – a simple contrast stretching filter.  Here, we have a collection of data (pixels), and we need to run a simple operation on each element of the pixel.  Once we know the minimum and maximum values, we most likely would have some simple code like the following: for (int row=0; row < pixelData.GetUpperBound(0); ++row) { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This simple routine loops through a two dimensional array of pixelData, and calls the AdjustContrast routine on each pixel. As I mentioned, when you’re decomposing a problem space, most iteration statements are potentially candidates for data decomposition.  Here, we’re using two for loops – one looping through rows in the image, and a second nested loop iterating through the columns.  We then perform one, independent operation on each element based on those loop positions. This is a prime candidate – we have no shared data, no dependencies on anything but the pixel which we want to change.  Since we’re using a for loop, we can easily parallelize this using the Parallel.For method in the TPL: Parallel.For(0, pixelData.GetUpperBound(0), row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); Here, by simply changing our first for loop to a call to Parallel.For, we can parallelize this portion of our routine.  Parallel.For works, as do many methods in the TPL, by creating a delegate and using it as an argument to a method.  In this case, our for loop iteration block becomes a delegate creating via a lambda expression.  This lets you write code that, superficially, looks similar to the familiar for loop, but functions quite differently at runtime. We could easily do this to our second for loop as well, but that may not be a good idea.  There is a balance to be struck when writing parallel code.  We want to have enough work items to keep all of our processors busy, but the more we partition our data, the more overhead we introduce.  In this case, we have an image of data – most likely hundreds of pixels in both dimensions.  By just parallelizing our first loop, each row of pixels can be run as a single task.  With hundreds of rows of data, we are providing fine enough granularity to keep all of our processors busy. If we parallelize both loops, we’re potentially creating millions of independent tasks.  This introduces extra overhead with no extra gain, and will actually reduce our overall performance.  This leads to my first guideline when writing parallel code: Partition your problem into enough tasks to keep each processor busy throughout the operation, but not more than necessary to keep each processor busy. Also note that I parallelized the outer loop.  I could have just as easily partitioned the inner loop.  However, partitioning the inner loop would have led to many more discrete work items, each with a smaller amount of work (operate on one pixel instead of one row of pixels).  My second guideline when writing parallel code reflects this: Partition your problem in a way to place the most work possible into each task. This typically means, in practice, that you will want to parallelize the routine at the “highest” point possible in the routine, typically the outermost loop.  If you’re looking at parallelizing methods which call other methods, you’ll want to try to partition your work high up in the stack – as you get into lower level methods, the performance impact of parallelizing your routines may not overcome the overhead introduced. Parallel.For works great for situations where we know the number of elements we’re going to process in advance.  If we’re iterating through an IList<T> or an array, this is a typical approach.  However, there are other iteration statements common in C#.  In many situations, we’ll use foreach instead of a for loop.  This can be more understandable and easier to read, but also has the advantage of working with collections which only implement IEnumerable<T>, where we do not know the number of elements involved in advance. As an example, lets take the following situation.  Say we have a collection of Customers, and we want to iterate through each customer, check some information about the customer, and if a certain case is met, send an email to the customer and update our instance to reflect this change.  Normally, this might look something like: foreach(var customer in customers) { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } } Here, we’re doing a fair amount of work for each customer in our collection, but we don’t know how many customers exist.  If we assume that theStore.GetLastContact(customer) and theStore.EmailCustomer(customer) are both side-effect free, thread safe operations, we could parallelize this using Parallel.ForEach: Parallel.ForEach(customers, customer => { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } }); Just like Parallel.For, we rework our loop into a method call accepting a delegate created via a lambda expression.  This keeps our new code very similar to our original iteration statement, however, this will now execute in parallel.  The same guidelines apply with Parallel.ForEach as with Parallel.For. The other iteration statements, do and while, do not have direct equivalents in the Task Parallel Library.  These, however, are very easy to implement using Parallel.ForEach and the yield keyword. Most applications can benefit from implementing some form of Data Parallelism.  Iterating through collections and performing “work” is a very common pattern in nearly every application.  When the problem can be decomposed by data, we often can parallelize the workload by merely changing foreach statements to Parallel.ForEach method calls, and for loops to Parallel.For method calls.  Any time your program operates on a collection, and does a set of work on each item in the collection where that work is not dependent on other information, you very likely have an opportunity to parallelize your routine.

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• Parallelism in .NET – Part 4, Imperative Data Parallelism: Aggregation

  - by Reed

  In the article on simple data parallelism, I described how to perform an operation on an entire collection of elements in parallel.  Often, this is not adequate, as the parallel operation is going to be performing some form of aggregation. Simple examples of this might include taking the sum of the results of processing a function on each element in the collection, or finding the minimum of the collection given some criteria.  This can be done using the techniques described in simple data parallelism, however, special care needs to be taken into account to synchronize the shared data appropriately.  The Task Parallel Library has tools to assist in this synchronization. The main issue with aggregation when parallelizing a routine is that you need to handle synchronization of data.  Since multiple threads will need to write to a shared portion of data.  Suppose, for example, that we wanted to parallelize a simple loop that looked for the minimum value within a dataset: double min = double.MaxValue; foreach(var item in collection) { double value = item.PerformComputation(); min = System.Math.Min(min, value); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This seems like a good candidate for parallelization, but there is a problem here.  If we just wrap this into a call to Parallel.ForEach, we’ll introduce a critical race condition, and get the wrong answer.  Let’s look at what happens here: // Buggy code! Do not use! double min = double.MaxValue; Parallel.ForEach(collection, item => { double value = item.PerformComputation(); min = System.Math.Min(min, value); }); This code has a fatal flaw: min will be checked, then set, by multiple threads simultaneously.  Two threads may perform the check at the same time, and set the wrong value for min.  Say we get a value of 1 in thread 1, and a value of 2 in thread 2, and these two elements are the first two to run.  If both hit the min check line at the same time, both will determine that min should change, to 1 and 2 respectively.  If element 1 happens to set the variable first, then element 2 sets the min variable, we’ll detect a min value of 2 instead of 1.  This can lead to wrong answers. Unfortunately, fixing this, with the Parallel.ForEach call we’re using, would require adding locking.  We would need to rewrite this like: // Safe, but slow double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach(collection, item => { double value = item.PerformComputation(); lock(syncObject) min = System.Math.Min(min, value); }); This will potentially add a huge amount of overhead to our calculation.  Since we can potentially block while waiting on the lock for every single iteration, we will most likely slow this down to where it is actually quite a bit slower than our serial implementation.  The problem is the lock statement – any time you use lock(object), you’re almost assuring reduced performance in a parallel situation.  This leads to two observations I’ll make: When parallelizing a routine, try to avoid locks. That being said: Always add any and all required synchronization to avoid race conditions. These two observations tend to be opposing forces – we often need to synchronize our algorithms, but we also want to avoid the synchronization when possible.  Looking at our routine, there is no way to directly avoid this lock, since each element is potentially being run on a separate thread, and this lock is necessary in order for our routine to function correctly every time. However, this isn’t the only way to design this routine to implement this algorithm.  Realize that, although our collection may have thousands or even millions of elements, we have a limited number of Processing Elements (PE).  Processing Element is the standard term for a hardware element which can process and execute instructions.  This typically is a core in your processor, but many modern systems have multiple hardware execution threads per core.  The Task Parallel Library will not execute the work for each item in the collection as a separate work item. Instead, when Parallel.ForEach executes, it will partition the collection into larger “chunks” which get processed on different threads via the ThreadPool.  This helps reduce the threading overhead, and help the overall speed.  In general, the Parallel class will only use one thread per PE in the system. Given the fact that there are typically fewer threads than work items, we can rethink our algorithm design.  We can parallelize our algorithm more effectively by approaching it differently.  Because the basic aggregation we are doing here (Min) is communitive, we do not need to perform this in a given order.  We knew this to be true already – otherwise, we wouldn’t have been able to parallelize this routine in the first place.  With this in mind, we can treat each thread’s work independently, allowing each thread to serially process many elements with no locking, then, after all the threads are complete, “merge” together the results. This can be accomplished via a different set of overloads in the Parallel class: Parallel.ForEach<TSource,TLocal>.  The idea behind these overloads is to allow each thread to begin by initializing some local state (TLocal).  The thread will then process an entire set of items in the source collection, providing that state to the delegate which processes an individual item.  Finally, at the end, a separate delegate is run which allows you to handle merging that local state into your final results. To rewriting our routine using Parallel.ForEach<TSource,TLocal>, we need to provide three delegates instead of one.  The most basic version of this function is declared as: public static ParallelLoopResult ForEach<TSource, TLocal>( IEnumerable<TSource> source, Func<TLocal> localInit, Func<TSource, ParallelLoopState, TLocal, TLocal> body, Action<TLocal> localFinally ) The first delegate (the localInit argument) is defined as Func<TLocal>.  This delegate initializes our local state.  It should return some object we can use to track the results of a single thread’s operations. The second delegate (the body argument) is where our main processing occurs, although now, instead of being an Action<T>, we actually provide a Func<TSource, ParallelLoopState, TLocal, TLocal> delegate.  This delegate will receive three arguments: our original element from the collection (TSource), a ParallelLoopState which we can use for early termination, and the instance of our local state we created (TLocal).  It should do whatever processing you wish to occur per element, then return the value of the local state after processing is completed. The third delegate (the localFinally argument) is defined as Action<TLocal>.  This delegate is passed our local state after it’s been processed by all of the elements this thread will handle.  This is where you can merge your final results together.  This may require synchronization, but now, instead of synchronizing once per element (potentially millions of times), you’ll only have to synchronize once per thread, which is an ideal situation. Now that I’ve explained how this works, lets look at the code: // Safe, and fast! double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach( collection, // First, we provide a local state initialization delegate. () => double.MaxValue, // Next, we supply the body, which takes the original item, loop state, // and local state, and returns a new local state (item, loopState, localState) => { double value = item.PerformComputation(); return System.Math.Min(localState, value); }, // Finally, we provide an Action<TLocal>, to "merge" results together localState => { // This requires locking, but it's only once per used thread lock(syncObj) min = System.Math.Min(min, localState); } ); Although this is a bit more complicated than the previous version, it is now both thread-safe, and has minimal locking.  This same approach can be used by Parallel.For, although now, it’s Parallel.For<TLocal>.  When working with Parallel.For<TLocal>, you use the same triplet of delegates, with the same purpose and results. Also, many times, you can completely avoid locking by using a method of the Interlocked class to perform the final aggregation in an atomic operation.  The MSDN example demonstrating this same technique using Parallel.For uses the Interlocked class instead of a lock, since they are doing a sum operation on a long variable, which is possible via Interlocked.Add. By taking advantage of local state, we can use the Parallel class methods to parallelize algorithms such as aggregation, which, at first, may seem like poor candidates for parallelization.  Doing so requires careful consideration, and often requires a slight redesign of the algorithm, but the performance gains can be significant if handled in a way to avoid excessive synchronization.

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• Parallelism in .NET – Part 11, Divide and Conquer via Parallel.Invoke

  - by Reed

  Many algorithms are easily written to work via recursion.  For example, most data-oriented tasks where a tree of data must be processed are much more easily handled by starting at the root, and recursively “walking” the tree.  Some algorithms work this way on flat data structures, such as arrays, as well.  This is a form of divide and conquer: an algorithm design which is based around breaking up a set of work recursively, “dividing” the total work in each recursive step, and “conquering” the work when the remaining work is small enough to be solved easily. Recursive algorithms, especially ones based on a form of divide and conquer, are often a very good candidate for parallelization. This is apparent from a common sense standpoint.  Since we’re dividing up the total work in the algorithm, we have an obvious, built-in partitioning scheme.  Once partitioned, the data can be worked upon independently, so there is good, clean isolation of data. Implementing this type of algorithm is fairly simple.  The Parallel class in .NET 4 includes a method suited for this type of operation: Parallel.Invoke.  This method works by taking any number of delegates defined as an Action, and operating them all in parallel.  The method returns when every delegate has completed: Parallel.Invoke( () => { Console.WriteLine("Action 1 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); }, () => { Console.WriteLine("Action 2 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); }, () => { Console.WriteLine("Action 3 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); } ); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Running this simple example demonstrates the ease of using this method.  For example, on my system, I get three separate thread IDs when running the above code.  By allowing any number of delegates to be executed directly, concurrently, the Parallel.Invoke method provides us an easy way to parallelize any algorithm based on divide and conquer.  We can divide our work in each step, and execute each task in parallel, recursively. For example, suppose we wanted to implement our own quicksort routine.  The quicksort algorithm can be designed based on divide and conquer.  In each iteration, we pick a pivot point, and use that to partition the total array.  We swap the elements around the pivot, then recursively sort the lists on each side of the pivot.  For example, let’s look at this simple, sequential implementation of quicksort: public static void QuickSort<T>(T[] array) where T : IComparable<T> { QuickSortInternal(array, 0, array.Length - 1); } private static void QuickSortInternal<T>(T[] array, int left, int right) where T : IComparable<T> { if (left >= right) { return; } SwapElements(array, left, (left + right) / 2); int last = left; for (int current = left + 1; current <= right; ++current) { if (array[current].CompareTo(array[left]) < 0) { ++last; SwapElements(array, last, current); } } SwapElements(array, left, last); QuickSortInternal(array, left, last - 1); QuickSortInternal(array, last + 1, right); } static void SwapElements<T>(T[] array, int i, int j) { T temp = array[i]; array[i] = array[j]; array[j] = temp; } Here, we implement the quicksort algorithm in a very common, divide and conquer approach.  Running this against the built-in Array.Sort routine shows that we get the exact same answers (although the framework’s sort routine is slightly faster).  On my system, for example, I can use framework’s sort to sort ten million random doubles in about 7.3s, and this implementation takes about 9.3s on average. Looking at this routine, though, there is a clear opportunity to parallelize.  At the end of QuickSortInternal, we recursively call into QuickSortInternal with each partition of the array after the pivot is chosen.  This can be rewritten to use Parallel.Invoke by simply changing it to: // Code above is unchanged... SwapElements(array, left, last); Parallel.Invoke( () => QuickSortInternal(array, left, last - 1), () => QuickSortInternal(array, last + 1, right) ); } This routine will now run in parallel.  When executing, we now see the CPU usage across all cores spike while it executes.  However, there is a significant problem here – by parallelizing this routine, we took it from an execution time of 9.3s to an execution time of approximately 14 seconds!  We’re using more resources as seen in the CPU usage, but the overall result is a dramatic slowdown in overall processing time. This occurs because parallelization adds overhead.  Each time we split this array, we spawn two new tasks to parallelize this algorithm!  This is far, far too many tasks for our cores to operate upon at a single time.  In effect, we’re “over-parallelizing” this routine.  This is a common problem when working with divide and conquer algorithms, and leads to an important observation: When parallelizing a recursive routine, take special care not to add more tasks than necessary to fully utilize your system. This can be done with a few different approaches, in this case.  Typically, the way to handle this is to stop parallelizing the routine at a certain point, and revert back to the serial approach.  Since the first few recursions will all still be parallelized, our “deeper” recursive tasks will be running in parallel, and can take full advantage of the machine.  This also dramatically reduces the overhead added by parallelizing, since we’re only adding overhead for the first few recursive calls.  There are two basic approaches we can take here.  The first approach would be to look at the total work size, and if it’s smaller than a specific threshold, revert to our serial implementation.  In this case, we could just check right-left, and if it’s under a threshold, call the methods directly instead of using Parallel.Invoke. The second approach is to track how “deep” in the “tree” we are currently at, and if we are below some number of levels, stop parallelizing.  This approach is a more general-purpose approach, since it works on routines which parse trees as well as routines working off of a single array, but may not work as well if a poor partitioning strategy is chosen or the tree is not balanced evenly. This can be written very easily.  If we pass a maxDepth parameter into our internal routine, we can restrict the amount of times we parallelize by changing the recursive call to: // Code above is unchanged... SwapElements(array, left, last); if (maxDepth < 1) { QuickSortInternal(array, left, last - 1, maxDepth); QuickSortInternal(array, last + 1, right, maxDepth); } else { --maxDepth; Parallel.Invoke( () => QuickSortInternal(array, left, last - 1, maxDepth), () => QuickSortInternal(array, last + 1, right, maxDepth)); } We no longer allow this to parallelize indefinitely – only to a specific depth, at which time we revert to a serial implementation.  By starting the routine with a maxDepth equal to Environment.ProcessorCount, we can restrict the total amount of parallel operations significantly, but still provide adequate work for each processing core. With this final change, my timings are much better.  On average, I get the following timings: Framework via Array.Sort: 7.3 seconds Serial Quicksort Implementation: 9.3 seconds Naive Parallel Implementation: 14 seconds Parallel Implementation Restricting Depth: 4.7 seconds Finally, we are now faster than the framework’s Array.Sort implementation.

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• Asp.Net MVC2 RenderAction changes page mime type?

  - by Gabe Moothart

  It appears that calling Html.RenderAction in Asp.Net MVC2 apps can alter the mime type of the page if the child action's type is different than the parent action's. The code below (testing in MVC2 RTM), which seems sensible to me, will return a result of type application/json when calling Home/Index. Instead of dispylaying the page, the browser will barf and ask you if you want to download it. My question: Am I missing something? Is this a bug? If so, what's the best workaround? controller: public class HomeController : Controller { public ActionResult Index() { ViewData[ "Message" ] = "Welcome to ASP.NET MVC!"; return View(); } [ChildActionOnly] public JsonResult States() { string[] states = new[] { "AK", "AL", "AR", "AZ", }; return Json(states, JsonRequestBehavior.AllowGet); } } view: <h2><%= Html.Encode(ViewData["Message"]) %></h2> <p> To learn more about ASP.NET MVC visit <a href="http://asp.net/mvc" title="ASP.NET MVC Website">http://asp.net/mvc</a>. </p> <script> var states = <% Html.RenderAction("States"); %>; </script>

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• jQuery Templates in ASP.NET - Blogs Series

  - by hajan

  In the previous days, I wrote several blog posts related to the great jQuery Templates plugin showing various examples that might help you get started working with the plugin in ASP.NET and VS.NET environment. Here is the list of all five blogs: Introduction to jQuery Templates jQuery Templates - tmpl(), template() and tmplItem() jQuery Templates - {Supported Tags} jQuery Templates with ASP.NET MVC jQuery Templates - XHTML Validation Thank you for reading and wait for my next blogs! All the best, Hajan

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• ASP.NET MVC AND TOOLBOX

  - by imran_ku07

     Introduction :           ASP.NET MVC popularity is not hidden from the today's world of web applications. One of the great thing in ASP.NET is the separation of concerns, in which presentation views are separate from the business or modal layer. In these views ASP.NET MVC provides some very good controls which generate commonly used HTML markup fragments using a shorter syntax. These presentation views are familiar to web forms developers. But a pain for developers to use these controls is that they need to type these helpers controls every time when they need to use a control, because they are more familiar to drag and drop controls from ToolBox. So in this article i will use a cool feature of Visual Studio that allows you to add these controls in ToolBox once and then, when needed, just drag and drop controls from ToolBox, very similar like in web forms.   Description :            Visual Studio ToolBox is rich enough that allows you to store code and HTML snippets in ToolBox. All you need is select the HTML Helper and then simply drag and drop into Toolbox. Repeat this Procedure for every HTML Helper in ASP.NET MVC.             When you need to use a HTML Helper, you can drag and drop it from ToolBox and become happy with drag and drop programming. Summary :              In this article you see that how Visual Studio helps you to drag and drop HTML snippets from Design view to toolbox. This is one of the coolest features in Visual Studio.

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• Dynamic ASP.NET controls using Infragistics

  - by Emil D

  So, in my asp.net webapp I need to dynamically load a custom control, based on the selected value of a dropdown list.That seems to work at first glance, but for some reason all infragistics controls that I have in my custom control appear, but won't work.I get a "Can't init [controlname]" warning in my browser.If I declare my custom control statically, this problem doesn't apprear Here's my code: Markup: <%@ Control Language="C#" AutoEventWireup="true" CodeBehind="GenericReportGUI.ascx.cs" Inherits="GenericReportGUI" %> <%@ Register assembly="Infragistics35.WebUI.Misc.v8.3, Version=8.3.20083.1009,Culture=neutral, PublicKeyToken=7dd5c3163f2cd0cb" namespace="Infragistics.WebUI.Misc" tagprefix="igmisc" %> <asp:UpdatePanel ID="myUpdatePanel" runat="server" UpdateMode="Conditional"> <ContentTemplate> <igmisc:WebPanel ID="WebPanel1" runat="server"> <Template> <div> <asp:PlaceHolder ID="Placeholder" runat="server"> </asp:PlaceHolder> </div> </Template> </igmisc:WebPanel> </ContentTemplate> </asp:UpdatePanel> Code-behind: public partial class GenericReportGUI : System.Web.UI.UserControl { protected void Page_Load(object sender, EventArgs e) { } protected override void OnPreRender( EventArgs e ) { base.OnPreRender(e); loadCustomControl(); } protected void loadCustomControl() { Placeholder.Controls.Clear(); string controlPath = getPath(); //getPath() returns the path to the .ascx file we need to load, based on the selected value of a dropdownlist try { Control newControl = LoadControl( controlPath ); Placeholder.Controls.Add( newControl ); } catch { //if the desired control cannot be loaded, display nothing } myUpdatePanel.Update();//Update the UpdatePanel that contains the custom control } } I'm a total noob when it comes to asp.net, so any help with this issue would be greatly appreciated.

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• Why updatepanel triggers another updatepanel?

  - by HasanGursoy

  I have two update panels at my ajax page. This is first time I'm using updatepanel and I don't know what is wrong. I think only btnFilter's Click event must trigger the second update panel's content but changing combo values (which also hides/unhides btnFilter button) makes second updatepanel change content (at least I see transferred data with firebug & second updatepanel blinks sometimes). Online here. <asp:UpdatePanel ID="upComparison" runat="server"> <ContentTemplate> Brand: <asp:DropDownList ID="ddlBrands" runat="server" AutoPostBack="true" OnSelectedIndexChanged="ddlBrands_SelectedIndexChanged" AppendDataBoundItems="true"> <asp:ListItem Value="" Text="Please select a brand..." /> </asp:DropDownList> <asp:Panel ID="pModels" runat="server" Visible="false"> Model: <asp:DropDownList ID="ddlModels" runat="server" AutoPostBack="true" OnSelectedIndexChanged="ddlModels_SelectedIndexChanged" /> </asp:Panel> <asp:Panel ID="pButton" runat="server" Visible="false"> <asp:UpdateProgress ID="upMain" runat="server" DisplayAfter="100"> <ProgressTemplate><img src="/Assets/Images/loader.gif" /> </ProgressTemplate> </asp:UpdateProgress> <asp:Button ID="btnFilter" runat="server" Text="Filter" OnClick="btnFilter_Click" /> </asp:Panel> </ContentTemplate> </asp:UpdatePanel> <asp:UpdatePanel ID="upList" runat="server"> <ContentTemplate> <asp:Repeater ID="rProducts" runat="server"> <ItemTemplate>some code here</ItemTemplate> </asp:Repeater> </ContentTemplate> <Triggers> <asp:AsyncPostBackTrigger ControlID="btnFilter" EventName="Click" /> </Triggers> </asp:UpdatePanel>

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• Introduction to Developing Mobile Web Applications in ASP.NET MVC 4

  - by bipinjoshi

  As mobile devices are becoming more and more popular, web developers are also finding it necessary to target mobile devices while building their web sites. While developing a mobile web site is challenging due to the complexity in terms of device detection, screen size and browser support, ASP.NET MVC4 makes a developer's life easy by providing easy ways to develop mobile web applications. To that end this article introduces you to the basics of developing web sites using ASP.NET MVC4 targeted at mobile devices.http://www.binaryintellect.net/articles/7a33d6fa-1dec-49fe-9487-30675d0a09f0.aspx

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• AJAX 4 no ASP.NET 4 Web Application

  - by renatohaddad

  Andei fazendo uns testes no AJAX Control Toolkit 4 que deverá ser usado com o ASP.NET 4 no Visual Studio .NET 2010 e confesso que gostei muito. O link para download é http://www.asp.net/ajaxlibrary/act.ashx e todas as instruções constam no site. Notei que há diversos controles novos e um que me chamou a atenção foi o de Upload assíncrono para controlar os uploads de arquivos para o server. Vale a pena estudar um pouco estas novidades. Para quem já usava o AJAX no ASP.NET 3.5, a idéia do Toolkit é igual, exceto a adição de novos controles. Com o AJAX vc pode mudar todo o comportamento da sua aplicação WEB, requisições no server passam a ser menos frequentes, o layout ajuda e muito com os controles do AJAX. Nativamente no VS 2010 já há o AJAX que a MS suporta nativamente (ScriptManager, UpdatePanel, UpdateProgress, etc), mas vale a pena implementar alguns controles do Toolkit. Bons estudos!

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• Is ASP.NET MVC destined to replace Webforms?

  - by johnny

  I found these questions, but a couple of them were a little old: http://stackoverflow.com/questions/191556/should-i-pursue-asp-net-webforms-or-asp-net-mvc http://stackoverflow.com/questions/88787/do-you-think-asp-net-mvc-will-compete-with-asp-net-webforms http://stackoverflow.com/questions/722637/asp-net-mvc-asp-net-webforms-why I do not believe these are duplicates and might be old enough that new light can be shed. If not please close this. I know that no one framework or language is necessarily the only tool for every job. But, do you see MVC eclipsing webforms or webforms going lower on the priority list for Microsoft? They will have to keep webforms for a long time because so many have invested in it, but they don't have to keep adding new functionality for it. I don't know if this is a good example, but it reminds me of web parts. I never saw much improvement in it from Microsoft. It works and I thought it was great until I started to really try and get a lot out of it. Then from what I could see it just wasn't being pursued by Microsoft that much, though it stayed in Visual Studio. Maybe that's a bad example; just what I remembered. EDIT: Also, if anyone has any statements from Microsoft on this subject it is appreciated. No offense to anyone. I was only hoping for something official.

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• Lazy Loading,Eager Loading,Explicit Loading in Entity Framework 4

  - by nikolaosk

  This is going to be the ninth post of a series of posts regarding ASP.Net and the Entity Framework and how we can use Entity Framework to access our datastore. You can find the first one here , the second one here , the third one here , the fourth one here , the fifth one here ,the sixth one here ,the seventh one here and the eighth one here . I have a post regarding ASP.Net and EntityDataSource . You can read it here .I have 3 more posts on Profiling Entity Framework applications. You can have a...(read more)

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• Cannot create instance of abstract class

  - by SmartestVEGA

  I am trying to compile the following code and i am getting the error: Cannot create instance of abstract class . Please help m_objExcel = new Excel.Application(); m_objBooks = (Excel.Workbooks)m_objExcel.Workbooks; m_objBook = (Excel._Workbook)(m_objBooks.Add(m_objOpt)); m_objSheets = (Excel.Sheets)m_objBook.Worksheets; m_objSheet = (Excel._Worksheet)(m_objSheets.get_Item(1)); // Create an array for the headers and add it to cells A1:C1. object[] objHeaders = {"Order ID", "Amount", "Tax"}; m_objRange = m_objSheet.get_Range("A1", "C1"); m_objRange.Value = objHeaders; m_objFont = m_objRange.Font; m_objFont.Bold=true; // Create an array with 3 columns and 100 rows and add it to // the worksheet starting at cell A2. object[,] objData = new Object[100,3]; Random rdm = new Random((int)DateTime.Now.Ticks); double nOrderAmt, nTax; for(int r=0;r<100;r++) { objData[r,0] = "ORD" + r.ToString("0000"); nOrderAmt = rdm.Next(1000); objData[r,1] = nOrderAmt.ToString("c"); nTax = nOrderAmt*0.07; objData[r,2] = nTax.ToString("c"); } m_objRange = m_objSheet.get_Range("A2", m_objOpt); m_objRange = m_objRange.get_Resize(100,3); m_objRange.Value = objData; // Save the Workbook and quit Excel. m_objBook.SaveAs(m_strSampleFolder + "Book2.xls", m_objOpt, m_objOpt, m_objOpt, m_objOpt, m_objOpt, Excel.XlSaveAsAccessMode.xlNoChange, m_objOpt, m_objOpt, m_objOpt, m_objOpt); m_objBook.Close(false, m_objOpt, m_objOpt); m_objExcel.Quit();

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• Specifying ASP.NET MVC attributes for auto-generated data models

  - by Lyubomyr Shaydariv

  Hello to everyone. I'm very new to ASP.NET MVC (as well as ASP.NET in general), and going to gain some knowledge for this technology, so I'm sorry I can ask some trivial questions. I have installed ASP.NET MVC 3 RC1 and I'm trying to do the following. Let's consider that I have a model that's completely auto-generated from a table using the "LINQ to SQL Classes" template in VS2010. The template generates 3 files (two .cs files and one .layout file respectively), and the generated partial class is expected to be used as an MVC model. Let's also consider, a single DB column, that's mapped into the model, may look like this: [global::System.Data.Linq.Mapping.ColumnAttribute(Storage = "_Name", DbType = "VarChar(128)")] public string Name { get { return this._Name; } set { if ( (this._Name != value) ) { // ... generated stuff goes here } } } The ASP.NET MVC engine also provides a beautiful declarative way to specify some additional stuff, like RequiredAttribute, DisplayNameAttribute and other nice attributes. But since the mapped model is a purely auto-genereated model, I've realized that I should not change the model manually, and specify the fields like: [Required] [DisplayName("Project name")] [StringLength(128)] [global::System.Data.Linq.Mapping.ColumnAttribute(Storage = "_Name", DbType = "VarChar(128)")] public string Name { ... though this approach works perfectly... until I change the model in the DBML-designer removing the ASP.NET MVC attributes automatically. So, how do I specify ASP.NET MVC attributes for the DBML models and their fields safely? Thanks in advance, and Merry Christmas.

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• When the property get and set method has been called?

  - by SmartestVEGA

  i have the following property declaration Public Property IsAreaSelected() As Integer Get Return If(ViewState("IsAreaSelected") Is Nothing, 0, Cint(ViewState("IsAreaSelected"))) End Get Set(ByVal value As Integer) ViewState("IsAreaSelected") = value End Set End Property i want to know when this set and get method will be called ? will it be called when i execute IsAreaSelected() =0 or is there anything like IsAreaSelected().get() or IsAreaSelected().set() ??

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• How to disable an ASP.NET linkbutton when clicked

  - by Jeff Widmer

  Scenario: User clicks a LinkButton in your ASP.NET page and you want to disable it immediately using javascript so that the user cannot accidentally click it again.  I wrote about disabling a regular submit button here: How to disable an ASP.NET button when clicked.  But the method described in the other blog post does not work for disabling a LinkButton.  This is because the Post Back Event Reference is called using a snippet of javascript from within the href of the anchor tag: <a id="MyContrl_MyButton" href="javascript:__doPostBack('MyContrl$MyButton','')">My Button</a> If you try to add an onclick event to disable the button, even though the button will become disabled, the href will still be allowed to be clicked multiple times (causing duplicate form submissions).  To get around this, in addition to disabling the button in the onclick javascript, you can set the href to “#” to prevent it from doing anything on the page.  You can add this to the LinkButton from your code behind like this: MyButton.Attributes.Add("onclick", "this.href='#';this.disabled=true;" + Page.ClientScript.GetPostBackEventReference(MyButton, "").ToString()); This code adds javascript to set the href to “#” and then disable the button in the onclick event of the LinkButton by appending to the Attributes collection of the ASP.NET LinkButton control.  Then the Post Back Event Reference for the button is called right after disabling the button.  Make sure you add the Post Back Event Reference to the onclick because now that you are changing the anchor href, the button still needs to perform the original postback. With the code above now the button onclick event will look something like this: onclick="this.href='#';this.disabled=true;__doPostBack('MyContrl$MyButton','');" The anchor href is set to “#”, the linkbutton is disabled, AND then the button post back method is called. Technorati Tags: ASP.NET LinkButton

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• How to handle concurrency in Entity Framework

  - by nikolaosk

  This is going to be the fifth post of a series of posts regarding ASP.Net and the Entity Framework and how we can use Entity Framework to access our datastore. You can find the first one here , the second one here and the third one here . You can read the fourth one here . I have a post regarding ASP.Net and EntityDataSource. You can read it here .I have 3 more posts on Profiling Entity Framework applications. You can have a look at them here , here and here . In this post I will be looking into...(read more)

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