Search Results

Search found 52776 results on 2112 pages for 'northwest arkansas net u'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 21/2112 | < Previous Page | 17 18 19 20 21 22 23 24 25 26 27 28  | Next Page >

  • ASP.NET custom templates, still ASP.NET controls possible?

    - by Sha Le
    Hello: we currently do not use asp.net controls (no web forms). The way we do is: 1 Read HTML file from disk 2 lookup database, parse tags and populate data finally, Response.Write(page.ToString()); here there is no possibility of using asp.net controls. What I am wondering is, if we use asp.net controls in those HTML files, is there way to process them during step 2? Thanks and appreciate your response.

    Read the article

  • Using ExtJS with ASP.NET, Webforms or MVC?

    - by TigrouMeow
    Hello, For a scenario using 0 ASP.NET controls at all but rather an 100% extJS interface, what would be the advantages of using ASP.NET MVC or ASP.NET WebForms? And the disadvantages? Is there a OBVIOUS way to do it properly? I would love to have feedback's on your experiences. Thank you!

    Read the article

  • Recommend ASP.NET 3.5 SP1 Hosting Providers

    - by tyndall
    Would like to see a list of affordable ASP.NET 3.5 SP1 Hosting providers build up. Along with your review of the service, lacking features, special features, etc... Discount ASP.NET MochaHost At last update MochaHost does not offer SP1  they now offer SP1 CrystalTech Gearhost HostMySite please add more update: Anybody see a better deal for shared hosting ASP.NET than ASP.NETpro From GearHost? I would like to see more SQL storage, but I need keep the multiple domain capabilities. For about the same price.

    Read the article

  • Linq To Sql or classic ADO.net?

    - by Spyros
    I am asking my self many times before start writting a new app or data access library , should I use LinqToSql or classic ADO.net , I have used both and the development time I spend on building an app with Linq To sql is like the 1/3 compared to ADO.net. The only think I like using Linq to sql is that I dont have to design the domain objects Linq does that for me and saves me from spend my time on boring things :P But is Linq to sql suitable for large scale projects , is there an overhead that we can avoid when using ADO.net ?

    Read the article

  • asp.net application install folder

    - by Maximilian Csuk
    Disclaimer: this is not a question about how to install asp.net or an application using it! Hi! I am pretty sure many of you have once installed some kind of forum, blog or CMS (mostly PHP powered applications). All of these contain a folder mostly named "install" where (after you copied the files to the webserver) point your browser to to complete the installation by entering for example database information (servername, username, password, ...). After that, most applications suggest that you delete this folder or at least change the permissions so nobody from the outside can access it anymore. Now to my question: how would you go about that in the asp.net world? I don't really like the "install folder"-approach and I thought there might be a different mechanism for .net/IIS. The person installing my application should be able to enter his database information as painless as possible, which should ultimatively be stored in the web.config file. If it makes a difference, I am using asp.net MVC. Thanks for your help!

    Read the article

  • Membership with Mysql, EF 1 and ASP.NET 3.5

    - by sanfra1983
    Hi, I created a web application with asp.net 3.5 and ado.net entity framework WebForms 1, but have not yet succeeded in creating a memebrship and roles. When I go on ASP.NET Configuration and click the Security Tab I get the following error: Keyword not supported. Parameter name: metadata Someone has already created an application with these same features to help me understand where is the problem? P.S.: I'm going crazy Thanks to all

    Read the article

  • Using ASP.NET C# and Javascript

    - by ctck
    I'm looking for the most efficient / standardized way of passing data between client javascript code and C# code behind in an ASP.NET application. Currently ive been using the following methods to achieve this but they all feel a bit like a fudge. The way i pass data from javascript to the C# code behind is by setting hidden asp variables and triggering a postback <asp:HiddenField ID="RandomList" runat="server" /> function SetDataField(data) { document.getElementById('<%=RandomList.ClientID%>').value = data; } Then in C# code i collect the list protected void GetData(object sender, EventArgs e) { var _list = RandomList.value; } Going back the other way i often use either scriptmanager to register a function and pass it data during Page_Load: ScriptManager.RegisterStartupScript(this.GetType(), "Set","get("Test();",true); or i add attributes to controls before a post back or during Initialization / pre rendering stages: Btn.Attributes.Add("onclick", "DisplayMessage("Hello");"); These methods have served me well and do the job. However they just dont feel complete. Is there a more standardized way of passing data between client side markup / javascript and backend code. Ive seen some posts like this one: Injecting JavaScrip : StackOverflow that describe HtmlElement class. Is this something is should look into? Thanks everyone for your time.

    Read the article

  • ASP.NET ViewState Tips and Tricks #2

    - by João Angelo
    If you need to store complex types in ViewState DO implement IStateManager to control view state persistence and reduce its size. By default a serializable object will be fully stored in view state using BinaryFormatter. A quick comparison for a complex type with two integers and one string property produces the following results measured using ASP.NET tracing: BinaryFormatter: 328 bytes in view state IStateManager: 28 bytes in view state BinaryFormatter sample code: // DO NOT [Serializable] public class Info { public int Id { get; set; } public string Name { get; set; } public int Age { get; set; } } public class ExampleControl : WebControl { protected override void OnLoad(EventArgs e) { base.OnLoad(e); if (!this.Page.IsPostBack) { this.User = new Info { Id = 1, Name = "John Doe", Age = 27 }; } } public Info User { get { object o = this.ViewState["Example_User"]; if (o == null) return null; return (Info)o; } set { this.ViewState["Example_User"] = value; } } } IStateManager sample code: // DO public class Info : IStateManager { public int Id { get; set; } public string Name { get; set; } public int Age { get; set; } private bool isTrackingViewState; bool IStateManager.IsTrackingViewState { get { return this.isTrackingViewState; } } void IStateManager.LoadViewState(object state) { var triplet = (Triplet)state; this.Id = (int)triplet.First; this.Name = (string)triplet.Second; this.Age = (int)triplet.Third; } object IStateManager.SaveViewState() { return new Triplet(this.Id, this.Name, this.Age); } void IStateManager.TrackViewState() { this.isTrackingViewState = true; } } public class ExampleControl : WebControl { protected override void OnLoad(EventArgs e) { base.OnLoad(e); if (!this.Page.IsPostBack) { this.User = new Info { Id = 1, Name = "John Doe", Age = 27 }; } } public Info User { get; set; } protected override object SaveViewState() { return new Pair( ((IStateManager)this.User).SaveViewState(), base.SaveViewState()); } protected override void LoadViewState(object savedState) { if (savedState != null) { var pair = (Pair)savedState; this.User = new Info(); ((IStateManager)this.User).LoadViewState(pair.First); base.LoadViewState(pair.Second); } } }

    Read the article

  • 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

    Read the article

  • Adding page title to each page while creating a PDF file using itextsharp in VB.NET

    - by Snowy
    I have recently started using itextsharp and gradually learning it. So far I created a PDF file and it seems great. I have added a table and some subtables as the first table cells to hold data. It is done using two for loops. The first one loops through all data and the second one is each individual data displayed in columns. The html outcome looks like the following: <table> <tr> <td>Page title in center</td> </tr> <tr> <td> <table> <tr> <td>FirstPersonName</td> <td>Rank1</td> <td>info1a</td> <td>infob</td> <td>infoc</td> </tr> </table> </td> <td> <table> <tr> <td>SecondPersonName</td> <td>Rank2</td> <td>info1a</td> <td>infob</td> <td>infoc</td> <td>infod</td> <td>infoe</td> </tr> </table> </td> <td> <table> <tr> <td>ThirdPersonName</td> <td>Rank2</td> <td>info1a</td> <td>infob</td> <td>infoc</td> <td>infod</td> <td>infoe</td> <td>infof</td> <td>infog</td> </tr> </table> </td> </tr> </table> For page headings, I added a cell at the top before any other cells. I need to add this heading to all pages. Depending on the size of data, some pages have two rows and some pages have three rows of data. So I can not tell exactly when the new page starts to add the heading/title. My question is how to add the heading/title to all pages. I use VB.net. I searched for answer online and had no success. Your help would be greatly appreciated.

    Read the article

  • 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.

    Read the article

  • Parallelism in .NET – Part 16, Creating Tasks via a TaskFactory

    - by Reed
    The Task class in the Task Parallel Library supplies a large set of features.  However, when creating the task, and assigning it to a TaskScheduler, and starting the Task, there are quite a few steps involved.  This gets even more cumbersome when multiple tasks are involved.  Each task must be constructed, duplicating any options required, then started individually, potentially on a specific scheduler.  At first glance, this makes the new Task class seem like more work than ThreadPool.QueueUserWorkItem in .NET 3.5. In order to simplify this process, and make Tasks simple to use in simple cases, without sacrificing their power and flexibility, the Task Parallel Library added a new class: TaskFactory. The TaskFactory class is intended to “Provide support for creating and scheduling Task objects.”  Its entire purpose is to simplify development when working with Task instances.  The Task class provides access to the default TaskFactory via the Task.Factory static property.  By default, TaskFactory uses the default TaskScheduler to schedule tasks on a ThreadPool thread.  By using Task.Factory, we can automatically create and start a task in a single “fire and forget” manner, similar to how we did with ThreadPool.QueueUserWorkItem: Task.Factory.StartNew(() => this.ExecuteBackgroundWork(myData) ); .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 provides us with the same level of simplicity we had with ThreadPool.QueueUserWorkItem, but even more power.  For example, we can now easily wait on the task: // Start our task on a background thread var task = Task.Factory.StartNew(() => this.ExecuteBackgroundWork(myData) ); // Do other work on the main thread, // while the task above executes in the background this.ExecuteWorkSynchronously(); // Wait for the background task to finish task.Wait(); TaskFactory simplifies creation and startup of simple background tasks dramatically. In addition to using the default TaskFactory, it’s often useful to construct a custom TaskFactory.  The TaskFactory class includes an entire set of constructors which allow you to specify the default configuration for every Task instance created by that factory.  This is particularly useful when using a custom TaskScheduler.  For example, look at the sample code for starting a task on the UI thread in Part 15: // Given the following, constructed on the UI thread // TaskScheduler uiScheduler = TaskScheduler.FromCurrentSynchronizationContext(); // When inside a background task, we can do string status = GetUpdatedStatus(); (new Task(() => { statusLabel.Text = status; })) .Start(uiScheduler); This is actually quite a bit more complicated than necessary.  When we create the uiScheduler instance, we can use that to construct a TaskFactory that will automatically schedule tasks on the UI thread.  To do that, we’d create the following on our main thread, prior to constructing our background tasks: // Construct a task scheduler from the current SynchronizationContext (UI thread) var uiScheduler = TaskScheduler.FromCurrentSynchronizationContext(); // Construct a new TaskFactory using our UI scheduler var uiTaskFactory = new TaskFactory(uiScheduler); If we do this, when we’re on a background thread, we can use this new TaskFactory to marshal a Task back onto the UI thread.  Our previous code simplifies to: // When inside a background task, we can do string status = GetUpdatedStatus(); // Update our UI uiTaskFactory.StartNew( () => statusLabel.Text = status); Notice how much simpler this becomes!  By taking advantage of the convenience provided by a custom TaskFactory, we can now marshal to set data on the UI thread in a single, clear line of code!

    Read the article

  • Parallelism in .NET – Part 8, PLINQ’s ForAll Method

    - by Reed
    Parallel LINQ extends LINQ to Objects, and is typically very similar.  However, as I previously discussed, there are some differences.  Although the standard way to handle simple Data Parellelism is via Parallel.ForEach, it’s possible to do the same thing via PLINQ. PLINQ adds a new method unavailable in standard LINQ which provides new functionality… LINQ is designed to provide a much simpler way of handling querying, including filtering, ordering, grouping, and many other benefits.  Reading the description in LINQ to Objects on MSDN, it becomes clear that the thinking behind LINQ deals with retrieval of data.  LINQ works by adding a functional programming style on top of .NET, allowing us to express filters in terms of predicate functions, for example. PLINQ is, generally, very similar.  Typically, when using PLINQ, we write declarative statements to filter a dataset or perform an aggregation.  However, PLINQ adds one new method, which provides a very different purpose: ForAll. The ForAll method is defined on ParallelEnumerable, and will work upon any ParallelQuery<T>.  Unlike the sequence operators in LINQ and PLINQ, ForAll is intended to cause side effects.  It does not filter a collection, but rather invokes an action on each element of the collection. At first glance, this seems like a bad idea.  For example, Eric Lippert clearly explained two philosophical objections to providing an IEnumerable<T>.ForEach extension method, one of which still applies when parallelized.  The sole purpose of this method is to cause side effects, and as such, I agree that the ForAll method “violates the functional programming principles that all the other sequence operators are based upon”, in exactly the same manner an IEnumerable<T>.ForEach extension method would violate these principles.  Eric Lippert’s second reason for disliking a ForEach extension method does not necessarily apply to ForAll – replacing ForAll with a call to Parallel.ForEach has the same closure semantics, so there is no loss there. Although ForAll may have philosophical issues, there is a pragmatic reason to include this method.  Without ForAll, we would take a fairly serious performance hit in many situations.  Often, we need to perform some filtering or grouping, then perform an action using the results of our filter.  Using a standard foreach statement to perform our action would avoid this philosophical issue: // Filter our collection var filteredItems = collection.AsParallel().Where( i => i.SomePredicate() ); // Now perform an action foreach (var item in filteredItems) { // These will now run serially item.DoSomething(); } .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 would cause a loss in performance, since we lose any parallelism in place, and cause all of our actions to be run serially. We could easily use a Parallel.ForEach instead, which adds parallelism to the actions: // Filter our collection var filteredItems = collection.AsParallel().Where( i => i.SomePredicate() ); // Now perform an action once the filter completes Parallel.ForEach(filteredItems, item => { // These will now run in parallel item.DoSomething(); }); This is a noticeable improvement, since both our filtering and our actions run parallelized.  However, there is still a large bottleneck in place here.  The problem lies with my comment “perform an action once the filter completes”.  Here, we’re parallelizing the filter, then collecting all of the results, blocking until the filter completes.  Once the filtering of every element is completed, we then repartition the results of the filter, reschedule into multiple threads, and perform the action on each element.  By moving this into two separate statements, we potentially double our parallelization overhead, since we’re forcing the work to be partitioned and scheduled twice as many times. This is where the pragmatism comes into play.  By violating our functional principles, we gain the ability to avoid the overhead and cost of rescheduling the work: // Perform an action on the results of our filter collection .AsParallel() .Where( i => i.SomePredicate() ) .ForAll( i => i.DoSomething() ); The ability to avoid the scheduling overhead is a compelling reason to use ForAll.  This really goes back to one of the key points I discussed in data parallelism: Partition your problem in a way to place the most work possible into each task.  Here, this means leaving the statement attached to the expression, even though it causes side effects and is not standard usage for LINQ. This leads to my one guideline for using ForAll: The ForAll extension method should only be used to process the results of a parallel query, as returned by a PLINQ expression. Any other usage scenario should use Parallel.ForEach, instead.

    Read the article

  • Parallelism in .NET – Part 17, Think Continuations, not Callbacks

    - by Reed
    In traditional asynchronous programming, we’d often use a callback to handle notification of a background task’s completion.  The Task class in the Task Parallel Library introduces a cleaner alternative to the traditional callback: continuation tasks. Asynchronous programming methods typically required callback functions.  For example, MSDN’s Asynchronous Delegates Programming Sample shows a class that factorizes a number.  The original method in the example has the following signature: public static bool Factorize(int number, ref int primefactor1, ref int primefactor2) { //... .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; } However, calling this is quite “tricky”, even if we modernize the sample to use lambda expressions via C# 3.0.  Normally, we could call this method like so: int primeFactor1 = 0; int primeFactor2 = 0; bool answer = Factorize(10298312, ref primeFactor1, ref primeFactor2); Console.WriteLine("{0}/{1} [Succeeded {2}]", primeFactor1, primeFactor2, answer); If we want to make this operation run in the background, and report to the console via a callback, things get tricker.  First, we need a delegate definition: public delegate bool AsyncFactorCaller( int number, ref int primefactor1, ref int primefactor2); Then we need to use BeginInvoke to run this method asynchronously: int primeFactor1 = 0; int primeFactor2 = 0; AsyncFactorCaller caller = new AsyncFactorCaller(Factorize); caller.BeginInvoke(10298312, ref primeFactor1, ref primeFactor2, result => { int factor1 = 0; int factor2 = 0; bool answer = caller.EndInvoke(ref factor1, ref factor2, result); Console.WriteLine("{0}/{1} [Succeeded {2}]", factor1, factor2, answer); }, null); This works, but is quite difficult to understand from a conceptual standpoint.  To combat this, the framework added the Event-based Asynchronous Pattern, but it isn’t much easier to understand or author. Using .NET 4’s new Task<T> class and a continuation, we can dramatically simplify the implementation of the above code, as well as make it much more understandable.  We do this via the Task.ContinueWith method.  This method will schedule a new Task upon completion of the original task, and provide the original Task (including its Result if it’s a Task<T>) as an argument.  Using Task, we can eliminate the delegate, and rewrite this code like so: var background = Task.Factory.StartNew( () => { int primeFactor1 = 0; int primeFactor2 = 0; bool result = Factorize(10298312, ref primeFactor1, ref primeFactor2); return new { Result = result, Factor1 = primeFactor1, Factor2 = primeFactor2 }; }); background.ContinueWith(task => Console.WriteLine("{0}/{1} [Succeeded {2}]", task.Result.Factor1, task.Result.Factor2, task.Result.Result)); This is much simpler to understand, in my opinion.  Here, we’re explicitly asking to start a new task, then continue the task with a resulting task.  In our case, our method used ref parameters (this was from the MSDN Sample), so there is a little bit of extra boiler plate involved, but the code is at least easy to understand. That being said, this isn’t dramatically shorter when compared with our C# 3 port of the MSDN code above.  However, if we were to extend our requirements a bit, we can start to see more advantages to the Task based approach.  For example, supposed we need to report the results in a user interface control instead of reporting it to the Console.  This would be a common operation, but now, we have to think about marshaling our calls back to the user interface.  This is probably going to require calling Control.Invoke or Dispatcher.Invoke within our callback, forcing us to specify a delegate within the delegate.  The maintainability and ease of understanding drops.  However, just as a standard Task can be created with a TaskScheduler that uses the UI synchronization context, so too can we continue a task with a specific context.  There are Task.ContinueWith method overloads which allow you to provide a TaskScheduler.  This means you can schedule the continuation to run on the UI thread, by simply doing: Task.Factory.StartNew( () => { int primeFactor1 = 0; int primeFactor2 = 0; bool result = Factorize(10298312, ref primeFactor1, ref primeFactor2); return new { Result = result, Factor1 = primeFactor1, Factor2 = primeFactor2 }; }).ContinueWith(task => textBox1.Text = string.Format("{0}/{1} [Succeeded {2}]", task.Result.Factor1, task.Result.Factor2, task.Result.Result), TaskScheduler.FromCurrentSynchronizationContext()); This is far more understandable than the alternative.  By using Task.ContinueWith in conjunction with TaskScheduler.FromCurrentSynchronizationContext(), we get a simple way to push any work onto a background thread, and update the user interface on the proper UI thread.  This technique works with Windows Presentation Foundation as well as Windows Forms, with no change in methodology.

    Read the article

  • MVC : Does Code to save data in cache or session belongs in controller?

    - by newbie
    I'm a bit confused if saving the information to session code below, belongs in the controller action as shown below or should it be part of my Model? I would add that I have other controller methods that will read this session value later. public ActionResult AddFriend(FriendsContext viewModel) { if (!ModelState.IsValid) { return View(viewModel); } // Start - Confused if the code block below belongs in Controller? Friend friend = new Friend(); friend.FirstName = viewModel.FirstName; friend.LastName = viewModel.LastName; friend.Email = viewModel.UserEmail; httpContext.Session["latest-friend"] = friend; // End Confusion return RedirectToAction("Home"); } I thought about adding a static utility class in my Model which does something like below, but it just seems stupid to add 2 lines of code in another file. public static void SaveLatestFriend(Friend friend, HttpContextBase httpContext) { httpContext.Session["latest-friend"] = friend; } public static Friend GetLatestFriend(HttpContextBase httpContext) { return httpContext.Session["latest-friend"] as Friend; }

    Read the article

  • add c# user control to existing asp.net vb.net project

    - by Fidel
    Hello, I've got an existing asp.net project written in vb.net. Another person has written a user control in c#. Could you please let me know the steps for adding that C# user control to the vb.net app? I've tried copying them to the folder and using "Add existing item", however it doesn't compile the code behind at all. Thanks, Fidel

    Read the article

  • An Unusual UpdatePanel

    - by João Angelo
    The code you are about to see was mostly to prove a point, to myself, and probably has limited applicability. Nonetheless, in the remote possibility this is useful to someone here it goes… So this is a control that acts like a normal UpdatePanel where all child controls are registered as postback triggers except for a single control specified by the TriggerControlID property. You could basically achieve the same thing by registering all controls as postback triggers in the regular UpdatePanel. However with this, that process is performed automatically. Finally, here is the code: public sealed class SingleAsyncTriggerUpdatePanel : WebControl, INamingContainer { public string TriggerControlID { get; set; } [TemplateInstance(TemplateInstance.Single)] [PersistenceMode(PersistenceMode.InnerProperty)] public ITemplate ContentTemplate { get; set; } public override ControlCollection Controls { get { this.EnsureChildControls(); return base.Controls; } } protected override void CreateChildControls() { if (string.IsNullOrWhiteSpace(this.TriggerControlID)) throw new InvalidOperationException( "The TriggerControlId property must be set."); this.Controls.Clear(); var updatePanel = new UpdatePanel() { ID = string.Concat(this.ID, "InnerUpdatePanel"), ChildrenAsTriggers = false, UpdateMode = UpdatePanelUpdateMode.Conditional, ContentTemplate = this.ContentTemplate }; updatePanel.Triggers.Add(new SingleControlAsyncUpdatePanelTrigger { ControlID = this.TriggerControlID }); this.Controls.Add(updatePanel); } } internal sealed class SingleControlAsyncUpdatePanelTrigger : UpdatePanelControlTrigger { private Control target; private ScriptManager scriptManager; public Control Target { get { if (this.target == null) { this.target = this.FindTargetControl(true); } return this.target; } } public ScriptManager ScriptManager { get { if (this.scriptManager == null) { var page = base.Owner.Page; if (page != null) { this.scriptManager = ScriptManager.GetCurrent(page); } } return this.scriptManager; } } protected override bool HasTriggered() { string asyncPostBackSourceElementID = this.ScriptManager.AsyncPostBackSourceElementID; if (asyncPostBackSourceElementID == this.Target.UniqueID) return true; return asyncPostBackSourceElementID.StartsWith( string.Concat(this.target.UniqueID, "$"), StringComparison.Ordinal); } protected override void Initialize() { base.Initialize(); foreach (Control control in FlattenControlHierarchy(this.Owner.Controls)) { if (control == this.Target) continue; bool isApplicableControl = false; isApplicableControl |= control is INamingContainer; isApplicableControl |= control is IPostBackDataHandler; isApplicableControl |= control is IPostBackEventHandler; if (isApplicableControl) { this.ScriptManager.RegisterPostBackControl(control); } } } private static IEnumerable<Control> FlattenControlHierarchy( ControlCollection collection) { foreach (Control control in collection) { yield return control; if (control.Controls.Count > 0) { foreach (Control child in FlattenControlHierarchy(control.Controls)) { yield return child; } } } } } You can use it like this, meaning that only the B2 button will trigger an async postback: <cc:SingleAsyncTriggerUpdatePanel ID="Test" runat="server" TriggerControlID="B2"> <ContentTemplate> <asp:Button ID="B1" Text="B1" runat="server" OnClick="Button_Click" /> <asp:Button ID="B2" Text="B2" runat="server" OnClick="Button_Click" /> <asp:Button ID="B3" Text="B3" runat="server" OnClick="Button_Click" /> <asp:Label ID="LInner" Text="LInner" runat="server" /> </ContentTemplate> </cc:SingleAsyncTriggerUpdatePanel>

    Read the article

  • Using JSON.NET for dynamic JSON parsing

    - by Rick Strahl
    With the release of ASP.NET Web API as part of .NET 4.5 and MVC 4.0, JSON.NET has effectively pushed out the .NET native serializers to become the default serializer for Web API. JSON.NET is vastly more flexible than the built in DataContractJsonSerializer or the older JavaScript serializer. The DataContractSerializer in particular has been very problematic in the past because it can't deal with untyped objects for serialization - like values of type object, or anonymous types which are quite common these days. The JavaScript Serializer that came before it actually does support non-typed objects for serialization but it can't do anything with untyped data coming in from JavaScript and it's overall model of extensibility was pretty limited (JavaScript Serializer is what MVC uses for JSON responses). JSON.NET provides a robust JSON serializer that has both high level and low level components, supports binary JSON, JSON contracts, Xml to JSON conversion, LINQ to JSON and many, many more features than either of the built in serializers. ASP.NET Web API now uses JSON.NET as its default serializer and is now pulled in as a NuGet dependency into Web API projects, which is great. Dynamic JSON Parsing One of the features that I think is getting ever more important is the ability to serialize and deserialize arbitrary JSON content dynamically - that is without mapping the JSON captured directly into a .NET type as DataContractSerializer or the JavaScript Serializers do. Sometimes it isn't possible to map types due to the differences in languages (think collections, dictionaries etc), and other times you simply don't have the structures in place or don't want to create them to actually import the data. If this topic sounds familiar - you're right! I wrote about dynamic JSON parsing a few months back before JSON.NET was added to Web API and when Web API and the System.Net HttpClient libraries included the System.Json classes like JsonObject and JsonArray. With the inclusion of JSON.NET in Web API these classes are now obsolete and didn't ship with Web API or the client libraries. I re-linked my original post to this one. In this post I'll discus JToken, JObject and JArray which are the dynamic JSON objects that make it very easy to create and retrieve JSON content on the fly without underlying types. Why Dynamic JSON? So, why Dynamic JSON parsing rather than strongly typed parsing? Since applications are interacting more and more with third party services it becomes ever more important to have easy access to those services with easy JSON parsing. Sometimes it just makes lot of sense to pull just a small amount of data out of large JSON document received from a service, because the third party service isn't directly related to your application's logic most of the time - and it makes little sense to map the entire service structure in your application. For example, recently I worked with the Google Maps Places API to return information about businesses close to me (or rather the app's) location. The Google API returns a ton of information that my application had no interest in - all I needed was few values out of the data. Dynamic JSON parsing makes it possible to map this data, without having to map the entire API to a C# data structure. Instead I could pull out the three or four values I needed from the API and directly store it on my business entities that needed to receive the data - no need to map the entire Maps API structure. Getting JSON.NET The easiest way to use JSON.NET is to grab it via NuGet and add it as a reference to your project. You can add it to your project with: PM> Install-Package Newtonsoft.Json From the Package Manager Console or by using Manage NuGet Packages in your project References. As mentioned if you're using ASP.NET Web API or MVC 4 JSON.NET will be automatically added to your project. Alternately you can also go to the CodePlex site and download the latest version including source code: http://json.codeplex.com/ Creating JSON on the fly with JObject and JArray Let's start with creating some JSON on the fly. It's super easy to create a dynamic object structure with any of the JToken derived JSON.NET objects. The most common JToken derived classes you are likely to use are JObject and JArray. JToken implements IDynamicMetaProvider and so uses the dynamic  keyword extensively to make it intuitive to create object structures and turn them into JSON via dynamic object syntax. Here's an example of creating a music album structure with child songs using JObject for the base object and songs and JArray for the actual collection of songs:[TestMethod] public void JObjectOutputTest() { // strong typed instance var jsonObject = new JObject(); // you can explicitly add values here using class interface jsonObject.Add("Entered", DateTime.Now); // or cast to dynamic to dynamically add/read properties dynamic album = jsonObject; album.AlbumName = "Dirty Deeds Done Dirt Cheap"; album.Artist = "AC/DC"; album.YearReleased = 1976; album.Songs = new JArray() as dynamic; dynamic song = new JObject(); song.SongName = "Dirty Deeds Done Dirt Cheap"; song.SongLength = "4:11"; album.Songs.Add(song); song = new JObject(); song.SongName = "Love at First Feel"; song.SongLength = "3:10"; album.Songs.Add(song); Console.WriteLine(album.ToString()); } This produces a complete JSON structure: { "Entered": "2012-08-18T13:26:37.7137482-10:00", "AlbumName": "Dirty Deeds Done Dirt Cheap", "Artist": "AC/DC", "YearReleased": 1976, "Songs": [ { "SongName": "Dirty Deeds Done Dirt Cheap", "SongLength": "4:11" }, { "SongName": "Love at First Feel", "SongLength": "3:10" } ] } Notice that JSON.NET does a nice job formatting the JSON, so it's easy to read and paste into blog posts :-). JSON.NET includes a bunch of configuration options that control how JSON is generated. Typically the defaults are just fine, but you can override with the JsonSettings object for most operations. The important thing about this code is that there's no explicit type used for holding the values to serialize to JSON. Rather the JSON.NET objects are the containers that receive the data as I build up my JSON structure dynamically, simply by adding properties. This means this code can be entirely driven at runtime without compile time restraints of structure for the JSON output. Here I use JObject to create a album 'object' and immediately cast it to dynamic. JObject() is kind of similar in behavior to ExpandoObject in that it allows you to add properties by simply assigning to them. Internally, JObject values are stored in pseudo collections of key value pairs that are exposed as properties through the IDynamicMetaObject interface exposed in JSON.NET's JToken base class. For objects the syntax is very clean - you add simple typed values as properties. For objects and arrays you have to explicitly create new JObject or JArray, cast them to dynamic and then add properties and items to them. Always remember though these values are dynamic - which means no Intellisense and no compiler type checking. It's up to you to ensure that the names and values you create are accessed consistently and without typos in your code. Note that you can also access the JObject instance directly (not as dynamic) and get access to the underlying JObject type. This means you can assign properties by string, which can be useful for fully data driven JSON generation from other structures. Below you can see both styles of access next to each other:// strong type instance var jsonObject = new JObject(); // you can explicitly add values here jsonObject.Add("Entered", DateTime.Now); // expando style instance you can just 'use' properties dynamic album = jsonObject; album.AlbumName = "Dirty Deeds Done Dirt Cheap"; JContainer (the base class for JObject and JArray) is a collection so you can also iterate over the properties at runtime easily:foreach (var item in jsonObject) { Console.WriteLine(item.Key + " " + item.Value.ToString()); } The functionality of the JSON objects are very similar to .NET's ExpandObject and if you used it before, you're already familiar with how the dynamic interfaces to the JSON objects works. Importing JSON with JObject.Parse() and JArray.Parse() The JValue structure supports importing JSON via the Parse() and Load() methods which can read JSON data from a string or various streams respectively. Essentially JValue includes the core JSON parsing to turn a JSON string into a collection of JsonValue objects that can be then referenced using familiar dynamic object syntax. Here's a simple example:public void JValueParsingTest() { var jsonString = @"{""Name"":""Rick"",""Company"":""West Wind"", ""Entered"":""2012-03-16T00:03:33.245-10:00""}"; dynamic json = JValue.Parse(jsonString); // values require casting string name = json.Name; string company = json.Company; DateTime entered = json.Entered; Assert.AreEqual(name, "Rick"); Assert.AreEqual(company, "West Wind"); } The JSON string represents an object with three properties which is parsed into a JObject class and cast to dynamic. Once cast to dynamic I can then go ahead and access the object using familiar object syntax. Note that the actual values - json.Name, json.Company, json.Entered - are actually of type JToken and I have to cast them to their appropriate types first before I can do type comparisons as in the Asserts at the end of the test method. This is required because of the way that dynamic types work which can't determine the type based on the method signature of the Assert.AreEqual(object,object) method. I have to either assign the dynamic value to a variable as I did above, or explicitly cast ( (string) json.Name) in the actual method call. The JSON structure can be much more complex than this simple example. Here's another example of an array of albums serialized to JSON and then parsed through with JsonValue():[TestMethod] public void JsonArrayParsingTest() { var jsonString = @"[ { ""Id"": ""b3ec4e5c"", ""AlbumName"": ""Dirty Deeds Done Dirt Cheap"", ""Artist"": ""AC/DC"", ""YearReleased"": 1976, ""Entered"": ""2012-03-16T00:13:12.2810521-10:00"", ""AlbumImageUrl"": ""http://ecx.images-amazon.com/images/I/61kTaH-uZBL._AA115_.jpg"", ""AmazonUrl"": ""http://www.amazon.com/gp/product/…ASIN=B00008BXJ4"", ""Songs"": [ { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Dirty Deeds Done Dirt Cheap"", ""SongLength"": ""4:11"" }, { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Love at First Feel"", ""SongLength"": ""3:10"" }, { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Big Balls"", ""SongLength"": ""2:38"" } ] }, { ""Id"": ""7b919432"", ""AlbumName"": ""End of the Silence"", ""Artist"": ""Henry Rollins Band"", ""YearReleased"": 1992, ""Entered"": ""2012-03-16T00:13:12.2800521-10:00"", ""AlbumImageUrl"": ""http://ecx.images-amazon.com/images/I/51FO3rb1tuL._SL160_AA160_.jpg"", ""AmazonUrl"": ""http://www.amazon.com/End-Silence-Rollins-Band/dp/B0000040OX/ref=sr_1_5?ie=UTF8&qid=1302232195&sr=8-5"", ""Songs"": [ { ""AlbumId"": ""7b919432"", ""SongName"": ""Low Self Opinion"", ""SongLength"": ""5:24"" }, { ""AlbumId"": ""7b919432"", ""SongName"": ""Grip"", ""SongLength"": ""4:51"" } ] } ]"; JArray jsonVal = JArray.Parse(jsonString) as JArray; dynamic albums = jsonVal; foreach (dynamic album in albums) { Console.WriteLine(album.AlbumName + " (" + album.YearReleased.ToString() + ")"); foreach (dynamic song in album.Songs) { Console.WriteLine("\t" + song.SongName); } } Console.WriteLine(albums[0].AlbumName); Console.WriteLine(albums[0].Songs[1].SongName); } JObject and JArray in ASP.NET Web API Of course these types also work in ASP.NET Web API controller methods. If you want you can accept parameters using these object or return them back to the server. The following contrived example receives dynamic JSON input, and then creates a new dynamic JSON object and returns it based on data from the first:[HttpPost] public JObject PostAlbumJObject(JObject jAlbum) { // dynamic input from inbound JSON dynamic album = jAlbum; // create a new JSON object to write out dynamic newAlbum = new JObject(); // Create properties on the new instance // with values from the first newAlbum.AlbumName = album.AlbumName + " New"; newAlbum.NewProperty = "something new"; newAlbum.Songs = new JArray(); foreach (dynamic song in album.Songs) { song.SongName = song.SongName + " New"; newAlbum.Songs.Add(song); } return newAlbum; } The raw POST request to the server looks something like this: POST http://localhost/aspnetwebapi/samples/PostAlbumJObject HTTP/1.1User-Agent: FiddlerContent-type: application/jsonHost: localhostContent-Length: 88 {AlbumName: "Dirty Deeds",Songs:[ { SongName: "Problem Child"},{ SongName: "Squealer"}]} and the output that comes back looks like this: {  "AlbumName": "Dirty Deeds New",  "NewProperty": "something new",  "Songs": [    {      "SongName": "Problem Child New"    },    {      "SongName": "Squealer New"    }  ]} The original values are echoed back with something extra appended to demonstrate that we're working with a new object. When you receive or return a JObject, JValue, JToken or JArray instance in a Web API method, Web API ignores normal content negotiation and assumes your content is going to be received and returned as JSON, so effectively the parameter and result type explicitly determines the input and output format which is nice. Dynamic to Strong Type Mapping You can also map JObject and JArray instances to a strongly typed object, so you can mix dynamic and static typing in the same piece of code. Using the 2 Album jsonString shown earlier, the code below takes an array of albums and picks out only a single album and casts that album to a static Album instance.[TestMethod] public void JsonParseToStrongTypeTest() { JArray albums = JArray.Parse(jsonString) as JArray; // pick out one album JObject jalbum = albums[0] as JObject; // Copy to a static Album instance Album album = jalbum.ToObject<Album>(); Assert.IsNotNull(album); Assert.AreEqual(album.AlbumName,jalbum.Value<string>("AlbumName")); Assert.IsTrue(album.Songs.Count > 0); } This is pretty damn useful for the scenario I mentioned earlier - you can read a large chunk of JSON and dynamically walk the property hierarchy down to the item you want to access, and then either access the specific item dynamically (as shown earlier) or map a part of the JSON to a strongly typed object. That's very powerful if you think about it - it leaves you in total control to decide what's dynamic and what's static. Strongly typed JSON Parsing With all this talk of dynamic let's not forget that JSON.NET of course also does strongly typed serialization which is drop dead easy. Here's a simple example on how to serialize and deserialize an object with JSON.NET:[TestMethod] public void StronglyTypedSerializationTest() { // Demonstrate deserialization from a raw string var album = new Album() { AlbumName = "Dirty Deeds Done Dirt Cheap", Artist = "AC/DC", Entered = DateTime.Now, YearReleased = 1976, Songs = new List<Song>() { new Song() { SongName = "Dirty Deeds Done Dirt Cheap", SongLength = "4:11" }, new Song() { SongName = "Love at First Feel", SongLength = "3:10" } } }; // serialize to string string json2 = JsonConvert.SerializeObject(album,Formatting.Indented); Console.WriteLine(json2); // make sure we can serialize back var album2 = JsonConvert.DeserializeObject<Album>(json2); Assert.IsNotNull(album2); Assert.IsTrue(album2.AlbumName == "Dirty Deeds Done Dirt Cheap"); Assert.IsTrue(album2.Songs.Count == 2); } JsonConvert is a high level static class that wraps lower level functionality, but you can also use the JsonSerializer class, which allows you to serialize/parse to and from streams. It's a little more work, but gives you a bit more control. The functionality available is easy to discover with Intellisense, and that's good because there's not a lot in the way of documentation that's actually useful. Summary JSON.NET is a pretty complete JSON implementation with lots of different choices for JSON parsing from dynamic parsing to static serialization, to complex querying of JSON objects using LINQ. It's good to see this open source library getting integrated into .NET, and pushing out the old and tired stock .NET parsers so that we finally have a bit more flexibility - and extensibility - in our JSON parsing. Good to go! Resources Sample Test Project http://json.codeplex.com/© Rick Strahl, West Wind Technologies, 2005-2012Posted in .NET  Web Api  AJAX   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

    Read the article

  • 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.

    Read the article

  • 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.

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 17 18 19 20 21 22 23 24 25 26 27 28  | Next Page >