Search Results

Search found 54748 results on 2190 pages for 'asp net authorization'.

Page 40/2190 | < Previous Page | 36 37 38 39 40 41 42 43 44 45 46 47  | Next Page >

  • ASP.NET WebForms vs MVC [after VS2010/.NET 4.0 announcement]

    - by fjxx
    Two of the biggest advantages of MVC over webforms were non-existent viewstate and URL routing. VS2010 and .NET 4.0 incorporates built-in URL routing for Webforms as well as better control for viewstate. I advocate use of MVC for extranet sites due to the MVC design pattern and its general lightweight nature but in light of this new announcement has Webforms closed the gap? Why would you still pick MVC over Webforms? Thanks

    Read the article

  • Returning date from Stored procedure in ASP.Net/VB.Net

    - by Mo
    Hi, I want to execute a method on VB.Net to return a date which is in the stored procedure. I tried using ExecuteScalar but it doesnt work it retruns error 'Implicit conversion from data type datetime to int is not allowed. Use the CONVERT function to run this query' Any help would be much appreciated please? thank you below is the code Public Function GetHolidaydate(ByVal struserID as String) As DateTime Dim objArgs1 As New clsSQLStoredProcedureParams objArgs1.Add("@userID", Me.Tag) objArgs1.Add("@Date", 0, 0, ParameterDirection.Output) Return (CDate(ExecuteScalar(clsLibrary.MyStoredProcedure.GetHolidayDate, objArgs1))) End Function

    Read the article

  • Hosting the Razor Engine for Templating in Non-Web Applications

    - by Rick Strahl
    Microsoft’s new Razor HTML Rendering Engine that is currently shipping with ASP.NET MVC previews can be used outside of ASP.NET. Razor is an alternative view engine that can be used instead of the ASP.NET Page engine that currently works with ASP.NET WebForms and MVC. It provides a simpler and more readable markup syntax and is much more light weight in terms of functionality than the full blown WebForms Page engine, focusing only on features that are more along the lines of a pure view engine (or classic ASP!) with focus on expression and code rendering rather than a complex control/object model. Like the Page engine though, the parser understands .NET code syntax which can be embedded into templates, and behind the scenes the engine compiles markup and script code into an executing piece of .NET code in an assembly. Although it ships as part of the ASP.NET MVC and WebMatrix the Razor Engine itself is not directly dependent on ASP.NET or IIS or HTTP in any way. And although there are some markup and rendering features that are optimized for HTML based output generation, Razor is essentially a free standing template engine. And what’s really nice is that unlike the ASP.NET Runtime, Razor is fairly easy to host inside of your own non-Web applications to provide templating functionality. Templating in non-Web Applications? Yes please! So why might you host a template engine in your non-Web application? Template rendering is useful in many places and I have a number of applications that make heavy use of it. One of my applications – West Wind Html Help Builder - exclusively uses template based rendering to merge user supplied help text content into customizable and executable HTML markup templates that provide HTML output for CHM style HTML Help. This is an older product and it’s not actually using .NET at the moment – and this is one reason I’m looking at Razor for script hosting at the moment. For a few .NET applications though I’ve actually used the ASP.NET Runtime hosting to provide templating and mail merge style functionality and while that works reasonably well it’s a very heavy handed approach. It’s very resource intensive and has potential issues with versioning in various different versions of .NET. The generic implementation I created in the article above requires a lot of fix up to mimic an HTTP request in a non-HTTP environment and there are a lot of little things that have to happen to ensure that the ASP.NET runtime works properly most of it having nothing to do with the templating aspect but just satisfying ASP.NET’s requirements. The Razor Engine on the other hand is fairly light weight and completely decoupled from the ASP.NET runtime and the HTTP processing. Rather it’s a pure template engine whose sole purpose is to render text templates. Hosting this engine in your own applications can be accomplished with a reasonable amount of code (actually just a few lines with the tools I’m about to describe) and without having to fake HTTP requests. It’s also much lighter on resource usage and you can easily attach custom properties to your base template implementation to easily pass context from the parent application into templates all of which was rather complicated with ASP.NET runtime hosting. Installing the Razor Template Engine You can get Razor as part of the MVC 3 (RC and later) or Web Matrix. Both are available as downloadable components from the Web Platform Installer Version 3.0 (!important – V2 doesn’t show these components). If you already have that version of the WPI installed just fire it up. You can get the latest version of the Web Platform Installer from here: http://www.microsoft.com/web/gallery/install.aspx Once the platform Installer 3.0 is installed install either MVC 3 or ASP.NET Web Pages. Once installed you’ll find a System.Web.Razor assembly in C:\Program Files\Microsoft ASP.NET\ASP.NET Web Pages\v1.0\Assemblies\System.Web.Razor.dll which you can add as a reference to your project. Creating a Wrapper The basic Razor Hosting API is pretty simple and you can host Razor with a (large-ish) handful of lines of code. I’ll show the basics of it later in this article. However, if you want to customize the rendering and handle assembly and namespace includes for the markup as well as deal with text and file inputs as well as forcing Razor to run in a separate AppDomain so you can unload the code-generated assemblies and deal with assembly caching for re-used templates little more work is required to create something that is more easily reusable. For this reason I created a Razor Hosting wrapper project that combines a bunch of this functionality into an easy to use hosting class, a hosting factory that can load the engine in a separate AppDomain and a couple of hosting containers that provided folder based and string based caching for templates for an easily embeddable and reusable engine with easy to use syntax. If you just want the code and play with the samples and source go grab the latest code from the Subversion Repository at: http://www.west-wind.com:8080/svn/articles/trunk/RazorHosting/ or a snapshot from: http://www.west-wind.com/files/tools/RazorHosting.zip Getting Started Before I get into how hosting with Razor works, let’s take a look at how you can get up and running quickly with the wrapper classes provided. It only takes a few lines of code. The easiest way to use these Razor Hosting Wrappers is to use one of the two HostContainers provided. One is for hosting Razor scripts in a directory and rendering them as relative paths from these script files on disk. The other HostContainer serves razor scripts from string templates… Let’s start with a very simple template that displays some simple expressions, some code blocks and demonstrates rendering some data from contextual data that you pass to the template in the form of a ‘context’. Here’s a simple Razor template: @using System.Reflection Hello @Context.FirstName! Your entry was entered on: @Context.Entered @{ // Code block: Update the host Windows Form passed in through the context Context.WinForm.Text = "Hello World from Razor at " + DateTime.Now.ToString(); } AppDomain Id: @AppDomain.CurrentDomain.FriendlyName Assembly: @Assembly.GetExecutingAssembly().FullName Code based output: @{ // Write output with Response object from code string output = string.Empty; for (int i = 0; i < 10; i++) { output += i.ToString() + " "; } Response.Write(output); } Pretty easy to see what’s going on here. The only unusual thing in this code is the Context object which is an arbitrary object I’m passing from the host to the template by way of the template base class. I’m also displaying the current AppDomain and the executing Assembly name so you can see how compiling and running a template actually loads up new assemblies. Also note that as part of my context I’m passing a reference to the current Windows Form down to the template and changing the title from within the script. It’s a silly example, but it demonstrates two-way communication between host and template and back which can be very powerful. The easiest way to quickly render this template is to use the RazorEngine<TTemplateBase> class. The generic parameter specifies a template base class type that is used by Razor internally to generate the class it generates from a template. The default implementation provided in my RazorHosting wrapper is RazorTemplateBase. Here’s a simple one that renders from a string and outputs a string: var engine = new RazorEngine<RazorTemplateBase>(); // we can pass any object as context - here create a custom context var context = new CustomContext() { WinForm = this, FirstName = "Rick", Entered = DateTime.Now.AddDays(-10) }; string output = engine.RenderTemplate(this.txtSource.Text new string[] { "System.Windows.Forms.dll" }, context); if (output == null) this.txtResult.Text = "*** ERROR:\r\n" + engine.ErrorMessage; else this.txtResult.Text = output; Simple enough. This code renders a template from a string input and returns a result back as a string. It  creates a custom context and passes that to the template which can then access the Context’s properties. Note that anything passed as ‘context’ must be serializable (or MarshalByRefObject) – otherwise you get an exception when passing the reference over AppDomain boundaries (discussed later). Passing a context is optional, but is a key feature in being able to share data between the host application and the template. Note that we use the Context object to access FirstName, Entered and even the host Windows Form object which is used in the template to change the Window caption from within the script! In the code above all the work happens in the RenderTemplate method which provide a variety of overloads to read and write to and from strings, files and TextReaders/Writers. Here’s another example that renders from a file input using a TextReader: using (reader = new StreamReader("templates\\simple.csHtml", true)) { result = host.RenderTemplate(reader, new string[] { "System.Windows.Forms.dll" }, this.CustomContext); } RenderTemplate() is fairly high level and it handles loading of the runtime, compiling into an assembly and rendering of the template. If you want more control you can use the lower level methods to control each step of the way which is important for the HostContainers I’ll discuss later. Basically for those scenarios you want to separate out loading of the engine, compiling into an assembly and then rendering the template from the assembly. Why? So we can keep assemblies cached. In the code above a new assembly is created for each template rendered which is inefficient and uses up resources. Depending on the size of your templates and how often you fire them you can chew through memory very quickly. This slighter lower level approach is only a couple of extra steps: // we can pass any object as context - here create a custom context var context = new CustomContext() { WinForm = this, FirstName = "Rick", Entered = DateTime.Now.AddDays(-10) }; var engine = new RazorEngine<RazorTemplateBase>(); string assId = null; using (StringReader reader = new StringReader(this.txtSource.Text)) { assId = engine.ParseAndCompileTemplate(new string[] { "System.Windows.Forms.dll" }, reader); } string output = engine.RenderTemplateFromAssembly(assId, context); if (output == null) this.txtResult.Text = "*** ERROR:\r\n" + engine.ErrorMessage; else this.txtResult.Text = output; The difference here is that you can capture the assembly – or rather an Id to it – and potentially hold on to it to render again later assuming the template hasn’t changed. The HostContainers take advantage of this feature to cache the assemblies based on certain criteria like a filename and file time step or a string hash that if not change indicate that an assembly can be reused. Note that ParseAndCompileTemplate returns an assembly Id rather than the assembly itself. This is done so that that the assembly always stays in the host’s AppDomain and is not passed across AppDomain boundaries which would cause load failures. We’ll talk more about this in a minute but for now just realize that assemblies references are stored in a list and are accessible by this ID to allow locating and re-executing of the assembly based on that id. Reuse of the assembly avoids recompilation overhead and creation of yet another assembly that loads into the current AppDomain. You can play around with several different versions of the above code in the main sample form:   Using Hosting Containers for more Control and Caching The above examples simply render templates into assemblies each and every time they are executed. While this works and is even reasonably fast, it’s not terribly efficient. If you render templates more than once it would be nice if you could cache the generated assemblies for example to avoid re-compiling and creating of a new assembly each time. Additionally it would be nice to load template assemblies into a separate AppDomain optionally to be able to be able to unload assembli es and also to protect your host application from scripting attacks with malicious template code. Hosting containers provide also provide a wrapper around the RazorEngine<T> instance, a factory (which allows creation in separate AppDomains) and an easy way to start and stop the container ‘runtime’. The Razor Hosting samples provide two hosting containers: RazorFolderHostContainer and StringHostContainer. The folder host provides a simple runtime environment for a folder structure similar in the way that the ASP.NET runtime handles a virtual directory as it’s ‘application' root. Templates are loaded from disk in relative paths and the resulting assemblies are cached unless the template on disk is changed. The string host also caches templates based on string hashes – if the same string is passed a second time a cached version of the assembly is used. Here’s how HostContainers work. I’ll use the FolderHostContainer because it’s likely the most common way you’d use templates – from disk based templates that can be easily edited and maintained on disk. The first step is to create an instance of it and keep it around somewhere (in the example it’s attached as a property to the Form): RazorFolderHostContainer Host = new RazorFolderHostContainer(); public RazorFolderHostForm() { InitializeComponent(); // The base path for templates - templates are rendered with relative paths // based on this path. Host.TemplatePath = Path.Combine(Environment.CurrentDirectory, TemplateBaseFolder); // Add any assemblies you want reference in your templates Host.ReferencedAssemblies.Add("System.Windows.Forms.dll"); // Start up the host container Host.Start(); } Next anytime you want to render a template you can use simple code like this: private void RenderTemplate(string fileName) { // Pass the template path via the Context var relativePath = Utilities.GetRelativePath(fileName, Host.TemplatePath); if (!Host.RenderTemplate(relativePath, this.Context, Host.RenderingOutputFile)) { MessageBox.Show("Error: " + Host.ErrorMessage); return; } this.webBrowser1.Navigate("file://" + Host.RenderingOutputFile); } You can also render the output to a string instead of to a file: string result = Host.RenderTemplateToString(relativePath,context); Finally if you want to release the engine and shut down the hosting AppDomain you can simply do: Host.Stop(); Stopping the AppDomain and restarting it (ie. calling Stop(); followed by Start()) is also a nice way to release all resources in the AppDomain. The FolderBased domain also supports partial Rendering based on root path based relative paths with the same caching characteristics as the main templates. From within a template you can call out to a partial like this: @RenderPartial(@"partials\PartialRendering.cshtml", Context) where partials\PartialRendering.cshtml is a relative to the template root folder. The folder host example lets you load up templates from disk and display the result in a Web Browser control which demonstrates using Razor HTML output from templates that contain HTML syntax which happens to me my target scenario for Html Help Builder.   The Razor Engine Wrapper Project The project I created to wrap Razor hosting has a fair bit of code and a number of classes associated with it. Most of the components are internally used and as you can see using the final RazorEngine<T> and HostContainer classes is pretty easy. The classes are extensible and I suspect developers will want to build more customized host containers for their applications. Host containers are the key to wrapping up all functionality – Engine, BaseTemplate, AppDomain Hosting, Caching etc in a logical piece that is ready to be plugged into an application. When looking at the code there are a couple of core features provided: Core Razor Engine Hosting This is the core Razor hosting which provides the basics of loading a template, compiling it into an assembly and executing it. This is fairly straightforward, but without a host container that can cache assemblies based on some criteria templates are recompiled and re-created each time which is inefficient (although pretty fast). The base engine wrapper implementation also supports hosting the Razor runtime in a separate AppDomain for security and the ability to unload it on demand. Host Containers The engine hosting itself doesn’t provide any sort of ‘runtime’ service like picking up files from disk, caching assemblies and so forth. So my implementation provides two HostContainers: RazorFolderHostContainer and RazorStringHostContainer. The FolderHost works off a base directory and loads templates based on relative paths (sort of like the ASP.NET runtime does off a virtual). The HostContainers also deal with caching of template assemblies – for the folder host the file date is tracked and checked for updates and unless the template is changed a cached assembly is reused. The StringHostContainer similiarily checks string hashes to figure out whether a particular string template was previously compiled and executed. The HostContainers also act as a simple startup environment and a single reference to easily store and reuse in an application. TemplateBase Classes The template base classes are the base classes that from which the Razor engine generates .NET code. A template is parsed into a class with an Execute() method and the class is based on this template type you can specify. RazorEngine<TBaseTemplate> can receive this type and the HostContainers default to specific templates in their base implementations. Template classes are customizable to allow you to create templates that provide application specific features and interaction from the template to your host application. How does the RazorEngine wrapper work? You can browse the source code in the links above or in the repository or download the source, but I’ll highlight some key features here. Here’s part of the RazorEngine implementation that can be used to host the runtime and that demonstrates the key code required to host the Razor runtime. The RazorEngine class is implemented as a generic class to reflect the Template base class type: public class RazorEngine<TBaseTemplateType> : MarshalByRefObject where TBaseTemplateType : RazorTemplateBase The generic type is used to internally provide easier access to the template type and assignments on it as part of the template processing. The class also inherits MarshalByRefObject to allow execution over AppDomain boundaries – something that all the classes discussed here need to do since there is much interaction between the host and the template. The first two key methods deal with creating a template assembly: /// <summary> /// Creates an instance of the RazorHost with various options applied. /// Applies basic namespace imports and the name of the class to generate /// </summary> /// <param name="generatedNamespace"></param> /// <param name="generatedClass"></param> /// <returns></returns> protected RazorTemplateEngine CreateHost(string generatedNamespace, string generatedClass) { Type baseClassType = typeof(TBaseTemplateType); RazorEngineHost host = new RazorEngineHost(new CSharpRazorCodeLanguage()); host.DefaultBaseClass = baseClassType.FullName; host.DefaultClassName = generatedClass; host.DefaultNamespace = generatedNamespace; host.NamespaceImports.Add("System"); host.NamespaceImports.Add("System.Text"); host.NamespaceImports.Add("System.Collections.Generic"); host.NamespaceImports.Add("System.Linq"); host.NamespaceImports.Add("System.IO"); return new RazorTemplateEngine(host); } /// <summary> /// Parses and compiles a markup template into an assembly and returns /// an assembly name. The name is an ID that can be passed to /// ExecuteTemplateByAssembly which picks up a cached instance of the /// loaded assembly. /// /// </summary> /// <param name="namespaceOfGeneratedClass">The namespace of the class to generate from the template</param> /// <param name="generatedClassName">The name of the class to generate from the template</param> /// <param name="ReferencedAssemblies">Any referenced assemblies by dll name only. Assemblies must be in execution path of host or in GAC.</param> /// <param name="templateSourceReader">Textreader that loads the template</param> /// <remarks> /// The actual assembly isn't returned here to allow for cross-AppDomain /// operation. If the assembly was returned it would fail for cross-AppDomain /// calls. /// </remarks> /// <returns>An assembly Id. The Assembly is cached in memory and can be used with RenderFromAssembly.</returns> public string ParseAndCompileTemplate( string namespaceOfGeneratedClass, string generatedClassName, string[] ReferencedAssemblies, TextReader templateSourceReader) { RazorTemplateEngine engine = CreateHost(namespaceOfGeneratedClass, generatedClassName); // Generate the template class as CodeDom GeneratorResults razorResults = engine.GenerateCode(templateSourceReader); // Create code from the codeDom and compile CSharpCodeProvider codeProvider = new CSharpCodeProvider(); CodeGeneratorOptions options = new CodeGeneratorOptions(); // Capture Code Generated as a string for error info // and debugging LastGeneratedCode = null; using (StringWriter writer = new StringWriter()) { codeProvider.GenerateCodeFromCompileUnit(razorResults.GeneratedCode, writer, options); LastGeneratedCode = writer.ToString(); } CompilerParameters compilerParameters = new CompilerParameters(ReferencedAssemblies); // Standard Assembly References compilerParameters.ReferencedAssemblies.Add("System.dll"); compilerParameters.ReferencedAssemblies.Add("System.Core.dll"); compilerParameters.ReferencedAssemblies.Add("Microsoft.CSharp.dll"); // dynamic support! // Also add the current assembly so RazorTemplateBase is available compilerParameters.ReferencedAssemblies.Add(Assembly.GetExecutingAssembly().CodeBase.Substring(8)); compilerParameters.GenerateInMemory = Configuration.CompileToMemory; if (!Configuration.CompileToMemory) compilerParameters.OutputAssembly = Path.Combine(Configuration.TempAssemblyPath, "_" + Guid.NewGuid().ToString("n") + ".dll"); CompilerResults compilerResults = codeProvider.CompileAssemblyFromDom(compilerParameters, razorResults.GeneratedCode); if (compilerResults.Errors.Count > 0) { var compileErrors = new StringBuilder(); foreach (System.CodeDom.Compiler.CompilerError compileError in compilerResults.Errors) compileErrors.Append(String.Format(Resources.LineX0TColX1TErrorX2RN, compileError.Line, compileError.Column, compileError.ErrorText)); this.SetError(compileErrors.ToString() + "\r\n" + LastGeneratedCode); return null; } AssemblyCache.Add(compilerResults.CompiledAssembly.FullName, compilerResults.CompiledAssembly); return compilerResults.CompiledAssembly.FullName; } Think of the internal CreateHost() method as setting up the assembly generated from each template. Each template compiles into a separate assembly. It sets up namespaces, and assembly references, the base class used and the name and namespace for the generated class. ParseAndCompileTemplate() then calls the CreateHost() method to receive the template engine generator which effectively generates a CodeDom from the template – the template is turned into .NET code. The code generated from our earlier example looks something like this: //------------------------------------------------------------------------------ // <auto-generated> // This code was generated by a tool. // Runtime Version:4.0.30319.1 // // Changes to this file may cause incorrect behavior and will be lost if // the code is regenerated. // </auto-generated> //------------------------------------------------------------------------------ namespace RazorTest { using System; using System.Text; using System.Collections.Generic; using System.Linq; using System.IO; using System.Reflection; public class RazorTemplate : RazorHosting.RazorTemplateBase { #line hidden public RazorTemplate() { } public override void Execute() { WriteLiteral("Hello "); Write(Context.FirstName); WriteLiteral("! Your entry was entered on: "); Write(Context.Entered); WriteLiteral("\r\n\r\n"); // Code block: Update the host Windows Form passed in through the context Context.WinForm.Text = "Hello World from Razor at " + DateTime.Now.ToString(); WriteLiteral("\r\nAppDomain Id:\r\n "); Write(AppDomain.CurrentDomain.FriendlyName); WriteLiteral("\r\n \r\nAssembly:\r\n "); Write(Assembly.GetExecutingAssembly().FullName); WriteLiteral("\r\n\r\nCode based output: \r\n"); // Write output with Response object from code string output = string.Empty; for (int i = 0; i < 10; i++) { output += i.ToString() + " "; } } } } Basically the template’s body is turned into code in an Execute method that is called. Internally the template’s Write method is fired to actually generate the output. Note that the class inherits from RazorTemplateBase which is the generic parameter I used to specify the base class when creating an instance in my RazorEngine host: var engine = new RazorEngine<RazorTemplateBase>(); This template class must be provided and it must implement an Execute() and Write() method. Beyond that you can create any class you chose and attach your own properties. My RazorTemplateBase class implementation is very simple: public class RazorTemplateBase : MarshalByRefObject, IDisposable { /// <summary> /// You can pass in a generic context object /// to use in your template code /// </summary> public dynamic Context { get; set; } /// <summary> /// Class that generates output. Currently ultra simple /// with only Response.Write() implementation. /// </summary> public RazorResponse Response { get; set; } public object HostContainer {get; set; } public object Engine { get; set; } public RazorTemplateBase() { Response = new RazorResponse(); } public virtual void Write(object value) { Response.Write(value); } public virtual void WriteLiteral(object value) { Response.Write(value); } /// <summary> /// Razor Parser implements this method /// </summary> public virtual void Execute() {} public virtual void Dispose() { if (Response != null) { Response.Dispose(); Response = null; } } } Razor fills in the Execute method when it generates its subclass and uses the Write() method to output content. As you can see I use a RazorResponse() class here to generate output. This isn’t necessary really, as you could use a StringBuilder or StringWriter() directly, but I prefer using Response object so I can extend the Response behavior as needed. The RazorResponse class is also very simple and merely acts as a wrapper around a TextWriter: public class RazorResponse : IDisposable { /// <summary> /// Internal text writer - default to StringWriter() /// </summary> public TextWriter Writer = new StringWriter(); public virtual void Write(object value) { Writer.Write(value); } public virtual void WriteLine(object value) { Write(value); Write("\r\n"); } public virtual void WriteFormat(string format, params object[] args) { Write(string.Format(format, args)); } public override string ToString() { return Writer.ToString(); } public virtual void Dispose() { Writer.Close(); } public virtual void SetTextWriter(TextWriter writer) { // Close original writer if (Writer != null) Writer.Close(); Writer = writer; } } The Rendering Methods of RazorEngine At this point I’ve talked about the assembly generation logic and the template implementation itself. What’s left is that once you’ve generated the assembly is to execute it. The code to do this is handled in the various RenderXXX methods of the RazorEngine class. Let’s look at the lowest level one of these which is RenderTemplateFromAssembly() and a couple of internal support methods that handle instantiating and invoking of the generated template method: public string RenderTemplateFromAssembly( string assemblyId, string generatedNamespace, string generatedClass, object context, TextWriter outputWriter) { this.SetError(); Assembly generatedAssembly = AssemblyCache[assemblyId]; if (generatedAssembly == null) { this.SetError(Resources.PreviouslyCompiledAssemblyNotFound); return null; } string className = generatedNamespace + "." + generatedClass; Type type; try { type = generatedAssembly.GetType(className); } catch (Exception ex) { this.SetError(Resources.UnableToCreateType + className + ": " + ex.Message); return null; } // Start with empty non-error response (if we use a writer) string result = string.Empty; using(TBaseTemplateType instance = InstantiateTemplateClass(type)) { if (instance == null) return null; if (outputWriter != null) instance.Response.SetTextWriter(outputWriter); if (!InvokeTemplateInstance(instance, context)) return null; // Capture string output if implemented and return // otherwise null is returned if (outputWriter == null) result = instance.Response.ToString(); } return result; } protected virtual TBaseTemplateType InstantiateTemplateClass(Type type) { TBaseTemplateType instance = Activator.CreateInstance(type) as TBaseTemplateType; if (instance == null) { SetError(Resources.CouldnTActivateTypeInstance + type.FullName); return null; } instance.Engine = this; // If a HostContainer was set pass that to the template too instance.HostContainer = this.HostContainer; return instance; } /// <summary> /// Internally executes an instance of the template, /// captures errors on execution and returns true or false /// </summary> /// <param name="instance">An instance of the generated template</param> /// <returns>true or false - check ErrorMessage for errors</returns> protected virtual bool InvokeTemplateInstance(TBaseTemplateType instance, object context) { try { instance.Context = context; instance.Execute(); } catch (Exception ex) { this.SetError(Resources.TemplateExecutionError + ex.Message); return false; } finally { // Must make sure Response is closed instance.Response.Dispose(); } return true; } The RenderTemplateFromAssembly method basically requires the namespace and class to instantate and creates an instance of the class using InstantiateTemplateClass(). It then invokes the method with InvokeTemplateInstance(). These two methods are broken out because they are re-used by various other rendering methods and also to allow subclassing and providing additional configuration tasks to set properties and pass values to templates at execution time. In the default mode instantiation sets the Engine and HostContainer (discussed later) so the template can call back into the template engine, and the context is set when the template method is invoked. The various RenderXXX methods use similar code although they create the assemblies first. If you’re after potentially cashing assemblies the method is the one to call and that’s exactly what the two HostContainer classes do. More on that in a minute, but before we get into HostContainers let’s talk about AppDomain hosting and the like. Running Templates in their own AppDomain With the RazorEngine class above, when a template is parsed into an assembly and executed the assembly is created (in memory or on disk – you can configure that) and cached in the current AppDomain. In .NET once an assembly has been loaded it can never be unloaded so if you’re loading lots of templates and at some time you want to release them there’s no way to do so. If however you load the assemblies in a separate AppDomain that new AppDomain can be unloaded and the assemblies loaded in it with it. In order to host the templates in a separate AppDomain the easiest thing to do is to run the entire RazorEngine in a separate AppDomain. Then all interaction occurs in the other AppDomain and no further changes have to be made. To facilitate this there is a RazorEngineFactory which has methods that can instantiate the RazorHost in a separate AppDomain as well as in the local AppDomain. The host creates the remote instance and then hangs on to it to keep it alive as well as providing methods to shut down the AppDomain and reload the engine. Sounds complicated but cross-AppDomain invocation is actually fairly easy to implement. Here’s some of the relevant code from the RazorEngineFactory class. Like the RazorEngine this class is generic and requires a template base type in the generic class name: public class RazorEngineFactory<TBaseTemplateType> where TBaseTemplateType : RazorTemplateBase Here are the key methods of interest: /// <summary> /// Creates an instance of the RazorHost in a new AppDomain. This /// version creates a static singleton that that is cached and you /// can call UnloadRazorHostInAppDomain to unload it. /// </summary> /// <returns></returns> public static RazorEngine<TBaseTemplateType> CreateRazorHostInAppDomain() { if (Current == null) Current = new RazorEngineFactory<TBaseTemplateType>(); return Current.GetRazorHostInAppDomain(); } public static void UnloadRazorHostInAppDomain() { if (Current != null) Current.UnloadHost(); Current = null; } /// <summary> /// Instance method that creates a RazorHost in a new AppDomain. /// This method requires that you keep the Factory around in /// order to keep the AppDomain alive and be able to unload it. /// </summary> /// <returns></returns> public RazorEngine<TBaseTemplateType> GetRazorHostInAppDomain() { LocalAppDomain = CreateAppDomain(null); if (LocalAppDomain == null) return null; /// Create the instance inside of the new AppDomain /// Note: remote domain uses local EXE's AppBasePath!!! RazorEngine<TBaseTemplateType> host = null; try { Assembly ass = Assembly.GetExecutingAssembly(); string AssemblyPath = ass.Location; host = (RazorEngine<TBaseTemplateType>) LocalAppDomain.CreateInstanceFrom(AssemblyPath, typeof(RazorEngine<TBaseTemplateType>).FullName).Unwrap(); } catch (Exception ex) { ErrorMessage = ex.Message; return null; } return host; } /// <summary> /// Internally creates a new AppDomain in which Razor templates can /// be run. /// </summary> /// <param name="appDomainName"></param> /// <returns></returns> private AppDomain CreateAppDomain(string appDomainName) { if (appDomainName == null) appDomainName = "RazorHost_" + Guid.NewGuid().ToString("n"); AppDomainSetup setup = new AppDomainSetup(); // *** Point at current directory setup.ApplicationBase = AppDomain.CurrentDomain.BaseDirectory; AppDomain localDomain = AppDomain.CreateDomain(appDomainName, null, setup); return localDomain; } /// <summary> /// Allow unloading of the created AppDomain to release resources /// All internal resources in the AppDomain are released including /// in memory compiled Razor assemblies. /// </summary> public void UnloadHost() { if (this.LocalAppDomain != null) { AppDomain.Unload(this.LocalAppDomain); this.LocalAppDomain = null; } } The static CreateRazorHostInAppDomain() is the key method that startup code usually calls. It uses a Current singleton instance to an instance of itself that is created cross AppDomain and is kept alive because it’s static. GetRazorHostInAppDomain actually creates a cross-AppDomain instance which first creates a new AppDomain and then loads the RazorEngine into it. The remote Proxy instance is returned as a result to the method and can be used the same as a local instance. The code to run with a remote AppDomain is simple: private RazorEngine<RazorTemplateBase> CreateHost() { if (this.Host != null) return this.Host; // Use Static Methods - no error message if host doesn't load this.Host = RazorEngineFactory<RazorTemplateBase>.CreateRazorHostInAppDomain(); if (this.Host == null) { MessageBox.Show("Unable to load Razor Template Host", "Razor Hosting", MessageBoxButtons.OK, MessageBoxIcon.Exclamation); } return this.Host; } This code relies on a local reference of the Host which is kept around for the duration of the app (in this case a form reference). To use this you’d simply do: this.Host = CreateHost(); if (host == null) return; string result = host.RenderTemplate( this.txtSource.Text, new string[] { "System.Windows.Forms.dll", "Westwind.Utilities.dll" }, this.CustomContext); if (result == null) { MessageBox.Show(host.ErrorMessage, "Template Execution Error", MessageBoxButtons.OK, MessageBoxIcon.Exclamation); return; } this.txtResult.Text = result; Now all templates run in a remote AppDomain and can be unloaded with simple code like this: RazorEngineFactory<RazorTemplateBase>.UnloadRazorHostInAppDomain(); this.Host = null; One Step further – Providing a caching ‘Runtime’ Once we can load templates in a remote AppDomain we can add some additional functionality like assembly caching based on application specific features. One of my typical scenarios is to render templates out of a scripts folder. So all templates live in a folder and they change infrequently. So a Folder based host that can compile these templates once and then only recompile them if something changes would be ideal. Enter host containers which are basically wrappers around the RazorEngine<t> and RazorEngineFactory<t>. They provide additional logic for things like file caching based on changes on disk or string hashes for string based template inputs. The folder host also provides for partial rendering logic through a custom template base implementation. There’s a base implementation in RazorBaseHostContainer, which provides the basics for hosting a RazorEngine, which includes the ability to start and stop the engine, cache assemblies and add references: public abstract class RazorBaseHostContainer<TBaseTemplateType> : MarshalByRefObject where TBaseTemplateType : RazorTemplateBase, new() { public RazorBaseHostContainer() { UseAppDomain = true; GeneratedNamespace = "__RazorHost"; } /// <summary> /// Determines whether the Container hosts Razor /// in a separate AppDomain. Seperate AppDomain /// hosting allows unloading and releasing of /// resources. /// </summary> public bool UseAppDomain { get; set; } /// <summary> /// Base folder location where the AppDomain /// is hosted. By default uses the same folder /// as the host application. /// /// Determines where binary dependencies are /// found for assembly references. /// </summary> public string BaseBinaryFolder { get; set; } /// <summary> /// List of referenced assemblies as string values. /// Must be in GAC or in the current folder of the host app/ /// base BinaryFolder /// </summary> public List<string> ReferencedAssemblies = new List<string>(); /// <summary> /// Name of the generated namespace for template classes /// </summary> public string GeneratedNamespace {get; set; } /// <summary> /// Any error messages /// </summary> public string ErrorMessage { get; set; } /// <summary> /// Cached instance of the Host. Required to keep the /// reference to the host alive for multiple uses. /// </summary> public RazorEngine<TBaseTemplateType> Engine; /// <summary> /// Cached instance of the Host Factory - so we can unload /// the host and its associated AppDomain. /// </summary> protected RazorEngineFactory<TBaseTemplateType> EngineFactory; /// <summary> /// Keep track of each compiled assembly /// and when it was compiled. /// /// Use a hash of the string to identify string /// changes. /// </summary> protected Dictionary<int, CompiledAssemblyItem> LoadedAssemblies = new Dictionary<int, CompiledAssemblyItem>(); /// <summary> /// Call to start the Host running. Follow by a calls to RenderTemplate to /// render individual templates. Call Stop when done. /// </summary> /// <returns>true or false - check ErrorMessage on false </returns> public virtual bool Start() { if (Engine == null) { if (UseAppDomain) Engine = RazorEngineFactory<TBaseTemplateType>.CreateRazorHostInAppDomain(); else Engine = RazorEngineFactory<TBaseTemplateType>.CreateRazorHost(); Engine.Configuration.CompileToMemory = true; Engine.HostContainer = this; if (Engine == null) { this.ErrorMessage = EngineFactory.ErrorMessage; return false; } } return true; } /// <summary> /// Stops the Host and releases the host AppDomain and cached /// assemblies. /// </summary> /// <returns>true or false</returns> public bool Stop() { this.LoadedAssemblies.Clear(); RazorEngineFactory<RazorTemplateBase>.UnloadRazorHostInAppDomain(); this.Engine = null; return true; } … } This base class provides most of the mechanics to host the runtime, but no application specific implementation for rendering. There are rendering functions but they just call the engine directly and provide no caching – there’s no context to decide how to cache and reuse templates. The key methods are Start and Stop and their main purpose is to start a new AppDomain (optionally) and shut it down when requested. The RazorFolderHostContainer – Folder Based Runtime Hosting Let’s look at the more application specific RazorFolderHostContainer implementation which is defined like this: public class RazorFolderHostContainer : RazorBaseHostContainer<RazorTemplateFolderHost> Note that a customized RazorTemplateFolderHost class template is used for this implementation that supports partial rendering in form of a RenderPartial() method that’s available to templates. The folder host’s features are: Render templates based on a Template Base Path (a ‘virtual’ if you will) Cache compiled assemblies based on the relative path and file time stamp File changes on templates cause templates to be recompiled into new assemblies Support for partial rendering using base folder relative pathing As shown in the startup examples earlier host containers require some startup code with a HostContainer tied to a persistent property (like a Form property): // The base path for templates - templates are rendered with relative paths // based on this path. HostContainer.TemplatePath = Path.Combine(Environment.CurrentDirectory, TemplateBaseFolder); // Default output rendering disk location HostContainer.RenderingOutputFile = Path.Combine(HostContainer.TemplatePath, "__Preview.htm"); // Add any assemblies you want reference in your templates HostContainer.ReferencedAssemblies.Add("System.Windows.Forms.dll"); // Start up the host container HostContainer.Start(); Once that’s done, you can render templates with the host container: // Pass the template path for full filename seleted with OpenFile Dialog // relativepath is: subdir\file.cshtml or file.cshtml or ..\file.cshtml var relativePath = Utilities.GetRelativePath(fileName, HostContainer.TemplatePath); if (!HostContainer.RenderTemplate(relativePath, Context, HostContainer.RenderingOutputFile)) { MessageBox.Show("Error: " + HostContainer.ErrorMessage); return; } webBrowser1.Navigate("file://" + HostContainer.RenderingOutputFile); The most critical task of the RazorFolderHostContainer implementation is to retrieve a template from disk, compile and cache it and then deal with deciding whether subsequent requests need to re-compile the template or simply use a cached version. Internally the GetAssemblyFromFileAndCache() handles this task: /// <summary> /// Internally checks if a cached assembly exists and if it does uses it /// else creates and compiles one. Returns an assembly Id to be /// used with the LoadedAssembly list. /// </summary> /// <param name="relativePath"></param> /// <param name="context"></param> /// <returns></returns> protected virtual CompiledAssemblyItem GetAssemblyFromFileAndCache(string relativePath) { string fileName = Path.Combine(TemplatePath, relativePath).ToLower(); int fileNameHash = fileName.GetHashCode(); if (!File.Exists(fileName)) { this.SetError(Resources.TemplateFileDoesnTExist + fileName); return null; } CompiledAssemblyItem item = null; this.LoadedAssemblies.TryGetValue(fileNameHash, out item); string assemblyId = null; // Check for cached instance if (item != null) { var fileTime = File.GetLastWriteTimeUtc(fileName); if (fileTime <= item.CompileTimeUtc) assemblyId = item.AssemblyId; } else item = new CompiledAssemblyItem(); // No cached instance - create assembly and cache if (assemblyId == null) { string safeClassName = GetSafeClassName(fileName); StreamReader reader = null; try { reader = new StreamReader(fileName, true); } catch (Exception ex) { this.SetError(Resources.ErrorReadingTemplateFile + fileName); return null; } assemblyId = Engine.ParseAndCompileTemplate(this.ReferencedAssemblies.ToArray(), reader); // need to ensure reader is closed if (reader != null) reader.Close(); if (assemblyId == null) { this.SetError(Engine.ErrorMessage); return null; } item.AssemblyId = assemblyId; item.CompileTimeUtc = DateTime.UtcNow; item.FileName = fileName; item.SafeClassName = safeClassName; this.LoadedAssemblies[fileNameHash] = item; } return item; } This code uses a LoadedAssembly dictionary which is comprised of a structure that holds a reference to a compiled assembly, a full filename and file timestamp and an assembly id. LoadedAssemblies (defined on the base class shown earlier) is essentially a cache for compiled assemblies and they are identified by a hash id. In the case of files the hash is a GetHashCode() from the full filename of the template. The template is checked for in the cache and if not found the file stamp is checked. If that’s newer than the cache’s compilation date the template is recompiled otherwise the version in the cache is used. All the core work defers to a RazorEngine<T> instance to ParseAndCompileTemplate(). The three rendering specific methods then are rather simple implementations with just a few lines of code dealing with parameter and return value parsing: /// <summary> /// Renders a template to a TextWriter. Useful to write output into a stream or /// the Response object. Used for partial rendering. /// </summary> /// <param name="relativePath">Relative path to the file in the folder structure</param> /// <param name="context">Optional context object or null</param> /// <param name="writer">The textwriter to write output into</param> /// <returns></returns> public bool RenderTemplate(string relativePath, object context, TextWriter writer) { // Set configuration data that is to be passed to the template (any object) Engine.TemplatePerRequestConfigurationData = new RazorFolderHostTemplateConfiguration() { TemplatePath = Path.Combine(this.TemplatePath, relativePath), TemplateRelativePath = relativePath, }; CompiledAssemblyItem item = GetAssemblyFromFileAndCache(relativePath); if (item == null) { writer.Close(); return false; } try { // String result will be empty as output will be rendered into the // Response object's stream output. However a null result denotes // an error string result = Engine.RenderTemplateFromAssembly(item.AssemblyId, context, writer); if (result == null) { this.SetError(Engine.ErrorMessage); return false; } } catch (Exception ex) { this.SetError(ex.Message); return false; } finally { writer.Close(); } return true; } /// <summary> /// Render a template from a source file on disk to a specified outputfile. /// </summary> /// <param name="relativePath">Relative path off the template root folder. Format: path/filename.cshtml</param> /// <param name="context">Any object that will be available in the template as a dynamic of this.Context</param> /// <param name="outputFile">Optional - output file where output is written to. If not specified the /// RenderingOutputFile property is used instead /// </param> /// <returns>true if rendering succeeds, false on failure - check ErrorMessage</returns> public bool RenderTemplate(string relativePath, object context, string outputFile) { if (outputFile == null) outputFile = RenderingOutputFile; try { using (StreamWriter writer = new StreamWriter(outputFile, false, Engine.Configuration.OutputEncoding, Engine.Configuration.StreamBufferSize)) { return RenderTemplate(relativePath, context, writer); } } catch (Exception ex) { this.SetError(ex.Message); return false; } return true; } /// <summary> /// Renders a template to string. Useful for RenderTemplate /// </summary> /// <param name="relativePath"></param> /// <param name="context"></param> /// <returns></returns> public string RenderTemplateToString(string relativePath, object context) { string result = string.Empty; try { using (StringWriter writer = new StringWriter()) { // String result will be empty as output will be rendered into the // Response object's stream output. However a null result denotes // an error if (!RenderTemplate(relativePath, context, writer)) { this.SetError(Engine.ErrorMessage); return null; } result = writer.ToString(); } } catch (Exception ex) { this.SetError(ex.Message); return null; } return result; } The idea is that you can create custom host container implementations that do exactly what you want fairly easily. Take a look at both the RazorFolderHostContainer and RazorStringHostContainer classes for the basic concepts you can use to create custom implementations. Notice also that you can set the engine’s PerRequestConfigurationData() from the host container: // Set configuration data that is to be passed to the template (any object) Engine.TemplatePerRequestConfigurationData = new RazorFolderHostTemplateConfiguration() { TemplatePath = Path.Combine(this.TemplatePath, relativePath), TemplateRelativePath = relativePath, }; which when set to a non-null value is passed to the Template’s InitializeTemplate() method. This method receives an object parameter which you can cast as needed: public override void InitializeTemplate(object configurationData) { // Pick up configuration data and stuff into Request object RazorFolderHostTemplateConfiguration config = configurationData as RazorFolderHostTemplateConfiguration; this.Request.TemplatePath = config.TemplatePath; this.Request.TemplateRelativePath = config.TemplateRelativePath; } With this data you can then configure any custom properties or objects on your main template class. It’s an easy way to pass data from the HostContainer all the way down into the template. The type you use is of type object so you have to cast it yourself, and it must be serializable since it will likely run in a separate AppDomain. This might seem like an ugly way to pass data around – normally I’d use an event delegate to call back from the engine to the host, but since this is running over AppDomain boundaries events get really tricky and passing a template instance back up into the host over AppDomain boundaries doesn’t work due to serialization issues. So it’s easier to pass the data from the host down into the template using this rather clumsy approach of set and forward. It’s ugly, but it’s something that can be hidden in the host container implementation as I’ve done here. It’s also not something you have to do in every implementation so this is kind of an edge case, but I know I’ll need to pass a bunch of data in some of my applications and this will be the easiest way to do so. Summing Up Hosting the Razor runtime is something I got jazzed up about quite a bit because I have an immediate need for this type of templating/merging/scripting capability in an application I’m working on. I’ve also been using templating in many apps and it’s always been a pain to deal with. The Razor engine makes this whole experience a lot cleaner and more light weight and with these wrappers I can now plug .NET based templating into my code literally with a few lines of code. That’s something to cheer about… I hope some of you will find this useful as well… Resources The examples and code require that you download the Razor runtimes. Projects are for Visual Studio 2010 running on .NET 4.0 Platform Installer 3.0 (install WebMatrix or MVC 3 for Razor Runtimes) Latest Code in Subversion Repository Download Snapshot of the Code Documentation (CHM Help File) © Rick Strahl, West Wind Technologies, 2005-2010Posted in ASP.NET  .NET  

    Read the article

  • Parallelism in .NET – Part 19, TaskContinuationOptions

    - by Reed
    My introduction to Task continuations demonstrates continuations on the Task class.  In addition, I’ve shown how continuations allow handling of multiple tasks in a clean, concise manner.  Continuations can also be used to handle exceptional situations using a clean, simple syntax. In addition to standard Task continuations , the Task class provides some options for filtering continuations automatically.  This is handled via the TaskContinationOptions enumeration, which provides hints to the TaskScheduler that it should only continue based on the operation of the antecedent task. This is especially useful when dealing with exceptions.  For example, we can extend the sample from our earlier continuation discussion to include support for handling exceptions thrown by the Factorize method: // Get a copy of the UI-thread task scheduler up front to use later var uiScheduler = TaskScheduler.FromCurrentSynchronizationContext(); // Start our task var factorize = 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 }; }); // When we succeed, report the results to the UI factorize.ContinueWith(task => textBox1.Text = string.Format("{0}/{1} [Succeeded {2}]", task.Result.Factor1, task.Result.Factor2, task.Result.Result), CancellationToken.None, TaskContinuationOptions.NotOnFaulted, uiScheduler); // When we have an exception, report it factorize.ContinueWith(task => textBox1.Text = string.Format("Error: {0}", task.Exception.Message), CancellationToken.None, TaskContinuationOptions.OnlyOnFaulted, uiScheduler); .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; } The above code works by using a combination of features.  First, we schedule our task, the same way as in the previous example.  However, in this case, we use a different overload of Task.ContinueWith which allows us to specify both a specific TaskScheduler (in order to have your continuation run on the UI’s synchronization context) as well as a TaskContinuationOption.  In the first continuation, we tell the continuation that we only want it to run when there was not an exception by specifying TaskContinuationOptions.NotOnFaulted.  When our factorize task completes successfully, this continuation will automatically run on the UI thread, and provide the appropriate feedback. However, if the factorize task has an exception – for example, if the Factorize method throws an exception due to an improper input value, the second continuation will run.  This occurs due to the specification of TaskContinuationOptions.OnlyOnFaulted in the options.  In this case, we’ll report the error received to the user. We can use TaskContinuationOptions to filter our continuations by whether or not an exception occurred and whether or not a task was cancelled.  This allows us to handle many situations, and is especially useful when trying to maintain a valid application state without ever blocking the user interface.  The same concepts can be extended even further, and allow you to chain together many tasks based on the success of the previous ones.  Continuations can even be used to create a state machine with full error handling, all without blocking the user interface thread.

    Read the article

  • How to best integrate HTML/design with C# code in ASP.Net or ASP.Net MVC?

    - by LuftMensch
    We're working on a new ASP.Net site. The last major site we did was in classic ASP--the procedure we used there was to have the HTML completed first, then "bring it to life" with the ASP code. In the ASP.Net world, how does this work? I.e. how do the designers do their work if much of the mark-up is actually being generated by the server controls? We are also looking at ASP.Net MVC as a potential lightweight alternative. Would be very interested to know what was worked best for people in both scenarios in terms of working with the designers and integrating their work with the code.

    Read the article

  • VB.NET ASP.NET Web Application woes (VS 2008)

    - by typoknig
    Hi all, I am making my first web application with ASP.NET and I am having a rough time. I have previously created the application I am working on as a Windows Form application and it works great, but I am having problems with the HTML side of things in the web application. My issues are pretty minor, but very annoying. I have worked with websites before and CSS, but as far as I can tell I do not have direct access to a CSS when creating a web application in VS 2008. My biggest issue is the positioning of components that I have dragged onto the "Default.aspx" form. For instance, how am I supposed to float a panel next to another one if I don't have a CSS, or how am I to correctly position a label?

    Read the article

  • ASP.NET - ViewState: empty placeholder generates view state

    - by Budda
    On my web-page I have PlaceHolder, not controls are loaded into it. <asp:PlaceHolder ID="PlaceHolderStatMain" runat="server"> </asp:PlaceHolder> I am looking the ViewState generated for the page, it is the following: <input type="hidden" name="__VIEWSTATE" id="__VIEWSTATE" value="/wEPDwUJLTg1NDkyNTUzD2QWAgIDD2QWAgIND2QWAmYPZBYCAgEPZBYCZg9kFgJmD2QWBmYPFQEYL3N0YXRfc3RhZGl1bS9sZWFndWVfV0VGZAIBDxUBGC9zdGF0X3N0YWRpdW0vbGVhZ3VlX0VFRmQCAg8VARgvc3RhdF9zdGFkaXVtL2xlYWd1ZV9GQ1VkZEuSBUr5LFL6WfCehNBJgjrq0GzwWCWN2qlU70V7LAAb" /> When I set EnableViewState to false: <asp:PlaceHolder ID="PlaceHolderStatMain" runat="server" EnableViewState="false"> </asp:PlaceHolder> The viewstate content was decreased significantly: <input type="hidden" name="__VIEWSTATE" id="__VIEWSTATE" value="/wEPDwUJLTg1NDkyNTUzZGTTn8Y28VwmpE/K7yPPkLFvhrqMdU8THijFW/BMFzk0tQ==" /> Question: how to remove 'useless' viewstate content without disabling viewstate for placeholder himself (I would like other control loaded into placeholder to has viewstate)? Is it possible at all? Any thought are welcome! P.S. I am using ASP.NET 4.0

    Read the article

  • how to set previously selected radio button checked in classic asp after page is postbacked

    - by Nikhil Vaghela
    I have never worked on classic ASP and unfortunately i am supposed to modify an old classisc ASP web site. ASP.Net ViewState does take care of maintaining control's sate automatically. How do i do it in classic ASP ? I have two radio buttons and a text box placed on my ASP page, when user types in something in the text box based on radio button selection we display different search results. Now what i need is to keep the previously selected radio button as checked after the page is postbacked. How do i do that ?

    Read the article

  • Monitoring .NET ASP.NET Applications

    - by James Hollingworth
    I have a number of applications running on top of ASP.NET I want to monitor. The main things I care about are: Exceptions: We currently some custom code which will email us when an exception occurs. If the application is failing hard it will crash our outlook... I know (and use) elmah which partly solves the problem however it is still just a big table of exceptions with a pretty(ish) UI. I want something that makes sense of all of these exceptions (e.g. groups exceptions, alerts when new ones occur, tells me what the common ones are that I should fix, etc) Logging: We currently log to files which are then accessible via a shared folder which dev's grep & tail. Does anyone know of better ways of presenting this information. In an ideal world I want to associate it with exceptions. Performance: Request times, memory usage, cpu, etc. whatever stats I can get I'm guessing this is probably going to be solved by a number of tools, has anyone got any suggestions?

    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

  • ASP.NET MVC: What is the lifetime of a Controller instance?

    - by Kivin
    I was unable to find any documentation on the MSDN site. Is the lifetime (construction and disposition) of the Controller object defined in the ASP.NET MVC Spec? The reason for this question is to determine whether or not it is safe to store contextual information in Controller members/properties or whether using the HttpContext would be more appropriate.

    Read the article

  • 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

    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

  • 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  

    Read the article

  • 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.

    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 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.

    Read the article

  • 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>.

    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 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.

    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

< Previous Page | 36 37 38 39 40 41 42 43 44 45 46 47  | Next Page >