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  • mac osx script - find mounted disc with name, copy file from desktop to it, when copy complete, unmount disc

    - by Joshc
    Is there some kind of mac script which finds a newly mounted disc drive that has the name 'EXAMPLE', then copies a file/folder to it and safely ejects the disc when copy has finished? I don't mind if the script needs to be executed by a short cut. And will it work if there are multiple drives plugged in? The reason I am asking is becuase i have 5000 usb memory sticks that I need to copy about 20mb worth of data to it. Thanks in advance for any ideas.

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  • ServerName no longer works as SQL Server 2008 Default instance name?

    - by TomK
    Folks, Somehow in struggling to install something (Sage MIP), I have unsettled my system's SQL Server 2008 instance names. If I fired up SSMS and connected to "MySystemName" (while logged into MySystemName), I used to immediately connect and could view my databases. Now if I connect to "(local)" or "." I connect just fine...but "MySystemName" gives me a timeout error. If I log in with "." and do "SELECT @@SERVERNAME" it comes back with "MySystemName" just fine. I've double checked that my network name is in the Security\Logins list, and it is, as a dbadmin. Any suggestions? I thought that having SQL Server 2005 Express might be a problem (the "battle of the default instances"), so I uninstalled that. No better.

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  • HOw to deny a particular mac address client not to obtain ip/name from dhcp & dns server..

    - by Deepak Narwal
    Hello Friends... I configures DHCP server on my rhel 5.4 machine.Clients are getting ip from this DHCP server.NO problem upto this.. NOw i want that a particular mac address client do not pick ip from this dhcp server.. Same question is with my DNS server. I want that a particular mac address client do not pick name from this dns server.. PLz discuss in little bit details i am very new in this field.I am learning these things.I hope YOu will give detailed explaiantion.. Thanks IN ADvance friends..

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  • Color drop down in Excel cell (with no text)? e.g. bgcolor = Red-Green-Amber-unknown

    - by adolf garlic
    I have an Excel sheet that I'm using to keep track of the status of certain things. I want to have a column which consists of cells containing a repeated drop down that allows you to select (as background) red amber green unknown I don't want any text in this cell, I just want a coloured block. Is this possible? I've tried playing around with data-validation-list (based on range containing all of said colours but to no avail)

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  • How can I resolve this error when using net start / stop: "The service name is invalid" ?

    - by JosephStyons
    We have a server that hosts a service (I'll call it "tomato"). Up until now, a client pc has been able to start and stop this service. They just double-click a batch file, and inside that batch file is the command net stop tomato or net start tomato They recently got a new physical computer, and now those same commands fail with the error: C:\>net stop tomato The service name is invalid. More help is available by typing NET HELPMSG 2185. What do I need to do to let the client pc start and stop this service remotely? Edit: I mis-remembered the original commands. They were not using "net start" and "net stop" remotely. They were using sc \\server_name start tomato and sc \\server_name stop tomato And those commands to indeed still work.

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  • wildcard host name bindings for multiple subdomains in multiple sites on IIS7 with a single IP address

    - by orca
    Situation: I have a single windows 2008 server with a single public IP address. I have multiple domains with wildcard A records pointing to the single IP address. I need each domain to be hosted by a different web site. (i.e. www.domain1.com by site domain1site) I need domain1.com to act like www.domain1.com I need each site to be able to have multiple subdomains (i.e. www.domain1.com, abc.domain1.com, xyz.domain1.com) Not relevant yet here it goes, I plan to handle each subdomain by a different application hosted in the same site (i.e. application /xyz in domain1site) However I found out that IIS7 does not support creating web sites with wildcard host name binding and setting it without any subdomain (i.e. domain1.com) does not work, even for www.domain1.com. Is there a simple solution? Does any IIS Extension like Application Request Routing provide such capability?

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  • Is there a way to backup all my files and replace with 0-byte files with same name?

    - by laggingreflex
    My main drive on laptop keeps filling up so I take a backup on a USB and delete the original files. But then I find myself getting (downloading or getting from someone else) files that I already have backed-up but couldn't recall at the moment. So is there a way I can keep a 0-byte file with the same name as teh backed-up copy so that when I'm asked whether to overwrite the existing file, I can easily choose no knowing I probably have this file already in the backup. EDIT: better yet, replace with a shortcut(.lnk) on the external drive so I can access the files hassle free and not get any errors because of 0-byte files being accidentally opened.

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  • What is the canonical name for domain names with extra parts?

    - by ConfusedFromIreland
    I am confused about domain names (I think) I call these things, i.e. names you can buy, 'domain names' bbc.co.uk google.com I call these things, i.e. extensions of names 'host names' www.bbc.co.uk mail.yahoo.com arts.mit.edu hello.there.example.com Is this naming scheme correct? Are there official definitions of these? In particular, what are each of the texts between the dots called (i.e. the name for "www", "bbc", "edu", "example")?

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  • When opening any file in excel, a 1 is added to ther name, and the default is to save a new copy…

    - by Chris
    Ok... I've searched a lot for this, but it's not an easy question to search for! When I open any files (xls, or xlsx) in Excel 2007, excel acts like it's a read only file, essentially creating a new file with the name plus a 1 on the end... Eg. I open NewDoc.xlsx Excel opens it as NewDoc1.xlsx and the save button brings up the save as dialogue in my default folder. Does anyone know how to set it back to allowing me to open, edit and save a document without having to browse to the original document and save over it!? My immediate thought was access permissions, but the file is in a network folder with my user given Full Control, I also tried creating a new file in that folder, and also on my local machine just in case - same result. To make it even stranger, if I browse to the original file using the save as dialogue, it will let me save over the original, without any further prompts.

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  • How to mount a iSCSI/SAN storage drive to a stable device name (one that can't change on re-connect)?

    - by jcalfee314
    We need stable device paths for our Twinstrata SAN drives. Many guides for setting up iSCSI connectors simply say to use a device path like /dev/sda or /dev/sdb. This is far from correct, I doubt that any setup exists that would be happy to have its device name suddenly change (from /dev/sda to /dev/sdb for example). The fix I found was to install multipath and start a multipathd on boot which then provides a stable mapping between the storage's WWID to a device path like this /dev/mapper/firebird_database. This is a method described in the CentOS/RedHat here: http://www.centos.org/docs/5/html/5.1/DM_Multipath/setup_procedure.html. This seems a little complicated though. We noticed that it is common to see UUIDs appear in fstab on new installs. So, the question is, why do we need an external program (multipathd) running to provide a stable device mount? Should there be a way to provide the WWID directly in /etc/fstab?

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  • Script to run chown on all folders and setting the owner as the folder name minus the trailing /

    - by Shikoki
    Some numpty ran chown -R username. in the /home folder on our webserver thinking he was in the desired folder. Needless to say the server is throwing a lot of wobbelys. We have over 200 websites and I don't want to chown them all individually so I'm trying to make a script that will change the owner of all the folders to the folder name, without the trailing /. This is all I have so far, once I can remove the / it will be fine, but I'd also like to check if the file contains a . in it, and if it doesn't then run the command, otherwise go to the next one. #!/bin/bash for f in * do test=$f; #manipluate the test variable chown -R $test $f done Any help would be great! Thanks in advance!

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  • How do I find all text with particular background color?

    - by Dave M G
    I have a LibreOffice Writer document that has undergone a process of editing, and sections of the text that needed to be rewritten were highlighted in yellow. As I fixed those sections, I removed the yellow highlight. Now, I want to make sure there are no remaining areas of highlighted text that have not been fixed or possibly the highlight was not removed. It's many hundreds of pages, so a manual scan is unfeasible. Also, it might be that one space or one character got accidentally left highlighted, and I want to ensure I've accounted for them all. How can I search the document to find all instances where text has been highlighted?

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  • SQL ERROR: Verify that the instance name is correct and that SQL Server is configured to allow remote connections?

    - by scepak
    I am getting following error while connecting to my local Sql Express. An error has occurred. Details of the exception: A network-related or instance-specific error occurred while establishing a conne ction to SQL Server. The server was not found or was not accessible. Verify that the instance name is correct and that SQL Server is configured to allow remote connections. (provider: SQL Network Interfaces, error: 26 - Error Locating Serve r/Instance Specified) Unable to connect to SQL Server database. I am able to connect to Sql Server using Management Studio.

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  • How to make RHEL have persistent local hdd name?

    - by Mxx
    I have 2 identical Dell R720 servers running identical Oracle Enterprise Linux(RHEL)6.4. Both servers (supposedly) configured in exactly the same way. However, one of the servers is behaving differently. Every other reboot its local HDD name(and related partitions) flip from /dev/sda to /dev/sdj. This is problematic because both servers are configured for multipathd, and if this flip happens their config does not match and Oracle DB(or its clusterware) complains that nodes are not configured identically. Why does one server has a consistent device names while the other server keeps flipping back and forth? How can I make local hdd to consistently be /dev/sda? I suspect this might have something to do with udev but I'm not sure.

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  • How to configure S3 or DNS to handle incomplete name (sans www) for web site?

    - by user193116
    I have a set up a bucket called "www.mydomainname.com" to host my website and I have configured the CNAME such that "www.mydomainname.com" points to the my endopint http://www.mydomainname.com.s3-website-us-east-1.amazonaws.com/ It works and when people who type the the full url "www.mydomainname.com" are able to see my index page But most people are in the habit of typing incoplete domain name -- they just type "mydomainname.com" and their browser fails to find my site. Is there a way to configure CName or S3 bucket such that typing "mydomainname.com" take them to my s3 website ? (I am using Networksolutions as my DNS provider).

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  • websites resolving in browser but not resolving in CLI. Can ping IP but not domain name (unknown host)

    - by tjkoding
    Hi guys I'm currently developing using rails and for some reason bundle install is returning the following output Error Bundler::HTTPError during request to dependency API Fetching full source index from https://rubygems.org/ Could not reach https://rubygems.org/ I've discovered that pinging by domain name keeps returning an unknown host. The browser is still resolving web pages just fine and I've managed to confirm that the problem is localized (i.e. the rubygems page isn't down). I'm completely lost so any help would be much appreciated. Thanks in advance!

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  • what TERM to use to get rid of color escape codes?

    - by slivu
    Is there a way to get rid of escape codes in terminal output? Say even if the script are sending that codes they are ignored by terminal and text displayed as is, without colors, bolds etc. I need to display terminal output on a HTML page. For now i'm using javascript to remove escape codes, but it becomes clunky cause i receive output by chars, and have to wait until all content received then update it, leading in weird effects.

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  • 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  

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  • PowerShell Script to Deploy Multiple VM on Azure in Parallel #azure #powershell

    - by Marco Russo (SQLBI)
    This blog is usually dedicated to Business Intelligence and SQL Server, but I didn’t found easily on the web simple PowerShell scripts to help me deploying a number of virtual machines on Azure that I use for testing and development. Since I need to deploy, start, stop and remove many virtual machines created from a common image I created (you know, Tabular is not part of the standard images provided by Microsoft…), I wanted to minimize the time required to execute every operation from my Windows Azure PowerShell console (but I suggest you using Windows PowerShell ISE), so I also wanted to fire the commands as soon as possible in parallel, without losing the result in the console. In order to execute multiple commands in parallel, I used the Start-Job cmdlet, and using Get-Job and Receive-Job I wait for job completion and display the messages generated during background command execution. This technique allows me to reduce execution time when I have to deploy, start, stop or remove virtual machines. Please note that a few operations on Azure acquire an exclusive lock and cannot be really executed in parallel, but only one part of their execution time is subject to this lock. Thus, you obtain a better response time also in these scenarios (this is the case of the provisioning of a new VM). Finally, when you remove the VMs you still have the disk containing the virtual machine to remove. This cannot be done just after the VM removal, because you have to wait that the removal operation is completed on Azure. So I wrote a script that you have to run a few minutes after VMs removal and delete disks (and VHD) no longer related to a VM. I just check that the disk were associated to the original image name used to provision the VMs (so I don’t remove other disks deployed by other batches that I might want to preserve). These examples are specific for my scenario, if you need more complex configurations you have to change and adapt the code. But if your need is to create multiple instances of the same VM running in a workgroup, these scripts should be good enough. I prepared the following PowerShell scripts: ProvisionVMs: Provision many VMs in parallel starting from the same image. It creates one service for each VM. RemoveVMs: Remove all the VMs in parallel – it also remove the service created for the VM StartVMs: Starts all the VMs in parallel StopVMs: Stops all the VMs in parallel RemoveOrphanDisks: Remove all the disks no longer used by any VMs. Run this script a few minutes after RemoveVMs script. ProvisionVMs # Name of subscription $SubscriptionName = "Copy the SubscriptionName property you get from Get-AzureSubscription"   # Name of storage account (where VMs will be deployed) $StorageAccount = "Copy the Label property you get from Get-AzureStorageAccount"   function ProvisionVM( [string]$VmName ) {     Start-Job -ArgumentList $VmName {         param($VmName) $Location = "Copy the Location property you get from Get-AzureStorageAccount" $InstanceSize = "A5" # You can use any other instance, such as Large, A6, and so on $AdminUsername = "UserName" # Write the name of the administrator account in the new VM $Password = "Password"      # Write the password of the administrator account in the new VM $Image = "Copy the ImageName property you get from Get-AzureVMImage" # You can list your own images using the following command: # Get-AzureVMImage | Where-Object {$_.PublisherName -eq "User" }         New-AzureVMConfig -Name $VmName -ImageName $Image -InstanceSize $InstanceSize |             Add-AzureProvisioningConfig -Windows -Password $Password -AdminUsername $AdminUsername|             New-AzureVM -Location $Location -ServiceName "$VmName" -Verbose     } }   # Set the proper storage - you might remove this line if you have only one storage in the subscription Set-AzureSubscription -SubscriptionName $SubscriptionName -CurrentStorageAccount $StorageAccount   # Select the subscription - this line is fundamental if you have access to multiple subscription # You might remove this line if you have only one subscription Select-AzureSubscription -SubscriptionName $SubscriptionName   # Every line in the following list provisions one VM using the name specified in the argument # You can change the number of lines - use a unique name for every VM - don't reuse names # already used in other VMs already deployed ProvisionVM "test10" ProvisionVM "test11" ProvisionVM "test12" ProvisionVM "test13" ProvisionVM "test14" ProvisionVM "test15" ProvisionVM "test16" ProvisionVM "test17" ProvisionVM "test18" ProvisionVM "test19" ProvisionVM "test20"   # Wait for all to complete While (Get-Job -State "Running") {     Get-Job -State "Completed" | Receive-Job     Start-Sleep 1 }   # Display output from all jobs Get-Job | Receive-Job   # Cleanup of jobs Remove-Job *   # Displays batch completed echo "Provisioning VM Completed" RemoveVMs # Name of subscription $SubscriptionName = "Copy the SubscriptionName property you get from Get-AzureSubscription"   function RemoveVM( [string]$VmName ) {     Start-Job -ArgumentList $VmName {         param($VmName)         Remove-AzureService -ServiceName $VmName -Force -Verbose     } }   # Select the subscription - this line is fundamental if you have access to multiple subscription # You might remove this line if you have only one subscription Select-AzureSubscription -SubscriptionName $SubscriptionName   # Every line in the following list remove one VM using the name specified in the argument # You can change the number of lines - use a unique name for every VM - don't reuse names # already used in other VMs already deployed RemoveVM "test10" RemoveVM "test11" RemoveVM "test12" RemoveVM "test13" RemoveVM "test14" RemoveVM "test15" RemoveVM "test16" RemoveVM "test17" RemoveVM "test18" RemoveVM "test19" RemoveVM "test20"   # Wait for all to complete While (Get-Job -State "Running") {     Get-Job -State "Completed" | Receive-Job     Start-Sleep 1 }   # Display output from all jobs Get-Job | Receive-Job   # Cleanup Remove-Job *   # Displays batch completed echo "Remove VM Completed" StartVMs # Name of subscription $SubscriptionName = "Copy the SubscriptionName property you get from Get-AzureSubscription"   function StartVM( [string]$VmName ) {     Start-Job -ArgumentList $VmName {         param($VmName)         Start-AzureVM -Name $VmName -ServiceName $VmName -Verbose     } }   # Select the subscription - this line is fundamental if you have access to multiple subscription # You might remove this line if you have only one subscription Select-AzureSubscription -SubscriptionName $SubscriptionName   # Every line in the following list starts one VM using the name specified in the argument # You can change the number of lines - use a unique name for every VM - don't reuse names # already used in other VMs already deployed StartVM "test10" StartVM "test11" StartVM "test11" StartVM "test12" StartVM "test13" StartVM "test14" StartVM "test15" StartVM "test16" StartVM "test17" StartVM "test18" StartVM "test19" StartVM "test20"   # Wait for all to complete While (Get-Job -State "Running") {     Get-Job -State "Completed" | Receive-Job     Start-Sleep 1 }   # Display output from all jobs Get-Job | Receive-Job   # Cleanup Remove-Job *   # Displays batch completed echo "Start VM Completed"   StopVMs # Name of subscription $SubscriptionName = "Copy the SubscriptionName property you get from Get-AzureSubscription"   function StopVM( [string]$VmName ) {     Start-Job -ArgumentList $VmName {         param($VmName)         Stop-AzureVM -Name $VmName -ServiceName $VmName -Verbose -Force     } }   # Select the subscription - this line is fundamental if you have access to multiple subscription # You might remove this line if you have only one subscription Select-AzureSubscription -SubscriptionName $SubscriptionName   # Every line in the following list stops one VM using the name specified in the argument # You can change the number of lines - use a unique name for every VM - don't reuse names # already used in other VMs already deployed StopVM "test10" StopVM "test11" StopVM "test12" StopVM "test13" StopVM "test14" StopVM "test15" StopVM "test16" StopVM "test17" StopVM "test18" StopVM "test19" StopVM "test20"   # Wait for all to complete While (Get-Job -State "Running") {     Get-Job -State "Completed" | Receive-Job     Start-Sleep 1 }   # Display output from all jobs Get-Job | Receive-Job   # Cleanup Remove-Job *   # Displays batch completed echo "Stop VM Completed" RemoveOrphanDisks $Image = "Copy the ImageName property you get from Get-AzureVMImage" # You can list your own images using the following command: # Get-AzureVMImage | Where-Object {$_.PublisherName -eq "User" }   # Remove all orphan disks coming from the image specified in $ImageName Get-AzureDisk |     Where-Object {$_.attachedto -eq $null -and $_.SourceImageName -eq $ImageName} |     Remove-AzureDisk -DeleteVHD -Verbose  

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

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

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

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

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

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

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

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

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

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

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