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  • &lt;%: %&gt;, HtmlEncode, IHtmlString and MvcHtmlString

    - by Shaun
    One of my colleague and friend, Robin is playing and struggling with the ASP.NET MVC 2 on a project these days while I’m struggling with a annoying client. Since it’s his first time to use ASP.NET MVC he was meetings with a lot of problem and I was very happy to share my experience to him. Yesterday he asked me when he attempted to insert a <br /> element into his page he found that the page was rendered like this which is bad. He found his <br /> was shown as a part of the string rather than creating a new line. After checked a bit in his code I found that it’s because he utilized a new ASP.NET markup supported in .NET 4.0 – “<%: %>”. If you have been using ASP.NET MVC 1 or in .NET 3.5 world it would be very common that using <%= %> to show something on the page from the backend code. But when you do it you must ensure that the string that are going to be displayed should be Html-safe, which means all the Html markups must be encoded. Otherwise this might cause an XSS (cross-site scripting) problem. So that you’d better use the code like this below to display anything on the page. In .NET 4.0 Microsoft introduced a new markup to solve this problem which is <%: %>. It will encode the content automatically so that you will no need to check and verify your code manually for the XSS issue mentioned below. But this also means that it will encode all things, include the Html element you want to be rendered. So I changed his code like this and it worked well. After helped him solved this problem and finished a spreadsheet for my boring project I considered a bit more on the <%: %>. Since it will encode all thing why it renders correctly when we use “<%: Html.TextBox(“name”) %>” to show a text box? As you know the Html.TextBox will render a “<input name="name" id="name" type="text"/>” element on the page. If <%: %> will encode everything it should not display a text box. So I dig into the source code of the MVC and found some comments in the class MvcHtmlString. 1: // In ASP.NET 4, a new syntax <%: %> is being introduced in WebForms pages, where <%: expression %> is equivalent to 2: // <%= HttpUtility.HtmlEncode(expression) %>. The intent of this is to reduce common causes of XSS vulnerabilities 3: // in WebForms pages (WebForms views in the case of MVC). This involves the addition of an interface 4: // System.Web.IHtmlString and a static method overload System.Web.HttpUtility::HtmlEncode(object). The interface 5: // definition is roughly: 6: // public interface IHtmlString { 7: // string ToHtmlString(); 8: // } 9: // And the HtmlEncode(object) logic is roughly: 10: // - If the input argument is an IHtmlString, return argument.ToHtmlString(), 11: // - Otherwise, return HtmlEncode(Convert.ToString(argument)). 12: // 13: // Unfortunately this has the effect that calling <%: Html.SomeHelper() %> in an MVC application running on .NET 4 14: // will end up encoding output that is already HTML-safe. As a result, we're changing out HTML helpers to return 15: // MvcHtmlString where appropriate. <%= Html.SomeHelper() %> will continue to work in both .NET 3.5 and .NET 4, but 16: // changing the return types to MvcHtmlString has the added benefit that <%: Html.SomeHelper() %> will also work 17: // properly in .NET 4 rather than resulting in a double-encoded output. MVC developers in .NET 4 will then be able 18: // to use the <%: %> syntax almost everywhere instead of having to remember where to use <%= %> and where to use 19: // <%: %>. This should help developers craft more secure web applications by default. 20: // 21: // To create an MvcHtmlString, use the static Create() method instead of calling the protected constructor. The comment said the encoding rule of the <%: %> would be: If the type of the content is IHtmlString it will NOT encode since the IHtmlString indicates that it’s Html-safe. Otherwise it will use HtmlEncode to encode the content. If we check the return type of the Html.TextBox method we will find that it’s MvcHtmlString, which was implemented the IHtmlString interface dynamically. That is the reason why the “<input name="name" id="name" type="text"/>” was not encoded by <%: %>. So if we want to tell ASP.NET MVC, or I should say the ASP.NET runtime that the content is Html-safe and no need, or should not be encoded we can convert the content into IHtmlString. So another resolution would be like this. Also we can create an extension method as well for better developing experience. 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Web; 5: using System.Web.Mvc; 6:  7: namespace ShaunXu.Blogs.IHtmlStringIssue 8: { 9: public static class Helpers 10: { 11: public static MvcHtmlString IsHtmlSafe(this string content) 12: { 13: return MvcHtmlString.Create(content); 14: } 15: } 16: } Then the view would be like this. And the page rendered correctly.         Summary In this post I explained a bit about the new markup in .NET 4.0 – <%: %> and its usage. I also explained a bit about how to control the page content, whether it should be encoded or not. We can see the ASP.NET MVC gives us more points to control the web pages.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Azure - Part 4 - Table Storage Service in Windows Azure

    - by Shaun
    In Windows Azure platform there are 3 storage we can use to save our data on the cloud. They are the Table, Blob and Queue. Before the Chinese New Year Microsoft announced that Azure SDK 1.1 had been released and it supports a new type of storage – Drive, which allows us to operate NTFS files on the cloud. I will cover it in the coming few posts but now I would like to talk a bit about the Table Storage.   Concept of Table Storage Service The most common development scenario is to retrieve, create, update and remove data from the data storage. In the normal way we communicate with database. When we attempt to move our application over to the cloud the most common requirement should be have a storage service. Windows Azure provides a in-build service that allow us to storage the structured data, which is called Windows Azure Table Storage Service. The data stored in the table service are like the collection of entities. And the entities are similar to rows or records in the tradtional database. An entity should had a partition key, a row key, a timestamp and set of properties. You can treat the partition key as a group name, the row key as a primary key and the timestamp as the identifer for solving the concurrency problem. Different with a table in a database, the table service does not enforce the schema for tables, which means you can have 2 entities in the same table with different property sets. The partition key is being used for the load balance of the Azure OS and the group entity transaction. As you know in the cloud you will never know which machine is hosting your application and your data. It could be moving based on the transaction weight and the number of the requests. If the Azure OS found that there are many requests connect to your Book entities with the partition key equals “Novel” it will move them to another idle machine to increase the performance. So when choosing the partition key for your entities you need to make sure they indecate the category or gourp information so that the Azure OS can perform the load balance as you wish.   Consuming the Table Although the table service looks like a database, you cannot access it through the way you are using now, neither ADO.NET nor ODBC. The table service exposed itself by ADO.NET Data Service protocol, which allows you can consume it through the RESTful style by Http requests. The Azure SDK provides a sets of classes for us to connect it. There are 2 classes we might need: TableServiceContext and TableServiceEntity. The TableServiceContext inherited from the DataServiceContext, which represents the runtime context of the ADO.NET data service. It provides 4 methods mainly used by us: CreateQuery: It will create a IQueryable instance from a given type of entity. AddObject: Add the specified entity into Table Service. UpdateObject: Update an existing entity in the Table Service. DeleteObject: Delete an entity from the Table Service. Beofre you operate the table service you need to provide the valid account information. It’s something like the connect string of the database but with your account name and the account key when you created the storage service on the Windows Azure Development Portal. After getting the CloudStorageAccount you can create the CloudTableClient instance which provides a set of methods for using the table service. A very useful method would be CreateTableIfNotExist. It will create the table container for you if it’s not exsited. And then you can operate the eneities to that table through the methods I mentioned above. Let me explain a bit more through an exmaple. We always like code rather than sentence.   Straightforward Accessing to the Table Here I would like to build a WCF service on the Windows Azure platform, and for now just one requirement: it would allow the client to create an account entity on the table service. The WCF service would have a method named Register and accept an instance of the account which the client wants to create. After perform some validation it will add the entity into the table service. So the first thing I should do is to create a Cloud Application on my VIstial Studio 2010 RC. (The Azure SDK 1.1 only supports VS2008 and VS2010 RC.) The solution should be like this below. Then I added a configuration items for the storage account through the Settings section under the cloud project. (Double click the Services file under Roles folder and navigate to the Setting section.) This setting will be used when to retrieve my storage account information. Since for now I just in the development phase I will select “UseDevelopmentStorage=true”. And then I navigated to the WebRole.cs file under my WCF project. If you have read my previous posts you would know that this file defines the process when the application start, and terminate on the cloud. What I need to do is to when the application start, set the configuration publisher to load my config file with the config name I specified. So the code would be like below. I removed the original service and contract created by the VS template and add my IAccountService contract and its implementation class - AccountService. And I add the service method Register with the parameters: email, password and it will return a boolean value to indicates the result which is very simple. At this moment if I press F5 the application will be established on my local development fabric and I can see my service runs well through the browser. Let’s implement the service method Rigister, add a new entity to the table service. As I said before the entities you want to store in the table service must have 3 properties: partition key, row key and timespan. You can create a class with these 3 properties. The Azure SDK provides us a base class for that named TableServiceEntity in Microsoft.WindowsAzure.StorageClient namespace. So what we need to do is more simply, create a class named Account and let it derived from the TableServiceEntity. And I need to add my own properties: Email, Password, DateCreated and DateDeleted. The DateDeleted is a nullable date time value to indecate whether this entity had been deleted and when. Do you notice that I missed something here? Yes it’s the partition key and row key I didn’t assigned. The TableServiceEntity base class defined 2 constructors one was a parameter-less constructor which will be used to fill values into the properties from the table service when retrieving data. The other was one with 2 parameters: partition key and row key. As I said below the partition key may affect the load balance and the row key must be unique so here I would like to use the email as the parition key and the email plus a Guid as the row key. OK now we finished the entity class we need to store onto the table service. The next step is to create a data access class for us to add it. Azure SDK gives us a base class for it named TableServiceContext as I mentioned below. So let’s create a class for operate the Account entities. The TableServiceContext need the storage account information for its constructor. It’s the combination of the storage service URI that we will create on Windows Azure platform, and the relevant account name and key. The TableServiceContext will use this information to find the related address and verify the account to operate the storage entities. Hence in my AccountDataContext class I need to override this constructor and pass the storage account into it. All entities will be saved in the table storage with one or many tables which we call them “table containers”. Before we operate an entity we need to make sure that the table container had been created on the storage. There’s a method we can use for that: CloudTableClient.CreateTableIfNotExist. So in the constructor I will perform it firstly to make sure all method will be invoked after the table had been created. Notice that I passed the storage account enpoint URI and the credentials to specify where my storage is located and who am I. Another advise is that, make your entity class name as the same as the table name when create the table. It will increase the performance when you operate it over the cloud especially querying. Since the Register WCF method will add a new account into the table service, here I will create a relevant method to add the account entity. Before implement, I should add a reference - System.Data.Services.Client to the project. This reference provides some common method within the ADO.NET Data Service which can be used in the Windows Azure Table Service. I will use its AddObject method to create my account entity. Since the table service are not fully implemented the ADO.NET Data Service, there are some methods in the System.Data.Services.Client that TableServiceContext doesn’t support, such as AddLinks, etc. Then I implemented the serivce method to add the account entity through the AccountDataContext. You can see in the service implmentation I load the storage account information through my configuration file and created the account table entity from the parameters. Then I created the AccountDataContext. If it’s my first time to invoke this method the constructor of the AccountDataContext will create a table container for me. Then I use Add method to add the account entity into the table. Next, let’s create a farely simple client application to test this service. I created a windows console application and added a service reference to my WCF service. The metadata information of the WCF service cannot be retrieved if it’s deployed on the Windows Azure even though the <serviceMetadata httpGetEnabled="true"/> had been set. If we need to get its metadata we can deploy it on the local development service and then changed the endpoint to the address which is on the cloud. In the client side app.config file I specified the endpoint to the local development fabric address. And the just implement the client to let me input an email and a password then invoke the WCF service to add my acocunt. Let’s run my application and see the result. Of course it should return TRUE to me. And in the local SQL Express I can see the data had been saved in the table.   Summary In this post I explained more about the Windows Azure Table Storage Service. I also created a small application for demostration of how to connect and consume it through the ADO.NET Data Service Managed Library provided within the Azure SDK. I only show how to create an eneity in the storage service. In the next post I would like to explain about how to query the entities with conditions thruogh LINQ. I also would like to refactor my AccountDataContext class to make it dyamic for any kinds of entities.   Hope this helps, Shaun   All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • First round playing with Memcached

    - by Shaun
    To be honest I have not been very interested in the caching before I’m going to a project which would be using the multi-site deployment and high connection and concurrency and very sensitive to the user experience. That means we must cache the output data for better performance. After looked for the Internet I finally focused on the Memcached. What’s the Memcached? I think the description on its main site gives us a very good and simple explanation. Free & open source, high-performance, distributed memory object caching system, generic in nature, but intended for use in speeding up dynamic web applications by alleviating database load. Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering. Memcached is simple yet powerful. Its simple design promotes quick deployment, ease of development, and solves many problems facing large data caches. Its API is available for most popular languages. The original Memcached was built on *nix system are is being widely used in the PHP world. Although it’s not a problem to use the Memcached installed on *nix system there are some windows version available fortunately. Since we are WISC (Windows – IIS – SQL Server – C#, which on the opposite of LAMP) it would be much easier for us to use the Memcached on Windows rather than *nix. I’m using the Memcached Win X64 version provided by NorthScale. There are also the x86 version and other operation system version.   Install Memcached Unpack the Memcached file to a folder on the machine you want it to be installed, we can see that there are only 3 files and the main file should be the “memcached.exe”. Memcached would be run on the server as a service. To install the service just open a command windows and navigate to the folder which contains the “memcached.exe”, let’s say “C:\Memcached\”, and then type “memcached.exe -d install”. If you are using Windows Vista and Windows 7 system please be execute the command through the administrator role. Right-click the command item in the start menu and use “Run as Administrator”, otherwise the Memcached would not be able to be installed successfully. Once installed successful we can type “memcached.exe -d start” to launch the service. Now it’s ready to be used. The default port of Memcached is 11211 but you can change it through the command argument. You can find the help by typing “memcached -h”.   Using Memcached Memcahed has many good and ready-to-use providers for vary program language. After compared and reviewed I chose the Memcached Providers. It’s built based on another 3rd party Memcached client named enyim.com Memcached Client. The Memcached Providers is very simple to set/get the cached objects through the Memcached servers and easy to be configured through the application configuration file (aka web.config and app.config). Let’s create a console application for the demonstration and add the 3 DLL files from the package of the Memcached Providers to the project reference. Then we need to add the configuration for the Memcached server. Create an App.config file and firstly add the section on top of it. Here we need three sections: the section for Memcached Providers, for enyim.com Memcached client and the log4net. 1: <configSections> 2: <section name="cacheProvider" 3: type="MemcachedProviders.Cache.CacheProviderSection, MemcachedProviders" 4: allowDefinition="MachineToApplication" 5: restartOnExternalChanges="true"/> 6: <sectionGroup name="enyim.com"> 7: <section name="memcached" 8: type="Enyim.Caching.Configuration.MemcachedClientSection, Enyim.Caching"/> 9: </sectionGroup> 10: <section name="log4net" 11: type="log4net.Config.Log4NetConfigurationSectionHandler,log4net"/> 12: </configSections> Then we will add the configuration for 3 of them in the App.config file. The Memcached server information would be defined under the enyim.com section since it will be responsible for connect to the Memcached server. Assuming I installed the Memcached on two servers with the default port, the configuration would be like this. 1: <enyim.com> 2: <memcached> 3: <servers> 4: <!-- put your own server(s) here--> 5: <add address="192.168.0.149" port="11211"/> 6: <add address="10.10.20.67" port="11211"/> 7: </servers> 8: <socketPool minPoolSize="10" maxPoolSize="100" connectionTimeout="00:00:10" deadTimeout="00:02:00"/> 9: </memcached> 10: </enyim.com> Memcached supports the multi-deployment which means you can install the Memcached on the servers as many as you need. The protocol of the Memcached responsible for routing the cached objects into the proper server. So it’s very easy to scale-out your system by Memcached. And then define the Memcached Providers configuration. The defaultExpireTime indicates how long the objected cached in the Memcached would be expired, the default value is 2000 ms. 1: <cacheProvider defaultProvider="MemcachedCacheProvider"> 2: <providers> 3: <add name="MemcachedCacheProvider" 4: type="MemcachedProviders.Cache.MemcachedCacheProvider, MemcachedProviders" 5: keySuffix="_MySuffix_" 6: defaultExpireTime="2000"/> 7: </providers> 8: </cacheProvider> The last configuration would be the log4net. 1: <log4net> 2: <!-- Define some output appenders --> 3: <appender name="ConsoleAppender" type="log4net.Appender.ConsoleAppender"> 4: <layout type="log4net.Layout.PatternLayout"> 5: <conversionPattern value="%date [%thread] %-5level %logger [%property{NDC}] - %message%newline"/> 6: </layout> 7: </appender> 8: <!--<threshold value="OFF" />--> 9: <!-- Setup the root category, add the appenders and set the default priority --> 10: <root> 11: <priority value="WARN"/> 12: <appender-ref ref="ConsoleAppender"> 13: <filter type="log4net.Filter.LevelRangeFilter"> 14: <levelMin value="WARN"/> 15: <levelMax value="FATAL"/> 16: </filter> 17: </appender-ref> 18: </root> 19: </log4net>   Get, Set and Remove the Cached Objects Once we finished the configuration it would be very simple to consume the Memcached servers. The Memcached Providers gives us a static class named DistCache that can be used to operate the Memcached servers. Get<T>: Retrieve the cached object from the Memcached servers. If failed it will return null or the default value. Add: Add an object with a unique key into the Memcached servers. Assuming that we have an operation that retrieve the email from the name which is time consuming. This is the operation that should be cached. The method would be like this. I utilized Thread.Sleep to simulate the long-time operation. 1: static string GetEmailByNameSlowly(string name) 2: { 3: Thread.Sleep(2000); 4: return name + "@ethos.com.cn"; 5: } Then in the real retrieving method we will firstly check whether the name, email information had been searched previously and cached. If yes we will just return them from the Memcached, otherwise we will invoke the slowly method to retrieve it and then cached. 1: static string GetEmailByName(string name) 2: { 3: var email = DistCache.Get<string>(name); 4: if (string.IsNullOrEmpty(email)) 5: { 6: Console.WriteLine("==> The name/email not be in memcached so need slow loading. (name = {0})==>", name); 7: email = GetEmailByNameSlowly(name); 8: DistCache.Add(name, email); 9: } 10: else 11: { 12: Console.WriteLine("==> The name/email had been in memcached. (name = {0})==>", name); 13: } 14: return email; 15: } Finally let’s finished the calling method and execute. 1: static void Main(string[] args) 2: { 3: var name = string.Empty; 4: while (name != "q") 5: { 6: Console.Write("==> Please enter the name to find the email: "); 7: name = Console.ReadLine(); 8:  9: var email = GetEmailByName(name); 10: Console.WriteLine("==> The email of {0} is {1}.", name, email); 11: } 12: } The first time I entered “ziyanxu” it takes about 2 seconds to get the email since there’s nothing cached. But the next time I entered “ziyanxu” it returned very quickly from the Memcached.   Summary In this post I explained a bit on why we need cache, what’s Memcached and how to use it through the C# application. The example is fairly simple but hopefully demonstrated on how to use it. Memcached is very easy and simple to be used since it gives you the full opportunity to consider what, when and how to cache the objects. And when using Memcached you don’t need to consider the cache servers. The Memcached would be like a huge object pool in front of you. The next step I’m thinking now are: What kind of data should be cached? And how to determined the key? How to implement the cache as a layer on top of the business layer so that the application will not notice that the cache is there. How to implement the cache by AOP so that the business logic no need to consider the cache. I will investigate on them in the future and will share my thoughts and results.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Communication Between Your PC and Azure VM via Windows Azure Connect

    - by Shaun
    With the new release of the Windows Azure platform there are a lot of new features available. In my previous post I introduced a little bit about one of them, the remote desktop access to azure virtual machine. Now I would like to talk about another cool stuff – Windows Azure Connect.   What’s Windows Azure Connect I would like to quote the definition of the Windows Azure Connect in MSDN With Windows Azure Connect, you can use a simple user interface to configure IP-sec protected connections between computers or virtual machines (VMs) in your organization’s network, and roles running in Windows Azure. IP-sec protects communications over Internet Protocol (IP) networks through the use of cryptographic security services. There’s an image available at the MSDN as well that I would like to forward here As we can see, using the Windows Azure Connect the Worker Role 1 and Web Role 1 are connected with the development machines and database servers which some of them are inside the organization some are not. With the Windows Azure Connect, the roles deployed on the cloud could consume the resource which located inside our Intranet or anywhere in the world. That means the roles can connect to the local database, access the local shared resource such as share files, folders and printers, etc.   Difference between Windows Azure Connect and AppFabric It seems that the Windows Azure Connect are duplicated with the Windows Azure AppFabric. Both of them are aiming to solve the problem on how to communication between the resource in the cloud and inside the local network. The table below lists the differences in my understanding. Category Windows Azure Connect Windows Azure AppFabric Purpose An IP-sec connection between the local machines and azure roles. An application service running on the cloud. Connectivity IP-sec, Domain-joint Net Tcp, Http, Https Components Windows Azure Connect Driver Service Bus, Access Control, Caching Usage Azure roles connect to local database server Azure roles use local shared files,  folders and printers, etc. Azure roles join the local AD. Expose the local service to Internet. Move the authorization process to the cloud. Integrate with existing identities such as Live ID, Google ID, etc. with existing local services. Utilize the distributed cache.   And also some scenarios on which of them should be used. Scenario Connect AppFabric I have a service deployed in the Intranet and I want the people can use it from the Internet.   Y I have a website deployed on Azure and need to use a database which deployed inside the company. And I don’t want to expose the database to the Internet. Y   I have a service deployed in the Intranet and is using AD authorization. I have a website deployed on Azure which needs to use this service. Y   I have a service deployed in the Intranet and some people on the Internet can use it but need to be authorized and authenticated.   Y I have a service in Intranet, and a website deployed on Azure. This service can be used from Internet and that website should be able to use it as well by AD authorization for more functionalities. Y Y   How to Enable Windows Azure Connect OK we talked a lot information about the Windows Azure Connect and differences with the Windows Azure AppFabric. Now let’s see how to enable and use the Windows Azure Connect. First of all, since this feature is in CTP stage we should apply before use it. On the Windows Azure Portal we can see our CTP features status under Home, Beta Program page. You can send the apply to join the Beta Programs to Microsoft in this page. After a few days the Microsoft will send an email to you (the email of your Live ID) when it’s available. In my case we can see that the Windows Azure Connect had been activated by Microsoft and then we can click the Connect button on top, or we can click the Virtual Network item from the left navigation bar.   The first thing we need, if it’s our first time to enter the Connect page, is to enable the Windows Azure Connect. After that we can see our Windows Azure Connect information in this page.   Add a Local Machine to Azure Connect As we explained below the Windows Azure Connect can make an IP-sec connection between the local machines and azure role instances. So that we firstly add a local machine into our Azure Connect. To do this we will click the Install Local Endpoint button on top and then the portal will give us an URL. Copy this URL to the machine we want to add and it will download the software to us. This software will be installed in the local machines which we want to join the Connect. After installed there will be a tray-icon appeared to indicate this machine had been joint our Connect. The local application will be refreshed to the Windows Azure Platform every 5 minutes but we can click the Refresh button to let it retrieve the latest status at once. Currently my local machine is ready for connect and we can see my machine in the Windows Azure Portal if we switched back to the portal and selected back Activated Endpoints node.   Add a Windows Azure Role to Azure Connect Let’s create a very simple azure project with a basic ASP.NET web role inside. To make it available on Windows Azure Connect we will open the azure project property of this role from the solution explorer in the Visual Studio, and select the Virtual Network tab, check the Activate Windows Azure Connect. The next step is to get the activation token from the Windows Azure Portal. In the same page there is a button named Get Activation Token. Click this button then the portal will display the token to me. We copied this token and pasted to the box in the Visual Studio tab. Then we deployed this application to azure. After completed the deployment we can see the role instance was listed in the Windows Azure Portal - Virtual Connect section.   Establish the Connect Group The final task is to create a connect group which contains the machines and role instances need to be connected each other. This can be done in the portal very easy. The machines and instances will NOT be connected until we created the group for them. The machines and instances can be used in one or more groups. In the Virtual Connect section click the Groups and Roles node from the left side navigation bar and clicked the Create Group button on top. This will bring up a dialog to us. What we need to do is to specify a group name, description; and then we need to select the local computers and azure role instances into this group. After the Azure Fabric updated the group setting we can see the groups and the endpoints in the page. And if we switch back to the local machine we can see that the tray-icon have been changed and the status turned connected. The Windows Azure Connect will update the group information every 5 minutes. If you find the status was still in Disconnected please right-click the tray-icon and select the Refresh menu to retrieve the latest group policy to make it connected.   Test the Azure Connect between the Local Machine and the Azure Role Instance Now our local machine and azure role instance had been connected. This means each of them can communication to others in IP level. For example we can open the SQL Server port so that our azure role can connect to it by using the machine name or the IP address. The Windows Azure Connect uses IPv6 to connect between the local machines and role instances. You can get the IP address from the Windows Azure Portal Virtual Network section when select an endpoint. I don’t want to take a full example for how to use the Connect but would like to have two very simple tests. The first one would be PING.   When a local machine and role instance are connected through the Windows Azure Connect we can PING any of them if we opened the ICMP protocol in the Filewall setting. To do this we need to run a command line before test. Open the command window on the local machine and the role instance, execute the command as following netsh advfirewall firewall add rule name="ICMPv6" dir=in action=allow enable=yes protocol=icmpv6 Thanks to Jason Chen, Patriek van Dorp, Anton Staykov and Steve Marx, they helped me to enable  the ICMPv6 setting. For the full discussion we made please visit here. You can use the Remote Desktop Access feature to logon the azure role instance. Please refer my previous blog post to get to know how to use the Remote Desktop Access in Windows Azure. Then we can PING the machine or the role instance by specifying its name. Below is the screen I PING my local machine from my azure instance. We can use the IPv6 address to PING each other as well. Like the image following I PING to my role instance from my local machine thought the IPv6 address.   Another example I would like to demonstrate here is folder sharing. I shared a folder in my local machine and then if we logged on the role instance we can see the folder content from the file explorer window.   Summary In this blog post I introduced about another new feature – Windows Azure Connect. With this feature our local resources and role instances (virtual machines) can be connected to each other. In this way we can make our azure application using our local stuff such as database servers, printers, etc. without expose them to Internet.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Windows Azure Evolution &ndash; Preview Developer Portal

    - by Shaun
    With the MEET Windows Azure event on 7th June, there are many new features and updates in windows azure platform. In the coming several posts I will try to cover some of them. And in the first post here I would like to just have a quick walkthrough of the new preview developer portal.   History of the Developer Portal If you have been working with windows azure since 2009 or 2010, you should remember the first version of the developer portal. It was built in HTML with very limited features. I have the impression when I was using is old one. The layout is not that attractive and you have very limited features. On November, 2010 alone with the SDK 1.3 release, the developer portal was getting a big jump. In order to give more usability and features this it turned to be built on Silverlight. Hence it runs like a desktop application with many windows, lists, commands and context menus. From 2010 till now many features were involved into this portal, such as the remote desktop, co-admin, virtual connect, VM role, etc.. And the portal itself became more and more complicated. But it brought some problems by using the Silverlight. The first one is the browser capability. As you know in most mobile and tablet device the browser doesn’t allow the rich content plugin, such as Flash and Silverlight. This means people cannot open and configure their azure services from their iPad, iPhone and Windows Phone, etc., even though what they need may just be restart a hosted service, or view the status of their databases. Another problem is the performance. Silverlight provides rich experience to the users, but also needs more bandwidth. So in this upgrade the preview developer portal will be back to use HTML, with JavaScript, as a mobile friendly, cross browser, interactively web site.   Preview Portal vs. Silverlight Portal Before I started to talk about the new preview portal I’d better highlight that, this preview portal is a PREVIEW version, which means even though you can do almost all features that already in the old one, as long as some cool new features I will mention in the coming several posts, there are something still under developed and migrated. So sometimes you need to switch back to the old one. For example, in preview portal there is no co-admin manage function, no remote desktop function and the SQL database manage function will take you back to the old SQL Azure Manage Portal. But as Microsoft said these missing features will be moved in the preview portal in the couple of next few months. Since the public URL of the developer portal, https://windows.azure.com/, had been changed to point to this preview one, you need to click to preview button on top of the page and click the “Take me to the previous portal” link.   Overview There are four parts in the preview portal. On the top is the header which shows the account you are currently logging in. If you click on the header it will show the top menu of windows azure, where you can navigate to the windows azure home page, the price information page, community and account, etc.. The navigation bar is on the left hand side, with the categories listed below. ALL ITEMS All items in your windows azure account, includes the web sites, services, databases, etc.. WEB SITES The web sites in your windows azure account. It will only show the web sites you have. The linked resources will be shown if you drill down into a web site. VIRTUAL MACHINES The virtual machines that you had been deployed to azure. CLOUD SERVICES All windows azure hosted services in your account. SQL DATABASES All SQL databases (SQL Azure) in your account. STORAGE All windows azure storage services in your account. NETWORKS The virtual network (Windows Azure Connect) you had been created. The available items will be listed in the main part of the page based on which category your currently selected. If there’s no item it will show the link to you to quick create. At the bottom of the page there will be the command and information bar. Based on what is selected and what is performed by the user, it will show the related information and commands. For example, in the image below when I was creating a new web site, the information bar told me that my web site is being provisioned; and there are two commands in the command bar. And once it ready the command bar will show some commands that I can do to my new web site. The “Web Sites” is a new feature introduced alone with this upgrade. It gives us an easier and quicker way to establish a website from the scratch or from some existing library. I will introduce it more details in the coming next post. Also in the command bar you can create a service by clicking the NEW button. It will slide the creation panel up to you.   Where’s My Hosted Services The Windows Azure Hosted Services had been renamed to the Cloud Services. Create a new service would be very easy. Just click the NEW button at the bottom of the page, and select the CLOUD SERVICE and QIUICK CREATE. This will create a blank hosted service without deployment and certificate. It just needs you to specify the service URL and the affinity/region. Then the service will be shown in the list. If you clicked the item all information will be shown in the main part. Since there’s no package deployed to this service so currently we cannot see any information about it. But we can upload the package by using the command at the bottom. And as you can see, we could manage the configuration, instances, certificates and we can scale up and down (change the VM size), in and out (increase and decrease the instance count) to our service. Assuming I had created an ASP.NET MVC 3 web role project in Visual Studio and completed the package. Then I can click the UPLOAD button in this page to deploy my package. In the popping up window I just specify my deployment name, package file and configure file. Also I can check the box below so that it will NOT warn me if only one instance of this deployment. Once we clicked the OK button our package will be uploaded and provisioned by the platform. After a while we can see the service was ready from the information bar. We can have the basic information about this service and deployment if we to the dashboard page. For example the usage overview diagram, status, URL, public IP address, etc.. In the configure page we can view and change the CSCFG content such as the monitor setting, connection strings, OS family. In scale page we can increase and decrease the count of the instances. And in the instances page we can view all instances status. And, if your services is using some SQL databases and storages they will be shown as the linked resources under the linked resources page. And you can manage the certificates of this service as well under the certificates page.   How About My Storage Services The storage service can be managed by clicking into the STORAGES link in the navigation bar. And we can create a new storage service from the NEW button. After specify the storage name and region it will be previsioned by the platform. If you want to copy or manage the storage key you can just click the Manage Keys button at the bottom, which is very easy. What I want to highlight here is that, you can monitor your storage service by enabling the monitor configuration. Click the storage item in the list and navigate to the configure page. As you can see in the page you can enable the monitoring for blob, table and queue. And you can also enable the logging when any requests come to the storage. But as the tooltip shown in the page, enabling the monitoring and logging will increase the usage of the storage, which means increase the bill of them. So make sure you enable them properly.   And My SQL Databases (SQL Azure) The last thing I want to quick introduce is the SQL databases, which was formally named SQL Azure. You can create a new SQL Database Server and a new database by clicking the ADD button under the SQL Database navigation item. In the popping up windows just specify the database name, the edition, size, collation and the server. You can select an existing SQL Database Server if you have, or cerate a new one. If you selected to create a new server, there will be another step you need to do, which is specify the server login, password and the region. Once it ready you can mange your databases as well as the servers in the portal. In a particular server you can update the firewall settings in its Configure page. So, What Else There are some other area on the preview portal I didn’t cover, such as the virtual machines, virtual network and web sites. Regarding the virtual machines and web sites I will talk about them in the future separated post. Regarding the virtual network, it the Windows Azure Connect we are familiar with. But as I mention in the beginning of this post, the preview portal is still under developed. Some features are not available here. For example, you cannot manage the co-admin of your subscriptions, you cannot open the remote desktop on your hosted services, and you cannot navigate to the Windows Azure Service Bus, Access Control and Caching, which formally named Windows Azure AppFabric directly. In these cases you need to navigate back to the old portal. So in the coming several months we might need to use both these two sites.   Summary In this post I quick introduced the new windows azure developer portal. Since it had been rearranged and renamed I demonstrated some features that existing in the old portal, such as how to create and deploy a hosted service, how to provision a storage service and SQL database. All features in the old portal had been, is being and will be migrated into this new portal, but some of them were in a different category and page we need to figure out.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Windows Azure Evolution &ndash; TFS Integration (WAWS Part 2)

    - by Shaun
    So this is the fourth blog post about the new features of Windows Azure and the second part of Windows Azure Web Sites. But this is not just focus on the WAWS since the function I’m going to introduce is available in both Windows Azure Web Sites and Windows Azure Cloud Service (a.k.a. hosted service). In the previous post I talked about the Windows Azure Web Sites and how to use its gallery to build a WordPress personal blog without coding. Besides the gallery we can create an empty web site and upload our website from vary approaches. And one of the highlighted feature here is that, we can make our web site integrated with a source control service, such as TFS and Git, so that it will be deployed automatically once a new commit or build available.   Create New Empty Web Site In the developer portal when creating a new web site, we can select QUICK CREATE item. This will create an empty web site with only one shared instance without any database associated. Let’s specify the URL, region and subscription and click OK. After a few seconds our website will be ready. And now we can click the BROWSE button to open this empty website. As you can see there is a welcome page available in my website even thought I didn’t upload or deploy anything. This means even though the website will be charged even before anything was deployed, similar as the cloud service (hosted service). It is because once we created a website, Windows Azure platform had arranged a hosting process (w3wp.exe) in the group of virtual machines.   Create Project in TFS Preview Service and Setup Link Currently the Windows Azure Web Sites can integrate with TFS and Git as its deployment source, and it only support the Microsoft TFS Preview Service for now. I will not deep into how to use the TFS preview service in this post but once we click into the website we had just created and then clicked the “Set up TFS publishing”, there will be a dialog helping us to connect to this service. If you don’t have an account you can click the link shown below to request one. Assuming we have already had an account of TFS service then we need to create a new project firstly. Go to your TFS service website and create a new project, giving the project name, description and the process template. Then, back to the developer portal and clicked the “Set up TFS publishing” link. In the popping up window I will provide my TFS service URL and click the “Authorize now” link. Click “Accept” button to allow my windows azure to connect to my TFS service. Then it will be back to the developer portal and list all projects in my account. Just select the one I had just created and click OK. Then our website is linking to the TFS project I specified and finally it will show similar like this below. This means the web site had been linked to the TFS successfully.   Work with TFS Preview Service in VS2010 In the figure above there are some links to guide us how to connect to the TFS server through Visual Studio 2010 and 2012 RC. If you are using Visual Studio 2012 RC, you don’t need any extension. But if you are using Visual Studio 2010 you must have SP1 and KB2581206 installed. To connect to my TFS service just open the Visual Studio and in the Team Explorer, we can add a new TFS server and paste the URL of my TFS service from the developer portal. And select the project I had just created, then it will be listed in my Team Explorer. Now let’s start to build our website. Since the website we are going to build will be deployed to WAWS, it’s NOT a cloud service, NOT a web role. So in this case we need to create a normal ASP.NET web application. For example, an ASP.NET MVC 3 web application. Next, right click on the solution and select “Add Solution to Source Control”, select the project I had just created. Then check my code in. Once the check-in finished we can see that there is a build running in the TFS server. And if we back to the developer portal, we will see in our web site deployment page there’s a deployment running. In fact, once we linked our web site to our TFS then it will create a new build definition in our TFS project. It will be triggered by each check-in and deploy to the web site we linked automatically. So that when our code had been compiled it will be published to our web site from our TFS server. Once the build and deployment finished we can see it’s now active on our developer portal. Now we can see the web site that created from my Visual Studio and deployed by my TFS.   Continue Deployment through VS and TFS A big benefit when using TFS publishing is the continue deployment. Now if I changed some code in my Visual Studio, for example update some text on the home page and check in my changes, then it will trigger an new build and deploy to my WAWS automatically. And even more, if we wanted to rollback to a previous version we can just select an existing deployment listed in the portal and click REDEPLOY at the bottom.   Q&A: Can Web Site use Storage work with a Worker Role? Stacy asked a question in my previous post, which was “can a web site use Windows Azure Storage and furthermore working with a worker role”. Since the web site is deployed on the windows azure virtual machines in data center, it must be able to use all windows azure features such as the storage, SQL databases, CDN, etc.. But since when using web site we normally have a standard ASP.NET web application, PHP website or NodeJS, the windows azure SDK was not referenced by default. But we can add them by ourselves. In our sample project let’s right click on my MVC project and clicked the “Manage NuGet packages”. And in the dialog I will search windows azure packages and select the “Windows Azure Storage” to install. Then we will have the assemblies to access windows azure storage such as tables, queues and blobs. Since I have a storage account already, let’s have a quick demo, just to list all blobs in a container. The code would be like this. 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Web; 5: using System.Web.Mvc; 6: using Microsoft.WindowsAzure; 7: using Microsoft.WindowsAzure.StorageClient; 8:  9: namespace WAASTFSDemo.Controllers 10: { 11: public class HomeController : Controller 12: { 13: public ActionResult Index() 14: { 15: ViewBag.Message = "Welcome to Windows Azure!"; 16:  17: var credentials = new StorageCredentialsAccountAndKey("[STORAGE_ACCOUNT]", "[STORAGE_KEY]"); 18: var account = new CloudStorageAccount(credentials, false); 19: var client = account.CreateCloudBlobClient(); 20: var container = client.GetContainerReference("shared"); 21: ViewBag.Blobs = container.ListBlobs().Select(b => b.Uri.AbsoluteUri); 22:  23: return View(); 24: } 25:  26: public ActionResult About() 27: { 28: return View(); 29: } 30: } 31: } 1: @{ 2: ViewBag.Title = "Home Page"; 3: } 4:  5: <h2>@ViewBag.Message</h2> 6: <p> 7: To learn more about ASP.NET MVC visit <a href="http://asp.net/mvc" title="ASP.NET MVC Website">http://asp.net/mvc</a>. 8: </p> 9: <div> 10: <ul> 11: @foreach (var blob in ViewBag.Blobs) 12: { 13: <li>@blob</li> 14: } 15: </ul> 16: </div> And then just check in the code, it will be deployed to my web site. Finally we can see the blobs in my storage.   This is just an example but it proves that web sites can connect to storage, table, blob and queue as well. So the answer to Stacy should be “yes”. The web site can use queue storage to work with worker role.   Summary In this post I demonstrated how to integrate with TFS from Windows Azure Web Sites. You can see our website can be built, uploaded and deployed automatically by TFS service. All we need to do is to provide the TFS name and select the project. Not only the Windows Azure Web Site, in this upgrade the Windows Azure Cloud Services (hosted service) can be published through TFS as well. Very similar as what we have shown below. But currently, only Microsoft TFS Service Preview can be integrated with Windows Azure. But I think in the future we can link the TFS in our enterprise and some 3rd party TFS such as CodePlex to Windows Azure.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Windows Azure Evolution - Web Sites (aka Antares) Part 1

    - by Shaun
    This is the 3rd post of my Windows Azure Evolution series, focus on the new features and enhancement which was alone with the Windows Azure Platform Upgrade June 2012, announced at the MEET Windows Azure event on 7th June. In the first post I introduced the new preview developer portal and how to works for the existing features such as cloud services, storages and SQL databases. In the second one I talked about the Windows Azure .NET SDK 1.7 on the latest Visual Studio 2012 RC on Windows 8. From this one I will begin to introduce some new features. Now let’s have a look on the first one of them, Windows Azure Web Sites.   Overview Windows Azure Web Sites (WAWS), as known as Antares, was a new feature still in preview stage in this upgrade. It allows people to quickly and easily deploy websites to a highly scalable cloud environment, uses the languages and open source apps of the choice then deploy such as FTP, Git and TFS. It also can be integrated with Windows Azure services like SQL Database, Caching, CDN and Storage easily. After read its introduction we may have a question: since we can deploy a website from both cloud service web role and web site, what’s the different between them? So, let’s have a quick compare.   CLOUD SERVICE WEB SITE OS Windows Server Windows Server Virtualization Windows Azure Virtual Machine Windows Azure Virtual Machine Host IIS IIS Platform ASP.NET WebForm, ASP.NET MVC, WCF ASP.NET WebForm, ASP.NET MVC, PHP Language C#, VB.NET C#, VB.NET, PHP Database SQL Database SQL Database, MySQL Architecture Multi layered, background worker, message queuing, etc.. Simple website with backend database. VS Project Windows Azure Cloud Service ASP.NET Web Form, ASP.NET MVC, etc.. Out-of-box Gallery (none) Drupal, DotNetNuke, WordPress, etc.. Deployment Package upload, Visual Studio publish FTP, Git, TFS, WebMatrix Compute Mode Dedicate VM Shared Across VMs, Dedicate VM Scale Scale up, scale out Scale up, scale out As you can see, there are many difference between the cloud service and web site, but the main point is that, the cloud service focus on those complex architecture web application. For example, if you want to build a website with frontend layer, middle business layer and data access layer, with some background worker process connected through the message queue, then you should better use cloud service, since it provides full control of your code and application. But if you just want to build a personal blog or a  business portal, then you can use the web site. Since the web site have many galleries, you can create them even without any coding and configuration. David Pallmann have an awesome figure explains the benefits between the could service, web site and virtual machine.   Create a Personal Blog in Web Site from Gallery As I mentioned above, one of the big feature in WAWS is to build a website from an existing gallery, which means we don’t need to coding and configure. What we need to do is open the windows azure developer portal and click the NEW button, select WEB SITE and FROM GALLERY. In the popping up windows there are many websites we can choose to use. For example, for personal blog there are Orchard CMS, WordPress; for CMS there are DotNetNuke, Drupal 7, mojoPortal. Let’s select WordPress and click the next button. The next step is to configure the web site. We will need to specify the DNS name and select the subscription and region. Since the WordPress uses MySQL as its backend database, we also need to create a MySQL database as well. Windows Azure Web Sites utilize ClearDB to host the MySQL databases. You cannot create a MySQL database directly from SQL Databases section. Finally, since we selected to create a new MySQL database we need to specify the database name and region in the last step. Also we need to accept the ClearDB’s terms as well. Then windows azure platform will download the WordPress codes and deploy the MySQL database and website. Then it will be ready to use. Select the website and click the BROWSE button, the WordPress administration page will be shown. After configured the WordPress here is my personal web blog on the cloud. It took me no more than 10 minutes to establish without any coding.   Monitor, Configure, Scale and Linked Resources Let’s click into the website I had just created in the portal and have a look on what we can do. In the website details page where are five sections. - Dashboard The overall information about this website, such as the basic usage status, public URL, compute mode, FTP address, subscription and links that we can specify the deployment credentials, TFS and Git publish setting, etc.. - Monitor Some status information such as the CPU usage, memory usage etc., errors, etc.. We can add more metrics by clicking the ADD METRICS button and the bottom as well. - Configure Here we can set the configurations of our website such as the .NET and PHP runtime version, diagnostics settings, application settings and the IIS default documents. - Scale This is something interesting. In WAWS there are two compute mode or called web site mode. One is “shared”, which means our website will be shared with other web sites in a group of windows azure virtual machines. Each web site have its own process (w3wp.exe) with some sandbox technology to isolate from others. When we need to scaling-out our web site in shared mode, we actually increased the working process count. Hence in shared mode we cannot specify the virtual machine size since they are shared across all web sites. This is a little bit different than the scaling mode of the cloud service (hosted service web role and worker role). The other mode called “dedicate”, which means our web site will use the whole windows azure virtual machine. This is the same hosting behavior as cloud service web role. In web role it will be deployed on the virtual machines we specified and all of them are only used by us. In web sites dedicate mode, it’s the same. In this mode when we scaling-out our web site we will use more virtual machines, and each of them will only host our own website. And we can specify the virtual machine size in this mode. In the developer portal we can select which mode we are using from the scale section. In shared mode we can only specify the instance count, but in dedicate mode we can specify the instance size as well as the instance count. - Linked Resource The MySQL database created alone with the creation of our WordPress web site is a linked resource. We can add more linked resources in this section.   Pricing For the web site itself, since this feature is in preview period if you are using shared mode, then you will get free up to 10 web sites. But if you are using dedicate mode, the price would be the virtual machines you are using. For example, if you are using dedicate and configured two middle size virtual machines then you will pay $230.40 per month. If there is SQL Database linked to your web site then they will be charged separately based on the Pay-As-You-Go price. For example a 1GB web edition database costs $9.99 per month. And the bandwidth will be charged as well. For example 10GB outbound data transfer costs $1.20 per month. For more information about the pricing please have a look at the windows azure pricing page.   Summary Windows Azure Web Sites gives us easier and quicker way to create, develop and deploy website to window azure platform. Comparing with the cloud service web role, the WAWS have many out-of-box gallery we can use directly. So if you just want to build a blog, CMS or business portal you don’t need to learn ASP.NET, you don’t need to learn how to configure DotNetNuke, you don’t need to learn how to prepare PHP and MySQL. By using WAWS gallery you can establish a website within 10 minutes without any lines of code. But in some cases we do need to code by ourselves. We may need to tweak the layout of our pages, or we may have a traditional ASP.NET or PHP web application which needed to migrated to the cloud. Besides the gallery WAWS also provides many features to download, upload code. It also provides the feature to integrate with some version control services such as TFS and Git. And it also provides the deploy approaches through FTP and Web Deploy. In the next post I will demonstrate how to use WebMatrix to download and modify the website, and how to use TFS and Git to deploy automatically one our code changes committed.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Install NPM Packages Automatically for Node.js on Windows Azure Web Site

    - by Shaun
    In one of my previous post I described and demonstrated how to use NPM packages in Node.js and Windows Azure Web Site (WAWS). In that post I used NPM command to install packages, and then use Git for Windows to commit my changes and sync them to WAWS git repository. Then WAWS will trigger a new deployment to host my Node.js application. Someone may notice that, a NPM package may contains many files and could be a little bit huge. For example, the “azure” package, which is the Windows Azure SDK for Node.js, is about 6MB. Another popular package “express”, which is a rich MVC framework for Node.js, is about 1MB. When I firstly push my codes to Windows Azure, all of them must be uploaded to the cloud. Is that possible to let Windows Azure download and install these packages for us? In this post, I will introduce how to make WAWS install all required packages for us when deploying.   Let’s Start with Demo Demo is most straightforward. Let’s create a new WAWS and clone it to my local disk. Drag the folder into Git for Windows so that it can help us commit and push. Please refer to this post if you are not familiar with how to use Windows Azure Web Site, Git deployment, git clone and Git for Windows. And then open a command windows and install a package in our code folder. Let’s say I want to install “express”. And then created a new Node.js file named “server.js” and pasted the code as below. 1: var express = require("express"); 2: var app = express(); 3: 4: app.get("/", function(req, res) { 5: res.send("Hello Node.js and Express."); 6: }); 7: 8: console.log("Web application opened."); 9: app.listen(process.env.PORT); If we switch to Git for Windows right now we will find that it detected the changes we made, which includes the “server.js” and all files under “node_modules” folder. What we need to upload should only be our source code, but the huge package files also have to be uploaded as well. Now I will show you how to exclude them and let Windows Azure install the package on the cloud. First we need to add a special file named “.gitignore”. It seems cannot be done directly from the file explorer since this file only contains extension name. So we need to do it from command line. Navigate to the local repository folder and execute the command below to create an empty file named “.gitignore”. If the command windows asked for input just press Enter. 1: echo > .gitignore Now open this file and copy the content below and save. 1: node_modules Now if we switch to Git for Windows we will found that the packages under the “node_modules” were not in the change list. So now if we commit and push, the “express” packages will not be uploaded to Windows Azure. Second, let’s tell Windows Azure which packages it needs to install when deploying. Create another file named “package.json” and copy the content below into that file and save. 1: { 2: "name": "npmdemo", 3: "version": "1.0.0", 4: "dependencies": { 5: "express": "*" 6: } 7: } Now back to Git for Windows, commit our changes and push it to WAWS. Then let’s open the WAWS in developer portal, we will see that there’s a new deployment finished. Click the arrow right side of this deployment we can see how WAWS handle this deployment. Especially we can find WAWS executed NPM. And if we opened the log we can review what command WAWS executed to install the packages and the installation output messages. As you can see WAWS installed “express” for me from the cloud side, so that I don’t need to upload the whole bunch of the package to Azure. Open this website and we can see the result, which proved the “express” had been installed successfully.   What’s Happened Under the Hood Now let’s explain a bit on what the “.gitignore” and “package.json” mean. The “.gitignore” is an ignore configuration file for git repository. All files and folders listed in the “.gitignore” will be skipped from git push. In the example below I copied “node_modules” into this file in my local repository. This means,  do not track and upload all files under the “node_modules” folder. So by using “.gitignore” I skipped all packages from uploading to Windows Azure. “.gitignore” can contain files, folders. It can also contain the files and folders that we do NOT want to ignore. In the next section we will see how to use the un-ignore syntax to make the SQL package included. The “package.json” file is the package definition file for Node.js application. We can define the application name, version, description, author, etc. information in it in JSON format. And we can also put the dependent packages as well, to indicate which packages this Node.js application is needed. In WAWS, name and version is necessary. And when a deployment happened, WAWS will look into this file, find the dependent packages, execute the NPM command to install them one by one. So in the demo above I copied “express” into this file so that WAWS will install it for me automatically. I updated the dependencies section of the “package.json” file manually. But this can be done partially automatically. If we have a valid “package.json” in our local repository, then when we are going to install some packages we can specify “--save” parameter in “npm install” command, so that NPM will help us upgrade the dependencies part. For example, when I wanted to install “azure” package I should execute the command as below. Note that I added “--save” with the command. 1: npm install azure --save Once it finished my “package.json” will be updated automatically. Each dependent packages will be presented here. The JSON key is the package name while the value is the version range. Below is a brief list of the version range format. For more information about the “package.json” please refer here. Format Description Example version Must match the version exactly. "azure": "0.6.7" >=version Must be equal or great than the version. "azure": ">0.6.0" 1.2.x The version number must start with the supplied digits, but any digit may be used in place of the x. "azure": "0.6.x" ~version The version must be at least as high as the range, and it must be less than the next major revision above the range. "azure": "~0.6.7" * Matches any version. "azure": "*" And WAWS will install the proper version of the packages based on what you defined here. The process of WAWS git deployment and NPM installation would be like this.   But Some Packages… As we know, when we specified the dependencies in “package.json” WAWS will download and install them on the cloud. For most of packages it works very well. But there are some special packages may not work. This means, if the package installation needs some special environment restraints it might be failed. For example, the SQL Server Driver for Node.js package needs “node-gyp”, Python and C++ 2010 installed on the target machine during the NPM installation. If we just put the “msnodesql” in “package.json” file and push it to WAWS, the deployment will be failed since there’s no “node-gyp”, Python and C++ 2010 in the WAWS virtual machine. For example, the “server.js” file. 1: var express = require("express"); 2: var app = express(); 3: 4: app.get("/", function(req, res) { 5: res.send("Hello Node.js and Express."); 6: }); 7:  8: var sql = require("msnodesql"); 9: var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:tqy4c0isfr.database.windows.net,1433;Database=msteched2012;Uid=shaunxu@tqy4c0isfr;Pwd=P@ssw0rd123;Encrypt=yes;Connection Timeout=30;"; 10: app.get("/sql", function (req, res) { 11: sql.open(connectionString, function (err, conn) { 12: if (err) { 13: console.log(err); 14: res.send(500, "Cannot open connection."); 15: } 16: else { 17: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 18: if (err) { 19: console.log(err); 20: res.send(500, "Cannot retrieve records."); 21: } 22: else { 23: res.json(results); 24: } 25: }); 26: } 27: }); 28: }); 29: 30: console.log("Web application opened."); 31: app.listen(process.env.PORT); The “package.json” file. 1: { 2: "name": "npmdemo", 3: "version": "1.0.0", 4: "dependencies": { 5: "express": "*", 6: "msnodesql": "*" 7: } 8: } And it failed to deploy to WAWS. From the NPM log we can see it’s because “msnodesql” cannot be installed on WAWS. The solution is, in “.gitignore” file we should ignore all packages except the “msnodesql”, and upload the package by ourselves. This can be done by use the content as below. We firstly un-ignored the “node_modules” folder. And then we ignored all sub folders but need git to check each sub folders. And then we un-ignore one of the sub folders named “msnodesql” which is the SQL Server Node.js Driver. 1: !node_modules/ 2:  3: node_modules/* 4: !node_modules/msnodesql For more information about the syntax of “.gitignore” please refer to this thread. Now if we go to Git for Windows we will find the “msnodesql” was included in the uncommitted set while “express” was not. I also need remove the dependency of “msnodesql” from “package.json”. Commit and push to WAWS. Now we can see the deployment successfully done. And then we can use the Windows Azure SQL Database from our Node.js application through the “msnodesql” package we uploaded.   Summary In this post I demonstrated how to leverage the deployment process of Windows Azure Web Site to install NPM packages during the publish action. With the “.gitignore” and “package.json” file we can ignore the dependent packages from our Node.js and let Windows Azure Web Site download and install them while deployed. For some special packages that cannot be installed by Windows Azure Web Site, such as “msnodesql”, we can put them into the publish payload as well. With the combination of Windows Azure Web Site, Node.js and NPM it makes even more easy and quick for us to develop and deploy our Node.js application to the cloud.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Make Your Menu Item Highlighted

    - by Shaun
    When I was working on the TalentOn project (Promotion in MSDN Chinese) I was asked to implement a functionality that makes the top menu items highlighted when the currently viewing page was in that section. This might be a common scenario in the web application development I think.   Simple Example When thinking about the solution of the highlighted menu items the biggest problem would be how to define the sections (menu item) and the pages it belongs to rather than making the menu highlighted. With the ASP.NET MVC framework we can use the controller – action infrastructure for us to achieve it. Each controllers would have a related menu item on the master page normally. The menu item would be highlighted if any of the views under this controller are being shown. Some specific menu items would be highlighted of that action was invoked, for example the home page, the about page, etc. The check rule can be specified on-demand. For example I can define the action LogOn and Register of Account controller should make the Account menu item highlighted while the ChangePassword should make the Profile menu item highlighted. I’m going to use the HtmlHelper to render the highlight-able menu item. The key point is that I need to pass the predication to check whether the current view belongs to this menu item which means this menu item should be highlighted or not. Hence I need a delegate as its parameter. The simplest code would be like this. 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Web; 5: using System.Web.Mvc; 6: using System.Web.Mvc.Html; 7:  8: namespace ShaunXu.Blogs.HighlighMenuItem 9: { 10: public static class HighlightMenuItemHelper 11: { 12: public static MvcHtmlString HighlightMenuItem(this HtmlHelper helper, 13: string text, string controllerName, string actionName, object routeData, object htmlAttributes, 14: string highlightText, object highlightHtmlAttributes, 15: Func<HtmlHelper, bool> highlightPredicate) 16: { 17: var shouldHighlight = highlightPredicate.Invoke(helper); 18: if (shouldHighlight) 19: { 20: return helper.ActionLink(string.IsNullOrWhiteSpace(highlightText) ? text : highlightText, 21: actionName, controllerName, routeData, highlightHtmlAttributes == null ? htmlAttributes : highlightHtmlAttributes); 22: } 23: else 24: { 25: return helper.ActionLink(text, actionName, controllerName, routeData, htmlAttributes); 26: } 27: } 28: } 29: } There are 3 groups of the parameters: the first group would be the same as the in-build ActionLink method parameters. It has the link text, controller name and action name, etc passed in so that I can render a valid linkage for the menu item. The second group would be more focus on the highlight link text and Html attributes. I will use them to render the highlight menu item. The third group, which contains one parameter, would be a predicate that tells me whether this menu item should be highlighted or not based on the user’s definition. And then I changed my master page of the sample MVC application. I let the Home and About menu highlighted only when the Index and About action are invoked. And I added a new menu named Account which should be highlighted for all actions/views under its Account controller. So my master would be like this. 1: <div id="menucontainer"> 2:  3: <ul id="menu"> 4: <li><% 1: : Html.HighlightMenuItem( 2: "Home", "Home", "Index", null, null, 3: "[Home]", null, 4: helper => helper.ViewContext.RouteData.Values["controller"].ToString() == "Home" 5: && helper.ViewContext.RouteData.Values["action"].ToString() == "Index")%></li> 5:  6: <li><% 1: : Html.HighlightMenuItem( 2: "About", "Home", "About", null, null, 3: "[About]", null, 4: helper => helper.ViewContext.RouteData.Values["controller"].ToString() == "Home" 5: && helper.ViewContext.RouteData.Values["action"].ToString() == "About")%></li> 7:  8: <li><% 1: : Html.HighlightMenuItem( 2: "Account", "Account", "LogOn", null, null, 3: "[Account]", null, 4: helper => helper.ViewContext.RouteData.Values["controller"].ToString() == "Account")%></li> 9: 10: </ul> 11:  12: </div> Note: You need to add the import section for the namespace “ShaunXu.Blogs.HighlighMenuItem” to make the extension method I created below available. So let’s see the result. When the home page was shown the Home menu was highlighted since at this moment it was controller = Home and action = Index. And if I clicked the About menu you can see it turned highlighted as now the action was About. And if I navigated to the register page the Account menu was highlighted since it should be like that when any actions under the Account controller was invoked.   Fluently Language Till now it’s a fully example for the highlight menu item but not perfect yet. Since the most common scenario would be: highlighted when the action invoked, or highlighted when any action was invoked under this controller, we can created 2 shortcut method so for them so that normally the developer will be no need to specify the delegation. Another place we can improve would be, to make the method more user-friendly, or I should say developer-friendly. As you can see when we want to add a highlight menu item we need to specify 8 parameters and we need to remember what they mean. In fact we can make the method more “fluently” so that the developer can have the hints when using it by the Visual Studio IntelliSense. Below is the full code for it. 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Web; 5: using System.Web.Mvc; 6: using System.Web.Mvc.Html; 7:  8: namespace Ethos.Xrm.HR 9: { 10: #region Helper 11:  12: public static class HighlightActionMenuHelper 13: { 14: public static IHighlightActionMenuProviderAfterCreated HighlightActionMenu(this HtmlHelper helper) 15: { 16: return new HighlightActionMenuProvider(helper); 17: } 18: } 19:  20: #endregion 21:  22: #region Interfaces 23:  24: public interface IHighlightActionMenuProviderAfterCreated 25: { 26: IHighlightActionMenuProviderAfterOn On(string actionName, string controllerName); 27: } 28:  29: public interface IHighlightActionMenuProviderAfterOn 30: { 31: IHighlightActionMenuProviderAfterWith With(string text, object routeData, object htmlAttributes); 32: } 33:  34: public interface IHighlightActionMenuProviderAfterWith 35: { 36: IHighlightActionMenuProviderAfterHighlightWhen HighlightWhen(Func<HtmlHelper, bool> predicate); 37: IHighlightActionMenuProviderAfterHighlightWhen HighlightWhenControllerMatch(); 38: IHighlightActionMenuProviderAfterHighlightWhen HighlightWhenControllerAndActionMatch(); 39: } 40:  41: public interface IHighlightActionMenuProviderAfterHighlightWhen 42: { 43: IHighlightActionMenuProviderAfterApplyHighlightStyle ApplyHighlighStyle(object highlightHtmlAttributes, string highlightText); 44: IHighlightActionMenuProviderAfterApplyHighlightStyle ApplyHighlighStyle(object highlightHtmlAttributes); 45: IHighlightActionMenuProviderAfterApplyHighlightStyle ApplyHighlighStyle(string cssClass, string highlightText); 46: IHighlightActionMenuProviderAfterApplyHighlightStyle ApplyHighlighStyle(string cssClass); 47: } 48:  49: public interface IHighlightActionMenuProviderAfterApplyHighlightStyle 50: { 51: MvcHtmlString ToActionLink(); 52: } 53:  54: #endregion 55:  56: public class HighlightActionMenuProvider : 57: IHighlightActionMenuProviderAfterCreated, 58: IHighlightActionMenuProviderAfterOn, IHighlightActionMenuProviderAfterWith, 59: IHighlightActionMenuProviderAfterHighlightWhen, IHighlightActionMenuProviderAfterApplyHighlightStyle 60: { 61: private HtmlHelper _helper; 62:  63: private string _controllerName; 64: private string _actionName; 65: private string _text; 66: private object _routeData; 67: private object _htmlAttributes; 68:  69: private Func<HtmlHelper, bool> _highlightPredicate; 70:  71: private string _highlightText; 72: private object _highlightHtmlAttributes; 73:  74: public HighlightActionMenuProvider(HtmlHelper helper) 75: { 76: _helper = helper; 77: } 78:  79: public IHighlightActionMenuProviderAfterOn On(string actionName, string controllerName) 80: { 81: _actionName = actionName; 82: _controllerName = controllerName; 83: return this; 84: } 85:  86: public IHighlightActionMenuProviderAfterWith With(string text, object routeData, object htmlAttributes) 87: { 88: _text = text; 89: _routeData = routeData; 90: _htmlAttributes = htmlAttributes; 91: return this; 92: } 93:  94: public IHighlightActionMenuProviderAfterHighlightWhen HighlightWhen(Func<HtmlHelper, bool> predicate) 95: { 96: _highlightPredicate = predicate; 97: return this; 98: } 99:  100: public IHighlightActionMenuProviderAfterHighlightWhen HighlightWhenControllerMatch() 101: { 102: return HighlightWhen((helper) => 103: { 104: return helper.ViewContext.RouteData.Values["controller"].ToString().ToLower() == _controllerName.ToLower(); 105: }); 106: } 107:  108: public IHighlightActionMenuProviderAfterHighlightWhen HighlightWhenControllerAndActionMatch() 109: { 110: return HighlightWhen((helper) => 111: { 112: return helper.ViewContext.RouteData.Values["controller"].ToString().ToLower() == _controllerName.ToLower() && 113: helper.ViewContext.RouteData.Values["action"].ToString().ToLower() == _actionName.ToLower(); 114: }); 115: } 116:  117: public IHighlightActionMenuProviderAfterApplyHighlightStyle ApplyHighlighStyle(object highlightHtmlAttributes, string highlightText) 118: { 119: _highlightText = highlightText; 120: _highlightHtmlAttributes = highlightHtmlAttributes; 121: return this; 122: } 123:  124: public IHighlightActionMenuProviderAfterApplyHighlightStyle ApplyHighlighStyle(object highlightHtmlAttributes) 125: { 126: return ApplyHighlighStyle(highlightHtmlAttributes, _text); 127: } 128:  129: public IHighlightActionMenuProviderAfterApplyHighlightStyle ApplyHighlighStyle(string cssClass, string highlightText) 130: { 131: return ApplyHighlighStyle(new { @class = cssClass }, highlightText); 132: } 133:  134: public IHighlightActionMenuProviderAfterApplyHighlightStyle ApplyHighlighStyle(string cssClass) 135: { 136: return ApplyHighlighStyle(new { @class = cssClass }, _text); 137: } 138:  139: public MvcHtmlString ToActionLink() 140: { 141: if (_highlightPredicate.Invoke(_helper)) 142: { 143: // should be highlight 144: return _helper.ActionLink(_highlightText, _actionName, _controllerName, _routeData, _highlightHtmlAttributes); 145: } 146: else 147: { 148: // should not be highlight 149: return _helper.ActionLink(_text, _actionName, _controllerName, _routeData, _htmlAttributes); 150: } 151: } 152: } 153: } So in the master page when I need the highlight menu item I can “tell” the helper how it should be, just like this. 1: <li> 2: <% 1: : Html.HighlightActionMenu() 2: .On("Index", "Home") 3: .With(SiteMasterStrings.Home, null, null) 4: .HighlightWhenControllerMatch() 5: .ApplyHighlighStyle(new { style = "background:url(../../Content/Images/topmenu_bg.gif) repeat-x;text-decoration:none;color:#feffff;" }) 6: .ToActionLink() %> 3: </li> While I’m typing the code the IntelliSense will advise me that I need a highlight action menu, on the Index action of the Home controller, with the “Home” as its link text and no need the additional route data and Html attributes, and it should be highlighted when the controller was “Home”, and if it’s highlighted the style should be like this and finally render it to me. This is something we call “Fluently Language”. If you had been using Moq you will see that’s very development-friendly, document-ly and easy to read.   Summary In this post I demonstrated how to implement a highlight menu item in ASP.NET MVC by using its controller – action infrastructure. We can see the ASP.NET MVC helps us to organize our web application better. And then I also told a little bit more on the “Fluently Language” and showed how it will make our code better and easy to be used.   Hope this helps, Shaun   All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Azure &ndash; Part 5 &ndash; Repository Pattern for Table Service

    - by Shaun
    In my last post I created a very simple WCF service with the user registration functionality. I created an entity for the user data and a DataContext class which provides some methods for operating the entities such as add, delete, etc. And in the service method I utilized it to add a new entity into the table service. But I didn’t have any validation before registering which is not acceptable in a real project. So in this post I would firstly add some validation before perform the data creation code and show how to use the LINQ for the table service.   LINQ to Table Service Since the table service utilizes ADO.NET Data Service to expose the data and the managed library of ADO.NET Data Service supports LINQ we can use it to deal with the data of the table service. Let me explain with my current example: I would like to ensure that when register a new user the email address should be unique. So I need to check the account entities in the table service before add. If you remembered, in my last post I mentioned that there’s a method in the TableServiceContext class – CreateQuery, which will create a IQueryable instance from a given type of entity. So here I would create a method under my AccountDataContext class to return the IQueryable<Account> which named Load. 1: public class AccountDataContext : TableServiceContext 2: { 3: private CloudStorageAccount _storageAccount; 4:  5: public AccountDataContext(CloudStorageAccount storageAccount) 6: : base(storageAccount.TableEndpoint.AbsoluteUri, storageAccount.Credentials) 7: { 8: _storageAccount = storageAccount; 9:  10: var tableStorage = new CloudTableClient(_storageAccount.TableEndpoint.AbsoluteUri, 11: _storageAccount.Credentials); 12: tableStorage.CreateTableIfNotExist("Account"); 13: } 14:  15: public void Add(Account accountToAdd) 16: { 17: AddObject("Account", accountToAdd); 18: SaveChanges(); 19: } 20:  21: public IQueryable<Account> Load() 22: { 23: return CreateQuery<Account>("Account"); 24: } 25: } The method returns the IQueryable<Account> so that I can perform the LINQ operation on it. And back to my service class, I will use it to implement my validation. 1: public bool Register(string email, string password) 2: { 3: var storageAccount = CloudStorageAccount.FromConfigurationSetting("DataConnectionString"); 4: var accountToAdd = new Account(email, password) { DateCreated = DateTime.Now }; 5: var accountContext = new AccountDataContext(storageAccount); 6:  7: // validation 8: var accountNumber = accountContext.Load() 9: .Where(a => a.Email == accountToAdd.Email) 10: .Count(); 11: if (accountNumber > 0) 12: { 13: throw new ApplicationException(string.Format("Your account {0} had been used.", accountToAdd.Email)); 14: } 15:  16: // create entity 17: try 18: { 19: accountContext.Add(accountToAdd); 20: return true; 21: } 22: catch (Exception ex) 23: { 24: Trace.TraceInformation(ex.ToString()); 25: } 26: return false; 27: } I used the Load method to retrieve the IQueryable<Account> and use Where method to find the accounts those email address are the same as the one is being registered. If it has I through an exception back to the client side. Let’s run it and test from my simple client application. Oops! Looks like we encountered an unexpected exception. It said the “Count” is not support by the ADO.NET Data Service LINQ managed library. That is because the table storage managed library (aka. TableServiceContext) is based on the ADO.NET Data Service and it supports very limit LINQ operation. Although I didn’t find a full list or documentation about which LINQ methods it supports I could even refer a page on msdn here. It gives us a roughly summary of which query operation the ADO.NET Data Service managed library supports and which doesn't. As you see the Count method is not in the supported list. Not only the query operation, there inner lambda expression in the Where method are limited when using the ADO.NET Data Service managed library as well. For example if you added (a => !a.DateDeleted.HasValue) in the Where method to exclude those deleted account it will raised an exception said "Invalid Input". Based on my experience you should always use the simple comparison (such as ==, >, <=, etc.) on the simple members (such as string, integer, etc.) and do not use any shortcut methods (such as string.Compare, string.IsNullOrEmpty etc.). 1: // validation 2: var accountNumber = accountContext.Load() 3: .Where(a => a.Email == accountToAdd.Email) 4: .ToList() 5: .Count; 6: if (accountNumber > 0) 7: { 8: throw new ApplicationException(string.Format("Your account {0} had been used.", accountToAdd.Email)); 9: } We changed the a bit and try again. Since I had created an account with my mail address so this time it gave me an exception said that the email had been used, which is correct.   Repository Pattern for Table Service The AccountDataContext takes the responsibility to save and load the account entity but only for that specific entity. Is that possible to have a dynamic or generic DataContext class which can operate any kinds of entity in my system? Of course yes. Although there's no typical database in table service we can threat the entities as the records, similar with the data entities if we used OR Mapping. As we can use some patterns for ORM architecture here we should be able to adopt the one of them - Repository Pattern in this example. We know that the base class - TableServiceContext provide 4 methods for operating the table entities which are CreateQuery, AddObject, UpdateObject and DeleteObject. And we can create a relationship between the enmity class, the table container name and entity set name. So it's really simple to have a generic base class for any kinds of entities. Let's rename the AccountDataContext to DynamicDataContext and make the type of Account as a type parameter if it. 1: public class DynamicDataContext<T> : TableServiceContext where T : TableServiceEntity 2: { 3: private CloudStorageAccount _storageAccount; 4: private string _entitySetName; 5:  6: public DynamicDataContext(CloudStorageAccount storageAccount) 7: : base(storageAccount.TableEndpoint.AbsoluteUri, storageAccount.Credentials) 8: { 9: _storageAccount = storageAccount; 10: _entitySetName = typeof(T).Name; 11:  12: var tableStorage = new CloudTableClient(_storageAccount.TableEndpoint.AbsoluteUri, 13: _storageAccount.Credentials); 14: tableStorage.CreateTableIfNotExist(_entitySetName); 15: } 16:  17: public void Add(T entityToAdd) 18: { 19: AddObject(_entitySetName, entityToAdd); 20: SaveChanges(); 21: } 22:  23: public void Update(T entityToUpdate) 24: { 25: UpdateObject(entityToUpdate); 26: SaveChanges(); 27: } 28:  29: public void Delete(T entityToDelete) 30: { 31: DeleteObject(entityToDelete); 32: SaveChanges(); 33: } 34:  35: public IQueryable<T> Load() 36: { 37: return CreateQuery<T>(_entitySetName); 38: } 39: } I saved the name of the entity type when constructed for performance matter. The table name, entity set name would be the same as the name of the entity class. The Load method returned a generic IQueryable instance which supports the lazy load feature. Then in my service class I changed the AccountDataContext to DynamicDataContext and that's all. 1: var accountContext = new DynamicDataContext<Account>(storageAccount); Run it again and register another account. The DynamicDataContext now can be used for any entities. For example, I would like the account has a list of notes which contains 3 custom properties: Account Email, Title and Content. We create the note entity class. 1: public class Note : TableServiceEntity 2: { 3: public string AccountEmail { get; set; } 4: public string Title { get; set; } 5: public string Content { get; set; } 6: public DateTime DateCreated { get; set; } 7: public DateTime? DateDeleted { get; set; } 8:  9: public Note() 10: : base() 11: { 12: } 13:  14: public Note(string email) 15: : base(email, string.Format("{0}_{1}", email, Guid.NewGuid().ToString())) 16: { 17: AccountEmail = email; 18: } 19: } And no need to tweak the DynamicDataContext we can directly go to the service class to implement the logic. Notice here I utilized two DynamicDataContext instances with the different type parameters: Note and Account. 1: public class NoteService : INoteService 2: { 3: public void Create(string email, string title, string content) 4: { 5: var storageAccount = CloudStorageAccount.FromConfigurationSetting("DataConnectionString"); 6: var accountContext = new DynamicDataContext<Account>(storageAccount); 7: var noteContext = new DynamicDataContext<Note>(storageAccount); 8:  9: // validate - email must be existed 10: var accounts = accountContext.Load() 11: .Where(a => a.Email == email) 12: .ToList() 13: .Count; 14: if (accounts <= 0) 15: throw new ApplicationException(string.Format("The account {0} does not exsit in the system please register and try again.", email)); 16:  17: // save the note 18: var noteToAdd = new Note(email) { Title = title, Content = content, DateCreated = DateTime.Now }; 19: noteContext.Add(noteToAdd); 20: } 21: } And updated our client application to test the service. I didn't implement any list service to show all notes but we can have a look on the local SQL database if we ran it at local development fabric.   Summary In this post I explained a bit about the limited LINQ support for the table service. And then I demonstrated about how to use the repository pattern in the table service data access layer and make the DataContext dynamically. The DynamicDataContext I created in this post is just a prototype. In fact we should create the relevant interface to make it testable and for better structure we'd better separate the DataContext classes for each individual kind of entity. So it should have IDataContextBase<T>, DataContextBase<T> and for each entity we would have class AccountDataContext<Account> : IDataContextBase<Account>, DataContextBase<Account> { … } class NoteDataContext<Note> : IDataContextBase<Note>, DataContextBase<Note> { … }   Besides the structured data saving and loading, another common scenario would be saving and loading some binary data such as images, files. In my next post I will show how to use the Blob Service to store the bindery data - make the account be able to upload their logo in my example.   Hope this helps, Shaun   All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Windows Azure Evolution &ndash; Caching (Preview)

    - by Shaun
    Caching is a popular topic when we are building a high performance and high scalable system not only on top of the cloud platform but the on-premise environment as well. On March 2011 the Windows Azure AppFabric Caching had been production launched. It provides an in-memory, distributed caching service over the cloud. And now, in this June 2012 update, the cache team announce a grand new caching solution on Windows Azure, which is called Windows Azure Caching (Preview). And the original Windows Azure AppFabric Caching was renamed to Windows Azure Shared Caching.   What’s Caching (Preview) If you had been using the Shared Caching you should know that it is constructed by a bunch of cache servers. And when you want to use you should firstly create a cache account from the developer portal and specify the size you want to use, which means how much memory you can use to store your data that wanted to be cached. Then you can add, get and remove them through your code through the cache URL. The Shared Caching is a multi-tenancy system which host all cached items across all users. So you don’t know which server your data was located. This caching mode works well and can take most of the cases. But it has some problems. The first one is the performance. Since the Shared Caching is a multi-tenancy system, which means all cache operations should go through the Shared Caching gateway and then routed to the server which have the data your are looking for. Even though there are some caches in the Shared Caching system it also takes time from your cloud services to the cache service. Secondary, the Shared Caching service works as a block box to the developer. The only thing we know is my cache endpoint, and that’s all. Someone may satisfied since they don’t want to care about anything underlying. But if you need to know more and want more control that’s impossible in the Shared Caching. The last problem would be the price and cost-efficiency. You pay the bill based on how much cache you requested per month. But when we host a web role or worker role, it seldom consumes all of the memory and CPU in the virtual machine (service instance). If using Shared Caching we have to pay for the cache service while waste of some of our memory and CPU locally. Since the issues above Microsoft offered a new caching mode over to us, which is the Caching (Preview). Instead of having a separated cache service, the Caching (Preview) leverage the memory and CPU in our cloud services (web role and worker role) as the cache clusters. Hence the Caching (Preview) runs on the virtual machines which hosted or near our cloud applications. Without any gateway and routing, since it located in the same data center and same racks, it provides really high performance than the Shared Caching. The Caching (Preview) works side-by-side to our application, initialized and worked as a Windows Service running in the virtual machines invoked by the startup tasks from our roles, we could get more information and control to them. And since the Caching (Preview) utilizes the memory and CPU from our existing cloud services, so it’s free. What we need to pay is the original computing price. And the resource on each machines could be used more efficiently.   Enable Caching (Preview) It’s very simple to enable the Caching (Preview) in a cloud service. Let’s create a new windows azure cloud project from Visual Studio and added an ASP.NET Web Role. Then open the role setting and select the Caching page. This is where we enable and configure the Caching (Preview) on a role. To enable the Caching (Preview) just open the “Enable Caching (Preview Release)” check box. And then we need to specify which mode of the caching clusters we want to use. There are two kinds of caching mode, co-located and dedicate. The co-located mode means we use the memory in the instances we run our cloud services (web role or worker role). By using this mode we must specify how many percentage of the memory will be used as the cache. The default value is 30%. So make sure it will not affect the role business execution. The dedicate mode will use all memory in the virtual machine as the cache. In fact it will reserve some for operation system, azure hosting etc.. But it will try to use as much as the available memory to be the cache. As you can see, the Caching (Preview) was defined based on roles, which means all instances of this role will apply the same setting and play as a whole cache pool, and you can consume it by specifying the name of the role, which I will demonstrate later. And in a windows azure project we can have more than one role have the Caching (Preview) enabled. Then we will have more caches. For example, let’s say I have a web role and worker role. The web role I specified 30% co-located caching and the worker role I specified dedicated caching. If I have 3 instances of my web role and 2 instances of my worker role, then I will have two caches. As the figure above, cache 1 was contributed by three web role instances while cache 2 was contributed by 2 worker role instances. Then we can add items into cache 1 and retrieve it from web role code and worker role code. But the items stored in cache 1 cannot be retrieved from cache 2 since they are isolated. Back to our Visual Studio we specify 30% of co-located cache and use the local storage emulator to store the cache cluster runtime status. Then at the bottom we can specify the named caches. Now we just use the default one. Now we had enabled the Caching (Preview) in our web role settings. Next, let’s have a look on how to consume our cache.   Consume Caching (Preview) The Caching (Preview) can only be consumed by the roles in the same cloud services. As I mentioned earlier, a cache contributed by web role can be connected from a worker role if they are in the same cloud service. But you cannot consume a Caching (Preview) from other cloud services. This is different from the Shared Caching. The Shared Caching is opened to all services if it has the connection URL and authentication token. To consume the Caching (Preview) we need to add some references into our project as well as some configuration in the Web.config. NuGet makes our life easy. Right click on our web role project and select “Manage NuGet packages”, and then search the package named “WindowsAzure.Caching”. In the package list install the “Windows Azure Caching Preview”. It will download all necessary references from the NuGet repository and update our Web.config as well. Open the Web.config of our web role and find the “dataCacheClients” node. Under this node we can specify the cache clients we are going to use. For each cache client it will use the role name to identity and find the cache. Since we only have this web role with the Caching (Preview) enabled so I pasted the current role name in the configuration. Then, in the default page I will add some code to show how to use the cache. I will have a textbox on the page where user can input his or her name, then press a button to generate the email address for him/her. And in backend code I will check if this name had been added in cache. If yes I will return the email back immediately. Otherwise, I will sleep the tread for 2 seconds to simulate the latency, then add it into cache and return back to the page. 1: protected void btnGenerate_Click(object sender, EventArgs e) 2: { 3: // check if name is specified 4: var name = txtName.Text; 5: if (string.IsNullOrWhiteSpace(name)) 6: { 7: lblResult.Text = "Error. Please specify name."; 8: return; 9: } 10:  11: bool cached; 12: var sw = new Stopwatch(); 13: sw.Start(); 14:  15: // create the cache factory and cache 16: var factory = new DataCacheFactory(); 17: var cache = factory.GetDefaultCache(); 18:  19: // check if the name specified is in cache 20: var email = cache.Get(name) as string; 21: if (email != null) 22: { 23: cached = true; 24: sw.Stop(); 25: } 26: else 27: { 28: cached = false; 29: // simulate the letancy 30: Thread.Sleep(2000); 31: email = string.Format("{0}@igt.com", name); 32: // add to cache 33: cache.Add(name, email); 34: } 35:  36: sw.Stop(); 37: lblResult.Text = string.Format( 38: "Cached = {0}. Duration: {1}s. {2} => {3}", 39: cached, sw.Elapsed.TotalSeconds.ToString("0.00"), name, email); 40: } The Caching (Preview) can be used on the local emulator so we just F5. The first time I entered my name it will take about 2 seconds to get the email back to me since it was not in the cache. But if we re-enter my name it will be back at once from the cache. Since the Caching (Preview) is distributed across all instances of the role, so we can scaling-out it by scaling-out our web role. Just use 2 instances and tweak some code to show the current instance ID in the page, and have another try. Then we can see the cache can be retrieved even though it was added by another instance.   Consume Caching (Preview) Across Roles As I mentioned, the Caching (Preview) can be consumed by all other roles within the same cloud service. For example, let’s add another web role in our cloud solution and add the same code in its default page. In the Web.config we add the cache client to one enabled in the last role, by specifying its role name here. Then we start the solution locally and go to web role 1, specify the name and let it generate the email to us. Since there’s no cache for this name so it will take about 2 seconds but will save the email into cache. And then we go to web role 2 and specify the same name. Then you can see it retrieve the email saved by the web role 1 and returned back very quickly. Finally then we can upload our application to Windows Azure and test again. Make sure you had changed the cache cluster status storage account to the real azure account.   More Awesome Features As a in-memory distributed caching solution, the Caching (Preview) has some fancy features I would like to highlight here. The first one is the high availability support. This is the first time I have heard that a distributed cache support high availability. In the distributed cache world if a cache cluster was failed, the data it stored will be lost. This behavior was introduced by Memcached and is followed by almost all distributed cache productions. But Caching (Preview) provides high availability, which means you can specify if the named cache will be backup automatically. If yes then the data belongs to this named cache will be replicated on another role instance of this role. Then if one of the instance was failed the data can be retrieved from its backup instance. To enable the backup just open the Caching page in Visual Studio. In the named cache you want to enable backup, change the Backup Copies value from 0 to 1. The value of Backup Copies only for 0 and 1. “0” means no backup and no high availability while “1” means enabled high availability with backup the data into another instance. But by using the high availability feature there are something we need to make sure. Firstly the high availability does NOT means the data in cache will never be lost for any kind of failure. For example, if we have a role with cache enabled that has 10 instances, and 9 of them was failed, then most of the cached data will be lost since the primary and backup instance may failed together. But normally is will not be happened since MS guarantees that it will use the instance in the different fault domain for backup cache. Another one is that, enabling the backup means you store two copies of your data. For example if you think 100MB memory is OK for cache, but you need at least 200MB if you enabled backup. Besides the high availability, the Caching (Preview) support more features introduced in Windows Server AppFabric Caching than the Windows Azure Shared Caching. It supports local cache with notification. It also support absolute and slide window expiration types as well. And the Caching (Preview) also support the Memcached protocol as well. This means if you have an application based on Memcached, you can use Caching (Preview) without any code changes. What you need to do is to change the configuration of how you connect to the cache. Similar as the Windows Azure Shared Caching, MS also offers the out-of-box ASP.NET session provider and output cache provide on top of the Caching (Preview).   Summary Caching is very important component when we building a cloud-based application. In the June 2012 update MS provides a new cache solution named Caching (Preview). Different from the existing Windows Azure Shared Caching, Caching (Preview) runs the cache cluster within the role instances we have deployed to the cloud. It gives more control, more performance and more cost-effect. So now we have two caching solutions in Windows Azure, the Shared Caching and Caching (Preview). If you need a central cache service which can be used by many cloud services and web sites, then you have to use the Shared Caching. But if you only need a fast, near distributed cache, then you’d better use Caching (Preview).   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Node.js Adventure - Host Node.js on Windows Azure Worker Role

    - by Shaun
    In my previous post I demonstrated about how to develop and deploy a Node.js application on Windows Azure Web Site (a.k.a. WAWS). WAWS is a new feature in Windows Azure platform. Since it’s low-cost, and it provides IIS and IISNode components so that we can host our Node.js application though Git, FTP and WebMatrix without any configuration and component installation. But sometimes we need to use the Windows Azure Cloud Service (a.k.a. WACS) and host our Node.js on worker role. Below are some benefits of using worker role. - WAWS leverages IIS and IISNode to host Node.js application, which runs in x86 WOW mode. It reduces the performance comparing with x64 in some cases. - WACS worker role does not need IIS, hence there’s no restriction of IIS, such as 8000 concurrent requests limitation. - WACS provides more flexibility and controls to the developers. For example, we can RDP to the virtual machines of our worker role instances. - WACS provides the service configuration features which can be changed when the role is running. - WACS provides more scaling capability than WAWS. In WAWS we can have at most 3 reserved instances per web site while in WACS we can have up to 20 instances in a subscription. - Since when using WACS worker role we starts the node by ourselves in a process, we can control the input, output and error stream. We can also control the version of Node.js.   Run Node.js in Worker Role Node.js can be started by just having its execution file. This means in Windows Azure, we can have a worker role with the “node.exe” and the Node.js source files, then start it in Run method of the worker role entry class. Let’s create a new windows azure project in Visual Studio and add a new worker role. Since we need our worker role execute the “node.exe” with our application code we need to add the “node.exe” into our project. Right click on the worker role project and add an existing item. By default the Node.js will be installed in the “Program Files\nodejs” folder so we can navigate there and add the “node.exe”. Then we need to create the entry code of Node.js. In WAWS the entry file must be named “server.js”, which is because it’s hosted by IIS and IISNode and IISNode only accept “server.js”. But here as we control everything we can choose any files as the entry code. For example, I created a new JavaScript file named “index.js” in project root. Since we created a C# Windows Azure project we cannot create a JavaScript file from the context menu “Add new item”. We have to create a text file, and then rename it to JavaScript extension. After we added these two files we should set their “Copy to Output Directory” property to “Copy Always”, or “Copy if Newer”. Otherwise they will not be involved in the package when deployed. Let’s paste a very simple Node.js code in the “index.js” as below. As you can see I created a web server listening at port 12345. 1: var http = require("http"); 2: var port = 12345; 3:  4: http.createServer(function (req, res) { 5: res.writeHead(200, { "Content-Type": "text/plain" }); 6: res.end("Hello World\n"); 7: }).listen(port); 8:  9: console.log("Server running at port %d", port); Then we need to start “node.exe” with this file when our worker role was started. This can be done in its Run method. I found the Node.js and entry JavaScript file name, and then create a new process to run it. Our worker role will wait for the process to be exited. If everything is OK once our web server was opened the process will be there listening for incoming requests, and should not be terminated. The code in worker role would be like this. 1: public override void Run() 2: { 3: // This is a sample worker implementation. Replace with your logic. 4: Trace.WriteLine("NodejsHost entry point called", "Information"); 5:  6: // retrieve the node.exe and entry node.js source code file name. 7: var node = Environment.ExpandEnvironmentVariables(@"%RoleRoot%\approot\node.exe"); 8: var js = "index.js"; 9:  10: // prepare the process starting of node.exe 11: var info = new ProcessStartInfo(node, js) 12: { 13: CreateNoWindow = false, 14: ErrorDialog = true, 15: WindowStyle = ProcessWindowStyle.Normal, 16: UseShellExecute = false, 17: WorkingDirectory = Environment.ExpandEnvironmentVariables(@"%RoleRoot%\approot") 18: }; 19: Trace.WriteLine(string.Format("{0} {1}", node, js), "Information"); 20:  21: // start the node.exe with entry code and wait for exit 22: var process = Process.Start(info); 23: process.WaitForExit(); 24: } Then we can run it locally. In the computer emulator UI the worker role started and it executed the Node.js, then Node.js windows appeared. Open the browser to verify the website hosted by our worker role. Next let’s deploy it to azure. But we need some additional steps. First, we need to create an input endpoint. By default there’s no endpoint defined in a worker role. So we will open the role property window in Visual Studio, create a new input TCP endpoint to the port we want our website to use. In this case I will use 80. Even though we created a web server we should add a TCP endpoint of the worker role, since Node.js always listen on TCP instead of HTTP. And then changed the “index.js”, let our web server listen on 80. 1: var http = require("http"); 2: var port = 80; 3:  4: http.createServer(function (req, res) { 5: res.writeHead(200, { "Content-Type": "text/plain" }); 6: res.end("Hello World\n"); 7: }).listen(port); 8:  9: console.log("Server running at port %d", port); Then publish it to Windows Azure. And then in browser we can see our Node.js website was running on WACS worker role. We may encounter an error if we tried to run our Node.js website on 80 port at local emulator. This is because the compute emulator registered 80 and map the 80 endpoint to 81. But our Node.js cannot detect this operation. So when it tried to listen on 80 it will failed since 80 have been used.   Use NPM Modules When we are using WAWS to host Node.js, we can simply install modules we need, and then just publish or upload all files to WAWS. But if we are using WACS worker role, we have to do some extra steps to make the modules work. Assuming that we plan to use “express” in our application. Firstly of all we should download and install this module through NPM command. But after the install finished, they are just in the disk but not included in the worker role project. If we deploy the worker role right now the module will not be packaged and uploaded to azure. Hence we need to add them to the project. On solution explorer window click the “Show all files” button, select the “node_modules” folder and in the context menu select “Include In Project”. But that not enough. We also need to make all files in this module to “Copy always” or “Copy if newer”, so that they can be uploaded to azure with the “node.exe” and “index.js”. This is painful step since there might be many files in a module. So I created a small tool which can update a C# project file, make its all items as “Copy always”. The code is very simple. 1: static void Main(string[] args) 2: { 3: if (args.Length < 1) 4: { 5: Console.WriteLine("Usage: copyallalways [project file]"); 6: return; 7: } 8:  9: var proj = args[0]; 10: File.Copy(proj, string.Format("{0}.bak", proj)); 11:  12: var xml = new XmlDocument(); 13: xml.Load(proj); 14: var nsManager = new XmlNamespaceManager(xml.NameTable); 15: nsManager.AddNamespace("pf", "http://schemas.microsoft.com/developer/msbuild/2003"); 16:  17: // add the output setting to copy always 18: var contentNodes = xml.SelectNodes("//pf:Project/pf:ItemGroup/pf:Content", nsManager); 19: UpdateNodes(contentNodes, xml, nsManager); 20: var noneNodes = xml.SelectNodes("//pf:Project/pf:ItemGroup/pf:None", nsManager); 21: UpdateNodes(noneNodes, xml, nsManager); 22: xml.Save(proj); 23:  24: // remove the namespace attributes 25: var content = xml.InnerXml.Replace("<CopyToOutputDirectory xmlns=\"\">", "<CopyToOutputDirectory>"); 26: xml.LoadXml(content); 27: xml.Save(proj); 28: } 29:  30: static void UpdateNodes(XmlNodeList nodes, XmlDocument xml, XmlNamespaceManager nsManager) 31: { 32: foreach (XmlNode node in nodes) 33: { 34: var copyToOutputDirectoryNode = node.SelectSingleNode("pf:CopyToOutputDirectory", nsManager); 35: if (copyToOutputDirectoryNode == null) 36: { 37: var n = xml.CreateNode(XmlNodeType.Element, "CopyToOutputDirectory", null); 38: n.InnerText = "Always"; 39: node.AppendChild(n); 40: } 41: else 42: { 43: if (string.Compare(copyToOutputDirectoryNode.InnerText, "Always", true) != 0) 44: { 45: copyToOutputDirectoryNode.InnerText = "Always"; 46: } 47: } 48: } 49: } Please be careful when use this tool. I created only for demo so do not use it directly in a production environment. Unload the worker role project, execute this tool with the worker role project file name as the command line argument, it will set all items as “Copy always”. Then reload this worker role project. Now let’s change the “index.js” to use express. 1: var express = require("express"); 2: var app = express(); 3:  4: var port = 80; 5:  6: app.configure(function () { 7: }); 8:  9: app.get("/", function (req, res) { 10: res.send("Hello Node.js!"); 11: }); 12:  13: app.get("/User/:id", function (req, res) { 14: var id = req.params.id; 15: res.json({ 16: "id": id, 17: "name": "user " + id, 18: "company": "IGT" 19: }); 20: }); 21:  22: app.listen(port); Finally let’s publish it and have a look in browser.   Use Windows Azure SQL Database We can use Windows Azure SQL Database (a.k.a. WACD) from Node.js as well on worker role hosting. Since we can control the version of Node.js, here we can use x64 version of “node-sqlserver” now. This is better than if we host Node.js on WAWS since it only support x86. Just install the “node-sqlserver” module from NPM, copy the “sqlserver.node” from “Build\Release” folder to “Lib” folder. Include them in worker role project and run my tool to make them to “Copy always”. Finally update the “index.js” to use WASD. 1: var express = require("express"); 2: var sql = require("node-sqlserver"); 3:  4: var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:{SERVER NAME}.database.windows.net,1433;Database={DATABASE NAME};Uid={LOGIN}@{SERVER NAME};Pwd={PASSWORD};Encrypt=yes;Connection Timeout=30;"; 5: var port = 80; 6:  7: var app = express(); 8:  9: app.configure(function () { 10: app.use(express.bodyParser()); 11: }); 12:  13: app.get("/", function (req, res) { 14: sql.open(connectionString, function (err, conn) { 15: if (err) { 16: console.log(err); 17: res.send(500, "Cannot open connection."); 18: } 19: else { 20: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 21: if (err) { 22: console.log(err); 23: res.send(500, "Cannot retrieve records."); 24: } 25: else { 26: res.json(results); 27: } 28: }); 29: } 30: }); 31: }); 32:  33: app.get("/text/:key/:culture", function (req, res) { 34: sql.open(connectionString, function (err, conn) { 35: if (err) { 36: console.log(err); 37: res.send(500, "Cannot open connection."); 38: } 39: else { 40: var key = req.params.key; 41: var culture = req.params.culture; 42: var command = "SELECT * FROM [Resource] WHERE [Key] = '" + key + "' AND [Culture] = '" + culture + "'"; 43: conn.queryRaw(command, function (err, results) { 44: if (err) { 45: console.log(err); 46: res.send(500, "Cannot retrieve records."); 47: } 48: else { 49: res.json(results); 50: } 51: }); 52: } 53: }); 54: }); 55:  56: app.get("/sproc/:key/:culture", function (req, res) { 57: sql.open(connectionString, function (err, conn) { 58: if (err) { 59: console.log(err); 60: res.send(500, "Cannot open connection."); 61: } 62: else { 63: var key = req.params.key; 64: var culture = req.params.culture; 65: var command = "EXEC GetItem '" + key + "', '" + culture + "'"; 66: conn.queryRaw(command, function (err, results) { 67: if (err) { 68: console.log(err); 69: res.send(500, "Cannot retrieve records."); 70: } 71: else { 72: res.json(results); 73: } 74: }); 75: } 76: }); 77: }); 78:  79: app.post("/new", function (req, res) { 80: var key = req.body.key; 81: var culture = req.body.culture; 82: var val = req.body.val; 83:  84: sql.open(connectionString, function (err, conn) { 85: if (err) { 86: console.log(err); 87: res.send(500, "Cannot open connection."); 88: } 89: else { 90: var command = "INSERT INTO [Resource] VALUES ('" + key + "', '" + culture + "', N'" + val + "')"; 91: conn.queryRaw(command, function (err, results) { 92: if (err) { 93: console.log(err); 94: res.send(500, "Cannot retrieve records."); 95: } 96: else { 97: res.send(200, "Inserted Successful"); 98: } 99: }); 100: } 101: }); 102: }); 103:  104: app.listen(port); Publish to azure and now we can see our Node.js is working with WASD through x64 version “node-sqlserver”.   Summary In this post I demonstrated how to host our Node.js in Windows Azure Cloud Service worker role. By using worker role we can control the version of Node.js, as well as the entry code. And it’s possible to do some pre jobs before the Node.js application started. It also removed the IIS and IISNode limitation. I personally recommended to use worker role as our Node.js hosting. But there are some problem if you use the approach I mentioned here. The first one is, we need to set all JavaScript files and module files as “Copy always” or “Copy if newer” manually. The second one is, in this way we cannot retrieve the cloud service configuration information. For example, we defined the endpoint in worker role property but we also specified the listening port in Node.js hardcoded. It should be changed that our Node.js can retrieve the endpoint. But I can tell you it won’t be working here. In the next post I will describe another way to execute the “node.exe” and Node.js application, so that we can get the cloud service configuration in Node.js. I will also demonstrate how to use Windows Azure Storage from Node.js by using the Windows Azure Node.js SDK.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Scaling-out Your Services by Message Bus based WCF Transport Extension &ndash; Part 1 &ndash; Background

    - by Shaun
    Cloud computing gives us more flexibility on the computing resource, we can provision and deploy an application or service with multiple instances over multiple machines. With the increment of the service instances, how to balance the incoming message and workload would become a new challenge. Currently there are two approaches we can use to pass the incoming messages to the service instances, I would like call them dispatcher mode and pulling mode.   Dispatcher Mode The dispatcher mode introduces a role which takes the responsible to find the best service instance to process the request. The image below describes the sharp of this mode. There are four clients communicate with the service through the underlying transportation. For example, if we are using HTTP the clients might be connecting to the same service URL. On the server side there’s a dispatcher listening on this URL and try to retrieve all messages. When a message came in, the dispatcher will find a proper service instance to process it. There are three mechanism to find the instance: Round-robin: Dispatcher will always send the message to the next instance. For example, if the dispatcher sent the message to instance 2, then the next message will be sent to instance 3, regardless if instance 3 is busy or not at that moment. Random: Dispatcher will find a service instance randomly, and same as the round-robin mode it regardless if the instance is busy or not. Sticky: Dispatcher will send all related messages to the same service instance. This approach always being used if the service methods are state-ful or session-ful. But as you can see, all of these approaches are not really load balanced. The clients will send messages at any time, and each message might take different process duration on the server side. This means in some cases, some of the service instances are very busy while others are almost idle. For example, if we were using round-robin mode, it could be happened that most of the simple task messages were passed to instance 1 while the complex ones were sent to instance 3, even though instance 1 should be idle. This brings some problem in our architecture. The first one is that, the response to the clients might be longer than it should be. As it’s shown in the figure above, message 6 and 9 can be processed by instance 1 or instance 2, but in reality they were dispatched to the busy instance 3 since the dispatcher and round-robin mode. Secondly, if there are many requests came from the clients in a very short period, service instances might be filled by tons of pending tasks and some instances might be crashed. Third, if we are using some cloud platform to host our service instances, for example the Windows Azure, the computing resource is billed by service deployment period instead of the actual CPU usage. This means if any service instance is idle it is wasting our money! Last one, the dispatcher would be the bottleneck of our system since all incoming messages must be routed by the dispatcher. If we are using HTTP or TCP as the transport, the dispatcher would be a network load balance. If we wants more capacity, we have to scale-up, or buy a hardware load balance which is very expensive, as well as scaling-out the service instances. Pulling Mode Pulling mode doesn’t need a dispatcher to route the messages. All service instances are listening to the same transport and try to retrieve the next proper message to process if they are idle. Since there is no dispatcher in pulling mode, it requires some features on the transportation. The transportation must support multiple client connection and server listening. HTTP and TCP doesn’t allow multiple clients are listening on the same address and port, so it cannot be used in pulling mode directly. All messages in the transportation must be FIFO, which means the old message must be received before the new one. Message selection would be a plus on the transportation. This means both service and client can specify some selection criteria and just receive some specified kinds of messages. This feature is not mandatory but would be very useful when implementing the request reply and duplex WCF channel modes. Otherwise we must have a memory dictionary to store the reply messages. I will explain more about this in the following articles. Message bus, or the message queue would be best candidate as the transportation when using the pulling mode. First, it allows multiple application to listen on the same queue, and it’s FIFO. Some of the message bus also support the message selection, such as TIBCO EMS, RabbitMQ. Some others provide in memory dictionary which can store the reply messages, for example the Redis. The principle of pulling mode is to let the service instances self-managed. This means each instance will try to retrieve the next pending incoming message if they finished the current task. This gives us more benefit and can solve the problems we met with in the dispatcher mode. The incoming message will be received to the best instance to process, which means this will be very balanced. And it will not happen that some instances are busy while other are idle, since the idle one will retrieve more tasks to make them busy. Since all instances are try their best to be busy we can use less instances than dispatcher mode, which more cost effective. Since there’s no dispatcher in the system, there is no bottleneck. When we introduced more service instances, in dispatcher mode we have to change something to let the dispatcher know the new instances. But in pulling mode since all service instance are self-managed, there no extra change at all. If there are many incoming messages, since the message bus can queue them in the transportation, service instances would not be crashed. All above are the benefits using the pulling mode, but it will introduce some problem as well. The process tracking and debugging become more difficult. Since the service instances are self-managed, we cannot know which instance will process the message. So we need more information to support debug and track. Real-time response may not be supported. All service instances will process the next message after the current one has done, if we have some real-time request this may not be a good solution. Compare with the Pros and Cons above, the pulling mode would a better solution for the distributed system architecture. Because what we need more is the scalability, cost-effect and the self-management.   WCF and WCF Transport Extensibility Windows Communication Foundation (WCF) is a framework for building service-oriented applications. In the .NET world WCF is the best way to implement the service. In this series I’m going to demonstrate how to implement the pulling mode on top of a message bus by extending the WCF. I don’t want to deep into every related field in WCF but will highlight its transport extensibility. When we implemented an RPC foundation there are many aspects we need to deal with, for example the message encoding, encryption, authentication and message sending and receiving. In WCF, each aspect is represented by a channel. A message will be passed through all necessary channels and finally send to the underlying transportation. And on the other side the message will be received from the transport and though the same channels until the business logic. This mode is called “Channel Stack” in WCF, and the last channel in the channel stack must always be a transport channel, which takes the responsible for sending and receiving the messages. As we are going to implement the WCF over message bus and implement the pulling mode scaling-out solution, we need to create our own transport channel so that the client and service can exchange messages over our bus. Before we deep into the transport channel, let’s have a look on the message exchange patterns that WCF defines. Message exchange pattern (MEP) defines how client and service exchange the messages over the transportation. WCF defines 3 basic MEPs which are datagram, Request-Reply and Duplex. Datagram: Also known as one-way, or fire-forgot mode. The message sent from the client to the service, and no need any reply from the service. The client doesn’t care about the message result at all. Request-Reply: Very common used pattern. The client send the request message to the service and wait until the reply message comes from the service. Duplex: The client sent message to the service, when the service processing the message it can callback to the client. When callback the service would be like a client while the client would be like a service. In WCF, each MEP represent some channels associated. MEP Channels Datagram IInputChannel, IOutputChannel Request-Reply IRequestChannel, IReplyChannel Duplex IDuplexChannel And the channels are created by ChannelListener on the server side, and ChannelFactory on the client side. The ChannelListener and ChannelFactory are created by the TransportBindingElement. The TransportBindingElement is created by the Binding, which can be defined as a new binding or from a custom binding. For more information about the transport channel mode, please refer to the MSDN document. The figure below shows the transport channel objects when using the request-reply MEP. And this is the datagram MEP. And this is the duplex MEP. After investigated the WCF transport architecture, channel mode and MEP, we finally identified what we should do to extend our message bus based transport layer. They are: Binding: (Optional) Defines the channel elements in the channel stack and added our transport binding element at the bottom of the stack. But we can use the build-in CustomBinding as well. TransportBindingElement: Defines which MEP is supported in our transport and create the related ChannelListener and ChannelFactory. This also defines the scheme of the endpoint if using this transport. ChannelListener: Create the server side channel based on the MEP it’s. We can have one ChannelListener to create channels for all supported MEPs, or we can have ChannelListener for each MEP. In this series I will use the second approach. ChannelFactory: Create the client side channel based on the MEP it’s. We can have one ChannelFactory to create channels for all supported MEPs, or we can have ChannelFactory for each MEP. In this series I will use the second approach. Channels: Based on the MEPs we want to support, we need to implement the channels accordingly. For example, if we want our transport support Request-Reply mode we should implement IRequestChannel and IReplyChannel. In this series I will implement all 3 MEPs listed above one by one. Scaffold: In order to make our transport extension works we also need to implement some scaffold stuff. For example we need some classes to send and receive message though out message bus. We also need some codes to read and write the WCF message, etc.. These are not necessary but would be very useful in our example.   Message Bus There is only one thing remained before we can begin to implement our scaling-out support WCF transport, which is the message bus. As I mentioned above, the message bus must have some features to fulfill all the WCF MEPs. In my company we will be using TIBCO EMS, which is an enterprise message bus product. And I have said before we can use any message bus production if it’s satisfied with our requests. Here I would like to introduce an interface to separate the message bus from the WCF. This allows us to implement the bus operations by any kinds bus we are going to use. The interface would be like this. 1: public interface IBus : IDisposable 2: { 3: string SendRequest(string message, bool fromClient, string from, string to = null); 4:  5: void SendReply(string message, bool fromClient, string replyTo); 6:  7: BusMessage Receive(bool fromClient, string replyTo); 8: } There are only three methods for the bus interface. Let me explain one by one. The SendRequest method takes the responsible for sending the request message into the bus. The parameters description are: message: The WCF message content. fromClient: Indicates if this message was came from the client. from: The channel ID that this message was sent from. The channel ID will be generated when any kinds of channel was created, which will be explained in the following articles. to: The channel ID that this message should be received. In Request-Reply and Duplex MEP this is necessary since the reply message must be received by the channel which sent the related request message. The SendReply method takes the responsible for sending the reply message. It’s very similar as the previous one but no “from” parameter. This is because it’s no need to reply a reply message again in any MEPs. The Receive method takes the responsible for waiting for a incoming message, includes the request message and specified reply message. It returned a BusMessage object, which contains some information about the channel information. The code of the BusMessage class is 1: public class BusMessage 2: { 3: public string MessageID { get; private set; } 4: public string From { get; private set; } 5: public string ReplyTo { get; private set; } 6: public string Content { get; private set; } 7:  8: public BusMessage(string messageId, string fromChannelId, string replyToChannelId, string content) 9: { 10: MessageID = messageId; 11: From = fromChannelId; 12: ReplyTo = replyToChannelId; 13: Content = content; 14: } 15: } Now let’s implement a message bus based on the IBus interface. Since I don’t want you to buy and install the TIBCO EMS or any other message bus products, I will implement an in process memory bus. This bus is only for test and sample purpose. It can only be used if the service and client are in the same process. Very straightforward. 1: public class InProcMessageBus : IBus 2: { 3: private readonly ConcurrentDictionary<Guid, InProcMessageEntity> _queue; 4: private readonly object _lock; 5:  6: public InProcMessageBus() 7: { 8: _queue = new ConcurrentDictionary<Guid, InProcMessageEntity>(); 9: _lock = new object(); 10: } 11:  12: public string SendRequest(string message, bool fromClient, string from, string to = null) 13: { 14: var entity = new InProcMessageEntity(message, fromClient, from, to); 15: _queue.TryAdd(entity.ID, entity); 16: return entity.ID.ToString(); 17: } 18:  19: public void SendReply(string message, bool fromClient, string replyTo) 20: { 21: var entity = new InProcMessageEntity(message, fromClient, null, replyTo); 22: _queue.TryAdd(entity.ID, entity); 23: } 24:  25: public BusMessage Receive(bool fromClient, string replyTo) 26: { 27: InProcMessageEntity e = null; 28: while (true) 29: { 30: lock (_lock) 31: { 32: var entity = _queue 33: .Where(kvp => kvp.Value.FromClient == fromClient && (kvp.Value.To == replyTo || string.IsNullOrWhiteSpace(kvp.Value.To))) 34: .FirstOrDefault(); 35: if (entity.Key != Guid.Empty && entity.Value != null) 36: { 37: _queue.TryRemove(entity.Key, out e); 38: } 39: } 40: if (e == null) 41: { 42: Thread.Sleep(100); 43: } 44: else 45: { 46: return new BusMessage(e.ID.ToString(), e.From, e.To, e.Content); 47: } 48: } 49: } 50:  51: public void Dispose() 52: { 53: } 54: } The InProcMessageBus stores the messages in the objects of InProcMessageEntity, which can take some extra information beside the WCF message itself. 1: public class InProcMessageEntity 2: { 3: public Guid ID { get; set; } 4: public string Content { get; set; } 5: public bool FromClient { get; set; } 6: public string From { get; set; } 7: public string To { get; set; } 8:  9: public InProcMessageEntity() 10: : this(string.Empty, false, string.Empty, string.Empty) 11: { 12: } 13:  14: public InProcMessageEntity(string content, bool fromClient, string from, string to) 15: { 16: ID = Guid.NewGuid(); 17: Content = content; 18: FromClient = fromClient; 19: From = from; 20: To = to; 21: } 22: }   Summary OK, now I have all necessary stuff ready. The next step would be implementing our WCF message bus transport extension. In this post I described two scaling-out approaches on the service side especially if we are using the cloud platform: dispatcher mode and pulling mode. And I compared the Pros and Cons of them. Then I introduced the WCF channel stack, channel mode and the transport extension part, and identified what we should do to create our own WCF transport extension, to let our WCF services using pulling mode based on a message bus. And finally I provided some classes that need to be used in the future posts that working against an in process memory message bus, for the demonstration purpose only. In the next post I will begin to implement the transport extension step by step.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Upload File to Windows Azure Blob in Chunks through ASP.NET MVC, JavaScript and HTML5

    - by Shaun
    Originally posted on: http://geekswithblogs.net/shaunxu/archive/2013/07/01/upload-file-to-windows-azure-blob-in-chunks-through-asp.net.aspxMany people are using Windows Azure Blob Storage to store their data in the cloud. Blob storage provides 99.9% availability with easy-to-use API through .NET SDK and HTTP REST. For example, we can store JavaScript files, images, documents in blob storage when we are building an ASP.NET web application on a Web Role in Windows Azure. Or we can store our VHD files in blob and mount it as a hard drive in our cloud service. If you are familiar with Windows Azure, you should know that there are two kinds of blob: page blob and block blob. The page blob is optimized for random read and write, which is very useful when you need to store VHD files. The block blob is optimized for sequential/chunk read and write, which has more common usage. Since we can upload block blob in blocks through BlockBlob.PutBlock, and them commit them as a whole blob with invoking the BlockBlob.PutBlockList, it is very powerful to upload large files, as we can upload blocks in parallel, and provide pause-resume feature. There are many documents, articles and blog posts described on how to upload a block blob. Most of them are focus on the server side, which means when you had received a big file, stream or binaries, how to upload them into blob storage in blocks through .NET SDK.  But the problem is, how can we upload these large files from client side, for example, a browser. This questioned to me when I was working with a Chinese customer to help them build a network disk production on top of azure. The end users upload their files from the web portal, and then the files will be stored in blob storage from the Web Role. My goal is to find the best way to transform the file from client (end user’s machine) to the server (Web Role) through browser. In this post I will demonstrate and describe what I had done, to upload large file in chunks with high speed, and save them as blocks into Windows Azure Blob Storage.   Traditional Upload, Works with Limitation The simplest way to implement this requirement is to create a web page with a form that contains a file input element and a submit button. 1: @using (Html.BeginForm("About", "Index", FormMethod.Post, new { enctype = "multipart/form-data" })) 2: { 3: <input type="file" name="file" /> 4: <input type="submit" value="upload" /> 5: } And then in the backend controller, we retrieve the whole content of this file and upload it in to the blob storage through .NET SDK. We can split the file in blocks and upload them in parallel and commit. The code had been well blogged in the community. 1: [HttpPost] 2: public ActionResult About(HttpPostedFileBase file) 3: { 4: var container = _client.GetContainerReference("test"); 5: container.CreateIfNotExists(); 6: var blob = container.GetBlockBlobReference(file.FileName); 7: var blockDataList = new Dictionary<string, byte[]>(); 8: using (var stream = file.InputStream) 9: { 10: var blockSizeInKB = 1024; 11: var offset = 0; 12: var index = 0; 13: while (offset < stream.Length) 14: { 15: var readLength = Math.Min(1024 * blockSizeInKB, (int)stream.Length - offset); 16: var blockData = new byte[readLength]; 17: offset += stream.Read(blockData, 0, readLength); 18: blockDataList.Add(Convert.ToBase64String(BitConverter.GetBytes(index)), blockData); 19:  20: index++; 21: } 22: } 23:  24: Parallel.ForEach(blockDataList, (bi) => 25: { 26: blob.PutBlock(bi.Key, new MemoryStream(bi.Value), null); 27: }); 28: blob.PutBlockList(blockDataList.Select(b => b.Key).ToArray()); 29:  30: return RedirectToAction("About"); 31: } This works perfect if we selected an image, a music or a small video to upload. But if I selected a large file, let’s say a 6GB HD-movie, after upload for about few minutes the page will be shown as below and the upload will be terminated. In ASP.NET there is a limitation of request length and the maximized request length is defined in the web.config file. It’s a number which less than about 4GB. So if we want to upload a really big file, we cannot simply implement in this way. Also, in Windows Azure, a cloud service network load balancer will terminate the connection if exceed the timeout period. From my test the timeout looks like 2 - 3 minutes. Hence, when we need to upload a large file we cannot just use the basic HTML elements. Besides the limitation mentioned above, the simple HTML file upload cannot provide rich upload experience such as chunk upload, pause and pause-resume. So we need to find a better way to upload large file from the client to the server.   Upload in Chunks through HTML5 and JavaScript In order to break those limitation mentioned above we will try to upload the large file in chunks. This takes some benefit to us such as - No request size limitation: Since we upload in chunks, we can define the request size for each chunks regardless how big the entire file is. - No timeout problem: The size of chunks are controlled by us, which means we should be able to make sure request for each chunk upload will not exceed the timeout period of both ASP.NET and Windows Azure load balancer. It was a big challenge to upload big file in chunks until we have HTML5. There are some new features and improvements introduced in HTML5 and we will use them to implement our solution.   In HTML5, the File interface had been improved with a new method called “slice”. It can be used to read part of the file by specifying the start byte index and the end byte index. For example if the entire file was 1024 bytes, file.slice(512, 768) will read the part of this file from the 512nd byte to 768th byte, and return a new object of interface called "Blob”, which you can treat as an array of bytes. In fact,  a Blob object represents a file-like object of immutable, raw data. The File interface is based on Blob, inheriting blob functionality and expanding it to support files on the user's system. For more information about the Blob please refer here. File and Blob is very useful to implement the chunk upload. We will use File interface to represent the file the user selected from the browser and then use File.slice to read the file in chunks in the size we wanted. For example, if we wanted to upload a 10MB file with 512KB chunks, then we can read it in 512KB blobs by using File.slice in a loop.   Assuming we have a web page as below. User can select a file, an input box to specify the block size in KB and a button to start upload. 1: <div> 2: <input type="file" id="upload_files" name="files[]" /><br /> 3: Block Size: <input type="number" id="block_size" value="512" name="block_size" />KB<br /> 4: <input type="button" id="upload_button_blob" name="upload" value="upload (blob)" /> 5: </div> Then we can have the JavaScript function to upload the file in chunks when user clicked the button. 1: <script type="text/javascript"> 1: 2: $(function () { 3: $("#upload_button_blob").click(function () { 4: }); 5: });</script> Firstly we need to ensure the client browser supports the interfaces we are going to use. Just try to invoke the File, Blob and FormData from the “window” object. If any of them is “undefined” the condition result will be “false” which means your browser doesn’t support these premium feature and it’s time for you to get your browser updated. FormData is another new feature we are going to use in the future. It could generate a temporary form for us. We will use this interface to create a form with chunk and associated metadata when invoked the service through ajax. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: if (window.File && window.Blob && window.FormData) { 4: alert("Your brwoser is awesome, let's rock!"); 5: } 6: else { 7: alert("Oh man plz update to a modern browser before try is cool stuff out."); 8: return; 9: } 10: }); Each browser supports these interfaces by their own implementation and currently the Blob, File and File.slice are supported by Chrome 21, FireFox 13, IE 10, Opera 12 and Safari 5.1 or higher. After that we worked on the files the user selected one by one since in HTML5, user can select multiple files in one file input box. 1: var files = $("#upload_files")[0].files; 2: for (var i = 0; i < files.length; i++) { 3: var file = files[i]; 4: var fileSize = file.size; 5: var fileName = file.name; 6: } Next, we calculated the start index and end index for each chunks based on the size the user specified from the browser. We put them into an array with the file name and the index, which will be used when we upload chunks into Windows Azure Blob Storage as blocks since we need to specify the target blob name and the block index. At the same time we will store the list of all indexes into another variant which will be used to commit blocks into blob in Azure Storage once all chunks had been uploaded successfully. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10:  11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: var blockSizeInKB = $("#block_size").val(); 14: var blockSize = blockSizeInKB * 1024; 15: var blocks = []; 16: var offset = 0; 17: var index = 0; 18: var list = ""; 19: while (offset < fileSize) { 20: var start = offset; 21: var end = Math.min(offset + blockSize, fileSize); 22:  23: blocks.push({ 24: name: fileName, 25: index: index, 26: start: start, 27: end: end 28: }); 29: list += index + ","; 30:  31: offset = end; 32: index++; 33: } 34: } 35: }); Now we have all chunks’ information ready. The next step should be upload them one by one to the server side, and at the server side when received a chunk it will upload as a block into Blob Storage, and finally commit them with the index list through BlockBlobClient.PutBlockList. But since all these invokes are ajax calling, which means not synchronized call. So we need to introduce a new JavaScript library to help us coordinate the asynchronize operation, which named “async.js”. You can download this JavaScript library here, and you can find the document here. I will not explain this library too much in this post. We will put all procedures we want to execute as a function array, and pass into the proper function defined in async.js to let it help us to control the execution sequence, in series or in parallel. Hence we will define an array and put the function for chunk upload into this array. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4:  5: // start to upload each files in chunks 6: var files = $("#upload_files")[0].files; 7: for (var i = 0; i < files.length; i++) { 8: var file = files[i]; 9: var fileSize = file.size; 10: var fileName = file.name; 11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: ... ... 14:  15: // define the function array and push all chunk upload operation into this array 16: blocks.forEach(function (block) { 17: putBlocks.push(function (callback) { 18: }); 19: }); 20: } 21: }); 22: }); As you can see, I used File.slice method to read each chunks based on the start and end byte index we calculated previously, and constructed a temporary HTML form with the file name, chunk index and chunk data through another new feature in HTML5 named FormData. Then post this form to the backend server through jQuery.ajax. This is the key part of our solution. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: blocks.forEach(function (block) { 15: putBlocks.push(function (callback) { 16: // load blob based on the start and end index for each chunks 17: var blob = file.slice(block.start, block.end); 18: // put the file name, index and blob into a temporary from 19: var fd = new FormData(); 20: fd.append("name", block.name); 21: fd.append("index", block.index); 22: fd.append("file", blob); 23: // post the form to backend service (asp.net mvc controller action) 24: $.ajax({ 25: url: "/Home/UploadInFormData", 26: data: fd, 27: processData: false, 28: contentType: "multipart/form-data", 29: type: "POST", 30: success: function (result) { 31: if (!result.success) { 32: alert(result.error); 33: } 34: callback(null, block.index); 35: } 36: }); 37: }); 38: }); 39: } 40: }); Then we will invoke these functions one by one by using the async.js. And once all functions had been executed successfully I invoked another ajax call to the backend service to commit all these chunks (blocks) as the blob in Windows Azure Storage. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.series(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); That’s all in the client side. The outline of our logic would be - Calculate the start and end byte index for each chunks based on the block size. - Defined the functions of reading the chunk form file and upload the content to the backend service through ajax. - Execute the functions defined in previous step with “async.js”. - Commit the chunks by invoking the backend service in Windows Azure Storage finally.   Save Chunks as Blocks into Blob Storage In above we finished the client size JavaScript code. It uploaded the file in chunks to the backend service which we are going to implement in this step. We will use ASP.NET MVC as our backend service, and it will receive the chunks, upload into Windows Azure Bob Storage in blocks, then finally commit as one blob. As in the client side we uploaded chunks by invoking the ajax call to the URL "/Home/UploadInFormData", I created a new action under the Index controller and it only accepts HTTP POST request. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: } 8: catch (Exception e) 9: { 10: error = e.ToString(); 11: } 12:  13: return new JsonResult() 14: { 15: Data = new 16: { 17: success = string.IsNullOrWhiteSpace(error), 18: error = error 19: } 20: }; 21: } Then I retrieved the file name, index and the chunk content from the Request.Form object, which was passed from our client side. And then, used the Windows Azure SDK to create a blob container (in this case we will use the container named “test”.) and create a blob reference with the blob name (same as the file name). Then uploaded the chunk as a block of this blob with the index, since in Blob Storage each block must have an index (ID) associated with so that finally we can put all blocks as one blob by specifying their block ID list. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var index = int.Parse(Request.Form["index"]); 9: var file = Request.Files[0]; 10: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 11:  12: var container = _client.GetContainerReference("test"); 13: container.CreateIfNotExists(); 14: var blob = container.GetBlockBlobReference(name); 15: blob.PutBlock(id, file.InputStream, null); 16: } 17: catch (Exception e) 18: { 19: error = e.ToString(); 20: } 21:  22: return new JsonResult() 23: { 24: Data = new 25: { 26: success = string.IsNullOrWhiteSpace(error), 27: error = error 28: } 29: }; 30: } Next, I created another action to commit the blocks into blob once all chunks had been uploaded. Similarly, I retrieved the blob name from the Request.Form. I also retrieved the chunks ID list, which is the block ID list from the Request.Form in a string format, split them as a list, then invoked the BlockBlob.PutBlockList method. After that our blob will be shown in the container and ready to be download. 1: [HttpPost] 2: public JsonResult Commit() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var list = Request.Form["list"]; 9: var ids = list 10: .Split(',') 11: .Where(id => !string.IsNullOrWhiteSpace(id)) 12: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 13: .ToArray(); 14:  15: var container = _client.GetContainerReference("test"); 16: container.CreateIfNotExists(); 17: var blob = container.GetBlockBlobReference(name); 18: blob.PutBlockList(ids); 19: } 20: catch (Exception e) 21: { 22: error = e.ToString(); 23: } 24:  25: return new JsonResult() 26: { 27: Data = new 28: { 29: success = string.IsNullOrWhiteSpace(error), 30: error = error 31: } 32: }; 33: } Now we finished all code we need. The whole process of uploading would be like this below. Below is the full client side JavaScript code. 1: <script type="text/javascript" src="~/Scripts/async.js"></script> 2: <script type="text/javascript"> 3: $(function () { 4: $("#upload_button_blob").click(function () { 5: // assert the browser support html5 6: if (window.File && window.Blob && window.FormData) { 7: alert("Your brwoser is awesome, let's rock!"); 8: } 9: else { 10: alert("Oh man plz update to a modern browser before try is cool stuff out."); 11: return; 12: } 13:  14: // start to upload each files in chunks 15: var files = $("#upload_files")[0].files; 16: for (var i = 0; i < files.length; i++) { 17: var file = files[i]; 18: var fileSize = file.size; 19: var fileName = file.name; 20:  21: // calculate the start and end byte index for each blocks(chunks) 22: // with the index, file name and index list for future using 23: var blockSizeInKB = $("#block_size").val(); 24: var blockSize = blockSizeInKB * 1024; 25: var blocks = []; 26: var offset = 0; 27: var index = 0; 28: var list = ""; 29: while (offset < fileSize) { 30: var start = offset; 31: var end = Math.min(offset + blockSize, fileSize); 32:  33: blocks.push({ 34: name: fileName, 35: index: index, 36: start: start, 37: end: end 38: }); 39: list += index + ","; 40:  41: offset = end; 42: index++; 43: } 44:  45: // define the function array and push all chunk upload operation into this array 46: var putBlocks = []; 47: blocks.forEach(function (block) { 48: putBlocks.push(function (callback) { 49: // load blob based on the start and end index for each chunks 50: var blob = file.slice(block.start, block.end); 51: // put the file name, index and blob into a temporary from 52: var fd = new FormData(); 53: fd.append("name", block.name); 54: fd.append("index", block.index); 55: fd.append("file", blob); 56: // post the form to backend service (asp.net mvc controller action) 57: $.ajax({ 58: url: "/Home/UploadInFormData", 59: data: fd, 60: processData: false, 61: contentType: "multipart/form-data", 62: type: "POST", 63: success: function (result) { 64: if (!result.success) { 65: alert(result.error); 66: } 67: callback(null, block.index); 68: } 69: }); 70: }); 71: }); 72:  73: // invoke the functions one by one 74: // then invoke the commit ajax call to put blocks into blob in azure storage 75: async.series(putBlocks, function (error, result) { 76: var data = { 77: name: fileName, 78: list: list 79: }; 80: $.post("/Home/Commit", data, function (result) { 81: if (!result.success) { 82: alert(result.error); 83: } 84: else { 85: alert("done!"); 86: } 87: }); 88: }); 89: } 90: }); 91: }); 92: </script> And below is the full ASP.NET MVC controller code. 1: public class HomeController : Controller 2: { 3: private CloudStorageAccount _account; 4: private CloudBlobClient _client; 5:  6: public HomeController() 7: : base() 8: { 9: _account = CloudStorageAccount.Parse(CloudConfigurationManager.GetSetting("DataConnectionString")); 10: _client = _account.CreateCloudBlobClient(); 11: } 12:  13: public ActionResult Index() 14: { 15: ViewBag.Message = "Modify this template to jump-start your ASP.NET MVC application."; 16:  17: return View(); 18: } 19:  20: [HttpPost] 21: public JsonResult UploadInFormData() 22: { 23: var error = string.Empty; 24: try 25: { 26: var name = Request.Form["name"]; 27: var index = int.Parse(Request.Form["index"]); 28: var file = Request.Files[0]; 29: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 30:  31: var container = _client.GetContainerReference("test"); 32: container.CreateIfNotExists(); 33: var blob = container.GetBlockBlobReference(name); 34: blob.PutBlock(id, file.InputStream, null); 35: } 36: catch (Exception e) 37: { 38: error = e.ToString(); 39: } 40:  41: return new JsonResult() 42: { 43: Data = new 44: { 45: success = string.IsNullOrWhiteSpace(error), 46: error = error 47: } 48: }; 49: } 50:  51: [HttpPost] 52: public JsonResult Commit() 53: { 54: var error = string.Empty; 55: try 56: { 57: var name = Request.Form["name"]; 58: var list = Request.Form["list"]; 59: var ids = list 60: .Split(',') 61: .Where(id => !string.IsNullOrWhiteSpace(id)) 62: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 63: .ToArray(); 64:  65: var container = _client.GetContainerReference("test"); 66: container.CreateIfNotExists(); 67: var blob = container.GetBlockBlobReference(name); 68: blob.PutBlockList(ids); 69: } 70: catch (Exception e) 71: { 72: error = e.ToString(); 73: } 74:  75: return new JsonResult() 76: { 77: Data = new 78: { 79: success = string.IsNullOrWhiteSpace(error), 80: error = error 81: } 82: }; 83: } 84: } And if we selected a file from the browser we will see our application will upload chunks in the size we specified to the server through ajax call in background, and then commit all chunks in one blob. Then we can find the blob in our Windows Azure Blob Storage.   Optimized by Parallel Upload In previous example we just uploaded our file in chunks. This solved the problem that ASP.NET MVC request content size limitation as well as the Windows Azure load balancer timeout. But it might introduce the performance problem since we uploaded chunks in sequence. In order to improve the upload performance we could modify our client side code a bit to make the upload operation invoked in parallel. The good news is that, “async.js” library provides the parallel execution function. If you remembered the code we invoke the service to upload chunks, it utilized “async.series” which means all functions will be executed in sequence. Now we will change this code to “async.parallel”. This will invoke all functions in parallel. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallel(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); In this way all chunks will be uploaded to the server side at the same time to maximize the bandwidth usage. This should work if the file was not very large and the chunk size was not very small. But for large file this might introduce another problem that too many ajax calls are sent to the server at the same time. So the best solution should be, upload the chunks in parallel with maximum concurrency limitation. The code below specified the concurrency limitation to 4, which means at the most only 4 ajax calls could be invoked at the same time. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallelLimit(putBlocks, 4, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: });   Summary In this post we discussed how to upload files in chunks to the backend service and then upload them into Windows Azure Blob Storage in blocks. We focused on the frontend side and leverage three new feature introduced in HTML 5 which are - File.slice: Read part of the file by specifying the start and end byte index. - Blob: File-like interface which contains the part of the file content. - FormData: Temporary form element that we can pass the chunk alone with some metadata to the backend service. Then we discussed the performance consideration of chunk uploading. Sequence upload cannot provide maximized upload speed, but the unlimited parallel upload might crash the browser and server if too many chunks. So we finally came up with the solution to upload chunks in parallel with the concurrency limitation. We also demonstrated how to utilize “async.js” JavaScript library to help us control the asynchronize call and the parallel limitation.   Regarding the chunk size and the parallel limitation value there is no “best” value. You need to test vary composition and find out the best one for your particular scenario. It depends on the local bandwidth, client machine cores and the server side (Windows Azure Cloud Service Virtual Machine) cores, memory and bandwidth. Below is one of my performance test result. The client machine was Windows 8 IE 10 with 4 cores. I was using Microsoft Cooperation Network. The web site was hosted on Windows Azure China North data center (in Beijing) with one small web role (1.7GB 1 core CPU, 1.75GB memory with 100Mbps bandwidth). The test cases were - Chunk size: 512KB, 1MB, 2MB, 4MB. - Upload Mode: Sequence, parallel (unlimited), parallel with limit (4 threads, 8 threads). - Chunk Format: base64 string, binaries. - Target file: 100MB. - Each case was tested 3 times. Below is the test result chart. Some thoughts, but not guidance or best practice: - Parallel gets better performance than series. - No significant performance improvement between parallel 4 threads and 8 threads. - Transform with binaries provides better performance than base64. - In all cases, chunk size in 1MB - 2MB gets better performance.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Service Discovery in WCF 4.0 &ndash; Part 1

    - by Shaun
    When designing a service oriented architecture (SOA) system, there will be a lot of services with many service contracts, endpoints and behaviors. Besides the client calling the service, in a large distributed system a service may invoke other services. In this case, one service might need to know the endpoints it invokes. This might not be a problem in a small system. But when you have more than 10 services this might be a problem. For example in my current product, there are around 10 services, such as the user authentication service, UI integration service, location service, license service, device monitor service, event monitor service, schedule job service, accounting service, player management service, etc..   Benefit of Discovery Service Since almost all my services need to invoke at least one other service. This would be a difficult task to make sure all services endpoints are configured correctly in every service. And furthermore, it would be a nightmare when a service changed its endpoint at runtime. Hence, we need a discovery service to remove the dependency (configuration dependency). A discovery service plays as a service dictionary which stores the relationship between the contracts and the endpoints for every service. By using the discovery service, when service X wants to invoke service Y, it just need to ask the discovery service where is service Y, then the discovery service will return all proper endpoints of service Y, then service X can use the endpoint to send the request to service Y. And when some services changed their endpoint address, all need to do is to update its records in the discovery service then all others will know its new endpoint. In WCF 4.0 Discovery it supports both managed proxy discovery mode and ad-hoc discovery mode. In ad-hoc mode there is no standalone discovery service. When a client wanted to invoke a service, it will broadcast an message (normally in UDP protocol) to the entire network with the service match criteria. All services which enabled the discovery behavior will receive this message and only those matched services will send their endpoint back to the client. The managed proxy discovery service works as I described above. In this post I will only cover the managed proxy mode, where there’s a discovery service. For more information about the ad-hoc mode please refer to the MSDN.   Service Announcement and Probe The main functionality of discovery service should be return the proper endpoint addresses back to the service who is looking for. In most cases the consume service (as a client) will send the contract which it wanted to request to the discovery service. And then the discovery service will find the endpoint and respond. Sometimes the contract and endpoint are not enough. It also contains versioning, extensions attributes. This post I will only cover the case includes contract and endpoint. When a client (or sometimes a service who need to invoke another service) need to connect to a target service, it will firstly request the discovery service through the “Probe” method with the criteria. Basically the criteria contains the contract type name of the target service. Then the discovery service will search its endpoint repository by the criteria. The repository might be a database, a distributed cache or a flat XML file. If it matches, the discovery service will grab the endpoint information (it’s called discovery endpoint metadata in WCF) and send back. And this is called “Probe”. Finally the client received the discovery endpoint metadata and will use the endpoint to connect to the target service. Besides the probe, discovery service should take the responsible to know there is a new service available when it goes online, as well as stopped when it goes offline. This feature is named “Announcement”. When a service started and stopped, it will announce to the discovery service. So the basic functionality of a discovery service should includes: 1, An endpoint which receive the service online message, and add the service endpoint information in the discovery repository. 2, An endpoint which receive the service offline message, and remove the service endpoint information from the discovery repository. 3, An endpoint which receive the client probe message, and return the matches service endpoints, and return the discovery endpoint metadata. WCF 4.0 discovery service just covers all these features in it's infrastructure classes.   Discovery Service in WCF 4.0 WCF 4.0 introduced a new assembly named System.ServiceModel.Discovery which has all necessary classes and interfaces to build a WS-Discovery compliant discovery service. It supports ad-hoc and managed proxy modes. For the case mentioned in this post, what we need to build is a standalone discovery service, which is the managed proxy discovery service mode. To build a managed discovery service in WCF 4.0 just create a new class inherits from the abstract class System.ServiceModel.Discovery.DiscoveryProxy. This class implemented and abstracted the procedures of service announcement and probe. And it exposes 8 abstract methods where we can implement our own endpoint register, unregister and find logic. These 8 methods are asynchronized, which means all invokes to the discovery service are asynchronously, for better service capability and performance. 1, OnBeginOnlineAnnouncement, OnEndOnlineAnnouncement: Invoked when a service sent the online announcement message. We need to add the endpoint information to the repository in this method. 2, OnBeginOfflineAnnouncement, OnEndOfflineAnnouncement: Invoked when a service sent the offline announcement message. We need to remove the endpoint information from the repository in this method. 3, OnBeginFind, OnEndFind: Invoked when a client sent the probe message that want to find the service endpoint information. We need to look for the proper endpoints by matching the client’s criteria through the repository in this method. 4, OnBeginResolve, OnEndResolve: Invoked then a client sent the resolve message. Different from the find method, when using resolve method the discovery service will return the exactly one service endpoint metadata to the client. In our example we will NOT implement this method.   Let’s create our own discovery service, inherit the base System.ServiceModel.Discovery.DiscoveryProxy. We also need to specify the service behavior in this class. Since the build-in discovery service host class only support the singleton mode, we must set its instance context mode to single. 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Text; 5: using System.ServiceModel.Discovery; 6: using System.ServiceModel; 7:  8: namespace Phare.Service 9: { 10: [ServiceBehavior(InstanceContextMode = InstanceContextMode.Single, ConcurrencyMode = ConcurrencyMode.Multiple)] 11: public class ManagedProxyDiscoveryService : DiscoveryProxy 12: { 13: protected override IAsyncResult OnBeginFind(FindRequestContext findRequestContext, AsyncCallback callback, object state) 14: { 15: throw new NotImplementedException(); 16: } 17:  18: protected override IAsyncResult OnBeginOfflineAnnouncement(DiscoveryMessageSequence messageSequence, EndpointDiscoveryMetadata endpointDiscoveryMetadata, AsyncCallback callback, object state) 19: { 20: throw new NotImplementedException(); 21: } 22:  23: protected override IAsyncResult OnBeginOnlineAnnouncement(DiscoveryMessageSequence messageSequence, EndpointDiscoveryMetadata endpointDiscoveryMetadata, AsyncCallback callback, object state) 24: { 25: throw new NotImplementedException(); 26: } 27:  28: protected override IAsyncResult OnBeginResolve(ResolveCriteria resolveCriteria, AsyncCallback callback, object state) 29: { 30: throw new NotImplementedException(); 31: } 32:  33: protected override void OnEndFind(IAsyncResult result) 34: { 35: throw new NotImplementedException(); 36: } 37:  38: protected override void OnEndOfflineAnnouncement(IAsyncResult result) 39: { 40: throw new NotImplementedException(); 41: } 42:  43: protected override void OnEndOnlineAnnouncement(IAsyncResult result) 44: { 45: throw new NotImplementedException(); 46: } 47:  48: protected override EndpointDiscoveryMetadata OnEndResolve(IAsyncResult result) 49: { 50: throw new NotImplementedException(); 51: } 52: } 53: } Then let’s implement the online, offline and find methods one by one. WCF discovery service gives us full flexibility to implement the endpoint add, remove and find logic. For the demo purpose we will use an internal dictionary to store the services’ endpoint metadata. In the next post we will see how to serialize and store these information in database. Define a concurrent dictionary inside the service class since our it will be used in the multiple threads scenario. 1: [ServiceBehavior(InstanceContextMode = InstanceContextMode.Single, ConcurrencyMode = ConcurrencyMode.Multiple)] 2: public class ManagedProxyDiscoveryService : DiscoveryProxy 3: { 4: private ConcurrentDictionary<EndpointAddress, EndpointDiscoveryMetadata> _services; 5:  6: public ManagedProxyDiscoveryService() 7: { 8: _services = new ConcurrentDictionary<EndpointAddress, EndpointDiscoveryMetadata>(); 9: } 10: } Then we can simply implement the logic of service online and offline. 1: protected override IAsyncResult OnBeginOnlineAnnouncement(DiscoveryMessageSequence messageSequence, EndpointDiscoveryMetadata endpointDiscoveryMetadata, AsyncCallback callback, object state) 2: { 3: _services.AddOrUpdate(endpointDiscoveryMetadata.Address, endpointDiscoveryMetadata, (key, value) => endpointDiscoveryMetadata); 4: return new OnOnlineAnnouncementAsyncResult(callback, state); 5: } 6:  7: protected override void OnEndOnlineAnnouncement(IAsyncResult result) 8: { 9: OnOnlineAnnouncementAsyncResult.End(result); 10: } 11:  12: protected override IAsyncResult OnBeginOfflineAnnouncement(DiscoveryMessageSequence messageSequence, EndpointDiscoveryMetadata endpointDiscoveryMetadata, AsyncCallback callback, object state) 13: { 14: EndpointDiscoveryMetadata endpoint = null; 15: _services.TryRemove(endpointDiscoveryMetadata.Address, out endpoint); 16: return new OnOfflineAnnouncementAsyncResult(callback, state); 17: } 18:  19: protected override void OnEndOfflineAnnouncement(IAsyncResult result) 20: { 21: OnOfflineAnnouncementAsyncResult.End(result); 22: } Regards the find method, the parameter FindRequestContext.Criteria has a method named IsMatch, which can be use for us to evaluate which service metadata is satisfied with the criteria. So the implementation of find method would be like this. 1: protected override IAsyncResult OnBeginFind(FindRequestContext findRequestContext, AsyncCallback callback, object state) 2: { 3: _services.Where(s => findRequestContext.Criteria.IsMatch(s.Value)) 4: .Select(s => s.Value) 5: .All(meta => 6: { 7: findRequestContext.AddMatchingEndpoint(meta); 8: return true; 9: }); 10: return new OnFindAsyncResult(callback, state); 11: } 12:  13: protected override void OnEndFind(IAsyncResult result) 14: { 15: OnFindAsyncResult.End(result); 16: } As you can see, we checked all endpoints metadata in repository by invoking the IsMatch method. Then add all proper endpoints metadata into the parameter. Finally since all these methods are asynchronized we need some AsyncResult classes as well. Below are the base class and the inherited classes used in previous methods. 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Text; 5: using System.Threading; 6:  7: namespace Phare.Service 8: { 9: abstract internal class AsyncResult : IAsyncResult 10: { 11: AsyncCallback callback; 12: bool completedSynchronously; 13: bool endCalled; 14: Exception exception; 15: bool isCompleted; 16: ManualResetEvent manualResetEvent; 17: object state; 18: object thisLock; 19:  20: protected AsyncResult(AsyncCallback callback, object state) 21: { 22: this.callback = callback; 23: this.state = state; 24: this.thisLock = new object(); 25: } 26:  27: public object AsyncState 28: { 29: get 30: { 31: return state; 32: } 33: } 34:  35: public WaitHandle AsyncWaitHandle 36: { 37: get 38: { 39: if (manualResetEvent != null) 40: { 41: return manualResetEvent; 42: } 43: lock (ThisLock) 44: { 45: if (manualResetEvent == null) 46: { 47: manualResetEvent = new ManualResetEvent(isCompleted); 48: } 49: } 50: return manualResetEvent; 51: } 52: } 53:  54: public bool CompletedSynchronously 55: { 56: get 57: { 58: return completedSynchronously; 59: } 60: } 61:  62: public bool IsCompleted 63: { 64: get 65: { 66: return isCompleted; 67: } 68: } 69:  70: object ThisLock 71: { 72: get 73: { 74: return this.thisLock; 75: } 76: } 77:  78: protected static TAsyncResult End<TAsyncResult>(IAsyncResult result) 79: where TAsyncResult : AsyncResult 80: { 81: if (result == null) 82: { 83: throw new ArgumentNullException("result"); 84: } 85:  86: TAsyncResult asyncResult = result as TAsyncResult; 87:  88: if (asyncResult == null) 89: { 90: throw new ArgumentException("Invalid async result.", "result"); 91: } 92:  93: if (asyncResult.endCalled) 94: { 95: throw new InvalidOperationException("Async object already ended."); 96: } 97:  98: asyncResult.endCalled = true; 99:  100: if (!asyncResult.isCompleted) 101: { 102: asyncResult.AsyncWaitHandle.WaitOne(); 103: } 104:  105: if (asyncResult.manualResetEvent != null) 106: { 107: asyncResult.manualResetEvent.Close(); 108: } 109:  110: if (asyncResult.exception != null) 111: { 112: throw asyncResult.exception; 113: } 114:  115: return asyncResult; 116: } 117:  118: protected void Complete(bool completedSynchronously) 119: { 120: if (isCompleted) 121: { 122: throw new InvalidOperationException("This async result is already completed."); 123: } 124:  125: this.completedSynchronously = completedSynchronously; 126:  127: if (completedSynchronously) 128: { 129: this.isCompleted = true; 130: } 131: else 132: { 133: lock (ThisLock) 134: { 135: this.isCompleted = true; 136: if (this.manualResetEvent != null) 137: { 138: this.manualResetEvent.Set(); 139: } 140: } 141: } 142:  143: if (callback != null) 144: { 145: callback(this); 146: } 147: } 148:  149: protected void Complete(bool completedSynchronously, Exception exception) 150: { 151: this.exception = exception; 152: Complete(completedSynchronously); 153: } 154: } 155: } 1: using System; 2: using System.Collections.Generic; 3: using System.Linq; 4: using System.Text; 5: using System.ServiceModel.Discovery; 6: using Phare.Service; 7:  8: namespace Phare.Service 9: { 10: internal sealed class OnOnlineAnnouncementAsyncResult : AsyncResult 11: { 12: public OnOnlineAnnouncementAsyncResult(AsyncCallback callback, object state) 13: : base(callback, state) 14: { 15: this.Complete(true); 16: } 17:  18: public static void End(IAsyncResult result) 19: { 20: AsyncResult.End<OnOnlineAnnouncementAsyncResult>(result); 21: } 22:  23: } 24:  25: sealed class OnOfflineAnnouncementAsyncResult : AsyncResult 26: { 27: public OnOfflineAnnouncementAsyncResult(AsyncCallback callback, object state) 28: : base(callback, state) 29: { 30: this.Complete(true); 31: } 32:  33: public static void End(IAsyncResult result) 34: { 35: AsyncResult.End<OnOfflineAnnouncementAsyncResult>(result); 36: } 37: } 38:  39: sealed class OnFindAsyncResult : AsyncResult 40: { 41: public OnFindAsyncResult(AsyncCallback callback, object state) 42: : base(callback, state) 43: { 44: this.Complete(true); 45: } 46:  47: public static void End(IAsyncResult result) 48: { 49: AsyncResult.End<OnFindAsyncResult>(result); 50: } 51: } 52:  53: sealed class OnResolveAsyncResult : AsyncResult 54: { 55: EndpointDiscoveryMetadata matchingEndpoint; 56:  57: public OnResolveAsyncResult(EndpointDiscoveryMetadata matchingEndpoint, AsyncCallback callback, object state) 58: : base(callback, state) 59: { 60: this.matchingEndpoint = matchingEndpoint; 61: this.Complete(true); 62: } 63:  64: public static EndpointDiscoveryMetadata End(IAsyncResult result) 65: { 66: OnResolveAsyncResult thisPtr = AsyncResult.End<OnResolveAsyncResult>(result); 67: return thisPtr.matchingEndpoint; 68: } 69: } 70: } Now we have finished the discovery service. The next step is to host it. The discovery service is a standard WCF service. So we can use ServiceHost on a console application, windows service, or in IIS as usual. The following code is how to host the discovery service we had just created in a console application. 1: static void Main(string[] args) 2: { 3: using (var host = new ServiceHost(new ManagedProxyDiscoveryService())) 4: { 5: host.Opened += (sender, e) => 6: { 7: host.Description.Endpoints.All((ep) => 8: { 9: Console.WriteLine(ep.ListenUri); 10: return true; 11: }); 12: }; 13:  14: try 15: { 16: // retrieve the announcement, probe endpoint and binding from configuration 17: var announcementEndpointAddress = new EndpointAddress(ConfigurationManager.AppSettings["announcementEndpointAddress"]); 18: var probeEndpointAddress = new EndpointAddress(ConfigurationManager.AppSettings["probeEndpointAddress"]); 19: var binding = Activator.CreateInstance(Type.GetType(ConfigurationManager.AppSettings["bindingType"], true, true)) as Binding; 20: var announcementEndpoint = new AnnouncementEndpoint(binding, announcementEndpointAddress); 21: var probeEndpoint = new DiscoveryEndpoint(binding, probeEndpointAddress); 22: probeEndpoint.IsSystemEndpoint = false; 23: // append the service endpoint for announcement and probe 24: host.AddServiceEndpoint(announcementEndpoint); 25: host.AddServiceEndpoint(probeEndpoint); 26:  27: host.Open(); 28:  29: Console.WriteLine("Press any key to exit."); 30: Console.ReadKey(); 31: } 32: catch (Exception ex) 33: { 34: Console.WriteLine(ex.ToString()); 35: } 36: } 37:  38: Console.WriteLine("Done."); 39: Console.ReadKey(); 40: } What we need to notice is that, the discovery service needs two endpoints for announcement and probe. In this example I just retrieve them from the configuration file. I also specified the binding of these two endpoints in configuration file as well. 1: <?xml version="1.0"?> 2: <configuration> 3: <startup> 4: <supportedRuntime version="v4.0" sku=".NETFramework,Version=v4.0"/> 5: </startup> 6: <appSettings> 7: <add key="announcementEndpointAddress" value="net.tcp://localhost:10010/announcement"/> 8: <add key="probeEndpointAddress" value="net.tcp://localhost:10011/probe"/> 9: <add key="bindingType" value="System.ServiceModel.NetTcpBinding, System.ServiceModel, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089"/> 10: </appSettings> 11: </configuration> And this is the console screen when I ran my discovery service. As you can see there are two endpoints listening for announcement message and probe message.   Discoverable Service and Client Next, let’s create a WCF service that is discoverable, which means it can be found by the discovery service. To do so, we need to let the service send the online announcement message to the discovery service, as well as offline message before it shutdown. Just create a simple service which can make the incoming string to upper. The service contract and implementation would be like this. 1: [ServiceContract] 2: public interface IStringService 3: { 4: [OperationContract] 5: string ToUpper(string content); 6: } 1: public class StringService : IStringService 2: { 3: public string ToUpper(string content) 4: { 5: return content.ToUpper(); 6: } 7: } Then host this service in the console application. In order to make the discovery service easy to be tested the service address will be changed each time it’s started. 1: static void Main(string[] args) 2: { 3: var baseAddress = new Uri(string.Format("net.tcp://localhost:11001/stringservice/{0}/", Guid.NewGuid().ToString())); 4:  5: using (var host = new ServiceHost(typeof(StringService), baseAddress)) 6: { 7: host.Opened += (sender, e) => 8: { 9: Console.WriteLine("Service opened at {0}", host.Description.Endpoints.First().ListenUri); 10: }; 11:  12: host.AddServiceEndpoint(typeof(IStringService), new NetTcpBinding(), string.Empty); 13:  14: host.Open(); 15:  16: Console.WriteLine("Press any key to exit."); 17: Console.ReadKey(); 18: } 19: } Currently this service is NOT discoverable. We need to add a special service behavior so that it could send the online and offline message to the discovery service announcement endpoint when the host is opened and closed. WCF 4.0 introduced a service behavior named ServiceDiscoveryBehavior. When we specified the announcement endpoint address and appended it to the service behaviors this service will be discoverable. 1: var announcementAddress = new EndpointAddress(ConfigurationManager.AppSettings["announcementEndpointAddress"]); 2: var announcementBinding = Activator.CreateInstance(Type.GetType(ConfigurationManager.AppSettings["bindingType"], true, true)) as Binding; 3: var announcementEndpoint = new AnnouncementEndpoint(announcementBinding, announcementAddress); 4: var discoveryBehavior = new ServiceDiscoveryBehavior(); 5: discoveryBehavior.AnnouncementEndpoints.Add(announcementEndpoint); 6: host.Description.Behaviors.Add(discoveryBehavior); The ServiceDiscoveryBehavior utilizes the service extension and channel dispatcher to implement the online and offline announcement logic. In short, it injected the channel open and close procedure and send the online and offline message to the announcement endpoint.   On client side, when we have the discovery service, a client can invoke a service without knowing its endpoint. WCF discovery assembly provides a class named DiscoveryClient, which can be used to find the proper service endpoint by passing the criteria. In the code below I initialized the DiscoveryClient, specified the discovery service probe endpoint address. Then I created the find criteria by specifying the service contract I wanted to use and invoke the Find method. This will send the probe message to the discovery service and it will find the endpoints back to me. The discovery service will return all endpoints that matches the find criteria, which means in the result of the find method there might be more than one endpoints. In this example I just returned the first matched one back. In the next post I will show how to extend our discovery service to make it work like a service load balancer. 1: static EndpointAddress FindServiceEndpoint() 2: { 3: var probeEndpointAddress = new EndpointAddress(ConfigurationManager.AppSettings["probeEndpointAddress"]); 4: var probeBinding = Activator.CreateInstance(Type.GetType(ConfigurationManager.AppSettings["bindingType"], true, true)) as Binding; 5: var discoveryEndpoint = new DiscoveryEndpoint(probeBinding, probeEndpointAddress); 6:  7: EndpointAddress address = null; 8: FindResponse result = null; 9: using (var discoveryClient = new DiscoveryClient(discoveryEndpoint)) 10: { 11: result = discoveryClient.Find(new FindCriteria(typeof(IStringService))); 12: } 13:  14: if (result != null && result.Endpoints.Any()) 15: { 16: var endpointMetadata = result.Endpoints.First(); 17: address = endpointMetadata.Address; 18: } 19: return address; 20: } Once we probed the discovery service we will receive the endpoint. So in the client code we can created the channel factory from the endpoint and binding, and invoke to the service. When creating the client side channel factory we need to make sure that the client side binding should be the same as the service side. WCF discovery service can be used to find the endpoint for a service contract, but the binding is NOT included. This is because the binding was not in the WS-Discovery specification. In the next post I will demonstrate how to add the binding information into the discovery service. At that moment the client don’t need to create the binding by itself. Instead it will use the binding received from the discovery service. 1: static void Main(string[] args) 2: { 3: Console.WriteLine("Say something..."); 4: var content = Console.ReadLine(); 5: while (!string.IsNullOrWhiteSpace(content)) 6: { 7: Console.WriteLine("Finding the service endpoint..."); 8: var address = FindServiceEndpoint(); 9: if (address == null) 10: { 11: Console.WriteLine("There is no endpoint matches the criteria."); 12: } 13: else 14: { 15: Console.WriteLine("Found the endpoint {0}", address.Uri); 16:  17: var factory = new ChannelFactory<IStringService>(new NetTcpBinding(), address); 18: factory.Opened += (sender, e) => 19: { 20: Console.WriteLine("Connecting to {0}.", factory.Endpoint.ListenUri); 21: }; 22: var proxy = factory.CreateChannel(); 23: using (proxy as IDisposable) 24: { 25: Console.WriteLine("ToUpper: {0} => {1}", content, proxy.ToUpper(content)); 26: } 27: } 28:  29: Console.WriteLine("Say something..."); 30: content = Console.ReadLine(); 31: } 32: } Similarly, the discovery service probe endpoint and binding were defined in the configuration file. 1: <?xml version="1.0"?> 2: <configuration> 3: <startup> 4: <supportedRuntime version="v4.0" sku=".NETFramework,Version=v4.0"/> 5: </startup> 6: <appSettings> 7: <add key="announcementEndpointAddress" value="net.tcp://localhost:10010/announcement"/> 8: <add key="probeEndpointAddress" value="net.tcp://localhost:10011/probe"/> 9: <add key="bindingType" value="System.ServiceModel.NetTcpBinding, System.ServiceModel, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089"/> 10: </appSettings> 11: </configuration> OK, now let’s have a test. Firstly start the discovery service, and then start our discoverable service. When it started it will announced to the discovery service and registered its endpoint into the repository, which is the local dictionary. And then start the client and type something. As you can see the client asked the discovery service for the endpoint and then establish the connection to the discoverable service. And more interesting, do NOT close the client console but terminate the discoverable service but press the enter key. This will make the service send the offline message to the discovery service. Then start the discoverable service again. Since we made it use a different address each time it started, currently it should be hosted on another address. If we enter something in the client we could see that it asked the discovery service and retrieve the new endpoint, and connect the the service.   Summary In this post I discussed the benefit of using the discovery service and the procedures of service announcement and probe. I also demonstrated how to leverage the WCF Discovery feature in WCF 4.0 to build a simple managed discovery service. For test purpose, in this example I used the in memory dictionary as the discovery endpoint metadata repository. And when finding I also just return the first matched endpoint back. I also hard coded the bindings between the discoverable service and the client. In next post I will show you how to solve the problem mentioned above, as well as some additional feature for production usage. You can download the code here.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Node.js Adventure - When Node Flying in Wind

    - by Shaun
    In the first post of this series I mentioned some popular modules in the community, such as underscore, async, etc.. I also listed a module named “Wind (zh-CN)”, which is created by one of my friend, Jeff Zhao (zh-CN). Now I would like to use a separated post to introduce this module since I feel it brings a new async programming style in not only Node.js but JavaScript world. If you know or heard about the new feature in C# 5.0 called “async and await”, or you learnt F#, you will find the “Wind” brings the similar async programming experience in JavaScript. By using “Wind”, we can write async code that looks like the sync code. The callbacks, async stats and exceptions will be handled by “Wind” automatically and transparently.   What’s the Problem: Dense “Callback” Phobia Let’s firstly back to my second post in this series. As I mentioned in that post, when we wanted to read some records from SQL Server we need to open the database connection, and then execute the query. In Node.js all IO operation are designed as async callback pattern which means when the operation was done, it will invoke a function which was taken from the last parameter. For example the database connection opening code would be like this. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: } 8: }); And then if we need to query the database the code would be like this. It nested in the previous function. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: conn.queryRaw(command, function(error, results) { 8: if(error) { 9: // failed to execute this command 10: } 11: else { 12: // records retrieved successfully 13: } 14: }; 15: } 16: }); Assuming if we need to copy some data from this database to another then we need to open another connection and execute the command within the function under the query function. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: conn.queryRaw(command, function(error, results) { 8: if(error) { 9: // failed to execute this command 10: } 11: else { 12: // records retrieved successfully 13: target.open(targetConnectionString, function(error, t_conn) { 14: if(error) { 15: // connect failed 16: } 17: else { 18: t_conn.queryRaw(copy_command, function(error, results) { 19: if(error) { 20: // copy failed 21: } 22: else { 23: // and then, what do you want to do now... 24: } 25: }; 26: } 27: }; 28: } 29: }; 30: } 31: }); This is just an example. In the real project the logic would be more complicated. This means our application might be messed up and the business process will be fragged by many callback functions. I would like call this “Dense Callback Phobia”. This might be a challenge how to make code straightforward and easy to read, something like below. 1: try 2: { 3: // open source connection 4: var s_conn = sqlConnect(s_connectionString); 5: // retrieve data 6: var results = sqlExecuteCommand(s_conn, s_command); 7: 8: // open target connection 9: var t_conn = sqlConnect(t_connectionString); 10: // prepare the copy command 11: var t_command = getCopyCommand(results); 12: // execute the copy command 13: sqlExecuteCommand(s_conn, t_command); 14: } 15: catch (ex) 16: { 17: // error handling 18: }   What’s the Problem: Sync-styled Async Programming Similar as the previous problem, the callback-styled async programming model makes the upcoming operation as a part of the current operation, and mixed with the error handling code. So it’s very hard to understand what on earth this code will do. And since Node.js utilizes non-blocking IO mode, we cannot invoke those operations one by one, as they will be executed concurrently. For example, in this post when I tried to copy the records from Windows Azure SQL Database (a.k.a. WASD) to Windows Azure Table Storage, if I just insert the data into table storage one by one and then print the “Finished” message, I will see the message shown before the data had been copied. This is because all operations were executed at the same time. In order to make the copy operation and print operation executed synchronously I introduced a module named “async” and the code was changed as below. 1: async.forEach(results.rows, 2: function (row, callback) { 3: var resource = { 4: "PartitionKey": row[1], 5: "RowKey": row[0], 6: "Value": row[2] 7: }; 8: client.insertEntity(tableName, resource, function (error) { 9: if (error) { 10: callback(error); 11: } 12: else { 13: console.log("entity inserted."); 14: callback(null); 15: } 16: }); 17: }, 18: function (error) { 19: if (error) { 20: error["target"] = "insertEntity"; 21: res.send(500, error); 22: } 23: else { 24: console.log("all done."); 25: res.send(200, "Done!"); 26: } 27: }); It ensured that the “Finished” message will be printed when all table entities had been inserted. But it cannot promise that the records will be inserted in sequence. It might be another challenge to make the code looks like in sync-style? 1: try 2: { 3: forEach(row in rows) { 4: var entity = { /* ... */ }; 5: tableClient.insert(tableName, entity); 6: } 7:  8: console.log("Finished"); 9: } 10: catch (ex) { 11: console.log(ex); 12: }   How “Wind” Helps “Wind” is a JavaScript library which provides the control flow with plain JavaScript for asynchronous programming (and more) without additional pre-compiling steps. It’s available in NPM so that we can install it through “npm install wind”. Now let’s create a very simple Node.js application as the example. This application will take some website URLs from the command arguments and tried to retrieve the body length and print them in console. Then at the end print “Finish”. I’m going to use “request” module to make the HTTP call simple so I also need to install by the command “npm install request”. The code would be like this. 1: var request = require("request"); 2:  3: // get the urls from arguments, the first two arguments are `node.exe` and `fetch.js` 4: var args = process.argv.splice(2); 5:  6: // main function 7: var main = function() { 8: for(var i = 0; i < args.length; i++) { 9: // get the url 10: var url = args[i]; 11: // send the http request and try to get the response and body 12: request(url, function(error, response, body) { 13: if(!error && response.statusCode == 200) { 14: // log the url and the body length 15: console.log( 16: "%s: %d.", 17: response.request.uri.href, 18: body.length); 19: } 20: else { 21: // log error 22: console.log(error); 23: } 24: }); 25: } 26: 27: // finished 28: console.log("Finished"); 29: }; 30:  31: // execute the main function 32: main(); Let’s execute this application. (I made them in multi-lines for better reading.) 1: node fetch.js 2: "http://www.igt.com/us-en.aspx" 3: "http://www.igt.com/us-en/games.aspx" 4: "http://www.igt.com/us-en/cabinets.aspx" 5: "http://www.igt.com/us-en/systems.aspx" 6: "http://www.igt.com/us-en/interactive.aspx" 7: "http://www.igt.com/us-en/social-gaming.aspx" 8: "http://www.igt.com/support.aspx" Below is the output. As you can see the finish message was printed at the beginning, and the pages’ length retrieved in a different order than we specified. This is because in this code the request command, console logging command are executed asynchronously and concurrently. Now let’s introduce “Wind” to make them executed in order, which means it will request the websites one by one, and print the message at the end.   First of all we need to import the “Wind” package and make sure the there’s only one global variant named “Wind”, and ensure it’s “Wind” instead of “wind”. 1: var Wind = require("wind");   Next, we need to tell “Wind” which code will be executed asynchronously so that “Wind” can control the execution process. In this case the “request” operation executed asynchronously so we will create a “Task” by using a build-in helps function in “Wind” named Wind.Async.Task.create. 1: var requestBodyLengthAsync = function(url) { 2: return Wind.Async.Task.create(function(t) { 3: request(url, function(error, response, body) { 4: if(error || response.statusCode != 200) { 5: t.complete("failure", error); 6: } 7: else { 8: var data = 9: { 10: uri: response.request.uri.href, 11: length: body.length 12: }; 13: t.complete("success", data); 14: } 15: }); 16: }); 17: }; The code above created a “Task” from the original request calling code. In “Wind” a “Task” means an operation will be finished in some time in the future. A “Task” can be started by invoke its start() method, but no one knows when it actually will be finished. The Wind.Async.Task.create helped us to create a task. The only parameter is a function where we can put the actual operation in, and then notify the task object it’s finished successfully or failed by using the complete() method. In the code above I invoked the request method. If it retrieved the response successfully I set the status of this task as “success” with the URL and body length. If it failed I set this task as “failure” and pass the error out.   Next, we will change the main() function. In “Wind” if we want a function can be controlled by Wind we need to mark it as “async”. This should be done by using the code below. 1: var main = eval(Wind.compile("async", function() { 2: })); When the application is running, Wind will detect “eval(Wind.compile(“async”, function” and generate an anonymous code from the body of this original function. Then the application will run the anonymous code instead of the original one. In our example the main function will be like this. 1: var main = eval(Wind.compile("async", function() { 2: for(var i = 0; i < args.length; i++) { 3: try 4: { 5: var result = $await(requestBodyLengthAsync(args[i])); 6: console.log( 7: "%s: %d.", 8: result.uri, 9: result.length); 10: } 11: catch (ex) { 12: console.log(ex); 13: } 14: } 15: 16: console.log("Finished"); 17: })); As you can see, when I tried to request the URL I use a new command named “$await”. It tells Wind, the operation next to $await will be executed asynchronously, and the main thread should be paused until it finished (or failed). So in this case, my application will be pause when the first response was received, and then print its body length, then try the next one. At the end, print the finish message.   Finally, execute the main function. The full code would be like this. 1: var request = require("request"); 2: var Wind = require("wind"); 3:  4: var args = process.argv.splice(2); 5:  6: var requestBodyLengthAsync = function(url) { 7: return Wind.Async.Task.create(function(t) { 8: request(url, function(error, response, body) { 9: if(error || response.statusCode != 200) { 10: t.complete("failure", error); 11: } 12: else { 13: var data = 14: { 15: uri: response.request.uri.href, 16: length: body.length 17: }; 18: t.complete("success", data); 19: } 20: }); 21: }); 22: }; 23:  24: var main = eval(Wind.compile("async", function() { 25: for(var i = 0; i < args.length; i++) { 26: try 27: { 28: var result = $await(requestBodyLengthAsync(args[i])); 29: console.log( 30: "%s: %d.", 31: result.uri, 32: result.length); 33: } 34: catch (ex) { 35: console.log(ex); 36: } 37: } 38: 39: console.log("Finished"); 40: })); 41:  42: main().start();   Run our new application. At the beginning we will see the compiled and generated code by Wind. Then we can see the pages were requested one by one, and at the end the finish message was printed. Below is the code Wind generated for us. As you can see the original code, the output code were shown. 1: // Original: 2: function () { 3: for(var i = 0; i < args.length; i++) { 4: try 5: { 6: var result = $await(requestBodyLengthAsync(args[i])); 7: console.log( 8: "%s: %d.", 9: result.uri, 10: result.length); 11: } 12: catch (ex) { 13: console.log(ex); 14: } 15: } 16: 17: console.log("Finished"); 18: } 19:  20: // Compiled: 21: /* async << function () { */ (function () { 22: var _builder_$0 = Wind.builders["async"]; 23: return _builder_$0.Start(this, 24: _builder_$0.Combine( 25: _builder_$0.Delay(function () { 26: /* var i = 0; */ var i = 0; 27: /* for ( */ return _builder_$0.For(function () { 28: /* ; i < args.length */ return i < args.length; 29: }, function () { 30: /* ; i ++) { */ i ++; 31: }, 32: /* try { */ _builder_$0.Try( 33: _builder_$0.Delay(function () { 34: /* var result = $await(requestBodyLengthAsync(args[i])); */ return _builder_$0.Bind(requestBodyLengthAsync(args[i]), function (result) { 35: /* console.log("%s: %d.", result.uri, result.length); */ console.log("%s: %d.", result.uri, result.length); 36: return _builder_$0.Normal(); 37: }); 38: }), 39: /* } catch (ex) { */ function (ex) { 40: /* console.log(ex); */ console.log(ex); 41: return _builder_$0.Normal(); 42: /* } */ }, 43: null 44: ) 45: /* } */ ); 46: }), 47: _builder_$0.Delay(function () { 48: /* console.log("Finished"); */ console.log("Finished"); 49: return _builder_$0.Normal(); 50: }) 51: ) 52: ); 53: /* } */ })   How Wind Works Someone may raise a big concern when you find I utilized “eval” in my code. Someone may assume that Wind utilizes “eval” to execute some code dynamically while “eval” is very low performance. But I would say, Wind does NOT use “eval” to run the code. It only use “eval” as a flag to know which code should be compiled at runtime. When the code was firstly been executed, Wind will check and find “eval(Wind.compile(“async”, function”. So that it knows this function should be compiled. Then it utilized parse-js to analyze the inner JavaScript and generated the anonymous code in memory. Then it rewrite the original code so that when the application was running it will use the anonymous one instead of the original one. Since the code generation was done at the beginning of the application was started, in the future no matter how long our application runs and how many times the async function was invoked, it will use the generated code, no need to generate again. So there’s no significant performance hurt when using Wind.   Wind in My Previous Demo Let’s adopt Wind into one of my previous demonstration and to see how it helps us to make our code simple, straightforward and easy to read and understand. In this post when I implemented the functionality that copied the records from my WASD to table storage, the logic would be like this. 1, Open database connection. 2, Execute a query to select all records from the table. 3, Recreate the table in Windows Azure table storage. 4, Create entities from each of the records retrieved previously, and then insert them into table storage. 5, Finally, show message as the HTTP response. But as the image below, since there are so many callbacks and async operations, it’s very hard to understand my logic from the code. Now let’s use Wind to rewrite our code. First of all, of course, we need the Wind package. Then we need to include the package files into project and mark them as “Copy always”. Add the Wind package into the source code. Pay attention to the variant name, you must use “Wind” instead of “wind”. 1: var express = require("express"); 2: var async = require("async"); 3: var sql = require("node-sqlserver"); 4: var azure = require("azure"); 5: var Wind = require("wind"); Now we need to create some async functions by using Wind. All async functions should be wrapped so that it can be controlled by Wind which are open database, retrieve records, recreate table (delete and create) and insert entity in table. Below are these new functions. All of them are created by using Wind.Async.Task.create. 1: sql.openAsync = function (connectionString) { 2: return Wind.Async.Task.create(function (t) { 3: sql.open(connectionString, function (error, conn) { 4: if (error) { 5: t.complete("failure", error); 6: } 7: else { 8: t.complete("success", conn); 9: } 10: }); 11: }); 12: }; 13:  14: sql.queryAsync = function (conn, query) { 15: return Wind.Async.Task.create(function (t) { 16: conn.queryRaw(query, function (error, results) { 17: if (error) { 18: t.complete("failure", error); 19: } 20: else { 21: t.complete("success", results); 22: } 23: }); 24: }); 25: }; 26:  27: azure.recreateTableAsync = function (tableName) { 28: return Wind.Async.Task.create(function (t) { 29: client.deleteTable(tableName, function (error, successful, response) { 30: console.log("delete table finished"); 31: client.createTableIfNotExists(tableName, function (error, successful, response) { 32: console.log("create table finished"); 33: if (error) { 34: t.complete("failure", error); 35: } 36: else { 37: t.complete("success", null); 38: } 39: }); 40: }); 41: }); 42: }; 43:  44: azure.insertEntityAsync = function (tableName, entity) { 45: return Wind.Async.Task.create(function (t) { 46: client.insertEntity(tableName, entity, function (error, entity, response) { 47: if (error) { 48: t.complete("failure", error); 49: } 50: else { 51: t.complete("success", null); 52: } 53: }); 54: }); 55: }; Then in order to use these functions we will create a new function which contains all steps for data copying. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: } 4: catch (ex) { 5: console.log(ex); 6: res.send(500, "Internal error."); 7: } 8: })); Let’s execute steps one by one with the “$await” keyword introduced by Wind so that it will be invoked in sequence. First is to open the database connection. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: } 7: catch (ex) { 8: console.log(ex); 9: res.send(500, "Internal error."); 10: } 11: })); Then retrieve all records from the database connection. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: } 10: catch (ex) { 11: console.log(ex); 12: res.send(500, "Internal error."); 13: } 14: })); After recreated the table, we need to create the entities and insert them into table storage. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage one by one 14: for (var i = 0; i < results.rows.length; i++) { 15: var entity = { 16: "PartitionKey": results.rows[i][1], 17: "RowKey": results.rows[i][0], 18: "Value": results.rows[i][2] 19: }; 20: $await(azure.insertEntityAsync(tableName, entity)); 21: console.log("entity inserted"); 22: } 23: } 24: } 25: catch (ex) { 26: console.log(ex); 27: res.send(500, "Internal error."); 28: } 29: })); Finally, send response back to the browser. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage one by one 14: for (var i = 0; i < results.rows.length; i++) { 15: var entity = { 16: "PartitionKey": results.rows[i][1], 17: "RowKey": results.rows[i][0], 18: "Value": results.rows[i][2] 19: }; 20: $await(azure.insertEntityAsync(tableName, entity)); 21: console.log("entity inserted"); 22: } 23: // send response 24: console.log("all done"); 25: res.send(200, "All done!"); 26: } 27: } 28: catch (ex) { 29: console.log(ex); 30: res.send(500, "Internal error."); 31: } 32: })); If we compared with the previous code we will find now it became more readable and much easy to understand. It’s very easy to know what this function does even though without any comments. When user go to URL “/was/copyRecords” we will execute the function above. The code would be like this. 1: app.get("/was/copyRecords", function (req, res) { 2: copyRecords(req, res).start(); 3: }); And below is the logs printed in local compute emulator console. As we can see the functions executed one by one and then finally the response back to me browser.   Scaffold Functions in Wind Wind provides not only the async flow control and compile functions, but many scaffold methods as well. We can build our async code more easily by using them. I’m going to introduce some basic scaffold functions here. In the code above I created some functions which wrapped from the original async function such as open database, create table, etc.. All of them are very similar, created a task by using Wind.Async.Task.create, return error or result object through Task.complete function. In fact, Wind provides some functions for us to create task object from the original async functions. If the original async function only has a callback parameter, we can use Wind.Async.Binding.fromCallback method to get the task object directly. For example the code below returned the task object which wrapped the file exist check function. 1: var Wind = require("wind"); 2: var fs = require("fs"); 3:  4: fs.existsAsync = Wind.Async.Binding.fromCallback(fs.exists); In Node.js a very popular async function pattern is that, the first parameter in the callback function represent the error object, and the other parameters is the return values. In this case we can use another build-in function in Wind named Wind.Async.Binding.fromStandard. For example, the open database function can be created from the code below. 1: sql.openAsync = Wind.Async.Binding.fromStandard(sql.open); 2:  3: /* 4: sql.openAsync = function (connectionString) { 5: return Wind.Async.Task.create(function (t) { 6: sql.open(connectionString, function (error, conn) { 7: if (error) { 8: t.complete("failure", error); 9: } 10: else { 11: t.complete("success", conn); 12: } 13: }); 14: }); 15: }; 16: */ When I was testing the scaffold functions under Wind.Async.Binding I found for some functions, such as the Azure SDK insert entity function, cannot be processed correctly. So I personally suggest writing the wrapped method manually.   Another scaffold method in Wind is the parallel tasks coordination. In this example, the steps of open database, retrieve records and recreated table should be invoked one by one, but it can be executed in parallel when copying data from database to table storage. In Wind there’s a scaffold function named Task.whenAll which can be used here. Task.whenAll accepts a list of tasks and creates a new task. It will be returned only when all tasks had been completed, or any errors occurred. For example in the code below I used the Task.whenAll to make all copy operation executed at the same time. 1: var copyRecordsInParallel = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage in parallal 14: var tasks = new Array(results.rows.length); 15: for (var i = 0; i < results.rows.length; i++) { 16: var entity = { 17: "PartitionKey": results.rows[i][1], 18: "RowKey": results.rows[i][0], 19: "Value": results.rows[i][2] 20: }; 21: tasks[i] = azure.insertEntityAsync(tableName, entity); 22: } 23: $await(Wind.Async.Task.whenAll(tasks)); 24: // send response 25: console.log("all done"); 26: res.send(200, "All done!"); 27: } 28: } 29: catch (ex) { 30: console.log(ex); 31: res.send(500, "Internal error."); 32: } 33: })); 34:  35: app.get("/was/copyRecordsInParallel", function (req, res) { 36: copyRecordsInParallel(req, res).start(); 37: });   Besides the task creation and coordination, Wind supports the cancellation solution so that we can send the cancellation signal to the tasks. It also includes exception solution which means any exceptions will be reported to the caller function.   Summary In this post I introduced a Node.js module named Wind, which created by my friend Jeff Zhao. As you can see, different from other async library and framework, adopted the idea from F# and C#, Wind utilizes runtime code generation technology to make it more easily to write async, callback-based functions in a sync-style way. By using Wind there will be almost no callback, and the code will be very easy to understand. Currently Wind is still under developed and improved. There might be some problems but the author, Jeff, should be very happy and enthusiastic to learn your problems, feedback, suggestion and comments. You can contact Jeff by - Email: [email protected] - Group: https://groups.google.com/d/forum/windjs - GitHub: https://github.com/JeffreyZhao/wind/issues   Source code can be download here.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Node.js Adventure - Storage Services and Service Runtime

    - by Shaun
    When I described on how to host a Node.js application on Windows Azure, one of questions might be raised about how to consume the vary Windows Azure services, such as the storage, service bus, access control, etc.. Interact with windows azure services is available in Node.js through the Windows Azure Node.js SDK, which is a module available in NPM. In this post I would like to describe on how to use Windows Azure Storage (a.k.a. WAS) as well as the service runtime.   Consume Windows Azure Storage Let’s firstly have a look on how to consume WAS through Node.js. As we know in the previous post we can host Node.js application on Windows Azure Web Site (a.k.a. WAWS) as well as Windows Azure Cloud Service (a.k.a. WACS). In theory, WAWS is also built on top of WACS worker roles with some more features. Hence in this post I will only demonstrate for hosting in WACS worker role. The Node.js code can be used when consuming WAS when hosted on WAWS. But since there’s no roles in WAWS, the code for consuming service runtime mentioned in the next section cannot be used for WAWS node application. We can use the solution that I created in my last post. Alternatively we can create a new windows azure project in Visual Studio with a worker role, add the “node.exe” and “index.js” and install “express” and “node-sqlserver” modules, make all files as “Copy always”. In order to use windows azure services we need to have Windows Azure Node.js SDK, as knows as a module named “azure” which can be installed through NPM. Once we downloaded and installed, we need to include them in our worker role project and make them as “Copy always”. You can use my “Copy all always” tool mentioned in my last post to update the currently worker role project file. You can also find the source code of this tool here. The source code of Windows Azure SDK for Node.js can be found in its GitHub page. It contains two parts. One is a CLI tool which provides a cross platform command line package for Mac and Linux to manage WAWS and Windows Azure Virtual Machines (a.k.a. WAVM). The other is a library for managing and consuming vary windows azure services includes tables, blobs, queues, service bus and the service runtime. I will not cover all of them but will only demonstrate on how to use tables and service runtime information in this post. You can find the full document of this SDK here. Back to Visual Studio and open the “index.js”, let’s continue our application from the last post, which was working against Windows Azure SQL Database (a.k.a. WASD). The code should looks like this. 1: var express = require("express"); 2: var sql = require("node-sqlserver"); 3:  4: var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:ac6271ya9e.database.windows.net,1433;Database=synctile;Uid=shaunxu@ac6271ya9e;Pwd={PASSWORD};Encrypt=yes;Connection Timeout=30;"; 5: var port = 80; 6:  7: var app = express(); 8:  9: app.configure(function () { 10: app.use(express.bodyParser()); 11: }); 12:  13: app.get("/", function (req, res) { 14: sql.open(connectionString, function (err, conn) { 15: if (err) { 16: console.log(err); 17: res.send(500, "Cannot open connection."); 18: } 19: else { 20: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 21: if (err) { 22: console.log(err); 23: res.send(500, "Cannot retrieve records."); 24: } 25: else { 26: res.json(results); 27: } 28: }); 29: } 30: }); 31: }); 32:  33: app.get("/text/:key/:culture", function (req, res) { 34: sql.open(connectionString, function (err, conn) { 35: if (err) { 36: console.log(err); 37: res.send(500, "Cannot open connection."); 38: } 39: else { 40: var key = req.params.key; 41: var culture = req.params.culture; 42: var command = "SELECT * FROM [Resource] WHERE [Key] = '" + key + "' AND [Culture] = '" + culture + "'"; 43: conn.queryRaw(command, function (err, results) { 44: if (err) { 45: console.log(err); 46: res.send(500, "Cannot retrieve records."); 47: } 48: else { 49: res.json(results); 50: } 51: }); 52: } 53: }); 54: }); 55:  56: app.get("/sproc/:key/:culture", function (req, res) { 57: sql.open(connectionString, function (err, conn) { 58: if (err) { 59: console.log(err); 60: res.send(500, "Cannot open connection."); 61: } 62: else { 63: var key = req.params.key; 64: var culture = req.params.culture; 65: var command = "EXEC GetItem '" + key + "', '" + culture + "'"; 66: conn.queryRaw(command, function (err, results) { 67: if (err) { 68: console.log(err); 69: res.send(500, "Cannot retrieve records."); 70: } 71: else { 72: res.json(results); 73: } 74: }); 75: } 76: }); 77: }); 78:  79: app.post("/new", function (req, res) { 80: var key = req.body.key; 81: var culture = req.body.culture; 82: var val = req.body.val; 83:  84: sql.open(connectionString, function (err, conn) { 85: if (err) { 86: console.log(err); 87: res.send(500, "Cannot open connection."); 88: } 89: else { 90: var command = "INSERT INTO [Resource] VALUES ('" + key + "', '" + culture + "', N'" + val + "')"; 91: conn.queryRaw(command, function (err, results) { 92: if (err) { 93: console.log(err); 94: res.send(500, "Cannot retrieve records."); 95: } 96: else { 97: res.send(200, "Inserted Successful"); 98: } 99: }); 100: } 101: }); 102: }); 103:  104: app.listen(port); Now let’s create a new function, copy the records from WASD to table service. 1. Delete the table named “resource”. 2. Create a new table named “resource”. These 2 steps ensures that we have an empty table. 3. Load all records from the “resource” table in WASD. 4. For each records loaded from WASD, insert them into the table one by one. 5. Prompt to user when finished. In order to use table service we need the storage account and key, which can be found from the developer portal. Just select the storage account and click the Manage Keys button. Then create two local variants in our Node.js application for the storage account name and key. Since we need to use WAS we need to import the azure module. Also I created another variant stored the table name. In order to work with table service I need to create the storage client for table service. This is very similar as the Windows Azure SDK for .NET. As the code below I created a new variant named “client” and use “createTableService”, specified my storage account name and key. 1: var azure = require("azure"); 2: var storageAccountName = "synctile"; 3: var storageAccountKey = "/cOy9L7xysXOgPYU9FjDvjrRAhaMX/5tnOpcjqloPNDJYucbgTy7MOrAW7CbUg6PjaDdmyl+6pkwUnKETsPVNw=="; 4: var tableName = "resource"; 5: var client = azure.createTableService(storageAccountName, storageAccountKey); Now create a new function for URL “/was/init” so that we can trigger it through browser. Then in this function we will firstly load all records from WASD. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: } 18: } 19: }); 20: } 21: }); 22: }); When we succeed loaded all records we can start to transform them into table service. First I need to recreate the table in table service. This can be done by deleting and creating the table through table client I had just created previously. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: // transform the records 26: } 27: }); 28: }); 29: } 30: } 31: }); 32: } 33: }); 34: }); As you can see, the azure SDK provide its methods in callback pattern. In fact, almost all modules in Node.js use the callback pattern. For example, when I deleted a table I invoked “deleteTable” method, provided the name of the table and a callback function which will be performed when the table had been deleted or failed. Underlying, the azure module will perform the table deletion operation in POSIX async threads pool asynchronously. And once it’s done the callback function will be performed. This is the reason we need to nest the table creation code inside the deletion function. If we perform the table creation code after the deletion code then they will be invoked in parallel. Next, for each records in WASD I created an entity and then insert into the table service. Finally I send the response to the browser. Can you find a bug in the code below? I will describe it later in this post. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: // transform the records 26: for (var i = 0; i < results.rows.length; i++) { 27: var entity = { 28: "PartitionKey": results.rows[i][1], 29: "RowKey": results.rows[i][0], 30: "Value": results.rows[i][2] 31: }; 32: client.insertEntity(tableName, entity, function (error) { 33: if (error) { 34: error["target"] = "insertEntity"; 35: res.send(500, error); 36: } 37: else { 38: console.log("entity inserted"); 39: } 40: }); 41: } 42: // send the 43: console.log("all done"); 44: res.send(200, "All done!"); 45: } 46: }); 47: }); 48: } 49: } 50: }); 51: } 52: }); 53: }); Now we can publish it to the cloud and have a try. But normally we’d better test it at the local emulator first. In Node.js SDK there are three build-in properties which provides the account name, key and host address for local storage emulator. We can use them to initialize our table service client. We also need to change the SQL connection string to let it use my local database. The code will be changed as below. 1: // windows azure sql database 2: //var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:ac6271ya9e.database.windows.net,1433;Database=synctile;Uid=shaunxu@ac6271ya9e;Pwd=eszqu94XZY;Encrypt=yes;Connection Timeout=30;"; 3: // sql server 4: var connectionString = "Driver={SQL Server Native Client 11.0};Server={.};Database={Caspar};Trusted_Connection={Yes};"; 5:  6: var azure = require("azure"); 7: var storageAccountName = "synctile"; 8: var storageAccountKey = "/cOy9L7xysXOgPYU9FjDvjrRAhaMX/5tnOpcjqloPNDJYucbgTy7MOrAW7CbUg6PjaDdmyl+6pkwUnKETsPVNw=="; 9: var tableName = "resource"; 10: // windows azure storage 11: //var client = azure.createTableService(storageAccountName, storageAccountKey); 12: // local storage emulator 13: var client = azure.createTableService(azure.ServiceClient.DEVSTORE_STORAGE_ACCOUNT, azure.ServiceClient.DEVSTORE_STORAGE_ACCESS_KEY, azure.ServiceClient.DEVSTORE_TABLE_HOST); Now let’s run the application and navigate to “localhost:12345/was/init” as I hosted it on port 12345. We can find it transformed the data from my local database to local table service. Everything looks fine. But there is a bug in my code. If we have a look on the Node.js command window we will find that it sent response before all records had been inserted, which is not what I expected. The reason is that, as I mentioned before, Node.js perform all IO operations in non-blocking model. When we inserted the records we executed the table service insert method in parallel, and the operation of sending response was also executed in parallel, even though I wrote it at the end of my logic. The correct logic should be, when all entities had been copied to table service with no error, then I will send response to the browser, otherwise I should send error message to the browser. To do so I need to import another module named “async”, which helps us to coordinate our asynchronous code. Install the module and import it at the beginning of the code. Then we can use its “forEach” method for the asynchronous code of inserting table entities. The first argument of “forEach” is the array that will be performed. The second argument is the operation for each items in the array. And the third argument will be invoked then all items had been performed or any errors occurred. Here we can send our response to browser. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: async.forEach(results.rows, 26: // transform the records 27: function (row, callback) { 28: var entity = { 29: "PartitionKey": row[1], 30: "RowKey": row[0], 31: "Value": row[2] 32: }; 33: client.insertEntity(tableName, entity, function (error) { 34: if (error) { 35: callback(error); 36: } 37: else { 38: console.log("entity inserted."); 39: callback(null); 40: } 41: }); 42: }, 43: // send reponse 44: function (error) { 45: if (error) { 46: error["target"] = "insertEntity"; 47: res.send(500, error); 48: } 49: else { 50: console.log("all done"); 51: res.send(200, "All done!"); 52: } 53: } 54: ); 55: } 56: }); 57: }); 58: } 59: } 60: }); 61: } 62: }); 63: }); Run it locally and now we can find the response was sent after all entities had been inserted. Query entities against table service is simple as well. Just use the “queryEntity” method from the table service client and providing the partition key and row key. We can also provide a complex query criteria as well, for example the code here. In the code below I queried an entity by the partition key and row key, and return the proper localization value in response. 1: app.get("/was/:key/:culture", function (req, res) { 2: var key = req.params.key; 3: var culture = req.params.culture; 4: client.queryEntity(tableName, culture, key, function (error, entity) { 5: if (error) { 6: res.send(500, error); 7: } 8: else { 9: res.json(entity); 10: } 11: }); 12: }); And then tested it on local emulator. Finally if we want to publish this application to the cloud we should change the database connection string and storage account. For more information about how to consume blob and queue service, as well as the service bus please refer to the MSDN page.   Consume Service Runtime As I mentioned above, before we published our application to the cloud we need to change the connection string and account information in our code. But if you had played with WACS you should have known that the service runtime provides the ability to retrieve configuration settings, endpoints and local resource information at runtime. Which means we can have these values defined in CSCFG and CSDEF files and then the runtime should be able to retrieve the proper values. For example we can add some role settings though the property window of the role, specify the connection string and storage account for cloud and local. And the can also use the endpoint which defined in role environment to our Node.js application. In Node.js SDK we can get an object from “azure.RoleEnvironment”, which provides the functionalities to retrieve the configuration settings and endpoints, etc.. In the code below I defined the connection string variants and then use the SDK to retrieve and initialize the table client. 1: var connectionString = ""; 2: var storageAccountName = ""; 3: var storageAccountKey = ""; 4: var tableName = ""; 5: var client; 6:  7: azure.RoleEnvironment.getConfigurationSettings(function (error, settings) { 8: if (error) { 9: console.log("ERROR: getConfigurationSettings"); 10: console.log(JSON.stringify(error)); 11: } 12: else { 13: console.log(JSON.stringify(settings)); 14: connectionString = settings["SqlConnectionString"]; 15: storageAccountName = settings["StorageAccountName"]; 16: storageAccountKey = settings["StorageAccountKey"]; 17: tableName = settings["TableName"]; 18:  19: console.log("connectionString = %s", connectionString); 20: console.log("storageAccountName = %s", storageAccountName); 21: console.log("storageAccountKey = %s", storageAccountKey); 22: console.log("tableName = %s", tableName); 23:  24: client = azure.createTableService(storageAccountName, storageAccountKey); 25: } 26: }); In this way we don’t need to amend the code for the configurations between local and cloud environment since the service runtime will take care of it. At the end of the code we will listen the application on the port retrieved from SDK as well. 1: azure.RoleEnvironment.getCurrentRoleInstance(function (error, instance) { 2: if (error) { 3: console.log("ERROR: getCurrentRoleInstance"); 4: console.log(JSON.stringify(error)); 5: } 6: else { 7: console.log(JSON.stringify(instance)); 8: if (instance["endpoints"] && instance["endpoints"]["nodejs"]) { 9: var endpoint = instance["endpoints"]["nodejs"]; 10: app.listen(endpoint["port"]); 11: } 12: else { 13: app.listen(8080); 14: } 15: } 16: }); But if we tested the application right now we will find that it cannot retrieve any values from service runtime. This is because by default, the entry point of this role was defined to the worker role class. In windows azure environment the service runtime will open a named pipeline to the entry point instance, so that it can connect to the runtime and retrieve values. But in this case, since the entry point was worker role and the Node.js was opened inside the role, the named pipeline was established between our worker role class and service runtime, so our Node.js application cannot use it. To fix this problem we need to open the CSDEF file under the azure project, add a new element named Runtime. Then add an element named EntryPoint which specify the Node.js command line. So that the Node.js application will have the connection to service runtime, then it’s able to read the configurations. Start the Node.js at local emulator we can find it retrieved the connections, storage account for local. And if we publish our application to azure then it works with WASD and storage service through the configurations for cloud.   Summary In this post I demonstrated how to use Windows Azure SDK for Node.js to interact with storage service, especially the table service. I also demonstrated on how to use WACS service runtime, how to retrieve the configuration settings and the endpoint information. And in order to make the service runtime available to my Node.js application I need to create an entry point element in CSDEF file and set “node.exe” as the entry point. I used five posts to introduce and demonstrate on how to run a Node.js application on Windows platform, how to use Windows Azure Web Site and Windows Azure Cloud Service worker role to host our Node.js application. I also described how to work with other services provided by Windows Azure platform through Windows Azure SDK for Node.js. Node.js is a very new and young network application platform. But since it’s very simple and easy to learn and deploy, as well as, it utilizes single thread non-blocking IO model, Node.js became more and more popular on web application and web service development especially for those IO sensitive projects. And as Node.js is very good at scaling-out, it’s more useful on cloud computing platform. Use Node.js on Windows platform is new, too. The modules for SQL database and Windows Azure SDK are still under development and enhancement. It doesn’t support SQL parameter in “node-sqlserver”. It does support using storage connection string to create the storage client in “azure”. But Microsoft is working on make them easier to use, working on add more features and functionalities.   PS, you can download the source code here. You can download the source code of my “Copy all always” tool here.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Android Webview : Display numberpad?

    - by Shaun
    Hi all, I implemented a WebView in my android app displaying a web form. One of the fields ask for the user to manually enter his phone number (in case the phone does not allow extracting of phone number). Right now, the qwerty soft keyboard pops up when user selects the field. Is there a way I can have the numberpad display instead? (Remember I'm using HTML and not native controls) Thanks! Shaun

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  • Oracle presentations at the CIPS ICE Conference, November 5 - 7, Edmonton, Alberta, Canada

    - by Darin Pendergraft
    Oracle will be presenting at the CIPS ICE conference the last week of October in Calgary and the first week of November in Edmonton. Here is a list of the presentations for Edmonton: SHAW Conference Centre • Session Title: Identity and Access Management Integrated; Analyzing the Platform vs Point Solution Approach • Speaker: Darin Pendergraft • Monday, November 5th @ 10:45 AM - 12:00 PM • Session Title: Is Your IT Security Strategy Putting Your Institution at Risk? • Speaker: Spiros Angelopoulos • Monday, November 5th @ 1:45 PM - 3:00 PM Three sessions under the TRAIN: Practical Knowledge Track • Monday, November 5th @ 10:45 AM, 1:45 PM, 3:30 PM • Title: What's new in the Java Platform   Presenter: Donald Smith • Title: Java Enterprise Edition 6   Presenter: Shaun Smith • Title: The Road Ahead for Java SE, JavaFX and Java EE    Presenters: Donald Smith and Shaun Smith To learn more about the conference, and to see the other sessions go to the conference website.

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  • How should I deal with persisting an Android WebView if my activity gets destroyed while showing ano

    - by Shaun Crampton
    Hi, I'm building an Android application that's based around an enhanced WebView (based on PhoneGap). I've enhanced the WebView so that from JavaScript running inside you can invoke the native contact picker to choose a phone number (which may be supplied by Facebook for example). The problem I have is that the native contact picker runs in an activity in another process and the Android docs say that while another activity is open my activity may get destroyed due to memory constraints. I haven't actually seen this happen in my application but if it did then I'm guessing my WebView's state would be destroyed and the code that was waiting for the picked contact would be terminated. It seems a bit crazy that the activity requesting a contact could be destroyed while the contact picker is open. Does anyone know if that does indeed happen? Is there a way to persist the state of the WebView if it does? Thanks, -Shaun

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  • homebrew path issue

    - by Shaun Stanislaus
    Master:~ shaunstanislaus$ ruby <(curl -fsSkL raw.github.com/mxcl/homebrew/go) ==> This script will install: /usr/local/bin/brew /usr/local/Library/... /usr/local/share/man/man1/brew.1 Press enter to continue ==> Downloading and Installing Homebrew... remote: Counting objects: 82368, done. remote: Compressing objects: 100% (39323/39323), done. remote: Total 82368 (delta 56782), reused 65301 (delta 42220) Receiving objects: 100% (82368/82368), 11.68 MiB | 1.59 MiB/s, done. Resolving deltas: 100% (56782/56782), done. From https://github.com/mxcl/homebrew * [new branch] master -> origin/master HEAD is now at 2ea1a0e smpeg: depends on gtk ==> Installation successful! You should run `brew doctor' *before* you install anything. Now type: brew help Master:~ shaunstanislaus$ brew doctor -bash: /usr/local/bin/brew: /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/bin/ruby: bad interpreter: No such file or directory Master:~ shaunstanislaus$ echo $PATH /usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin:/opt/X11/bin:/Users/shaunstanislaus/Library/Application Support/GoodSync:/opt/local/bin:/opt/local/sbin:/usr/local/sbin:/Users/shaunstanislaus/.ec2/bin:/Users/shaunstanislaus/.rvm/bin /usr/local/bin/brew: /System/Library/Frameworks/Ruby.framework/Versions/1.8/usr/bin/ruby: bad interpreter: No such file or directory how do i fix this path issue? i can't use brew command and i think i previously symlink to wrong location. please advice, thank you.

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  • Given an instance of a Ruby object, how do I get its metaclass?

    - by Stanislaus Wernstrom
    Normally, I might get the metaclass for a particular instance of a Ruby object with something like this: class C def metaclass class << self; self; end end end # This is this instance's metaclass. C.new.metaclass => #<Class:#<C:0x01234567>> # Successive invocations will have different metaclasses, # since they're different instances. C.new.metaclass => #<Class:#<C:0x01233...>> C.new.metaclass => #<Class:#<C:0x01232...>> C.new.metaclass => #<Class:#<C:0x01231...>> Let's say I just want to know the metaclass of an arbitrary object instance obj of an arbitrary class, and I don't want to define a metaclass (or similar) method on the class of obj. Is there a way to do that?

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  • ASP.NET MVC 2 RTM Available

    - by Shaun
    Shiju Varghese posted an article on his(her) blog and said that the RTM of the ASP.NET MVC 2 had been released and available to download. You can get the installation packeage and the release note here. And based on the release note there’s no breaking changes from RC2 to RTM. Let’s play with the new ASP.NET MVC and look forward the Visual Studio 2010 RTM.

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  • Article Sharing &ndash; Windows Azure Memcached Plugin

    - by Shaun
    I just found that David Aiken, a windows azure developer and evangelist, wrote a cool article about how to use Memcached in Windows Azure through the new feature Azure Plugin. http://www.davidaiken.com/2011/01/11/windows-azure-memcached-plugin/ I think the best solution for distributed cache in Azure would be the Windows Azure AppFabric Caching but since it’s only in CTP and avaiable in the US data center David’s solution would be the best. Only one thing I’m concerning about, is the stability of windows verion Memcached.

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  • Misaligned Display on Resume

    - by Shaun Killingbeck
    I have an odd issue with my laptop display when resuming from suspend. When I have an additional monitor connected there is no issue. However without an additional monitor connected, after resuming only the left 10% of the laptop screen (just enough to show the Unity Launcher and a bit more) is visibly working, although strangely in a screenshot this same 10% is shown on the right hand side of the screenshot: I ran xrandr --verbose before and after resume, and the only difference (using diff) was: 2c2 < LVDS connected 1366x768+0+0 (0x98) normal (normal left inverted right x axis y axis) 344mm x 194mm --- > LVDS connected 1366x768+1280+0 (0x98) normal (normal left inverted right x axis y axis) 344mm x 194mm This seems to suggest the screen position has been shifted by 1280 horizontally, the width of the second monitor I use. Indeed, running the command xrandr --output LVDS --pos 0x0 does bring the screen back to normal. However, I don't want to have to run this command every time, I'd prefer to cure the source of the problem than just correct the symptoms. Any ideas on how to get Ubuntu to keep the display configuration settings from before suspend when it resumes? or why it changes at all? Heres some technical details that might be pertinent: HP Pavilion DV6 Laptop Ubuntu 13.04 AMD Radeon HD 6400M Series AMD Radeon HD 6520G Using proprietary flgrx-updates driver and amdcccle (Catalyst Control Center) (Unfortunately the open source driver causes my laptop to run even hotter than it already does, otherwise I'd use that) The contents of Xorg.conf: Section "ServerLayout" Identifier "amdcccle Layout" Screen 0 "amdcccle-Screen[0]-0" 0 0 EndSection Section "Module" Load "glx" EndSection Section "Monitor" Identifier "0-LVDS" Option "VendorName" "ATI Proprietary Driver" Option "ModelName" "Generic Autodetecting Monitor" Option "DPMS" "true" Option "PreferredMode" "1280x768" Option "TargetRefresh" "60" Option "Position" "0 0" Option "Rotate" "normal" Option "Disable" "false" EndSection Section "Monitor" Identifier "0-CRT1" Option "VendorName" "ATI Proprietary Driver" Option "ModelName" "Generic Autodetecting Monitor" Option "DPMS" "true" Option "PreferredMode" "1280x768" Option "TargetRefresh" "60" Option "Position" "0 0" Option "Rotate" "normal" Option "Disable" "false" EndSection Section "Monitor" Identifier "1-LVDS" Option "VendorName" "ATI Proprietary Driver" Option "ModelName" "Generic Autodetecting Monitor" Option "DPMS" "true" Option "TargetRefresh" "60" Option "Position" "1280 0" Option "Rotate" "normal" Option "Disable" "false" Option "PreferredMode" "1366x768" EndSection Section "Monitor" Identifier "1-CRT1" Option "VendorName" "ATI Proprietary Driver" Option "ModelName" "Generic Autodetecting Monitor" Option "DPMS" "true" Option "TargetRefresh" "60" Option "Position" "0 0" Option "Rotate" "normal" Option "Disable" "false" Option "PreferredMode" "1280x1024" EndSection Section "Device" Identifier "amdcccle-Device[0]-0" Driver "fglrx" Option "Monitor-LVDS" "1-LVDS" Option "Monitor-CRT1" "1-CRT1" BusID "PCI:0:1:0" EndSection Section "Device" Identifier "amdcccle-Device[0]-1" Driver "fglrx" Option "Monitor-LVDS" "1-LVDS" BusID "PCI:0:1:0" Screen 1 EndSection Section "Screen" Identifier "Default Screen" DefaultDepth 24 EndSection Section "Screen" Identifier "amdcccle-Screen[0]-0" Device "amdcccle-Device[0]-0" DefaultDepth 24 SubSection "Display" Viewport 0 0 Virtual 2646 2646 Depth 24 EndSubSection EndSection Section "Screen" Identifier "amdcccle-Screen[0]-1" Device "amdcccle-Device[0]-1" DefaultDepth 24 SubSection "Display" Viewport 0 0 Depth 24 EndSubSection EndSection

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