steven xu - Page 30 - Developer IT

The case of the phantom ADF developer (and other yarns)

- by Chris Muir

A few years of ADF experience means I see common mistakes made by different developers, some I regularly make myself. This post is designed to assist beginners to Oracle JDeveloper Application Development Framework (ADF) avoid a common ADF pitfall, the case of the phantom ADF developer [add Scooby-Doo music here]. ADF Business Components - triggers, default table values and instead of views. Oracle's JDeveloper tutorials help with the A-B-Cs of ADF development, typically built on the nice 'n safe demo schema provided by with the Oracle database such as the HR demo schema. However it's not too long until ADF beginners, having built up some confidence from learning with the tutorials and vanilla demo schemas, start building ADF Business Components based upon their own existing database schema objects. This is where unexpected problems can sneak in. The crime Developers may encounter a surprising error at runtime when editing a record they just created or updated and committed to the database, based on their own existing tables, namely the error: JBO-25014: Another user has changed the row with primary key oracle.jbo.Key[x] ...where X is the primary key value of the row at hand. In a production environment with multiple users this error may be legit, one of the other users has updated the row since you queried it. Yet in a development environment this error is just plain confusing. If developers are isolated in their own database, creating and editing records they know other users can't possibly be working with, or all the other developers have gone home for the day, how is this error possible? There are no other users? It must be the phantom ADF developer! [insert dramatic music here] The following picture is what you'll see in the Business Component Browser, and you'll receive a similar error message via an ADF Faces page: A false conclusion What can possibly cause this issue if it isn't our phantom ADF developer? Doesn't ADF BC implement record locking, locking database records when the row is modified in the ADF middle-tier by a user? How can our phantom ADF developer even take out a lock if this is the case? Maybe ADF has a bug, maybe ADF isn't implementing record locking at all? Shouldn't we see the error "JBO-26030: Failed to lock the record, another user holds the lock" as we attempt to modify the record, why do we see JBO-25014? : Let's verify that ADF is in fact issuing the correct SQL LOCK-FOR-UPDATE statement to the database. First we need to verify ADF's locking strategy. It is determined by the Application Module's jbo.locking.mode property. The default (as of JDev 11.1.1.4.0 if memory serves me correct) and recommended value is optimistic, and the other valid value is pessimistic. Next we need a mechanism to check that ADF is issuing the LOCK statements to the database. We could ask DBAs to monitor locks with OEM, but optimally we'd rather not involve overworked DBAs in this process, so instead we can use the ADF runtime setting –Djbo.debugoutput=console. At runtime this options turns on instrumentation within the ADF BC layer, which among a lot of extra detail displayed in the log window, will show the actual SQL statement issued to the database, including the LOCK statement we're looking to confirm. Setting our locking mode to pessimistic, opening the Business Components Browser of a JSF page allowing us to edit a record, say the CHARGEABLE field within a BOOKINGS record where BOOKING_NO = 1206, upon editing the record see among others the following log entries: [421] Built select: 'SELECT BOOKING_NO, EVENT_NO, RESOURCE_CODE, CHARGEABLE, MADE_BY, QUANTITY, COST, STATUS, COMMENTS FROM BOOKINGS Bookings'[422] Executing LOCK...SELECT BOOKING_NO, EVENT_NO, RESOURCE_CODE, CHARGEABLE, MADE_BY, QUANTITY, COST, STATUS, COMMENTS FROM BOOKINGS Bookings WHERE BOOKING_NO=:1 FOR UPDATE NOWAIT[423] Where binding param 1: 1206 As can be seen on line 422, in fact a LOCK-FOR-UPDATE is indeed issued to the database. Later when we commit the record we see: [441] OracleSQLBuilder: SAVEPOINT 'BO_SP'[442] OracleSQLBuilder Executing, Lock 1 DML on: BOOKINGS (Update)[443] UPDATE buf Bookings>#u SQLStmtBufLen: 210, actual=62[444] UPDATE BOOKINGS Bookings SET CHARGEABLE=:1 WHERE BOOKING_NO=:2[445] Update binding param 1: N[446] Where binding param 2: 1206[447] BookingsView1 notify COMMIT ... [448] _LOCAL_VIEW_USAGE_model_Bookings_ResourceTypesView1 notify COMMIT ... [449] EntityCache close prepared statement ....and as a result the changes are saved to the database, and the lock is released. Let's see what happens when we use the optimistic locking mode, this time to change the same BOOKINGS record CHARGEABLE column again. As soon as we edit the record we see little activity in the logs, nothing to indicate any SQL statement, let alone a LOCK has been taken out on the row. However when we save our records by issuing a commit, the following is recorded in the logs: [509] OracleSQLBuilder: SAVEPOINT 'BO_SP'[510] OracleSQLBuilder Executing doEntitySelect on: BOOKINGS (true)[511] Built select: 'SELECT BOOKING_NO, EVENT_NO, RESOURCE_CODE, CHARGEABLE, MADE_BY, QUANTITY, COST, STATUS, COMMENTS FROM BOOKINGS Bookings'[512] Executing LOCK...SELECT BOOKING_NO, EVENT_NO, RESOURCE_CODE, CHARGEABLE, MADE_BY, QUANTITY, COST, STATUS, COMMENTS FROM BOOKINGS Bookings WHERE BOOKING_NO=:1 FOR UPDATE NOWAIT[513] Where binding param 1: 1205[514] OracleSQLBuilder Executing, Lock 2 DML on: BOOKINGS (Update)[515] UPDATE buf Bookings>#u SQLStmtBufLen: 210, actual=62[516] UPDATE BOOKINGS Bookings SET CHARGEABLE=:1 WHERE BOOKING_NO=:2[517] Update binding param 1: Y[518] Where binding param 2: 1205[519] BookingsView1 notify COMMIT ... [520] _LOCAL_VIEW_USAGE_model_Bookings_ResourceTypesView1 notify COMMIT ... [521] EntityCache close prepared statement Again even though we're seeing the midtier delay the LOCK statement until commit time, it is in fact occurring on line 412, and released as part of the commit issued on line 419. Therefore with either optimistic or pessimistic locking a lock is indeed issued. Our conclusion at this point must be, unless there's the unlikely cause the LOCK statement is never really hitting the database, or the even less likely cause the database has a bug, then ADF does in fact take out a lock on the record before allowing the current user to update it. So there's no way our phantom ADF developer could even modify the record if he tried without at least someone receiving a lock error. Hmm, we can only conclude the locking mode is a red herring and not the true cause of our problem. Who is the phantom? At this point we'll need to conclude that the error message "JBO-25014: Another user has changed" is somehow legit, even though we don't understand yet what's causing it. This leads onto two further questions, how does ADF know another user has changed the row, and what's been changed anyway? To answer the first question, how does ADF know another user has changed the row, the Fusion Guide's section 4.10.11 How to Protect Against Losing Simultaneous Updated Data , that details the Entity Object Change-Indicator property, gives us the answer: At runtime the framework provides automatic "lost update" detection for entity objects to ensure that a user cannot unknowingly modify data that another user has updated and committed in the meantime. Typically, this check is performed by comparing the original values of each persistent entity attribute against the corresponding current column values in the database at the time the underlying row is locked. Before updating a row, the entity object verifies that the row to be updated is still consistent with the current state of the database. The guide further suggests to make this solution more efficient: You can make the lost update detection more efficient by identifying any attributes of your entity whose values you know will be updated whenever the entity is modified. Typical candidates include a version number column or an updated date column in the row.....To detect whether the row has been modified since the user queried it in the most efficient way, select the Change Indicator option to compare only the change-indicator attribute values. We now know that ADF BC doesn't use the locking mechanism at all to protect the current user against updates, but rather it keeps a copy of the original record fetched, separate to the user changed version of the record, and it compares the original record against the one in the database when the lock is taken out. If values don't match, be it the default compare-all-columns behaviour, or the more efficient Change Indicator mechanism, ADF BC will throw the JBO-25014 error. This leaves one last question. Now we know the mechanism under which ADF identifies a changed row, what we don't know is what's changed and who changed it? The real culprit What's changed? We know the record in the mid-tier has been changed by the user, however ADF doesn't use the changed record in the mid-tier to compare to the database record, but rather a copy of the original record before it was changed. This leaves us to conclude the database record has changed, but how and by who? There are three potential causes: Database triggers The database trigger among other uses, can be configured to fire PLSQL code on a database table insert, update or delete. In particular in an insert or update the trigger can override the value assigned to a particular column. The trigger execution is actioned by the database on behalf of the user initiating the insert or update action. Why this causes the issue specific to our ADF use, is when we insert or update a record in the database via ADF, ADF keeps a copy of the record written to the database. However the cached record is instantly out of date as the database triggers have modified the record that was actually written to the database. Thus when we update the record we just inserted or updated for a second time to the database, ADF compares its original copy of the record to that in the database, and it detects the record has been changed – giving us JBO-25014. This is probably the most common cause of this problem. Default values A second reason this issue can occur is another database feature, default column values. When creating a database table the schema designer can define default values for specific columns. For example a CREATED_BY column could be set to SYSDATE, or a flag column to Y or N. Default values are only used by the database when a user inserts a new record and the specific column is assigned NULL. The database in this case will overwrite the column with the default value. As per the database trigger section, it then becomes apparent why ADF chokes on this feature, though it can only specifically occur in an insert-commit-update-commit scenario, not the update-commit-update-commit scenario. Instead of trigger views I must admit I haven't double checked this scenario but it seems plausible, that of the Oracle database's instead of trigger view (sometimes referred to as instead of views). A view in the database is based on a query, and dependent on the queries complexity, may support insert, update and delete functionality to a limited degree. In order to support fully insertable, updateable and deletable views, Oracle introduced the instead of view, that gives the view designer the ability to not only define the view query, but a set of programmatic PLSQL triggers where the developer can define their own logic for inserts, updates and deletes. While this provides the database programmer a very powerful feature, it can cause issues for our ADF application. On inserting or updating a record in the instead of view, the record and it's data that goes in is not necessarily the data that comes out when ADF compares the records, as the view developer has the option to practically do anything with the incoming data, including throwing it away or pushing it to tables which aren't used by the view underlying query for fetching the data. Readers are at this point reminded that this article is specifically about how the JBO-25014 error occurs in the context of 1 developer on an isolated database. The article is not considering how the error occurs in a production environment where there are multiple users who can cause this error in a legitimate fashion. Assuming none of the above features are the cause of the problem, and optimistic locking is turned on (this error is not possible if pessimistic locking is the default mode *and* none of the previous causes are possible), JBO-25014 is quite feasible in a production ADF application if 2 users modify the same record. At this point under project timelines pressure, the obvious fix for developers is to drop both database triggers and default values from the underlying tables. However we must be careful that these legacy constructs aren't used and assumed to be in place by other legacy systems. Dropping the database triggers or default value that the existing Oracle Forms applications assumes and requires to be in place could cause unexpected behaviour and bugs in the Forms application. Proficient software engineers would recognize such a change may require a partial or full regression test of the existing legacy system, a potentially costly and timely exercise, not ideal. Solving the mystery once and for all Luckily ADF has built in functionality to deal with this issue, though it's not a surprise, as Oracle as the author of ADF also built the database, and are fully aware of the Oracle database's feature set. At the Entity Object attribute level, the Refresh After Insert and Refresh After Update properties. Simply selecting these instructs ADF BC after inserting or updating a record to the database, to expect the database to modify the said attributes, and read a copy of the changed attributes back into its cached mid-tier record. Thus next time the developer modifies the current record, the comparison between the mid-tier record and the database record match, and JBO-25014: Another user has changed" is no longer an issue. [Post edit - as per the comment from Oracle's Steven Davelaar below, as he correctly points out the above solution will not work for instead-of-triggers views as it relies on SQL RETURNING clause which is incompatible with this type of view] Alternatively you can set the Change Indicator on one of the attributes. This will work as long as the relating column for the attribute in the database itself isn't inadvertently updated. In turn you're possibly just masking the issue rather than solving it, because if another developer turns the Change Indicator back on the original issue will return.

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Looking into Enum Support in Entity Framework 5.0 Code First

- by nikolaosk

In this post I will show you with a hands-on demo the enum support that is available in Visual Studio 2012, .Net Framework 4.5 and Entity Framework 5.0. You can have a look at this post to learn about the support of multilple diagrams per model that exists in Entity Framework 5.0. We will demonstrate this with a step by step example. I will use Visual Studio 2012 Ultimate. You can also use Visual Studio 2012 Express Edition. Before I move on to the actual demo I must say that in EF 5.0 an enumeration can have the following types. Byte Int16 Int32 Int64 Sbyte Obviously I cannot go into much detail on what EF is and what it does. I will give again a short introduction.The .Net framework provides support for Object Relational Mapping through EF. So EF is a an ORM tool and it is now the main data access technology that microsoft works on. I use it quite extensively in my projects. Through EF we have many things out of the box provided for us. We have the automatic generation of SQL code.It maps relational data to strongly types objects.All the changes made to the objects in the memory are persisted in a transactional way back to the data store. You can find in this post an example on how to use the Entity Framework to retrieve data from an SQL Server Database using the "Database/Schema First" approach. In this approach we make all the changes at the database level and then we update the model with those changes. In this post you can see an example on how to use the "Model First" approach when working with ASP.Net and the Entity Framework. This model was firstly introduced in EF version 4.0 and we could start with a blank model and then create a database from that model.When we made changes to the model , we could recreate the database from the new model. You can search in my blog, because I have posted many posts regarding ASP.Net and EF. I assume you have a working knowledge of C# and know a few things about EF. The Code First approach is the more code-centric than the other two. Basically we write POCO classes and then we persist to a database using something called DBContext. Code First relies on DbContext. We create 2,3 classes (e.g Person,Product) with properties and then these classes interact with the DbContext class. We can create a new database based upon our POCOS classes and have tables generated from those classes.We do not have an .edmx file in this approach.By using this approach we can write much easier unit tests. DbContext is a new context class and is smaller,lightweight wrapper for the main context class which is ObjectContext (Schema First and Model First). Let's begin building our sample application. 1) Launch Visual Studio. Create an ASP.Net Empty Web application. Choose an appropriate name for your application. 2) Add a web form, default.aspx page to the application. 3) Now we need to make sure the Entity Framework is included in our project. Go to Solution Explorer, right-click on the project name.Then select Manage NuGet Packages...In the Manage NuGet Packages dialog, select the Online tab and choose the EntityFramework package.Finally click Install. Have a look at the picture below 4) Create a new folder. Name it CodeFirst . 5) Add a new item in your application, a class file. Name it Footballer.cs. This is going to be a simple POCO class.Place it in the CodeFirst folder. The code follows public class Footballer { public int FootballerID { get; set; } public string FirstName { get; set; } public string LastName { get; set; } public double Weight { get; set; } public double Height { get; set; } public DateTime JoinedTheClub { get; set; } public int Age { get; set; } public List<Training> Trainings { get; set; } public FootballPositions Positions { get; set; } } Now I am going to define my enum values in the same class file, Footballer.cs public enum FootballPositions { Defender, Midfielder, Striker } 6) Now we need to create the Training class. Add a new class to your application and place it in the CodeFirst folder.The code for the class follows. public class Training { public int TrainingID { get; set; } public int TrainingDuration { get; set; } public string TrainingLocation { get; set; } } 7) Then we need to create a context class that inherits from DbContext.Add a new class to the CodeFirst folder.Name it FootballerDBContext.Now that we have the entity classes created, we must let the model know.I will have to use the DbSet<T> property.The code for this class follows public class FootballerDBContext:DbContext { public DbSet<Footballer> Footballers { get; set; } public DbSet<Training> Trainings { get; set; } } Do not forget to add (using System.Data.Entity;) in the beginning of the class file 8) We must take care of the connection string. It is very easy to create one in the web.config.It does not matter that we do not have a database yet.When we run the DbContext and query against it,it will use a connection string in the web.config and will create the database based on the classes. In my case the connection string inside the web.config, looks like this <connectionStrings> <add name="CodeFirstDBContext" connectionString="server=.\SqlExpress;integrated security=true;" providerName="System.Data.SqlClient"/> </connectionStrings> 9) Now it is time to create Linq to Entities queries to retrieve data from the database . Add a new class to your application in the CodeFirst folder.Name the file DALfootballer.cs We will create a simple public method to retrieve the footballers. The code for the class follows public class DALfootballer { FootballerDBContext ctx = new FootballerDBContext(); public List<Footballer> GetFootballers() { var query = from player in ctx.Footballers where player.FirstName=="Jamie" select player; return query.ToList(); } } 10) Place a GridView control on the Default.aspx page and leave the default name.Add an ObjectDataSource control on the Default.aspx page and leave the default name. Set the DatasourceID property of the GridView control to the ID of the ObjectDataSource control.(DataSourceID="ObjectDataSource1" ). Let's configure the ObjectDataSource control. Click on the smart tag item of the ObjectDataSource control and select Configure Data Source. In the Wizzard that pops up select the DALFootballer class and then in the next step choose the GetFootballers() method.Click Finish to complete the steps of the wizzard. Build your application. 11) Let's create an Insert method in order to insert data into the tables. I will create an Insert() method and for simplicity reasons I will place it in the Default.aspx.cs file. private void Insert() { var footballers = new List<Footballer> { new Footballer { FirstName = "Steven",LastName="Gerrard", Height=1.85, Weight=85,Age=32, JoinedTheClub=DateTime.Parse("12/12/1999"),Positions=FootballPositions.Midfielder, Trainings = new List<Training> { new Training {TrainingDuration = 3, TrainingLocation="MelWood"}, new Training {TrainingDuration = 2, TrainingLocation="Anfield"}, new Training {TrainingDuration = 2, TrainingLocation="MelWood"}, } }, new Footballer { FirstName = "Jamie",LastName="Garragher", Height=1.89, Weight=89,Age=34, JoinedTheClub=DateTime.Parse("12/02/2000"),Positions=FootballPositions.Defender, Trainings = new List<Training> { new Training {TrainingDuration = 3, TrainingLocation="MelWood"}, new Training {TrainingDuration = 5, TrainingLocation="Anfield"}, new Training {TrainingDuration = 6, TrainingLocation="Anfield"}, } } }; footballers.ForEach(foot => ctx.Footballers.Add(foot)); ctx.SaveChanges(); } 12) In the Page_Load() event handling routine I called the Insert() method. protected void Page_Load(object sender, EventArgs e) { Insert(); } 13) Run your application and you will see that the following result,hopefully. You can see clearly that the data is returned along with the enum value. 14) You must have also a look at the database.Launch SSMS and see the database and its objects (data) created from EF Code First.Have a look at the picture below. Hopefully now you have seen the support that exists in EF 5.0 for enums.Hope it helps !!!

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CodePlex Daily Summary for Monday, June 11, 2012

CodePlex Daily Summary for Monday, June 11, 2012Popular ReleasesCasanova Language: Casanova IDE alpha release: This is the first release for the Casanova IDE. It features the major capabilities of the framework: support for rules, scripts, input management, and basic content management. The IDE is still under major development. Planned features include: multiplayer support 3D rendering syntax highlighting basic Intellisense slightly improved syntax for rules and scripts audio in-game menus Also, do not forget to download and install OpenAL: http://connect.creativelabs.com/openal/Download...Liberty: v3.2.1.0 Release 10th June 2012: Change Log -Added -Liberty is now digitally signed! If the certificate on Liberty.exe is missing, invalid, or does not state that it was developed by "Xbox Chaos, Open Source Developer," your copy of Liberty may have been altered in some (possibly malicious) way. -Reach Mass biped max health and shield changer -Fixed -H3/ODST Fixed all of the glitches that users kept reporting (also reverted the changes made in 3.2.0.2) -Reach Made some tag names clearer and more consistent between m...SVNUG.CodePlex: Cloud Development with Windows Azure: This release contains the slides for the Cloud Development with Windows Azure presentation.WCF Data Service (OData) Regression & Load Testing Tool: Latest: This is latest stable releaseSHA-1 Hash Checker: SHA-1 Hash Checker (for Windows): Fixed major bugs. Removed false negatives.AutoUpdaterdotNET: AutoUpdater.NET 1.0: Everything seems perfect if you find any problem you can report to http://www.rbsoft.org/contact.htmlMedia Companion: Media Companion 3.503b: It has been a while, so it's about time we release another build! Major effort has been for fixing trailer downloads, plus a little bit of work for episode guide tag in TV show NFOs.Microsoft SQL Server Product Samples: Database: AdventureWorks Sample Reports 2008 R2: AdventureWorks Sample Reports 2008 R2.zip contains several reports include Sales Reason Comparisons SQL2008R2.rdl which uses Adventure Works DW 2008R2 as a data source reference. For more information, go to Sales Reason Comparisons report.Json.NET: Json.NET 4.5 Release 7: Fix - Fixed Metro build to pass Windows Application Certification Kit on Windows 8 Release Preview Fix - Fixed Metro build error caused by an anonymous type Fix - Fixed ItemConverter not being used when serializing dictionaries Fix - Fixed an incorrect object being passed to the Error event when serializing dictionaries Fix - Fixed decimal properties not being correctly ignored with DefaultValueHandlingLINQ Extensions Library: 1.0.3.0: New to release 1.0.3.0:Combinatronics: Combinations (unique) Combinations (with repetition) Permutations (unique) Permutations (with repetition) Convert jagged arrays to fixed multidimensional arrays Convert fixed multidimensional arrays to jagged arrays ElementAtMax ElementAtMin ElementAtAverage New set of array extension (1.0.2.8):Rotate Flip Resize (maintaing data) Split Fuse Replace Append and Prepend extensions (1.0.2.7) IndexOf extensions (1.0.2.7) Ne...????????API for .Net SDK: SDK for .Net ??? Release 1: 6?11????? ??? - ?Entities???????????EntityBase，???ToString()???????json???，??????4.0???????。2.0?3.5???！ ??? - Request????????AccessToken??????source=appkey?????。????，????????，???????public_timeline?????????。 ?? - ???ClinetLogin??????????RefreshToken???????false???。 ?? - ???RepostTimeline????Statuses???null???。 ?? - Utility?BuildPostData?，?WeiboParameter??value?NULL????????。 ??????? ??? - ??.Net 2.0/3.5/4.0????。??????VS2010??????????。VS2008????????，??????????。 ??? - ??.Net 4.0???SDK...Audio Pitch & Shift: Audio Pitch And Shift 4.5.0: Added Instruments tab for modules Open folder content feature Some bug fixesPython Tools for Visual Studio: 1.5 Beta 1: We’re pleased to announce the release of Python Tools for Visual Studio 1.5 Beta. Python Tools for Visual Studio (PTVS) is an open-source plug-in for Visual Studio which supports programming with the Python language. PTVS supports a broad range of features including: • Supports CPython, IronPython, Jython and PyPy • Python editor with advanced member, signature intellisense and refactoring • Code navigation: “Find all refs”, goto definition, and object browser • Local and remote debugging •...Circuit Diagram: Circuit Diagram 2.0 Beta 1: New in this release: Automatically flip components when placing Delete components using keyboard delete key Resize document Document properties window Print document Recent files list Confirm when exiting with unsaved changes Thumbnail previews in Windows Explorer for CDDX files Show shortcut keys in toolbox Highlight selected item in toolbox Zoom using mouse scroll wheel while holding down ctrl key Plugin support for: Custom export formats Custom import formats Open...Umbraco CMS: Umbraco CMS 5.2 Beta: The future of Umbracov5 represents the future architecture of Umbraco, so please be aware that while it's technically superior to v4 it's not yet on a par feature or performance-wise. What's new? For full details see our http://progress.umbraco.org task tracking page showing all items complete for 5.2. In a nutshellPackage Builder Starter Kits Dynamic Extension Methods Querying / IsHelpers Friendly alt template URLs Localization Various bug fixes / performance enhancements Gett...JayData - The cross-platform HTML5 data-management library for JavaScript: JayData 1.0.5: JayData is a unified data access library for JavaScript developers to query and update data from different sources like WebSQL, IndexedDB, OData, Facebook or YQL. See it in action in this 6 minutes video New features in JayData 1.0.5http://jaydata.org/blog/jaydata-1.0.5-is-here-with-authentication-support-and-more http://jaydata.org/blog/release-notes Sencha Touch 2 module (read-only)This module can be used to bind data retrieved by JayData to Sencha Touch 2 generated user interface. (exam...32feet.NET: 3.5: This version changes the 32feet.NET library (both desktop and NETCF) to use .NET Framework version 3.5. Previously we compiled for .NET v2.0. There are no code changes from our version 3.4. See the 3.4 release for more information. Changes due to compiling for .NET 3.5Applications should be changed to use NET/NETCF v3.5. Removal of class InTheHand.Net.Bluetooth.AsyncCompletedEventArgs, which we provided on NETCF. We now just use the standard .NET System.ComponentModel.AsyncCompletedEvent...Application Architecture Guidelines: Application Architecture Guidelines 3.0.7: 3.0.7Jolt Environment: Jolt v2 Stable: Many new features. Follow development here for more information: http://www.rune-server.org/runescape-development/rs-503-client-server/projects/298763-jolt-environment-v2.html Setup instructions in downloadSharePoint Euro 2012 - UEFA European Football Predictor: havivi.euro2012.wsp (1.5): New fetures:Multilingual Support Max users property in Standings Web Part Games time zone change (UTC +1) bug fix - Version 1.4 locking problem http://euro2012.codeplex.com/discussions/358262 bug fix - Field Title not found (v.1.3) German SP http://euro2012.codeplex.com/discussions/358189#post844228 Bug fix - Access is denied.for users with contribute rights Bug fix - Installing on non-English version of SharePoint Bug fix - Title Rules Installing SharePoint Euro 2012 PredictorSharePoint E...New Projects2D map editor for Game Tool Development class: This project contains a basic 2D map editor, which can read a tileset (or chipset) to create a custom map. The user can then load and save maps previously created (file format .map). ArtifexCore: ArtifexCore - a compilation of unique, original, and revamped RunUO/OrbSA projects.ASP.NET MVC 4 - Sports Store using Visual Studio 2011 Beta: This is a the output of "Sports Store" exercise in Pro ASP.NET MVC 3 Framework by Adam Freeman and Steven Sanderson. Instead of MVC 3 as recommended in the book, I have used MVC 4.clabinet: clabinet is a cloud based file cabinetCopy File Location - Explorer Shortcut: This Explorer Extension adds a shortcut menu to all files and folders to copy the full location to the Clipboard.CSSSEVER: ???????????DoodleLabyrinthLogic: A starter '100 rogues' type logic library for rogue-like buildersEasyFlash Cart Builder: EasyFlash Cart Builder is a tool for linking files together into an EasyFlash cartridge. Generic enumeration: Provides string representation of C# enumerations.Hacker Typer for WP7: This is a hackertyper.net Windows Phone based application HTML Batch Logger: This is a simple Log class that can be used in any .NET C# Console Application. You can use it to log into an HTML file, console window, or database. kinect ????????????: ???、??????????????????????、????????????????。???、??????????????????。?????????、????????????????、??????????????????。laskjdfqewr131231: example omes projectnlite web libraray: Lite Web Framework,????Page，??Ndf???WebApiNMemory - an in-memory relational database for .NET: NMemory is a lightweight in-memory relational database engine that can be hosted by .NET applications. It supports traditional database features like indexes, foreign key relations, transaction handling and isolation.NoManaComponets: A attempt at a reusable library for common tasks in XNA like avatar management, text rendering and shading. Currently abandoned.NP: network client appObject Viewer: A UserControl that can display any object.PowerPoint Graph Creator: The main purpose of this PowerPoint add-in is to help people who sometimes need to draw graphs into the PPT and then for example add some animations or want to load to existing graphs into PPT but don't have a lot of time to re-draw every thing.Project Blue Tigris: This Project aims at enabling users to control and interact with Windows without the need to touch the keyboard or the mouse, through a new user interface using gestures and voice commands. This project will utilize webcam and microphones connected to the computer when installed. This is our vision. It would be great if you join us.QTP FT Uninstaller: KnowledgeInbox QTP/FT Uninstaller is a tool designed for uninstalling HP's QuickTest Professional or Functional Testing products in one click. The tool should only be used in cases where QTP was working fine earlier and after some update or installation it stopped working. The tool scans the system registry for all files associated with QTP and deletes them. Note: Using this uninstaller may impact tools like HP Sprinter, Quality Center. You should re-install those tools also after using t...Radius Client for Microsoft® .NET Micro Framework: Client for Remote Authentication Dial In User Service (RADIUS)Regression Suite: RegressionSuite is a software test suite that incorporates measurement of the startup lag, measurement of accurate execution times, generating execution statistics, customized input distributions, and processable regression specific details as part of the regular unit tests. Essentially, RegressionSuite provides the frame-work around which the individual unit regressors are invoked (and details and statistics collected). Unit regressors are grouped into named regressor sets (or modules), a...Sern: Nothing yet.SharePoint List Number to Text Custom Column: Number to text custom column in SharePoint is a project that is useful in any financial SharePoint implementation to automatically generate the corresponding number representation in textual format, this feature is designed to be easy extended to any language and it’s initially in Arabic and English languages.you can find all related source code in download section SharpDND: A attempt to create a open source DLL for the openSRD. Designed with customization in mind if completed the tools included could build out pathfinder and other RPG rulesets.SmartSense: SmartSense is a wearable holographic gesture and voice controlled intelligent system. Human-computer interaction (HCI) is a heavily researched area in today’s technology driven world. Most people experience HCI using a mouse and keyboard as input devices. We wanted a more natural way to interact with the computer that also allows instant access to information. We are developing a real-time system that is always on and available to collect data at any moment but also is accessible “on-the-fly...Sumzlib: sumzlib is a set of class library that provides useful algorithms in static method. this project is written in vb.netWCF Data Service (OData) Regression & Load Testing Tool: This is a tool that is especially being developed to regress OData Services. Current release only support few test like ($select, Top, etc ), more test will be added over the time. It is a Multithreaded Regression Test Tool that can generate result in Excel format including diagnostic error data and performance data like turnaround time as well. It can be used for bulk testing of several services at the same time It can be quite useful to for those who are developing several service...X.Web.Microdata: This project is intended to represent an mitcrodata entitie in the .NET Framework. (Particularly in ASP.NET) The X.Web.Microdata represent the http://www.data-vocabulary.org/ (and Google) microdata notation And X.Web.Microdata.SchemaOrg represent http://schema.org/ microdata notatio

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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 – 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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Responsive Design for your ADF Faces Web Applications

- by Shay Shmeltzer

Responsive web applications are a common pattern for designing web pages that adjust their UI based on the device that access them. With the increase in the number of ADF applications that are being accessed from mobile phones and tablet we are getting more and more questions around this topic. Steven Davelaar wrote a comprehensive article covering key concepts in this area that you can find here. The article focuses on what I would refer to as server adaptive application, where the server adapts the UI it generates based on the device that is accessing the server. However there is one more technique that is not covered in that article and can be used with Oracle ADF - it is CSS manipulation on the client that can achieve responsive design. I'll cover this technique in this blog entry. The main advantage of this technique is that the UI manipulation does not require the server to send over a new UI when a change is needed. This for example allows your page to change immediately when you change the orientation of your device. (By the way this example was developed for one of the seminars in the upcoming Oracle ADF OTN Virtual Developer Day). In the demo that you'll see below you'll see a single page that changes the way it is displayed based on the orientation of the device. Here is the page with the tablet in landscape and portrait: To achieve this I'm using a CSS media query in my page template that changes the display property of a couple of style classes that are used in my page. The media query has this format: @media screen and (max-width:700px) { .narrow { display: inline; } .wide { display: none; } .adjustFont { font-size: small; } .icon-home { font-size: 24px; } } This changes the properties of the same styleClasses that are defined in my application's skin. Here is a quick demo video that shows you the full application and explains how it works. For those looking to replicate this, here are the basic files: skin1.css @charset "UTF-8";/**ADFFaces_Skin_File / DO NOT REMOVE**/@namespace af "http://xmlns.oracle.com/adf/faces/rich";@namespace dvt "http://xmlns.oracle.com/dss/adf/faces";.wide { display: inline;}.narrow { display: none;}.adjustFont { font-size: large;}.icon-home { font-family: 'UIShellUGH'; -webkit-font-smoothing: antialiased; font-size: 36px; color: #ffa000;} pageTemplate: <?xml version='1.0' encoding='UTF-8'?><af:pageTemplateDef xmlns:af="http://xmlns.oracle.com/adf/faces/rich" var="attrs" definition="private" xmlns:afc="http://xmlns.oracle.com/adf/faces/rich/component"> <af:xmlContent> <afc:component> <afc:description>A template that will work on phones and desktop</afc:description> <afc:display-name>ResponsiveTemplate</afc:display-name> <afc:facet> <afc:facet-name>main</afc:facet-name> </afc:facet> </afc:component> </af:xmlContent> <meta name="viewport" content="width=device-width, initial-scale=1"/> <af:resource type="css">@media screen and (max-width:700px) { .narrow { display: inline; } .wide { display: none; } .adjustFont { font-size: small; } .icon-home { font-size: 24px; } }@font-face { font-family: 'UIShellUGH'; src: url(data:application/x-font-woff;charset=utf-8;base64,d09GRk9UVE8AA..removed code here...AzV6b1g==)format('truetype'); font-weight: normal; font-style: normal; } </af:resource> <af:panelGroupLayout id="pt_pgl4" layout="vertical" styleClass="sizeStyle"> <af:panelGridLayout id="pt_pgl1"> <af:gridRow marginTop="5px" height="40px" id="pt_gr1"> <af:gridCell marginStart="5px" width="100%" marginEnd="5px" id="pt_gc1"> <af:panelGroupLayout id="pt_pgl3" halign="center" layout="horizontal"> <af:outputText value="h" id="ot2" styleClass="icon-home"/> <af:outputText value="HR System" id="ot3" styleClass="adjustFont"/> </af:panelGroupLayout> </af:gridCell> </af:gridRow> <af:gridRow marginTop="5px" height="auto" id="pt_gr2"> <af:gridCell marginStart="5px" width="100%" marginEnd="5px" id="pt_gc2" halign="stretch"> <af:panelGroupLayout id="pt_pgl2" layout="scroll"> <af:facetRef facetName="main"/> </af:panelGroupLayout> </af:gridCell> </af:gridRow> <af:gridRow marginTop="5px" height="20px" marginBottom="5px" id="pt_gr3"> <af:gridCell marginStart="5px" width="100%" marginEnd="5px" id="pt_gc3"> <af:panelGroupLayout id="pt_pgl5" layout="vertical" halign="center"> <af:separator id="pt_s1"/> <af:outputText value="Copyright Oracle Corp. 2013" id="pt_ot1" styleClass="adjustFont"/> </af:panelGroupLayout> </af:gridCell> </af:gridRow> </af:panelGridLayout> </af:panelGroupLayout></af:pageTemplateDef> Example from the page: <af:gridRow id="gr3"> <af:gridCell id="gc7" columnSpan="2"> <af:panelGroupLayout id="pgl8" styleClass="narrow"> <af:link text="Menu" id="l1"> <af:showPopupBehavior triggerType="action" popupId="p1" align="afterEnd"/> </af:link> </af:panelGroupLayout> <af:panelGroupLayout id="pgl7" styleClass="wide"> <af:navigationPane id="np1" hint="buttons"> <af:commandNavigationItem text="Departments" id="cni1"/> <af:commandNavigationItem text="Employees" id="cni2"/> <af:commandNavigationItem text="Salaries" id="cni3"/> <af:commandNavigationItem text="Jobs" id="cni4"/> <af:commandNavigationItem text="Services" id="cni5"/> <af:commandNavigationItem text="Support" id="cni6"/> <af:commandNavigationItem text="Help" id="cni7"/> </af:navigationPane> </af:panelGroupLayout> </af:gridCell> </af:gridRow>

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Intro Bar like stack overflow

- by Dasa

I have a simple top bar using jquery like the one on stackoverflow, but i want it to only appear on the first time a person visits the website. below is the HTML followed by the "bxSlider.js" file <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html> <head> <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.3.2/jquery.min.js"></script> <script type="text/javascript" src="bxSlider.js"></script> <title>topbar</title> <style type="text/css" media="screen"> #message { font-family:Arial,Helvetica,sans-serif; position:fixed; top:0px; left:0px; width:100%; z-index:105; text-align:center; color:white; padding:2px 0px 2px 0px; background-color:#8E1609; } #example1 { text-align: center; width: 80%; } .close-notify { white-space: nowrap; float:right; margin-right:10px; color:#fff; text-decoration:none; padding-left:3px; padding-right:3px } .close-notify a { color: #fff; } h4, p { margin:0px; padding:0px; } </style> </head> <body> <DIV ID='message' style="display: none;"> <DIV ID="example1"> <DIV CLASS="item"> <h4>Head 1</h4> <p>Text 1</p> </div> <DIV CLASS="item"> <h4>Head 2</h4> <p>Text 2</p> </div> </div> <a href="#" CLASS="close-notify" onclick="closeNotice()">X</a> </div> <script type="text/javascript"> $(document).ready(function() { $("#message").fadeIn("slow"); $('#example1').bxSlider({ mode: 'slide', speed: 250, wrapper_CLASS: 'example1_container' }); }); function closeNotice() { $("#message").fadeOut("slow"); } </script> </body> </html> /** * * * bxSlider: Content slider / fade / ticker using the jQuery javascript library. * * Author: Steven Wanderski * Email: [email protected] * URL: http://bxslider.com * * **/ jQuery.fn.bxSlider = function(options){ ///////////////////////////////////////////////////////////////////////////////////////////////////////////// // Declare variables and functions ///////////////////////////////////////////////////////////////////////////////////////////////////////////// var defaults = { mode: 'slide', speed: 500, auto: false, auto_direction: 'left', pause: 2500, controls: true, prev_text: 'prev', next_text: 'next', width: $(this).children().width(), prev_img: '', next_img: '', ticker_direction: 'left', wrapper_class: 'container' }; options = $.extend(defaults, options); if(options.mode == 'ticker'){ options.auto = true; } var $this = $(this); var $parent_width = options.width; var current = 0; var is_working = false; var child_count = $this.children().size(); var i = 0; var j = 0; var k = 0; function animate_next(){ is_working = true; $this.animate({'left':'-' + $parent_width * 2 + 'px'}, options.speed, function(){ $this.css({'left':'-' + $parent_width + 'px'}).children(':first').appendTo($this); is_working = false; }); } function animate_prev(){ is_working = true; $this.animate({'left': 0}, options.speed, function(){ $this.css({'left':'-' + $parent_width + 'px'}).children(':last').insertBefore($this.children(':first')); is_working = false; }); } function fade(direction){ if(direction == 'next'){ var last_before_switch = child_count - 1; var start_over = 0; var incr = k + 1; }else if(direction == 'prev'){ var last_before_switch = 0; var start_over = child_count -1; var incr = k - 1; } is_working = true; if(k == last_before_switch){ $this.children().eq(k).fadeTo(options.speed, 0); $this.children().eq(start_over).fadeTo(options.speed, 1, function(){ is_working = false; k = start_over; }); }else{ $this.children().eq(k).fadeTo(options.speed, 0); $this.children().eq(incr).fadeTo(options.speed, 1, function(){ is_working = false; k = incr; }); } } function add_controls(){ ///////////////////////////////////////////////////////////////////////////////////////////////////////////// // Check if user selected images to use for next / prev ///////////////////////////////////////////////////////////////////////////////////////////////////////////// if(options.prev_img != '' || options.next_img != ''){ $this.parent().append('<a class="slider_prev" href=""><img src="' + options.prev_img + '" alt=""/></a><a class="slider_next" href=""><img src="' + options.next_img + '" alt="" /></a>'); }else{ $this.parent().append('<a class="slider_prev" href="">' + options.prev_text + '</a><a class="slider_next" href="">' + options.next_text + '</a>'); } $this.parent().find('.slider_prev').css({'float':'left', 'outline':'0', 'color':'yellow'}); $this.parent().find('.slider_next').css({'float':'right', 'outline':'0', 'color':'yellow'}); ///////////////////////////////////////////////////////////////////////////////////////////////////////////// // Accomodate padding-top for controls when elements are absolutely positioned (only in fade mode) ///////////////////////////////////////////////////////////////////////////////////////////////////////////// if(options.mode == 'fade'){ $this.parent().find('.slider_prev').css({'paddingTop' : $this.children().height()}) $this.parent().find('.slider_next').css({'paddingTop' : $this.children().height()}) } ///////////////////////////////////////////////////////////////////////////////////////////////////////////// // Actions when user clicks next / prev buttons ///////////////////////////////////////////////////////////////////////////////////////////////////////////// $this.parent().find('.slider_next').click(function(){ if(!is_working){ if(options.mode == 'slide'){ animate_next(); if(options.auto){ clearInterval($.t); $.t = setInterval(function(){animate_next();}, options.pause); } }else if(options.mode == 'fade'){ fade('next'); if(options.auto){ clearInterval($.t); $.t = setInterval(function(){fade('next');}, options.pause); } } } return false; }); $this.parent().find('.slider_prev').click(function(){ if(!is_working){ if(options.mode == 'slide'){ animate_prev(); if(options.auto){ clearInterval($.t); $.t = setInterval(function(){animate_prev();}, options.pause); } }else if(options.mode == 'fade'){ fade('prev'); if(options.auto){ clearInterval($.t); $.t = setInterval(function(){fade('prev');}, options.pause); } } } return false; }); } function ticker() { if(options.ticker_direction == 'left'){ $this.animate({'left':'-' + $parent_width * 2 + 'px'}, options.speed, 'linear', function(){ $this.css({'left':'-' + $parent_width + 'px'}).children(':first').appendTo($this); ticker(); }); }else if(options.ticker_direction == 'right'){ $this.animate({'left': 0}, options.speed, 'linear', function(){ $this.css({'left':'-' + $parent_width + 'px'}).children(':last').insertBefore($this.children(':first')); ticker(); }); } } ///////////////////////////////////////////////////////////////////////////////////////////////////////////// // Create content wrapper and set CSS ///////////////////////////////////////////////////////////////////////////////////////////////////////////// $this.wrap('<div class="' + options.wrapper_class + '"></div>'); //console.log($this.parent().css('paddingTop')); if(options.mode == 'slide' || options.mode == 'ticker'){ $this.parent().css({ 'overflow' : 'hidden', 'position' : 'relative', 'margin' : '0 auto', 'width' : options.width + 'px' }); $this.css({ 'width' : '999999px', 'position' : 'relative', 'left' : '-' + $parent_width + 'px' }); $this.children().css({ 'float' : 'left', 'width' : $parent_width }); $this.children(':last').insertBefore($this.children(':first')); }else if(options.mode == 'fade'){ $this.parent().css({ 'overflow' : 'hidden', 'position' : 'relative', 'width' : options.width + 'px' //'height' : $this.children().height() }); if(!options.controls){ $this.parent().css({'height' : $this.children().height()}); } $this.children().css({ 'position' : 'absolute', 'width' : $parent_width, 'listStyle' : 'none', 'opacity' : 0 }); $this.children(':first').css({ 'opacity' : 1 }); } ///////////////////////////////////////////////////////////////////////////////////////////////////////////// // Check if user selected "auto" ///////////////////////////////////////////////////////////////////////////////////////////////////////////// if(!options.auto){ add_controls(); }else{ if(options.mode == 'ticker'){ ticker(); }else{ ///////////////////////////////////////////////////////////////////////////////////////////////////////////// // Set a timed interval ///////////////////////////////////////////////////////////////////////////////////////////////////////////// if(options.mode == 'slide'){ if(options.auto_direction == 'left'){ $.t = setInterval(function(){animate_next();}, options.pause); }else if(options.auto_direction == 'right'){ $.t = setInterval(function(){animate_prev();}, options.pause); } }else if(options.mode == 'fade'){ if(options.auto_direction == 'left'){ $.t = setInterval(function(){fade('next');}, options.pause); }else if(options.auto_direction == 'right'){ $.t = setInterval(function(){fade('prev');}, options.pause); } } if(options.controls){ add_controls(); } } } }

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