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  • Using the West Wind Web Toolkit to set up AJAX and REST Services

    - by Rick Strahl
    I frequently get questions about which option to use for creating AJAX and REST backends for ASP.NET applications. There are many solutions out there to do this actually, but when I have a choice - not surprisingly - I fall back to my own tools in the West Wind West Wind Web Toolkit. I've talked a bunch about the 'in-the-box' solutions in the past so for a change in this post I'll talk about the tools that I use in my own and customer applications to handle AJAX and REST based access to service resources using the West Wind West Wind Web Toolkit. Let me preface this by saying that I like things to be easy. Yes flexible is very important as well but not at the expense of over-complexity. The goal I've had with my tools is make it drop dead easy, with good performance while providing the core features that I'm after, which are: Easy AJAX/JSON Callbacks Ability to return any kind of non JSON content (string, stream, byte[], images) Ability to work with both XML and JSON interchangeably for input/output Access endpoints via POST data, RPC JSON calls, GET QueryString values or Routing interface Easy to use generic JavaScript client to make RPC calls (same syntax, just what you need) Ability to create clean URLS with Routing Ability to use standard ASP.NET HTTP Stack for HTTP semantics It's all about options! In this post I'll demonstrate most of these features (except XML) in a few simple and short samples which you can download. So let's take a look and see how you can build an AJAX callback solution with the West Wind Web Toolkit. Installing the Toolkit Assemblies The easiest and leanest way of using the Toolkit in your Web project is to grab it via NuGet: West Wind Web and AJAX Utilities (Westwind.Web) and drop it into the project by right clicking in your Project and choosing Manage NuGet Packages from anywhere in the Project.   When done you end up with your project looking like this: What just happened? Nuget added two assemblies - Westwind.Web and Westwind.Utilities and the client ww.jquery.js library. It also added a couple of references into web.config: The default namespaces so they can be accessed in pages/views and a ScriptCompressionModule that the toolkit optionally uses to compress script resources served from within the assembly (namely ww.jquery.js and optionally jquery.js). Creating a new Service The West Wind Web Toolkit supports several ways of creating and accessing AJAX services, but for this post I'll stick to the lower level approach that works from any plain HTML page or of course MVC, WebForms, WebPages. There's also a WebForms specific control that makes this even easier but I'll leave that for another post. So, to create a new standalone AJAX/REST service we can create a new HttpHandler in the new project either as a pure class based handler or as a generic .ASHX handler. Both work equally well, but generic handlers don't require any web.config configuration so I'll use that here. In the root of the project add a Generic Handler. I'm going to call this one StockService.ashx. Once the handler has been created, edit the code and remove all of the handler body code. Then change the base class to CallbackHandler and add methods that have a [CallbackMethod] attribute. Here's the modified base handler implementation now looks like with an added HelloWorld method: using System; using Westwind.Web; namespace WestWindWebAjax { /// <summary> /// Handler implements CallbackHandler to provide REST/AJAX services /// </summary> public class SampleService : CallbackHandler { [CallbackMethod] public string HelloWorld(string name) { return "Hello " + name + ". Time is: " + DateTime.Now.ToString(); } } } Notice that the class inherits from CallbackHandler and that the HelloWorld service method is marked up with [CallbackMethod]. We're done here. Services Urlbased Syntax Once you compile, the 'service' is live can respond to requests. All CallbackHandlers support input in GET and POST formats, and can return results as JSON or XML. To check our fancy HelloWorld method we can now access the service like this: http://localhost/WestWindWebAjax/StockService.ashx?Method=HelloWorld&name=Rick which produces a default JSON response - in this case a string (wrapped in quotes as it's JSON): (note by default JSON will be downloaded by most browsers not displayed - various options are available to view JSON right in the browser) If I want to return the same data as XML I can tack on a &format=xml at the end of the querystring which produces: <string>Hello Rick. Time is: 11/1/2011 12:11:13 PM</string> Cleaner URLs with Routing Syntax If you want cleaner URLs for each operation you can also configure custom routes on a per URL basis similar to the way that WCF REST does. To do this you need to add a new RouteHandler to your application's startup code in global.asax.cs one for each CallbackHandler based service you create: protected void Application_Start(object sender, EventArgs e) { CallbackHandlerRouteHandler.RegisterRoutes<StockService>(RouteTable.Routes); } With this code in place you can now add RouteUrl properties to any of your service methods. For the HelloWorld method that doesn't make a ton of sense but here is what a routed clean URL might look like in definition: [CallbackMethod(RouteUrl="stocks/HelloWorld/{name}")] public string HelloWorld(string name) { return "Hello " + name + ". Time is: " + DateTime.Now.ToString(); } The same URL I previously used now becomes a bit shorter and more readable with: http://localhost/WestWindWebAjax/HelloWorld/Rick It's an easy way to create cleaner URLs and still get the same functionality. Calling the Service with $.getJSON() Since the result produced is JSON you can now easily consume this data using jQuery's getJSON method. First we need a couple of scripts - jquery.js and ww.jquery.js in the page: <!DOCTYPE html> <html> <head> <link href="Css/Westwind.css" rel="stylesheet" type="text/css" /> <script src="scripts/jquery.min.js" type="text/javascript"></script> <script src="scripts/ww.jquery.min.js" type="text/javascript"></script> </head> <body> Next let's add a small HelloWorld example form (what else) that has a single textbox to type a name, a button and a div tag to receive the result: <fieldset> <legend>Hello World</legend> Please enter a name: <input type="text" name="txtHello" id="txtHello" value="" /> <input type="button" id="btnSayHello" value="Say Hello (POST)" /> <input type="button" id="btnSayHelloGet" value="Say Hello (GET)" /> <div id="divHelloMessage" class="errordisplay" style="display:none;width: 450px;" > </div> </fieldset> Then to call the HelloWorld method a little jQuery is used to hook the document startup and the button click followed by the $.getJSON call to retrieve the data from the server. <script type="text/javascript"> $(document).ready(function () { $("#btnSayHelloGet").click(function () { $.getJSON("SampleService.ashx", { Method: "HelloWorld", name: $("#txtHello").val() }, function (result) { $("#divHelloMessage") .text(result) .fadeIn(1000); }); });</script> .getJSON() expects a full URL to the endpoint of our service, which is the ASHX file. We can either provide a full URL (SampleService.ashx?Method=HelloWorld&name=Rick) or we can just provide the base URL and an object that encodes the query string parameters for us using an object map that has a property that matches each parameter for the server method. We can also use the clean URL routing syntax, but using the object parameter encoding actually is safer as the parameters will get properly encoded by jQuery. The result returned is whatever the result on the server method is - in this case a string. The string is applied to the divHelloMessage element and we're done. Obviously this is a trivial example, but it demonstrates the basics of getting a JSON response back to the browser. AJAX Post Syntax - using ajaxCallMethod() The previous example allows you basic control over the data that you send to the server via querystring parameters. This works OK for simple values like short strings, numbers and boolean values, but doesn't really work if you need to pass something more complex like an object or an array back up to the server. To handle traditional RPC type messaging where the idea is to map server side functions and results to a client side invokation, POST operations can be used. The easiest way to use this functionality is to use ww.jquery.js and the ajaxCallMethod() function. ww.jquery wraps jQuery's AJAX functions and knows implicitly how to call a CallbackServer method with parameters and parse the result. Let's look at another simple example that posts a simple value but returns something more interesting. Let's start with the service method: [CallbackMethod(RouteUrl="stocks/{symbol}")] public StockQuote GetStockQuote(string symbol) { Response.Cache.SetExpires(DateTime.UtcNow.Add(new TimeSpan(0, 2, 0))); StockServer server = new StockServer(); var quote = server.GetStockQuote(symbol); if (quote == null) throw new ApplicationException("Invalid Symbol passed."); return quote; } This sample utilizes a small StockServer helper class (included in the sample) that downloads a stock quote from Yahoo's financial site via plain HTTP GET requests and formats it into a StockQuote object. Lets create a small HTML block that lets us query for the quote and display it: <fieldset> <legend>Single Stock Quote</legend> Please enter a stock symbol: <input type="text" name="txtSymbol" id="txtSymbol" value="msft" /> <input type="button" id="btnStockQuote" value="Get Quote" /> <div id="divStockDisplay" class="errordisplay" style="display:none; width: 450px;"> <div class="label-left">Company:</div> <div id="stockCompany"></div> <div class="label-left">Last Price:</div> <div id="stockLastPrice"></div> <div class="label-left">Quote Time:</div> <div id="stockQuoteTime"></div> </div> </fieldset> The final result looks something like this:   Let's hook up the button handler to fire the request and fill in the data as shown: $("#btnStockQuote").click(function () { ajaxCallMethod("SampleService.ashx", "GetStockQuote", [$("#txtSymbol").val()], function (quote) { $("#divStockDisplay").show().fadeIn(1000); $("#stockCompany").text(quote.Company + " (" + quote.Symbol + ")"); $("#stockLastPrice").text(quote.LastPrice); $("#stockQuoteTime").text(quote.LastQuoteTime.formatDate("MMM dd, HH:mm EST")); }, onPageError); }); So we point at SampleService.ashx and the GetStockQuote method, passing a single parameter of the input symbol value. Then there are two handlers for success and failure callbacks.  The success handler is the interesting part - it receives the stock quote as a result and assigns its values to various 'holes' in the stock display elements. The data that comes back over the wire is JSON and it looks like this: { "Symbol":"MSFT", "Company":"Microsoft Corpora", "OpenPrice":26.11, "LastPrice":26.01, "NetChange":0.02, "LastQuoteTime":"2011-11-03T02:00:00Z", "LastQuoteTimeString":"Nov. 11, 2011 4:20pm" } which is an object representation of the data. JavaScript can evaluate this JSON string back into an object easily and that's the reslut that gets passed to the success function. The quote data is then applied to existing page content by manually selecting items and applying them. There are other ways to do this more elegantly like using templates, but here we're only interested in seeing how the data is returned. The data in the object is typed - LastPrice is a number and QuoteTime is a date. Note about the date value: JavaScript doesn't have a date literal although the JSON embedded ISO string format used above  ("2011-11-03T02:00:00Z") is becoming fairly standard for JSON serializers. However, JSON parsers don't deserialize dates by default and return them by string. This is why the StockQuote actually returns a string value of LastQuoteTimeString for the same date. ajaxMethodCallback always converts dates properly into 'real' dates and the example above uses the real date value along with a .formatDate() data extension (also in ww.jquery.js) to display the raw date properly. Errors and Exceptions So what happens if your code fails? For example if I pass an invalid stock symbol to the GetStockQuote() method you notice that the code does this: if (quote == null) throw new ApplicationException("Invalid Symbol passed."); CallbackHandler automatically pushes the exception message back to the client so it's easy to pick up the error message. Regardless of what kind of error occurs: Server side, client side, protocol errors - any error will fire the failure handler with an error object parameter. The error is returned to the client via a JSON response in the error callback. In the previous examples I called onPageError which is a generic routine in ww.jquery that displays a status message on the bottom of the screen. But of course you can also take over the error handling yourself: $("#btnStockQuote").click(function () { ajaxCallMethod("SampleService.ashx", "GetStockQuote", [$("#txtSymbol").val()], function (quote) { $("#divStockDisplay").fadeIn(1000); $("#stockCompany").text(quote.Company + " (" + quote.Symbol + ")"); $("#stockLastPrice").text(quote.LastPrice); $("#stockQuoteTime").text(quote.LastQuoteTime.formatDate("MMM dd, hh:mmt")); }, function (error, xhr) { $("#divErrorDisplay").text(error.message).fadeIn(1000); }); }); The error object has a isCallbackError, message and  stackTrace properties, the latter of which is only populated when running in Debug mode, and this object is returned for all errors: Client side, transport and server side errors. Regardless of which type of error you get the same object passed (as well as the XHR instance optionally) which makes for a consistent error retrieval mechanism. Specifying HttpVerbs You can also specify HTTP Verbs that are allowed using the AllowedHttpVerbs option on the CallbackMethod attribute: [CallbackMethod(AllowedHttpVerbs=HttpVerbs.GET | HttpVerbs.POST)] public string HelloWorld(string name) { … } If you're building REST style API's this might be useful to force certain request semantics onto the client calling. For the above if call with a non-allowed HttpVerb the request returns a 405 error response along with a JSON (or XML) error object result. The default behavior is to allow all verbs access (HttpVerbs.All). Passing in object Parameters Up to now the parameters I passed were very simple. But what if you need to send something more complex like an object or an array? Let's look at another example now that passes an object from the client to the server. Keeping with the Stock theme here lets add a method called BuyOrder that lets us buy some shares for a stock. Consider the following service method that receives an StockBuyOrder object as a parameter: [CallbackMethod] public string BuyStock(StockBuyOrder buyOrder) { var server = new StockServer(); var quote = server.GetStockQuote(buyOrder.Symbol); if (quote == null) throw new ApplicationException("Invalid or missing stock symbol."); return string.Format("You're buying {0} shares of {1} ({2}) stock at {3} for a total of {4} on {5}.", buyOrder.Quantity, quote.Company, quote.Symbol, quote.LastPrice.ToString("c"), (quote.LastPrice * buyOrder.Quantity).ToString("c"), buyOrder.BuyOn.ToString("MMM d")); } public class StockBuyOrder { public string Symbol { get; set; } public int Quantity { get; set; } public DateTime BuyOn { get; set; } public StockBuyOrder() { BuyOn = DateTime.Now; } } This is a contrived do-nothing example that simply echoes back what was passed in, but it demonstrates how you can pass complex data to a callback method. On the client side we now have a very simple form that captures the three values on a form: <fieldset> <legend>Post a Stock Buy Order</legend> Enter a symbol: <input type="text" name="txtBuySymbol" id="txtBuySymbol" value="GLD" />&nbsp;&nbsp; Qty: <input type="text" name="txtBuyQty" id="txtBuyQty" value="10" style="width: 50px" />&nbsp;&nbsp; Buy on: <input type="text" name="txtBuyOn" id="txtBuyOn" value="<%= DateTime.Now.ToString("d") %>" style="width: 70px;" /> <input type="button" id="btnBuyStock" value="Buy Stock" /> <div id="divStockBuyMessage" class="errordisplay" style="display:none"></div> </fieldset> The completed form and demo then looks something like this:   The client side code that picks up the input values and assigns them to object properties and sends the AJAX request looks like this: $("#btnBuyStock").click(function () { // create an object map that matches StockBuyOrder signature var buyOrder = { Symbol: $("#txtBuySymbol").val(), Quantity: $("#txtBuyQty").val() * 1, // number Entered: new Date() } ajaxCallMethod("SampleService.ashx", "BuyStock", [buyOrder], function (result) { $("#divStockBuyMessage").text(result).fadeIn(1000); }, onPageError); }); The code creates an object and attaches the properties that match the server side object passed to the BuyStock method. Each property that you want to update needs to be included and the type must match (ie. string, number, date in this case). Any missing properties will not be set but also not cause any errors. Pass POST data instead of Objects In the last example I collected a bunch of values from form variables and stuffed them into object variables in JavaScript code. While that works, often times this isn't really helping - I end up converting my types on the client and then doing another conversion on the server. If lots of input controls are on a page and you just want to pick up the values on the server via plain POST variables - that can be done too - and it makes sense especially if you're creating and filling the client side object only to push data to the server. Let's add another method to the server that once again lets us buy a stock. But this time let's not accept a parameter but rather send POST data to the server. Here's the server method receiving POST data: [CallbackMethod] public string BuyStockPost() { StockBuyOrder buyOrder = new StockBuyOrder(); buyOrder.Symbol = Request.Form["txtBuySymbol"]; ; int qty; int.TryParse(Request.Form["txtBuyQuantity"], out qty); buyOrder.Quantity = qty; DateTime time; DateTime.TryParse(Request.Form["txtBuyBuyOn"], out time); buyOrder.BuyOn = time; // Or easier way yet //FormVariableBinder.Unbind(buyOrder,null,"txtBuy"); var server = new StockServer(); var quote = server.GetStockQuote(buyOrder.Symbol); if (quote == null) throw new ApplicationException("Invalid or missing stock symbol."); return string.Format("You're buying {0} shares of {1} ({2}) stock at {3} for a total of {4} on {5}.", buyOrder.Quantity, quote.Company, quote.Symbol, quote.LastPrice.ToString("c"), (quote.LastPrice * buyOrder.Quantity).ToString("c"), buyOrder.BuyOn.ToString("MMM d")); } Clearly we've made this server method take more code than it did with the object parameter. We've basically moved the parameter assignment logic from the client to the server. As a result the client code to call this method is now a bit shorter since there's no client side shuffling of values from the controls to an object. $("#btnBuyStockPost").click(function () { ajaxCallMethod("SampleService.ashx", "BuyStockPost", [], // Note: No parameters - function (result) { $("#divStockBuyMessage").text(result).fadeIn(1000); }, onPageError, // Force all page Form Variables to be posted { postbackMode: "Post" }); }); The client simply calls the BuyStockQuote method and pushes all the form variables from the page up to the server which parses them instead. The feature that makes this work is one of the options you can pass to the ajaxCallMethod() function: { postbackMode: "Post" }); which directs the function to include form variable POST data when making the service call. Other options include PostNoViewState (for WebForms to strip out WebForms crap vars), PostParametersOnly (default), None. If you pass parameters those are always posted to the server except when None is set. The above code can be simplified a bit by using the FormVariableBinder helper, which can unbind form variables directly into an object: FormVariableBinder.Unbind(buyOrder,null,"txtBuy"); which replaces the manual Request.Form[] reading code. It receives the object to unbind into, a string of properties to skip, and an optional prefix which is stripped off form variables to match property names. The component is similar to the MVC model binder but it's independent of MVC. Returning non-JSON Data CallbackHandler also supports returning non-JSON/XML data via special return types. You can return raw non-JSON encoded strings like this: [CallbackMethod(ReturnAsRawString=true,ContentType="text/plain")] public string HelloWorldNoJSON(string name) { return "Hello " + name + ". Time is: " + DateTime.Now.ToString(); } Calling this method results in just a plain string - no JSON encoding with quotes around the result. This can be useful if your server handling code needs to return a string or HTML result that doesn't fit well for a page or other UI component. Any string output can be returned. You can also return binary data. Stream, byte[] and Bitmap/Image results are automatically streamed back to the client. Notice that you should set the ContentType of the request either on the CallbackMethod attribute or using Response.ContentType. This ensures the Web Server knows how to display your binary response. Using a stream response makes it possible to return any of data. Streamed data can be pretty handy to return bitmap data from a method. The following is a method that returns a stock history graph for a particular stock over a provided number of years: [CallbackMethod(ContentType="image/png",RouteUrl="stocks/history/graph/{symbol}/{years}")] public Stream GetStockHistoryGraph(string symbol, int years = 2,int width = 500, int height=350) { if (width == 0) width = 500; if (height == 0) height = 350; StockServer server = new StockServer(); return server.GetStockHistoryGraph(symbol,"Stock History for " + symbol,width,height,years); } I can now hook this up into the JavaScript code when I get a stock quote. At the end of the process I can assign the URL to the service that returns the image into the src property and so force the image to display. Here's the changed code: $("#btnStockQuote").click(function () { var symbol = $("#txtSymbol").val(); ajaxCallMethod("SampleService.ashx", "GetStockQuote", [symbol], function (quote) { $("#divStockDisplay").fadeIn(1000); $("#stockCompany").text(quote.Company + " (" + quote.Symbol + ")"); $("#stockLastPrice").text(quote.LastPrice); $("#stockQuoteTime").text(quote.LastQuoteTime.formatDate("MMM dd, hh:mmt")); // display a stock chart $("#imgStockHistory").attr("src", "stocks/history/graph/" + symbol + "/2"); },onPageError); }); The resulting output then looks like this: The charting code uses the new ASP.NET 4.0 Chart components via code to display a bar chart of the 2 year stock data as part of the StockServer class which you can find in the sample download. The ability to return arbitrary data from a service is useful as you can see - in this case the chart is clearly associated with the service and it's nice that the graph generation can happen off a handler rather than through a page. Images are common resources, but output can also be PDF reports, zip files for downloads etc. which is becoming increasingly more common to be returned from REST endpoints and other applications. Why reinvent? Obviously the examples I've shown here are pretty basic in terms of functionality. But I hope they demonstrate the core features of AJAX callbacks that you need to work through in most applications which is simple: return data, send back data and potentially retrieve data in various formats. While there are other solutions when it comes down to making AJAX callbacks and servicing REST like requests, I like the flexibility my home grown solution provides. Simply put it's still the easiest solution that I've found that addresses my common use cases: AJAX JSON RPC style callbacks Url based access XML and JSON Output from single method endpoint XML and JSON POST support, querystring input, routing parameter mapping UrlEncoded POST data support on callbacks Ability to return stream/raw string data Essentially ability to return ANYTHING from Service and pass anything All these features are available in various solutions but not together in one place. I've been using this code base for over 4 years now in a number of projects both for myself and commercial work and it's served me extremely well. Besides the AJAX functionality CallbackHandler provides, it's also an easy way to create any kind of output endpoint I need to create. Need to create a few simple routines that spit back some data, but don't want to create a Page or View or full blown handler for it? Create a CallbackHandler and add a method or multiple methods and you have your generic endpoints.  It's a quick and easy way to add small code pieces that are pretty efficient as they're running through a pretty small handler implementation. I can have this up and running in a couple of minutes literally without any setup and returning just about any kind of data. Resources Download the Sample NuGet: Westwind Web and AJAX Utilities (Westwind.Web) ajaxCallMethod() Documentation Using the AjaxMethodCallback WebForms Control West Wind Web Toolkit Home Page West Wind Web Toolkit Source Code © Rick Strahl, West Wind Technologies, 2005-2011Posted in ASP.NET  jQuery  AJAX   Tweet (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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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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  • Interview with Lenz Grimmer about MySQL Connect

    - by Keith Larson
    Keith Larson: Thank you for allowing me to do this interview with you.  I have been talking with a few different Oracle ACEs   about the MySQL Connect Conference. I figured the MySQL community might be missing you as well. You have been very busy with Oracle Linux but I know you still have an eye on the MySQL Community. How have things been?Lenz Grimmer: Thanks for including me in this series of interviews, I feel honored! I've read the other interviews, and really liked them. I still try to follow what's going on over in the MySQL community and it's good to see that many of the familiar faces are still around. Over the course of the 9 years that I was involved with MySQL, many colleagues and contacts turned into good friends and we still maintain close relationships.It's been almost 1.5 years ago that I moved into my new role here in the Linux team at Oracle, and I really enjoy working on a Linux distribution again (I worked for SUSE before I joined MySQL AB in 2002). I'm still learning a lot - Linux in the data center has greatly evolved in so many ways and there are a lot of new and exciting technologies to explore. Keith Larson: What were your thoughts when you heard that Oracle was going to deliver the MySQL Connect conference to the MySQL Community?Lenz Grimmer: I think it's testament to the fact that Oracle deeply cares about MySQL, despite what many skeptics may say. What started as "MySQL Sunday" two years ago has now evolved into a full-blown sub-conference, with 80 sessions at one of the largest corporate IT events in the world. I find this quite telling, not many products at Oracle enjoy this level of exposure! So it certainly makes me feel proud to see how far MySQL has come. Keith Larson: Have you had a chance to look over the sessions? What are your thoughts on them?Lenz Grimmer: I did indeed look at the final schedule.The content committee did a great job with selecting these sessions. I'm glad to see that the content selection was influenced by involving well-known and respected members of the MySQL community. The sessions cover a broad range of topics and technologies, both covering established topics as well as recent developments. Keith Larson: When you get a chance, what sessions do you plan on attending?Lenz Grimmer: I will actually be manning the Oracle booth in the exhibition area on one of these days, so I'm not sure if I'll have a lot of time attending sessions. But if I do, I'd love to see the keynotes and catch some of the sessions that talk about recent developments and new features in MySQL, High Availability and Clustering . Quite a lot has happened and it's hard to keep up with this constant flow of new MySQL releases.In particular, the following sessions caught my attention: MySQL Connect Keynote: The State of the Dolphin Evaluating MySQL High-Availability Alternatives CERN’s MySQL “as a Service” Deployment with Oracle VM: Empowering Users MySQL 5.6 Replication: Taking Scalability and High Availability to the Next Level What’s New in MySQL Server 5.6? MySQL Security: Past and Present MySQL at Twitter: Development and Deployment MySQL Community BOF MySQL Connect Keynote: MySQL Perspectives Keith Larson: So I will ask you just like I have asked the others I have interviewed, any tips that you would give to people for handling the long hours at conferences?Lenz Grimmer: Wear comfortable shoes and make sure to drink a lot! Also prepare a plan of the sessions you would like to attend beforehand and familiarize yourself with the venue, so you can get to the next talk in time without scrambling to find the location. The good thing about piggybacking on such a large conference like Oracle OpenWorld is that you benefit from the whole infrastructure. For example, there is a nice schedule builder that helps you to keep track of your sessions of interest. Other than that, bring enough business cards and talk to people, build up your network among your peers and other MySQL professionals! Keith Larson: What features of the MySQL 5.6 release do you look forward to the most ?Lenz Grimmer: There has been solid progress in so many areas like the InnoDB Storage Engine, the Optimizer, Replication or Performance Schema, it's hard for me to really highlight anything in particular. All in all, MySQL 5.6 sounds like a very promising release. I'm confident it will follow the tradition that Oracle already established with MySQL 5.5, which received a lot of praise even from very critical members of the MySQL community. If I had to name a single feature, I'm particularly and personally happy that the precise GIS functions have finally made it into a GA release - that was long overdue. Keith Larson:  In your opinion what is the best reason for someone to attend this event?Lenz Grimmer: This conference is an excellent opportunity to get in touch with the key people in the MySQL community and ecosystem and to get facts and information from the domain experts and developers that work on MySQL. The broad range of topics should attract people from a variety of roles and relations to MySQL, beginning with Developers and DBAs, to CIOs considering MySQL as a viable solution for their requirements. Keith Larson: You will be attending MySQL Connect and have some Oracle Linux Demos, do you see a growing demand for MySQL on Oracle Linux ?Lenz Grimmer: Yes! Oracle Linux is our recommended Linux distribution and we have a good relationship to the MySQL engineering group. They use Oracle Linux as a base Linux platform for development and QA, so we make sure that MySQL and Oracle Linux are well tested together. Setting up a MySQL server on Oracle Linux can be done very quickly, and many customers recognize the benefits of using them both in combination.Because Oracle Linux is available for free (including free bug fixes and errata), it's an ideal choice for running MySQL in your data center. You can run the same Linux distribution on both your development/staging systems as well as on the production machines, you decide which of these should be covered by a support subscription and at which level of support. This gives you flexibility and provides some really attractive cost-saving opportunities. Keith Larson: Since I am a Linux user and fan, what is on the horizon for  Oracle Linux?Lenz Grimmer: We're working hard on broadening the ecosystem around Oracle Linux, building up partnerships with ISVs and IHVs to certify Oracle Linux as a fully supported platform for their products. We also continue to collaborate closely with the Linux kernel community on various projects, to make sure that Linux scales and performs well on large systems and meets the demands of today's data centers. These improvements and enhancements will then rolled into the Unbreakable Enterprise Kernel, which is the key ingredient that sets Oracle Linux apart from other distributions. We also have a number of ongoing projects which are making good progress, and I'm sure you'll hear more about this at the upcoming OpenWorld conference :) Keith Larson: What is something that more people should be aware of when it comes to Oracle Linux and MySQL ?Lenz Grimmer: Many people assume that Oracle Linux is just tuned for Oracle products, such as the Oracle Database or our Engineered Systems. While it's of course true that we do a lot of testing and optimization for these workloads, Oracle Linux is and will remain a general-purpose Linux distribution that is a very good foundation for setting up a LAMP-Stack, for example. We also provide MySQL RPM packages for Oracle Linux, so you can easily stay up to date if you need something newer than what's included in the stock distribution.One more thing that is really unique to Oracle Linux is Ksplice, which allows you to apply security patches to the running Linux kernel, without having to reboot. This ensures that your MySQL database server keeps up and running and is not affected by any downtime. Keith Larson: What else would you like to add ?Lenz Grimmer: Thanks again for getting in touch with me, I appreciated the opportunity. I'm looking forward to MySQL Connect and Oracle OpenWorld and to meet you and many other people from the MySQL community that I haven't seen for quite some time! Keith Larson:  Thank you Lenz!

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  • SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

    - by Pinal Dave
    In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D:  S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or  SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand  the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

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  • Microsoft TechEd 2010 - Day 3 @ Bangalore

    - by sathya
    Microsoft TechEd 2010 - Day 3 @ Bangalore Sorry for my delayed post on day 3 because I had to travel from Blore to Chennai So I couldnt write for the past two days. On day 3 as usual we had lot of simultaneous tracks on various sessions. This day I choose the Your Data, Our Platform Track. It had sessions on the following 5 topics :   Developing Data-tier Applications in Visual Studio 2010 - by Sanjay Nagamangalam SQL Server Query Optimization, Execution and Debugging Query Performance - by Vinod Kumar M SQL Server Utility - Its about more than 1 SQL Server - by Vinod Kumar Jagannathan Data Recovery / Consistency with CheckDB - by Vinod Kumar M Developing with SQL Server Spatial and Deep dive into Spatial Indexing - by Pinal Dave Developing Data-tier Applications in Visual Studio 2010 - by Sanjay Nagamangalam This was one of the superb sessions i have attended. He explained all the concepts in detail with a demo. The important thing in this is there is something called Data-Tier application project which is newly introduced in this VS2010 with which we can manage all our data along with our application inside our VS itself. We can create DB,Tables,Procs,Views etc. here itself and once we deploy it creates a compressed file called .dacpac which stores all the changes in Table Schema,Created procs, etc. on to that single file which reduces our (developer's) effort in preparing the deployment scripts and giving it to the DBA. It also has some policy configurations which can be managed easily by checking some rules like in outlook. For Ex : IF the SQL Server Version > 10 then deploy else dont. This rule specifies that even if we try to deploy on SQL Server DB with version less than 10 It will not do it. And if we deploy some .dacpac to SQL server production db with the option upgrade DB with this dacpac once everything completes successfully it will say success else it rollsback to the prior version. Even if it gets deployed successfully and later @ a point of time you wish to revert it back to the prior version, you can go ahead and delete the existing dacpac version so that it reverts to the older version of the db changes. And for the good questions that were asked in the session T-Shirts were given. SQL Server Query Optimization, Execution and Debugging Query Performance - by Vinod Kumar M This one too was the best session. The speaker Vinod explained everything very much clearly. This was really useful session and you dont believe, as per my knowledge, in the total 3 days in the TechEd except the Keynote, for this session seats were full (House FULL)  People were even standing out to attend this session. Such a great one it was. The speaker did a deep dive in to the Query Plan section and showed which actually causes the problem. Its all about the thing that we need to understand about the execution of SQL server Queries. We think in a way and SQL Server never executes in that way. We need to understand that first. He also told about there might be two plans generated for a single query at a point of time because of parallel processors in the system. The Key is here in every query. There is something called Estimated Row Count and Actual Row Count in the query plan. If the estimated row count by SQL server tallies with the actual row count your performance will be awesome. He said some tweaks to achieve the same. After this as usual we had lunch SQL Server Utility - Its about more than 1 SQL Server - by Vinod Kumar Jagannathan This was more of a DBA's session. Am really sorry I was totally blank and I was not interested to attend this session and walked out to attend Migrating to the cloud by Harish Ranganathan (My favorite Speaker) but unfortunately that was some other persons session. There the speaker was telling about how to configure the connection strings in such a way that we can connect to the SQL Azure platform from our VS and also showed us how to deploy the same in to Windows Azure. In between there were lot of technical problems like laptop hang, user locked and he was switching between systems, also i came in the half so i wasnt able to listen that fully. In between, Since I got an MCTS certification they gave me T-Shirt with the lines 'Iam Certified. Are you?' and they asked me to wear that. If we wear that we might get spotted and they would give us some goodies  So on the 3rd day I was wearing that T-Shirt. I got spotted by the person Tarun who was coordinating things about the certification, and he was accompanied with a cameraman and they interviewed me about the certification and I was shown live in the Teched and was seen by 60000 live viewers of the TechEd. I was really happy on that. Data Recovery / Consistency with CheckDB - by Vinod Kumar M This was one of the best sessions too in the TechEd. This guy is really amazing. In front of us he crashed a DB and showed how to recover the same in 6 different ways for different no of failures. Showed about Different types of error msgs like : 823,824,825 msdb..suspect_pages DBCC CheckDB (different parameters to it) I am really waiting for his session to get uploaded live in the Teched Website. Here is his contact info If you wish to connect to him : Twitter : @vinodk_sql Website : www.ExtremeExperts.com Blog : http://blogs.sqlxml.org/vinodkumar Developing with SQL Server Spatial and Deep dive into Spatial Indexing - by Pinal Dave Pinal Dave is a King in SQL and he is a SQL MVP and he is the owner of SQLAuthority.com He took the session on Spatial Databases from the start. Showed about the different types of Spatial : Geometric and Geographic Geometric : x and y axis its a planar surface Geographic : Spherical surface with 3600  as the maximum which is used to represent the geographic points on the earth and easy to draw maps of different kinds. He had a lot of obstacles during his session like rain coming inside the hall, mic wires got bursted due to rain, Videos off on the display screens. In spite of that he asked the audience to come in the front rows and managed to take a good session without ppts and finally we got the displays on and he was showing demos on the same what he explained orally. That was really a fun filled informative session. He gave some books for the persons who asked good questions and answered well for his questions and I got one too  (It was a book on Data Mining - Wrox Publishers) And finally after all these things there was Keynote session for close of the TechEd. and we all assembled in a big hall where Mr.Ashok Soota, a man of age around 70  co-founder of Mindtree was called to give some lecture on his successes. He was explaining about his past and what all companies he switched and for what reasons and what are all his successes and what are all his failures and the learnings of him from his past failures. and his success and failures on his partnerships with the other concern. And there were some questions for him like What is your suggestion on young entrepreneur? How did you learn from past failures? What is reiterating your success? What is your suggestion on partnerships? How to choose partnerships? etc. And they said @ 7.30 Pm there would be a party night, but unfortunately i was not able to attend that because I had to catch my train and before that i had to pack things, so I started @ 7 itself. Thats it about the TechED!!! Stay tuned for further Technology updates.

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  • Database continuous integration step by step

    - by David Atkinson
    This post will describe how to set up basic database continuous integration using TeamCity to initiate the build process, SQL Source Control to put your database under source control, and the SQL Compare command line to keep a test database up to date. In my example I will be using Subversion as my source control repository. If you wish to follow my steps verbatim, please make sure you have TortoiseSVN, SQL Compare and SQL Source Control installed. Downloading and Installing TeamCity TeamCity (http://www.jetbrains.com/teamcity/index.html) is free for up to three agents, so it a great no-risk tool you can use to experiment with. 1. Download the latest version from the JetBrains website. For some reason the TeamCity executable didn't download properly for me, stalling frustratingly at 99%, so I tried again with the zip file download option (see screenshot below), which worked flawlessly. 2. Run the installer using the defaults. This results in a set-up with the server component and agent installed on the same machine, which is ideal for getting started with ease. 3. Check that the build agent is pointing to the server correctly. This has caught me out a few times before. This setting is in C:\TeamCity\buildAgent\conf\buildAgent.properties and for my installation is serverUrl=http\://localhost\:80 . If you need to change this value, if for example you've had to install the Server console to a different port number, the TeamCity Build Agent Service will need to be restarted for the change to take effect. 4. Open the TeamCity admin console on http://localhost , and specify your own designated username and password at first startup. Putting your database in source control using SQL Source Control 5. Assuming you've got SQL Source Control installed, select a development database in the SQL Server Management Studio Object Explorer and select Link Database to Source Control. 6. For the Link step you can either create your own empty folder in source control, or you can select Just Evaluating, which just creates a local subversion repository for you behind the scenes. 7. Once linked, note that your database turns green in the Object Explorer. Visit the Commit tab to do an initial commit of your database objects by typing in an appropriate comment and clicking Commit. 8. There is a hidden feature in SQL Source Control that opens up TortoiseSVN (provided it is installed) pointing to the linked repository. Keep Shift depressed and right click on the text to the right of 'Linked to', in the example below, it's the red Evaluation Repository text. Select Open TortoiseSVN Repo Browser. This screen should give you an idea of how SQL Source Control manages the object files behind the scenes. Back in the TeamCity admin console, we'll now create a new project to monitor the above repository location and to trigger a 'build' each time the repository changes. 9. In TeamCity Adminstration, select Create Project and give it a name, such as "My first database CI", and click Create. 10. Click on Create Build Configuration, and name it something like "Integration build". 11. Click VCS settings and then Create And Attach new VCS root. This is where you will tell TeamCity about the repository it should monitor. 12. In my case since I'm using the Just Evaluating option in SQL Source Control, I should select Subversion. 13. In the URL field paste your repository location. In my case this is file:///C:/Users/David.Atkinson/AppData/Local/Red Gate/SQL Source Control 3/EvaluationRepositories/WidgetDevelopment/WidgetDevelopment 14. Click on Test Connection to ensure that you can communicate with your source control system. Click Save. 15. Click Add Build Step, and Runner Type: Command Line. Should you be familiar with the other runner types, such as NAnt, MSBuild or Powershell, you can opt for these, but for the same of keeping it simple I will pick the simplest option. 16. If you have installed SQL Compare in the default location, set the Command Executable field to: C:\Program Files (x86)\Red Gate\SQL Compare 10\sqlcompare.exe 17. Flip back to SSMS briefly and add a new database to your server. This will be the database used for continuous integration testing. 18. Set the command parameters according to your server and the name of the database you have created. In my case I created database RedGateCI on server .\sql2008r2 /scripts1:. /server2:.\sql2008r2 /db2:RedGateCI /sync /verbose Note that if you pick a server instance that isn't on your local machine, you'll need the TCP/IP protocol enabled in SQL Server Configuration Manager otherwise the SQL Compare command line will not be able to connect. 19. Save and select Build Triggering / Add New Trigger / VCS Trigger. This is where you tell TeamCity when it should initiate a build. Click Save. 20. Now return to SQL Server Management Studio and make a schema change (eg add a new object) to your linked development database. A blue indicator will appear in the Object Explorer. Commit this change, typing in an appropriate check-in comment. All being good, within 60 seconds (a TeamCity default that can be changed) a build will be triggered. 21. Click on Projects in TeamCity to get back to the overview screen: The build log will show you the console output, which is useful for troubleshooting any issues: That's it! You now have continuous integration on your database. In future posts I'll cover how you can generate and test the database creation script, the database upgrade script, and run database unit tests as part of your continuous integration script. If you have any trouble getting this up and running please let me know, either by commenting on this post, or email me directly using the email address below. Technorati Tags: SQL Server

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  • Authenticating clients in the new WCF Http stack

    - by cibrax
    About this time last year, I wrote a couple of posts about how to use the “Interceptors” from the REST starker kit for implementing several authentication mechanisms like “SAML”, “Basic Authentication” or “OAuth” in the WCF Web programming model. The things have changed a lot since then, and Glenn finally put on our hands a new version of the Web programming model that deserves some attention and I believe will help us a lot to build more Http oriented services in the .NET stack. What you can get today from wcf.codeplex.com is a preview with some cool features like Http Processors (which I already discussed here), a new and improved version of the HttpClient library, Dependency injection and better TDD support among others. However, the framework still does not support an standard way of doing client authentication on the services (This is something planned for the upcoming releases I believe). For that reason, moving the existing authentication interceptors to this new programming model was one of the things I did in the last few days. In order to make authentication simple and easy to extend,  I first came up with a model based on what I called “Authentication Interceptors”. An authentication interceptor maps to an existing Http authentication mechanism and implements the following interface, public interface IAuthenticationInterceptor{ string Scheme { get; } bool DoAuthentication(HttpRequestMessage request, HttpResponseMessage response, out IPrincipal principal);} An authentication interceptors basically needs to returns the http authentication schema that implements in the property “Scheme”, and implements the authentication mechanism in the method “DoAuthentication”. As you can see, this last method “DoAuthentication” only relies on the HttpRequestMessage and HttpResponseMessage classes, making the testing of this interceptor very simple (There is no need to do some black magic with the WCF context or messages). After this, I implemented a couple of interceptors for supporting basic authentication and brokered authentication with SAML (using WIF) in my services. The following code illustrates how the basic authentication interceptors looks like. public class BasicAuthenticationInterceptor : IAuthenticationInterceptor{ Func<UsernameAndPassword, bool> userValidation; string realm;  public BasicAuthenticationInterceptor(Func<UsernameAndPassword, bool> userValidation, string realm) { if (userValidation == null) throw new ArgumentNullException("userValidation");  if (string.IsNullOrEmpty(realm)) throw new ArgumentNullException("realm");  this.userValidation = userValidation; this.realm = realm; }  public string Scheme { get { return "Basic"; } }  public bool DoAuthentication(HttpRequestMessage request, HttpResponseMessage response, out IPrincipal principal) { string[] credentials = ExtractCredentials(request); if (credentials.Length == 0 || !AuthenticateUser(credentials[0], credentials[1])) { response.StatusCode = HttpStatusCode.Unauthorized; response.Content = new StringContent("Access denied"); response.Headers.WwwAuthenticate.Add(new AuthenticationHeaderValue("Basic", "realm=" + this.realm));  principal = null;  return false; } else { principal = new GenericPrincipal(new GenericIdentity(credentials[0]), new string[] {});  return true; } }  private string[] ExtractCredentials(HttpRequestMessage request) { if (request.Headers.Authorization != null && request.Headers.Authorization.Scheme.StartsWith("Basic")) { string encodedUserPass = request.Headers.Authorization.Parameter.Trim();  Encoding encoding = Encoding.GetEncoding("iso-8859-1"); string userPass = encoding.GetString(Convert.FromBase64String(encodedUserPass)); int separator = userPass.IndexOf(':');  string[] credentials = new string[2]; credentials[0] = userPass.Substring(0, separator); credentials[1] = userPass.Substring(separator + 1);  return credentials; }  return new string[] { }; }  private bool AuthenticateUser(string username, string password) { var usernameAndPassword = new UsernameAndPassword { Username = username, Password = password };  if (this.userValidation(usernameAndPassword)) { return true; }  return false; }} This interceptor receives in the constructor a callback in the form of a Func delegate for authenticating the user and the “realm”, which is required as part of the implementation. The rest is a general implementation of the basic authentication mechanism using standard http request and response messages. I also implemented another interceptor for authenticating a SAML token with WIF. public class SamlAuthenticationInterceptor : IAuthenticationInterceptor{ SecurityTokenHandlerCollection handlers = null;  public SamlAuthenticationInterceptor(SecurityTokenHandlerCollection handlers) { if (handlers == null) throw new ArgumentNullException("handlers");  this.handlers = handlers; }  public string Scheme { get { return "saml"; } }  public bool DoAuthentication(HttpRequestMessage request, HttpResponseMessage response, out IPrincipal principal) { SecurityToken token = ExtractCredentials(request);  if (token != null) { ClaimsIdentityCollection claims = handlers.ValidateToken(token);  principal = new ClaimsPrincipal(claims);  return true; } else { response.StatusCode = HttpStatusCode.Unauthorized; response.Content = new StringContent("Access denied");  principal = null;  return false; } }  private SecurityToken ExtractCredentials(HttpRequestMessage request) { if (request.Headers.Authorization != null && request.Headers.Authorization.Scheme == "saml") { XmlTextReader xmlReader = new XmlTextReader(new StringReader(request.Headers.Authorization.Parameter));  var col = SecurityTokenHandlerCollection.CreateDefaultSecurityTokenHandlerCollection(); SecurityToken token = col.ReadToken(xmlReader);  return token; }  return null; }}This implementation receives a “SecurityTokenHandlerCollection” instance as part of the constructor. This class is part of WIF, and basically represents a collection of token managers to know how to handle specific xml authentication tokens (SAML is one of them). I also created a set of extension methods for injecting these interceptors as part of a service route when the service is initialized. var basicAuthentication = new BasicAuthenticationInterceptor((u) => true, "ContactManager");var samlAuthentication = new SamlAuthenticationInterceptor(serviceConfiguration.SecurityTokenHandlers); // use MEF for providing instancesvar catalog = new AssemblyCatalog(typeof(Global).Assembly);var container = new CompositionContainer(catalog);var configuration = new ContactManagerConfiguration(container); RouteTable.Routes.AddServiceRoute<ContactResource>("contact", configuration, basicAuthentication, samlAuthentication);RouteTable.Routes.AddServiceRoute<ContactsResource>("contacts", configuration, basicAuthentication, samlAuthentication); In the code above, I am injecting the basic authentication and saml authentication interceptors in the “contact” and “contacts” resource implementations that come as samples in the code preview. I will use another post to discuss more in detail how the brokered authentication with SAML model works with this new WCF Http bits. The code is available to download in this location.

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  • Java Cloud Service Integration to REST Service

    - by Jani Rautiainen
    Service (JCS) provides a platform to develop and deploy business applications in the cloud. In Fusion Applications Cloud deployments customers do not have the option to deploy custom applications developed with JDeveloper to ensure the integrity and supportability of the hosted application service. Instead the custom applications can be deployed to the JCS and integrated to the Fusion Application Cloud instance. This series of articles will go through the features of JCS, provide end-to-end examples on how to develop and deploy applications on JCS and how to integrate them with the Fusion Applications instance. In this article a custom application integrating with REST service will be implemented. We will use REST services provided by Taleo as an example; however the same approach will work with any REST service. In this example the data from the REST service is used to populate a dynamic table. Pre-requisites Access to Cloud instance In order to deploy the application access to a JCS instance is needed, a free trial JCS instance can be obtained from Oracle Cloud site. To register you will need a credit card even if the credit card will not be charged. To register simply click "Try it" and choose the "Java" option. The confirmation email will contain the connection details. See this video for example of the registration.Once the request is processed you will be assigned 2 service instances; Java and Database. Applications deployed to the JCS must use Oracle Database Cloud Service as their underlying database. So when JCS instance is created a database instance is associated with it using a JDBC data source.The cloud services can be monitored and managed through the web UI. For details refer to Getting Started with Oracle Cloud. JDeveloper JDeveloper contains Cloud specific features related to e.g. connection and deployment. To use these features download the JDeveloper from JDeveloper download site by clicking the "Download JDeveloper 11.1.1.7.1 for ADF deployment on Oracle Cloud" link, this version of JDeveloper will have the JCS integration features that will be used in this article. For versions that do not include the Cloud integration features the Oracle Java Cloud Service SDK or the JCS Java Console can be used for deployment. For details on installing and configuring the JDeveloper refer to the installation guideFor details on SDK refer to Using the Command-Line Interface to Monitor Oracle Java Cloud Service and Using the Command-Line Interface to Manage Oracle Java Cloud Service. Access to a local database The database associated with the JCS instance cannot be connected to with JDBC.  Since creating ADFbc business component requires a JDBC connection we will need access to a local database. 3rd party libraries This example will use some 3rd party libraries for implementing the REST service call and processing the input / output content. Other libraries may also be used, however these are tested to work. Jersey 1.x Jersey library will be used as a client to make the call to the REST service. JCS documentation for supported specifications states: Java API for RESTful Web Services (JAX-RS) 1.1 So Jersey 1.x will be used. Download the single-JAR Jersey bundle; in this example Jersey 1.18 JAR bundle is used. Json-simple Jjson-simple library will be used to process the json objects. Download the  JAR file; in this example json-simple-1.1.1.jar is used. Accessing data in Taleo Before implementing the application it is beneficial to familiarize oneself with the data in Taleo. Easiest way to do this is by using a RESTClient on your browser. Once added to the browser you can access the UI: The client can be used to call the REST services to test the URLs and data before adding them into the application. First derive the base URL for the service this can be done with: Method: GET URL: https://tbe.taleo.net/MANAGER/dispatcher/api/v1/serviceUrl/<company name> The response will contain the base URL to be used for the service calls for the company. Next obtain authentication token with: Method: POST URL: https://ch.tbe.taleo.net/CH07/ats/api/v1/login?orgCode=<company>&userName=<user name>&password=<password> The response includes an authentication token that can be used for few hours to authenticate with the service: {   "response": {     "authToken": "webapi26419680747505890557"   },   "status": {     "detail": {},     "success": true   } } To authenticate the service calls navigate to "Headers -> Custom Header": And add a new request header with: Name: Cookie Value: authToken=webapi26419680747505890557 Once authentication token is defined the tool can be used to invoke REST services; for example: Method: GET URL: https://ch.tbe.taleo.net/CH07/ats/api/v1/object/candidate/search.xml?status=16 This data will be used on the application to be created. For details on the Taleo REST services refer to the Taleo Business Edition REST API Guide. Create Application First Fusion Web Application is created and configured. Start JDeveloper and click "New Application": Application Name: JcsRestDemo Application Package Prefix: oracle.apps.jcs.test Application Template: Fusion Web Application (ADF) Configure Local Cloud Connection Follow the steps documented in the "Java Cloud Service ADF Web Application" article to configure a local database connection needed to create the ADFbc objects. Configure Libraries Add the 3rd party libraries into the class path. Create the following directory and copy the jar files into it: <JDEV_USER_HOME>/JcsRestDemo/lib  Select the "Model" project, navigate "Application -> Project Properties -> Libraries and Classpath -> Add JAR / Directory" and add the 2 3rd party libraries: Accessing Data from Taleo To access data from Taleo using the REST service the 3rd party libraries will be used. 2 Java classes are implemented, one representing the Candidate object and another for accessing the Taleo repository Candidate Candidate object is a POJO object used to represent the candidate data obtained from the Taleo repository. The data obtained will be used to populate the ADFbc object used to display the data on the UI. The candidate object contains simply the variables we obtain using the REST services and the getters / setters for them: Navigate "New -> General -> Java -> Java Class", enter "Candidate" as the name and create it in the package "oracle.apps.jcs.test.model".  Copy / paste the following as the content: import oracle.jbo.domain.Number; public class Candidate { private Number candId; private String firstName; private String lastName; public Candidate() { super(); } public Candidate(Number candId, String firstName, String lastName) { super(); this.candId = candId; this.firstName = firstName; this.lastName = lastName; } public void setCandId(Number candId) { this.candId = candId; } public Number getCandId() { return candId; } public void setFirstName(String firstName) { this.firstName = firstName; } public String getFirstName() { return firstName; } public void setLastName(String lastName) { this.lastName = lastName; } public String getLastName() { return lastName; } } Taleo Repository Taleo repository class will interact with the Taleo REST services. The logic will query data from Taleo and populate Candidate objects with the data. The Candidate object will then be used to populate the ADFbc object used to display data on the UI. Navigate "New -> General -> Java -> Java Class", enter "TaleoRepository" as the name and create it in the package "oracle.apps.jcs.test.model".  Copy / paste the following as the content (for details of the implementation refer to the documentation in the code): import com.sun.jersey.api.client.Client; import com.sun.jersey.api.client.ClientResponse; import com.sun.jersey.api.client.WebResource; import com.sun.jersey.core.util.MultivaluedMapImpl; import java.io.StringReader; import java.util.ArrayList; import java.util.Iterator; import java.util.List; import java.util.Map; import javax.ws.rs.core.MediaType; import javax.ws.rs.core.MultivaluedMap; import oracle.jbo.domain.Number; import org.json.simple.JSONArray; import org.json.simple.JSONObject; import org.json.simple.parser.JSONParser; /** * This class interacts with the Taleo REST services */ public class TaleoRepository { /** * Connection information needed to access the Taleo services */ String _company = null; String _userName = null; String _password = null; /** * Jersey client used to access the REST services */ Client _client = null; /** * Parser for processing the JSON objects used as * input / output for the services */ JSONParser _parser = null; /** * The base url for constructing the REST URLs. This is obtained * from Taleo with a service call */ String _baseUrl = null; /** * Authentication token obtained from Taleo using a service call. * The token can be used to authenticate on subsequent * service calls. The token will expire in 4 hours */ String _authToken = null; /** * Static url that can be used to obtain the url used to construct * service calls for a given company */ private static String _taleoUrl = "https://tbe.taleo.net/MANAGER/dispatcher/api/v1/serviceUrl/"; /** * Default constructor for the repository * Authentication details are passed as parameters and used to generate * authentication token. Note that each service call will * generate its own token. This is done to avoid dealing with the expiry * of the token. Also only 20 tokens are allowed per user simultaneously. * So instead for each call there is login / logout. * * @param company the company for which the service calls are made * @param userName the user name to authenticate with * @param password the password to authenticate with. */ public TaleoRepository(String company, String userName, String password) { super(); _company = company; _userName = userName; _password = password; _client = Client.create(); _parser = new JSONParser(); _baseUrl = getBaseUrl(); } /** * This obtains the base url for a company to be used * to construct the urls for service calls * @return base url for the service calls */ private String getBaseUrl() { String result = null; if (null != _baseUrl) { result = _baseUrl; } else { try { String company = _company; WebResource resource = _client.resource(_taleoUrl + company); ClientResponse response = resource.type(MediaType.APPLICATION_FORM_URLENCODED_TYPE).get(ClientResponse.class); String entity = response.getEntity(String.class); JSONObject jsonObject = (JSONObject)_parser.parse(new StringReader(entity)); JSONObject jsonResponse = (JSONObject)jsonObject.get("response"); result = (String)jsonResponse.get("URL"); } catch (Exception ex) { ex.printStackTrace(); } } return result; } /** * Generates authentication token, that can be used to authenticate on * subsequent service calls. Note that each service call will * generate its own token. This is done to avoid dealing with the expiry * of the token. Also only 20 tokens are allowed per user simultaneously. * So instead for each call there is login / logout. * @return authentication token that can be used to authenticate on * subsequent service calls */ private String login() { String result = null; try { MultivaluedMap<String, String> formData = new MultivaluedMapImpl(); formData.add("orgCode", _company); formData.add("userName", _userName); formData.add("password", _password); WebResource resource = _client.resource(_baseUrl + "login"); ClientResponse response = resource.type(MediaType.APPLICATION_FORM_URLENCODED_TYPE).post(ClientResponse.class, formData); String entity = response.getEntity(String.class); JSONObject jsonObject = (JSONObject)_parser.parse(new StringReader(entity)); JSONObject jsonResponse = (JSONObject)jsonObject.get("response"); result = (String)jsonResponse.get("authToken"); } catch (Exception ex) { throw new RuntimeException("Unable to login ", ex); } if (null == result) throw new RuntimeException("Unable to login "); return result; } /** * Releases a authentication token. Each call to login must be followed * by call to logout after the processing is done. This is required as * the tokens are limited to 20 per user and if not released the tokens * will only expire after 4 hours. * @param authToken */ private void logout(String authToken) { WebResource resource = _client.resource(_baseUrl + "logout"); resource.header("cookie", "authToken=" + authToken).post(ClientResponse.class); } /** * This method is used to obtain a list of candidates using a REST * service call. At this example the query is hard coded to query * based on status. The url constructed to access the service is: * <_baseUrl>/object/candidate/search.xml?status=16 * @return List of candidates obtained with the service call */ public List<Candidate> getCandidates() { List<Candidate> result = new ArrayList<Candidate>(); try { // First login, note that in finally block we must have logout _authToken = "authToken=" + login(); /** * Construct the URL, the resulting url will be: * <_baseUrl>/object/candidate/search.xml?status=16 */ MultivaluedMap<String, String> formData = new MultivaluedMapImpl(); formData.add("status", "16"); JSONArray searchResults = (JSONArray)getTaleoResource("object/candidate/search", "searchResults", formData); /** * Process the results, the resulting JSON object is something like * this (simplified for readability): * * { * "response": * { * "searchResults": * [ * { * "candidate": * { * "candId": 211, * "firstName": "Mary", * "lastName": "Stochi", * logic here will find the candidate object(s), obtain the desired * data from them, construct a Candidate object based on the data * and add it to the results. */ for (Object object : searchResults) { JSONObject temp = (JSONObject)object; JSONObject candidate = (JSONObject)findObject(temp, "candidate"); Long candIdTemp = (Long)candidate.get("candId"); Number candId = (null == candIdTemp ? null : new Number(candIdTemp)); String firstName = (String)candidate.get("firstName"); String lastName = (String)candidate.get("lastName"); result.add(new Candidate(candId, firstName, lastName)); } } catch (Exception ex) { ex.printStackTrace(); } finally { if (null != _authToken) logout(_authToken); } return result; } /** * Convenience method to construct url for the service call, invoke the * service and obtain a resource from the response * @param path the path for the service to be invoked. This is combined * with the base url to construct a url for the service * @param resource the key for the object in the response that will be * obtained * @param parameters any parameters used for the service call. The call * is slightly different depending whether parameters exist or not. * @return the resource from the response for the service call */ private Object getTaleoResource(String path, String resource, MultivaluedMap<String, String> parameters) { Object result = null; try { WebResource webResource = _client.resource(_baseUrl + path); ClientResponse response = null; if (null == parameters) response = webResource.header("cookie", _authToken).get(ClientResponse.class); else response = webResource.queryParams(parameters).header("cookie", _authToken).get(ClientResponse.class); String entity = response.getEntity(String.class); JSONObject jsonObject = (JSONObject)_parser.parse(new StringReader(entity)); result = findObject(jsonObject, resource); } catch (Exception ex) { ex.printStackTrace(); } return result; } /** * Convenience method to recursively find a object with an key * traversing down from a given root object. This will traverse a * JSONObject / JSONArray recursively to find a matching key, if found * the object with the key is returned. * @param root root object which contains the key searched for * @param key the key for the object to search for * @return the object matching the key */ private Object findObject(Object root, String key) { Object result = null; if (root instanceof JSONObject) { JSONObject rootJSON = (JSONObject)root; if (rootJSON.containsKey(key)) { result = rootJSON.get(key); } else { Iterator children = rootJSON.entrySet().iterator(); while (children.hasNext()) { Map.Entry entry = (Map.Entry)children.next(); Object child = entry.getValue(); if (child instanceof JSONObject || child instanceof JSONArray) { result = findObject(child, key); if (null != result) break; } } } } else if (root instanceof JSONArray) { JSONArray rootJSON = (JSONArray)root; for (Object child : rootJSON) { if (child instanceof JSONObject || child instanceof JSONArray) { result = findObject(child, key); if (null != result) break; } } } return result; } }   Creating Business Objects While JCS application can be created without a local database, the local database is required when using ADFbc objects even if database objects are not referred. For this example we will create a "Transient" view object that will be programmatically populated based the data obtained from Taleo REST services. Creating ADFbc objects Choose the "Model" project and navigate "New -> Business Tier : ADF Business Components : View Object". On the "Initialize Business Components Project" choose the local database connection created in previous step. On Step 1 enter "JcsRestDemoVO" on the "Name" and choose "Rows populated programmatically, not based on query": On step 2 create the following attributes: CandId Type: Number Updatable: Always Key Attribute: checked Name Type: String Updatable: Always On steps 3 and 4 accept defaults and click "Next".  On step 5 check the "Application Module" checkbox and enter "JcsRestDemoAM" as the name: Click "Finish" to generate the objects. Populating the VO To display the data on the UI the "transient VO" is populated programmatically based on the data obtained from the Taleo REST services. Open the "JcsRestDemoVOImpl.java". Copy / paste the following as the content (for details of the implementation refer to the documentation in the code): import java.sql.ResultSet; import java.util.List; import java.util.ListIterator; import oracle.jbo.server.ViewObjectImpl; import oracle.jbo.server.ViewRowImpl; import oracle.jbo.server.ViewRowSetImpl; // --------------------------------------------------------------------- // --- File generated by Oracle ADF Business Components Design Time. // --- Tue Feb 18 09:40:25 PST 2014 // --- Custom code may be added to this class. // --- Warning: Do not modify method signatures of generated methods. // --------------------------------------------------------------------- public class JcsRestDemoVOImpl extends ViewObjectImpl { /** * This is the default constructor (do not remove). */ public JcsRestDemoVOImpl() { } @Override public void executeQuery() { /** * For some reason we need to reset everything, otherwise * 2nd entry to the UI screen may fail with * "java.util.NoSuchElementException" in createRowFromResultSet * call to "candidates.next()". I am not sure why this is happening * as the Iterator is new and "hasNext" is true at the point * of the execution. My theory is that since the iterator object is * exactly the same the VO cache somehow reuses the iterator including * the pointer that has already exhausted the iterable elements on the * previous run. Working around the issue * here by cleaning out everything on the VO every time before query * is executed on the VO. */ getViewDef().setQuery(null); getViewDef().setSelectClause(null); setQuery(null); this.reset(); this.clearCache(); super.executeQuery(); } /** * executeQueryForCollection - overridden for custom java data source support. */ protected void executeQueryForCollection(Object qc, Object[] params, int noUserParams) { /** * Integrate with the Taleo REST services using TaleoRepository class. * A list of candidates matching a hard coded query is obtained. */ TaleoRepository repository = new TaleoRepository(<company>, <username>, <password>); List<Candidate> candidates = repository.getCandidates(); /** * Store iterator for the candidates as user data on the collection. * This will be used in createRowFromResultSet to create rows based on * the custom iterator. */ ListIterator<Candidate> candidatescIterator = candidates.listIterator(); setUserDataForCollection(qc, candidatescIterator); super.executeQueryForCollection(qc, params, noUserParams); } /** * hasNextForCollection - overridden for custom java data source support. */ protected boolean hasNextForCollection(Object qc) { boolean result = false; /** * Determines whether there are candidates for which to create a row */ ListIterator<Candidate> candidates = (ListIterator<Candidate>)getUserDataForCollection(qc); result = candidates.hasNext(); /** * If all candidates to be created indicate that processing is done */ if (!result) { setFetchCompleteForCollection(qc, true); } return result; } /** * createRowFromResultSet - overridden for custom java data source support. */ protected ViewRowImpl createRowFromResultSet(Object qc, ResultSet resultSet) { /** * Obtain the next candidate from the collection and create a row * for it. */ ListIterator<Candidate> candidates = (ListIterator<Candidate>)getUserDataForCollection(qc); ViewRowImpl row = createNewRowForCollection(qc); try { Candidate candidate = candidates.next(); row.setAttribute("CandId", candidate.getCandId()); row.setAttribute("Name", candidate.getFirstName() + " " + candidate.getLastName()); } catch (Exception e) { e.printStackTrace(); } return row; } /** * getQueryHitCount - overridden for custom java data source support. */ public long getQueryHitCount(ViewRowSetImpl viewRowSet) { /** * For this example this is not implemented rather we always return 0. */ return 0; } } Creating UI Choose the "ViewController" project and navigate "New -> Web Tier : JSF : JSF Page". On the "Create JSF Page" enter "JcsRestDemo" as name and ensure that the "Create as XML document (*.jspx)" is checked.  Open "JcsRestDemo.jspx" and navigate to "Data Controls -> JcsRestDemoAMDataControl -> JcsRestDemoVO1" and drag & drop the VO to the "<af:form> " as a "ADF Read-only Table": Accept the defaults in "Edit Table Columns". To execute the query navigate to to "Data Controls -> JcsRestDemoAMDataControl -> JcsRestDemoVO1 -> Operations -> Execute" and drag & drop the operation to the "<af:form> " as a "Button": Deploying to JCS Follow the same steps as documented in previous article"Java Cloud Service ADF Web Application". Once deployed the application can be accessed with URL: https://java-[identity domain].java.[data center].oraclecloudapps.com/JcsRestDemo-ViewController-context-root/faces/JcsRestDemo.jspx The UI displays a list of candidates obtained from the Taleo REST Services: Summary In this article we learned how to integrate with REST services using Jersey library in JCS. In future articles various other integration techniques will be covered.

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  • How to create a simple adf dashboard application with EJB 3.0

    - by Rodrigues, Raphael
    In this month's Oracle Magazine, Frank Nimphius wrote a very good article about an Oracle ADF Faces dashboard application to support persistent user personalization. You can read this entire article clicking here. The idea in this article is to extend the dashboard application. My idea here is to create a similar dashboard application, but instead ADF BC model layer, I'm intending to use EJB3.0. There are just a one small trick here and I'll show you. I'm using the HR usual oracle schema. The steps are: 1. Create a ADF Fusion Application with EJB as a layer model 2. Generate the entities from table (I'm using Department and Employees only) 3. Create a new Session Bean. I called it: HRSessionEJB 4. Create a new method like that: public List getAllDepartmentsHavingEmployees(){ JpaEntityManager jpaEntityManager = (JpaEntityManager)em.getDelegate(); Query query = jpaEntityManager.createNamedQuery("Departments.allDepartmentsHavingEmployees"); JavaBeanResult.setQueryResultClass(query, AggregatedDepartment.class); return query.getResultList(); } 5. In the Departments entity, create a new native query annotation: @Entity @NamedQueries( { @NamedQuery(name = "Departments.findAll", query = "select o from Departments o") }) @NamedNativeQueries({ @NamedNativeQuery(name="Departments.allDepartmentsHavingEmployees", query = "select e.department_id, d.department_name , sum(e.salary), avg(e.salary) , max(e.salary), min(e.salary) from departments d , employees e where d.department_id = e.department_id group by e.department_id, d.department_name")}) public class Departments implements Serializable {...} 6. Create a new POJO called AggregatedDepartment: package oramag.sample.dashboard.model; import java.io.Serializable; import java.math.BigDecimal; public class AggregatedDepartment implements Serializable{ @SuppressWarnings("compatibility:5167698678781240729") private static final long serialVersionUID = 1L; private BigDecimal departmentId; private String departmentName; private BigDecimal sum; private BigDecimal avg; private BigDecimal max; private BigDecimal min; public AggregatedDepartment() { super(); } public AggregatedDepartment(BigDecimal departmentId, String departmentName, BigDecimal sum, BigDecimal avg, BigDecimal max, BigDecimal min) { super(); this.departmentId = departmentId; this.departmentName = departmentName; this.sum = sum; this.avg = avg; this.max = max; this.min = min; } public void setDepartmentId(BigDecimal departmentId) { this.departmentId = departmentId; } public BigDecimal getDepartmentId() { return departmentId; } public void setDepartmentName(String departmentName) { this.departmentName = departmentName; } public String getDepartmentName() { return departmentName; } public void setSum(BigDecimal sum) { this.sum = sum; } public BigDecimal getSum() { return sum; } public void setAvg(BigDecimal avg) { this.avg = avg; } public BigDecimal getAvg() { return avg; } public void setMax(BigDecimal max) { this.max = max; } public BigDecimal getMax() { return max; } public void setMin(BigDecimal min) { this.min = min; } public BigDecimal getMin() { return min; } } 7. Create the util java class called JavaBeanResult. The function of this class is to configure a native SQL query to return POJOs in a single line of code using the utility class. Credits: http://onpersistence.blogspot.com.br/2010/07/eclipselink-jpa-native-constructor.html package oramag.sample.dashboard.model.util; /******************************************************************************* * Copyright (c) 2010 Oracle. All rights reserved. * This program and the accompanying materials are made available under the * terms of the Eclipse Public License v1.0 and Eclipse Distribution License v. 1.0 * which accompanies this distribution. * The Eclipse Public License is available at http://www.eclipse.org/legal/epl-v10.html * and the Eclipse Distribution License is available at * http://www.eclipse.org/org/documents/edl-v10.php. * * @author shsmith ******************************************************************************/ import java.lang.reflect.Constructor; import java.lang.reflect.InvocationTargetException; import java.util.ArrayList; import java.util.List; import javax.persistence.Query; import org.eclipse.persistence.exceptions.ConversionException; import org.eclipse.persistence.internal.helper.ConversionManager; import org.eclipse.persistence.internal.sessions.AbstractRecord; import org.eclipse.persistence.internal.sessions.AbstractSession; import org.eclipse.persistence.jpa.JpaHelper; import org.eclipse.persistence.queries.DatabaseQuery; import org.eclipse.persistence.queries.QueryRedirector; import org.eclipse.persistence.sessions.Record; import org.eclipse.persistence.sessions.Session; /*** * This class is a simple query redirector that intercepts the result of a * native query and builds an instance of the specified JavaBean class from each * result row. The order of the selected columns musts match the JavaBean class * constructor arguments order. * * To configure a JavaBeanResult on a native SQL query use: * JavaBeanResult.setQueryResultClass(query, SomeBeanClass.class); * where query is either a JPA SQL Query or native EclipseLink DatabaseQuery. * * @author shsmith * */ public final class JavaBeanResult implements QueryRedirector { private static final long serialVersionUID = 3025874987115503731L; protected Class resultClass; public static void setQueryResultClass(Query query, Class resultClass) { JavaBeanResult javaBeanResult = new JavaBeanResult(resultClass); DatabaseQuery databaseQuery = JpaHelper.getDatabaseQuery(query); databaseQuery.setRedirector(javaBeanResult); } public static void setQueryResultClass(DatabaseQuery query, Class resultClass) { JavaBeanResult javaBeanResult = new JavaBeanResult(resultClass); query.setRedirector(javaBeanResult); } protected JavaBeanResult(Class resultClass) { this.resultClass = resultClass; } @SuppressWarnings("unchecked") public Object invokeQuery(DatabaseQuery query, Record arguments, Session session) { List results = new ArrayList(); try { Constructor[] constructors = resultClass.getDeclaredConstructors(); Constructor javaBeanClassConstructor = null; // (Constructor) resultClass.getDeclaredConstructors()[0]; Class[] constructorParameterTypes = null; // javaBeanClassConstructor.getParameterTypes(); List rows = (List) query.execute( (AbstractSession) session, (AbstractRecord) arguments); for (Object[] columns : rows) { boolean found = false; for (Constructor constructor : constructors) { javaBeanClassConstructor = constructor; constructorParameterTypes = javaBeanClassConstructor.getParameterTypes(); if (columns.length == constructorParameterTypes.length) { found = true; break; } // if (columns.length != constructorParameterTypes.length) { // throw new ColumnParameterNumberMismatchException( // resultClass); // } } if (!found) throw new ColumnParameterNumberMismatchException( resultClass); Object[] constructorArgs = new Object[constructorParameterTypes.length]; for (int j = 0; j < columns.length; j++) { Object columnValue = columns[j]; Class parameterType = constructorParameterTypes[j]; // convert the column value to the correct type--if possible constructorArgs[j] = ConversionManager.getDefaultManager() .convertObject(columnValue, parameterType); } results.add(javaBeanClassConstructor.newInstance(constructorArgs)); } } catch (ConversionException e) { throw new ColumnParameterMismatchException(e); } catch (IllegalArgumentException e) { throw new ColumnParameterMismatchException(e); } catch (InstantiationException e) { throw new ColumnParameterMismatchException(e); } catch (IllegalAccessException e) { throw new ColumnParameterMismatchException(e); } catch (InvocationTargetException e) { throw new ColumnParameterMismatchException(e); } return results; } public final class ColumnParameterMismatchException extends RuntimeException { private static final long serialVersionUID = 4752000720859502868L; public ColumnParameterMismatchException(Throwable t) { super( "Exception while processing query results-ensure column order matches constructor parameter order", t); } } public final class ColumnParameterNumberMismatchException extends RuntimeException { private static final long serialVersionUID = 1776794744797667755L; public ColumnParameterNumberMismatchException(Class clazz) { super( "Number of selected columns does not match number of constructor arguments for: " + clazz.getName()); } } } 8. Create the DataControl and a jsf or jspx page 9. Drag allDepartmentsHavingEmployees from DataControl and drop in your page 10. Choose Graph > Type: Bar (Normal) > any layout 11. In the wizard screen, Bars label, adds: sum, avg, max, min. In the X Axis label, adds: departmentName, and click in OK button 12. Run the page, the result is showed below: You can download the workspace here . It was using the latest jdeveloper version 11.1.2.2.

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  • SQL SERVER – SSMS: Disk Usage Report

    - by Pinal Dave
    Let us start with humor!  I think we the series on various reports, we come to a logical point. We covered all the reports at server level. This means the reports we saw were targeted towards activities that are related to instance level operations. These are mostly like how a doctor diagnoses a patient. At this point I am reminded of a dialog which I read somewhere: Patient: Doc, It hurts when I touch my head. Doc: Ok, go on. What else have you experienced? Patient: It hurts even when I touch my eye, it hurts when I touch my arms, it even hurts when I touch my feet, etc. Doc: Hmmm … Patient: I feel it hurts when I touch anywhere in my body. Doc: Ahh … now I get it. You need a plaster to your finger John. Sometimes the server level gives an indicator to what is happening in the system, but we need to get to the root cause for a specific database. So, this is the first blog in series where we would start discussing about database level reports. To launch database level reports, expand selected server in Object Explorer, expand the Databases folder, and then right-click any database for which we want to look at reports. From the menu, select Reports, then Standard Reports, and then any of database level reports. In this blog, we would talk about four “disk” reports because they are similar: Disk Usage Disk Usage by Top Tables Disk Usage by Table Disk Usage by Partition Disk Usage This report shows multiple information about the database. Let us discuss them one by one.  We have divided the output into 5 different sections. Section 1 shows the high level summary of the database. It shows the space used by database files (mdf and ldf). Under the hood, the report uses, various DMVs and DBCC Commands, it is using sys.data_spaces and DBCC SHOWFILESTATS. Section 2 and 3 are pie charts. One for data file allocation and another for the transaction log file. Pie chart for “Data Files Space Usage (%)” shows space consumed data, indexes, allocated to the SQL Server database, and unallocated space which is allocated to the SQL Server database but not yet filled with anything. “Transaction Log Space Usage (%)” used DBCC SQLPERF (LOGSPACE) and shows how much empty space we have in the physical transaction log file. Section 4 shows the data from Default Trace and looks at Event IDs 92, 93, 94, 95 which are for “Data File Auto Grow”, “Log File Auto Grow”, “Data File Auto Shrink” and “Log File Auto Shrink” respectively. Here is an expanded view for that section. If default trace is not enabled, then this section would be replaced by the message “Trace Log is disabled” as highlighted below. Section 5 of the report uses DBCC SHOWFILESTATS to get information. Here is the enhanced version of that section. This shows the physical layout of the file. In case you have In-Memory Objects in the database (from SQL Server 2014), then report would show information about those as well. Here is the screenshot taken for a different database, which has In-Memory table. I have highlighted new things which are only shown for in-memory database. The new sections which are highlighted above are using sys.dm_db_xtp_checkpoint_files, sys.database_files and sys.data_spaces. The new type for in-memory OLTP is ‘FX’ in sys.data_space. The next set of reports is targeted to get information about a table and its storage. These reports can answer questions like: Which is the biggest table in the database? How many rows we have in table? Is there any table which has a lot of reserved space but its unused? Which partition of the table is having more data? Disk Usage by Top Tables This report provides detailed data on the utilization of disk space by top 1000 tables within the Database. The report does not provide data for memory optimized tables. Disk Usage by Table This report is same as earlier report with few difference. First Report shows only 1000 rows First Report does order by values in DMV sys.dm_db_partition_stats whereas second one does it based on name of the table. Both of the reports have interactive sort facility. We can click on any column header and change the sorting order of data. Disk Usage by Partition This report shows the distribution of the data in table based on partition in the table. This is so similar to previous output with the partition details now. Here is the query taken from profiler. SELECT row_number() OVER (ORDER BY a1.used_page_count DESC, a1.index_id) AS row_number ,      (dense_rank() OVER (ORDER BY a5.name, a2.name))%2 AS l1 ,      a1.OBJECT_ID ,      a5.name AS [schema] ,       a2.name ,       a1.index_id ,       a3.name AS index_name ,       a3.type_desc ,       a1.partition_number ,       a1.used_page_count * 8 AS total_used_pages ,       a1.reserved_page_count * 8 AS total_reserved_pages ,       a1.row_count FROM sys.dm_db_partition_stats a1 INNER JOIN sys.all_objects a2  ON ( a1.OBJECT_ID = a2.OBJECT_ID) AND a1.OBJECT_ID NOT IN (SELECT OBJECT_ID FROM sys.tables WHERE is_memory_optimized = 1) INNER JOIN sys.schemas a5 ON (a5.schema_id = a2.schema_id) LEFT OUTER JOIN  sys.indexes a3  ON ( (a1.OBJECT_ID = a3.OBJECT_ID) AND (a1.index_id = a3.index_id) ) WHERE (SELECT MAX(DISTINCT partition_number) FROM sys.dm_db_partition_stats a4 WHERE (a4.OBJECT_ID = a1.OBJECT_ID)) >= 1 AND a2.TYPE <> N'S' AND  a2.TYPE <> N'IT' ORDER BY a5.name ASC, a2.name ASC, a1.index_id, a1.used_page_count DESC, a1.partition_number Using all of the above reports, you should be able to get the usage of database files and also space used by tables. I think this is too much disk information for a single blog and I hope you have used them in the past to get data. Do let me know if you found anything interesting using these reports in your environments. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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  • New Feature in ODI 11.1.1.6: ODI for Big Data

    - by Julien Testut
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} By Ananth Tirupattur Starting with Oracle Data Integrator 11.1.1.6.0, ODI is offering a solution to process Big Data. This post provides an overview of this feature. With all the buzz around Big Data and before getting into the details of ODI for Big Data, I will provide a brief introduction to Big Data and Oracle Solution for Big Data. So, what is Big Data? Big data includes: structured data (this includes data from relation data stores, xml data stores), semi-structured data (this includes data from weblogs) unstructured data (this includes data from text blob, images) Traditionally, business decisions are based on the information gathered from transactional data. For example, transactional Data from CRM applications is fed to a decision system for analysis and decision making. Products such as ODI play a key role in enabling decision systems. However, with the emergence of massive amounts of semi-structured and unstructured data it is important for decision system to include them in the analysis to achieve better decision making capability. While there is an abundance of opportunities for business for gaining competitive advantages, process of Big Data has challenges. The challenges of processing Big Data include: Volume of data Velocity of data - The high Rate at which data is generated Variety of data In order to address these challenges and convert them into opportunities, we would need an appropriate framework, platform and the right set of tools. Hadoop is an open source framework which is highly scalable, fault tolerant system, for storage and processing large amounts of data. Hadoop provides 2 key services, distributed and reliable storage called Hadoop Distributed File System or HDFS and a framework for parallel data processing called Map-Reduce. Innovations in Hadoop and its related technology continue to rapidly evolve, hence therefore, it is highly recommended to follow information on the web to keep up with latest information. Oracle's vision is to provide a comprehensive solution to address the challenges faced by Big Data. Oracle is providing the necessary Hardware, software and tools for processing Big Data Oracle solution includes: Big Data Appliance Oracle NoSQL Database Cloudera distribution for Hadoop Oracle R Enterprise- R is a statistical package which is very popular among data scientists. ODI solution for Big Data Oracle Loader for Hadoop for loading data from Hadoop to Oracle. Further details can be found here: http://www.oracle.com/us/products/database/big-data-appliance/overview/index.html ODI Solution for Big Data: ODI’s goal is to minimize the need to understand the complexity of Hadoop framework and simplify the adoption of processing Big Data seamlessly in an enterprise. ODI is providing the capabilities for an integrated architecture for processing Big Data. This includes capability to load data in to Hadoop, process data in Hadoop and load data from Hadoop into Oracle. ODI is expanding its support for Big Data by providing the following out of the box Knowledge Modules (KMs). IKM File to Hive (LOAD DATA).Load unstructured data from File (Local file system or HDFS ) into Hive IKM Hive Control AppendTransform and validate structured data on Hive IKM Hive TransformTransform unstructured data on Hive IKM File/Hive to Oracle (OLH)Load processed data in Hive to Oracle RKM HiveReverse engineer Hive tables to generate models Using the Loading KM you can map files (local and HDFS files) to the corresponding Hive tables. For example, you can map weblog files categorized by date into a corresponding partitioned Hive table schema. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Using the Hive control Append KM you can validate and transform data in Hive. In the below example, two source Hive tables are joined and mapped to a target Hive table. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} The Hive Transform KM facilitates processing of semi-structured data in Hive. In the below example, the data from weblog is processed using a Perl script and mapped to target Hive table. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Using the Oracle Loader for Hadoop (OLH) KM you can load data from Hive table or HDFS to a corresponding table in Oracle. OLH is available as a standalone product. ODI greatly enhances OLH capability by generating the configuration and mapping files for OLH based on the configuration provided in the interface and KM options. ODI seamlessly invokes OLH when executing the scenario. In the below example, a HDFS file is mapped to a table in Oracle. Development and Deployment:The following diagram illustrates the development and deployment of ODI solution for Big Data. Using the ODI Studio on your development machine create and develop ODI solution for processing Big Data by connecting to a MySQL DB or Oracle database on a BDA machine or Hadoop cluster. Schedule the ODI scenarios to be executed on the ODI agent deployed on the BDA machine or Hadoop cluster. ODI Solution for Big Data provides several exciting new capabilities to facilitate the adoption of Big Data in an enterprise. You can find more information about the Oracle Big Data connectors on OTN. You can find an overview of all the new features introduced in ODI 11.1.1.6 in the following document: ODI 11.1.1.6 New Features Overview

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  • SQL SERVER – Faster SQL Server Databases and Applications – Power and Control with SafePeak Caching Options

    - by Pinal Dave
    Update: This blog post is written based on the SafePeak, which is available for free download. Today, I’d like to examine more closely one of my preferred technologies for accelerating SQL Server databases, SafePeak. Safepeak’s software provides a variety of advanced data caching options, techniques and tools to accelerate the performance and scalability of SQL Server databases and applications. I’d like to look more closely at some of these options, as some of these capabilities could help you address lagging database and performance on your systems. To better understand the available options, it is best to start by understanding the difference between the usual “Basic Caching” vs. SafePeak’s “Dynamic Caching”. Basic Caching Basic Caching (or the stale and static cache) is an ability to put the results from a query into cache for a certain period of time. It is based on TTL, or Time-to-live, and is designed to stay in cache no matter what happens to the data. For example, although the actual data can be modified due to DML commands (update/insert/delete), the cache will still hold the same obsolete query data. Meaning that with the Basic Caching is really static / stale cache.  As you can tell, this approach has its limitations. Dynamic Caching Dynamic Caching (or the non-stale cache) is an ability to put the results from a query into cache while maintaining the cache transaction awareness looking for possible data modifications. The modifications can come as a result of: DML commands (update/insert/delete), indirect modifications due to triggers on other tables, executions of stored procedures with internal DML commands complex cases of stored procedures with multiple levels of internal stored procedures logic. When data modification commands arrive, the caching system identifies the related cache items and evicts them from cache immediately. In the dynamic caching option the TTL setting still exists, although its importance is reduced, since the main factor for cache invalidation (or cache eviction) become the actual data updates commands. Now that we have a basic understanding of the differences between “basic” and “dynamic” caching, let’s dive in deeper. SafePeak: A comprehensive and versatile caching platform SafePeak comes with a wide range of caching options. Some of SafePeak’s caching options are automated, while others require manual configuration. Together they provide a complete solution for IT and Data managers to reach excellent performance acceleration and application scalability for  a wide range of business cases and applications. Automated caching of SQL Queries: Fully/semi-automated caching of all “read” SQL queries, containing any types of data, including Blobs, XMLs, Texts as well as all other standard data types. SafePeak automatically analyzes the incoming queries, categorizes them into SQL Patterns, identifying directly and indirectly accessed tables, views, functions and stored procedures; Automated caching of Stored Procedures: Fully or semi-automated caching of all read” stored procedures, including procedures with complex sub-procedure logic as well as procedures with complex dynamic SQL code. All procedures are analyzed in advance by SafePeak’s  Metadata-Learning process, their SQL schemas are parsed – resulting with a full understanding of the underlying code, objects dependencies (tables, views, functions, sub-procedures) enabling automated or semi-automated (manually review and activate by a mouse-click) cache activation, with full understanding of the transaction logic for cache real-time invalidation; Transaction aware cache: Automated cache awareness for SQL transactions (SQL and in-procs); Dynamic SQL Caching: Procedures with dynamic SQL are pre-parsed, enabling easy cache configuration, eliminating SQL Server load for parsing time and delivering high response time value even in most complicated use-cases; Fully Automated Caching: SQL Patterns (including SQL queries and stored procedures) that are categorized by SafePeak as “read and deterministic” are automatically activated for caching; Semi-Automated Caching: SQL Patterns categorized as “Read and Non deterministic” are patterns of SQL queries and stored procedures that contain reference to non-deterministic functions, like getdate(). Such SQL Patterns are reviewed by the SafePeak administrator and in usually most of them are activated manually for caching (point and click activation); Fully Dynamic Caching: Automated detection of all dependent tables in each SQL Pattern, with automated real-time eviction of the relevant cache items in the event of “write” commands (a DML or a stored procedure) to one of relevant tables. A default setting; Semi Dynamic Caching: A manual cache configuration option enabling reducing the sensitivity of specific SQL Patterns to “write” commands to certain tables/views. An optimization technique relevant for cases when the query data is either known to be static (like archive order details), or when the application sensitivity to fresh data is not critical and can be stale for short period of time (gaining better performance and reduced load); Scheduled Cache Eviction: A manual cache configuration option enabling scheduling SQL Pattern cache eviction based on certain time(s) during a day. A very useful optimization technique when (for example) certain SQL Patterns can be cached but are time sensitive. Example: “select customers that today is their birthday”, an SQL with getdate() function, which can and should be cached, but the data stays relevant only until 00:00 (midnight); Parsing Exceptions Management: Stored procedures that were not fully parsed by SafePeak (due to too complex dynamic SQL or unfamiliar syntax), are signed as “Dynamic Objects” with highest transaction safety settings (such as: Full global cache eviction, DDL Check = lock cache and check for schema changes, and more). The SafePeak solution points the user to the Dynamic Objects that are important for cache effectiveness, provides easy configuration interface, allowing you to improve cache hits and reduce cache global evictions. Usually this is the first configuration in a deployment; Overriding Settings of Stored Procedures: Override the settings of stored procedures (or other object types) for cache optimization. For example, in case a stored procedure SP1 has an “insert” into table T1, it will not be allowed to be cached. However, it is possible that T1 is just a “logging or instrumentation” table left by developers. By overriding the settings a user can allow caching of the problematic stored procedure; Advanced Cache Warm-Up: Creating an XML-based list of queries and stored procedure (with lists of parameters) for periodically automated pre-fetching and caching. An advanced tool allowing you to handle more rare but very performance sensitive queries pre-fetch them into cache allowing high performance for users’ data access; Configuration Driven by Deep SQL Analytics: All SQL queries are continuously logged and analyzed, providing users with deep SQL Analytics and Performance Monitoring. Reduce troubleshooting from days to minutes with database objects and SQL Patterns heat-map. The performance driven configuration helps you to focus on the most important settings that bring you the highest performance gains. Use of SafePeak SQL Analytics allows continuous performance monitoring and analysis, easy identification of bottlenecks of both real-time and historical data; Cloud Ready: Available for instant deployment on Amazon Web Services (AWS). As you can see, there are many options to configure SafePeak’s SQL Server database and application acceleration caching technology to best fit a lot of situations. If you’re not familiar with their technology, they offer free-trial software you can download that comes with a free “help session” to help get you started. You can access the free trial here. Also, SafePeak is available to use on Amazon Cloud. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Weekly Series – Memory Lane – #052

    - by Pinal Dave
    Let us continue with the final episode of the Memory Lane Series. Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Set Server Level FILLFACTOR Using T-SQL Script Specifies a percentage that indicates how full the Database Engine should make the leaf level of each index page during index creation or alteration. fillfactor must be an integer value from 1 to 100. The default is 0. Limitation of Online Index Rebuld Operation Online operation means when online operations are happening in the database are in normal operational condition, the processes which are participating in online operations does not require exclusive access to the database. Get Permissions of My Username / Userlogin on Server / Database A few days ago, I was invited to one of the largest database company. I was asked to review database schema and propose changes to it. There was special username or user logic was created for me, so I can review their database. I was very much interested to know what kind of permissions I was assigned per server level and database level. I did not feel like asking Sr. DBA the question about permissions. Simple Example of WHILE Loop With CONTINUE and BREAK Keywords This question is one of those questions which is very simple and most of the users get it correct, however few users find it confusing for the first time. I have tried to explain the usage of simple WHILE loop in the first example. BREAK keyword will exit the stop the while loop and control is moved to the next statement after the while loop. CONTINUE keyword skips all the statement after its execution and control is sent to the first statement of while loop. Forced Parameterization and Simple Parameterization – T-SQL and SSMS When the PARAMETERIZATION option is set to FORCED, any literal value that appears in a SELECT, INSERT, UPDATE or DELETE statement is converted to a parameter during query compilation. When the PARAMETERIZATION database option is SET to SIMPLE, the SQL Server query optimizer may choose to parameterize the queries. 2008 Transaction and Local Variables – Swap Variables – Update All At Once Concept Summary : Transaction have no effect over memory variables. When UPDATE statement is applied over any table (physical or memory) all the updates are applied at one time together when the statement is committed. First of all I suggest that you read the article listed above about the effect of transaction on local variant. As seen there local variables are independent of any transaction effect. Simulate INNER JOIN using LEFT JOIN statement – Performance Analysis Just a day ago, while I was working with JOINs I find one interesting observation, which has prompted me to create following example. Before we continue further let me make very clear that INNER JOIN should be used where it cannot be used and simulating INNER JOIN using any other JOINs will degrade the performance. If there are scopes to convert any OUTER JOIN to INNER JOIN it should be done with priority. 2009 Introduction to Business Intelligence – Important Terms & Definitions Business intelligence (BI) is a broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data from various data sources, thus providing enterprise users with reliable and timely information and analysis for improved decision making. Difference Between Candidate Keys and Primary Key Candidate Key – A Candidate Key can be any column or a combination of columns that can qualify as unique key in database. There can be multiple Candidate Keys in one table. Each Candidate Key can qualify as Primary Key. Primary Key – A Primary Key is a column or a combination of columns that uniquely identify a record. Only one Candidate Key can be Primary Key. 2010 Taking Multiple Backup of Database in Single Command – Mirrored Database Backup I recently had a very interesting experience. In one of my recent consultancy works, I was told by our client that they are going to take the backup of the database and will also a copy of it at the same time. I expressed that it was surely possible if they were going to use a mirror command. In addition, they told me that whenever they take two copies of the database, the size of the database, is always reduced. Now this was something not clear to me, I said it was not possible and so I asked them to show me the script. Corrupted Backup File and Unsuccessful Restore The CTO, who was also present at the location, got very upset with this situation. He then asked when the last successful restore test was done. As expected, the answer was NEVER.There were no successful restore tests done before. During that time, I was present and I could clearly see the stress, confusion, carelessness and anger around me. I did not appreciate the feeling and I was pretty sure that no one in there wanted the atmosphere like me. 2011 TRACEWRITE – Wait Type – Wait Related to Buffer and Resolution SQL Trace is a SQL Server database engine technology which monitors specific events generated when various actions occur in the database engine. When any event is fired it goes through various stages as well various routes. One of the routes is Trace I/O Provider, which sends data to its final destination either as a file or rowset. DATEDIFF – Accuracy of Various Dateparts If you want to have accuracy in seconds, you need to use a different approach. In the first example, the accurate method is to find the number of seconds first and then divide it by 60 to convert it in minutes. Dedicated Access Control for SQL Server Express Edition http://www.youtube.com/watch?v=1k00z82u4OI Book Signing at SQLPASS 2012 Who I Am And How I Got Here – True Story as Blog Post If there was a shortcut to success – I want to know. I learnt SQL Server hard way and I am still learning. There are so many things, I have to learn. There is not enough time to learn everything which we want to learn. I am constantly working on it every day. I welcome you to join my journey as well. Please join me in my journey to learn SQL Server – more the merrier. Vacation, Travel and Study – A New Concept Even those who have advanced degrees and went to college for years, or even decades, find studying hard.  There is a difference between studying for a career and studying for a certification.  At least to get a degree there is a variety of subjects, with labs, exams, and practice problems to make things more interesting. Order By Numeric Values Formatted as String We have a table which has a column containing alphanumeric data. The data always has first as an integer and later part as a string. The business need is to order the data based on the first part of the alphanumeric data which is an integer. Now the problem is that no matter how we use ORDER BY the result is not produced as expected. Let us understand this with an example. Resolving SQL Server Connection Errors – SQL in Sixty Seconds #030 – Video One of the most famous errors related to SQL Server is about connecting to SQL Server itself. Here is how it goes, most of the time developers have worked with SQL Server and knows pretty much every error which they face during development language. However, hardly they install fresh SQL Server. As the installation of the SQL Server is a rare occasion unless you are a DBA who is responsible for such an instance – the error faced during installations are pretty rare as well. http://www.youtube.com/watch?v=1k00z82u4OI Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • MySQL Cluster 7.3 Labs Release – Foreign Keys Are In!

    - by Mat Keep
    0 0 1 1097 6254 Homework 52 14 7337 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Summary (aka TL/DR): Support for Foreign Key constraints has been one of the most requested feature enhancements for MySQL Cluster. We are therefore extremely excited to announce that Foreign Keys are part of the first Labs Release of MySQL Cluster 7.3 – available for download, evaluation and feedback now! (Select the mysql-cluster-7.3-labs-June-2012 build) In this blog, I will attempt to discuss the design rationale, implementation, configuration and steps to get started in evaluating the first MySQL Cluster 7.3 Labs Release. Pace of Innovation It was only a couple of months ago that we announced the General Availability (GA) of MySQL Cluster 7.2, delivering 1 billion Queries per Minute, with 70x higher cross-shard JOIN performance, Memcached NoSQL key-value API and cross-data center replication.  This release has been a huge hit, with downloads and deployments quickly reaching record levels. The announcement of the first MySQL Cluster 7.3 Early Access lab release at today's MySQL Innovation Day event demonstrates the continued pace in Cluster development, and provides an opportunity for the community to evaluate and feedback on new features they want to see. What’s the Plan for MySQL Cluster 7.3? Well, Foreign Keys, as you may have gathered by now (!), and this is the focus of this first Labs Release. As with MySQL Cluster 7.2, we plan to publish a series of preview releases for 7.3 that will incrementally add new candidate features for a final GA release (subject to usual safe harbor statement below*), including: - New NoSQL APIs; - Features to automate the configuration and provisioning of multi-node clusters, on premise or in the cloud; - Performance and scalability enhancements; - Taking advantage of features in the latest MySQL 5.x Server GA. Design Rationale MySQL Cluster is designed as a “Not-Only-SQL” database. It combines attributes that enable users to blend the best of both relational and NoSQL technologies into solutions that deliver web scalability with 99.999% availability and real-time performance, including: Concurrent NoSQL and SQL access to the database; Auto-sharding with simple scale-out across commodity hardware; Multi-master replication with failover and recovery both within and across data centers; Shared-nothing architecture with no single point of failure; Online scaling and schema changes; ACID compliance and support for complex queries, across shards. Native support for Foreign Key constraints enables users to extend the benefits of MySQL Cluster into a broader range of use-cases, including: - Packaged applications in areas such as eCommerce and Web Content Management that prescribe databases with Foreign Key support. - In-house developments benefiting from Foreign Key constraints to simplify data models and eliminate the additional application logic needed to maintain data consistency and integrity between tables. Implementation The Foreign Key functionality is implemented directly within MySQL Cluster’s data nodes, allowing any client API accessing the cluster to benefit from them – whether using SQL or one of the NoSQL interfaces (Memcached, C++, Java, JPA or HTTP/REST.) The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL In addition, the MySQL Cluster implementation supports the online adding and dropping of Foreign Keys, ensuring the Cluster continues to serve both read and write requests during the operation. An important difference to note with the Foreign Key implementation in InnoDB is that MySQL Cluster does not support the updating of Primary Keys from within the Data Nodes themselves - instead the UPDATE is emulated with a DELETE followed by an INSERT operation. Therefore an UPDATE operation will return an error if the parent reference is using a Primary Key, unless using CASCADE action, in which case the delete operation will result in the corresponding rows in the child table being deleted. The Engineering team plans to change this behavior in a subsequent preview release. Also note that when using InnoDB "NO ACTION" is identical to "RESTRICT". In the case of MySQL Cluster “NO ACTION” means “deferred check”, i.e. the constraint is checked before commit, allowing user-defined triggers to automatically make changes in order to satisfy the Foreign Key constraints. Configuration There is nothing special you have to do here – Foreign Key constraint checking is enabled by default. If you intend to migrate existing tables from another database or storage engine, for example from InnoDB, there are a couple of best practices to observe: 1. Analyze the structure of the Foreign Key graph and run the ALTER TABLE ENGINE=NDB in the correct sequence to ensure constraints are enforced 2. Alternatively drop the Foreign Key constraints prior to the import process and then recreate when complete. Getting Started Read this blog for a demonstration of using Foreign Keys with MySQL Cluster.  You can download MySQL Cluster 7.3 Labs Release with Foreign Keys today - (select the mysql-cluster-7.3-labs-June-2012 build) If you are new to MySQL Cluster, the Getting Started guide will walk you through installing an evaluation cluster on a singe host (these guides reflect MySQL Cluster 7.2, but apply equally well to 7.3) Post any questions to the MySQL Cluster forum where our Engineering team will attempt to assist you. Post any bugs you find to the MySQL bug tracking system (select MySQL Cluster from the Category drop-down menu) And if you have any feedback, please post them to the Comments section of this blog. Summary MySQL Cluster 7.2 is the GA, production-ready release of MySQL Cluster. This first Labs Release of MySQL Cluster 7.3 gives you the opportunity to preview and evaluate future developments in the MySQL Cluster database, and we are very excited to be able to share that with you. Let us know how you get along with MySQL Cluster 7.3, and other features that you want to see in future releases. * Safe Harbor Statement This information is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

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  • Fraud Detection with the SQL Server Suite Part 2

    - by Dejan Sarka
    This is the second part of the fraud detection whitepaper. You can find the first part in my previous blog post about this topic. My Approach to Data Mining Projects It is impossible to evaluate the time and money needed for a complete fraud detection infrastructure in advance. Personally, I do not know the customer’s data in advance. I don’t know whether there is already an existing infrastructure, like a data warehouse, in place, or whether we would need to build one from scratch. Therefore, I always suggest to start with a proof-of-concept (POC) project. A POC takes something between 5 and 10 working days, and involves personnel from the customer’s site – either employees or outsourced consultants. The team should include a subject matter expert (SME) and at least one information technology (IT) expert. The SME must be familiar with both the domain in question as well as the meaning of data at hand, while the IT expert should be familiar with the structure of data, how to access it, and have some programming (preferably Transact-SQL) knowledge. With more than one IT expert the most time consuming work, namely data preparation and overview, can be completed sooner. I assume that the relevant data is already extracted and available at the very beginning of the POC project. If a customer wants to have their people involved in the project directly and requests the transfer of knowledge, the project begins with training. I strongly advise this approach as it offers the establishment of a common background for all people involved, the understanding of how the algorithms work and the understanding of how the results should be interpreted, a way of becoming familiar with the SQL Server suite, and more. Once the data has been extracted, the customer’s SME (i.e. the analyst), and the IT expert assigned to the project will learn how to prepare the data in an efficient manner. Together with me, knowledge and expertise allow us to focus immediately on the most interesting attributes and identify any additional, calculated, ones soon after. By employing our programming knowledge, we can, for example, prepare tens of derived variables, detect outliers, identify the relationships between pairs of input variables, and more, in only two or three days, depending on the quantity and the quality of input data. I favor the customer’s decision of assigning additional personnel to the project. For example, I actually prefer to work with two teams simultaneously. I demonstrate and explain the subject matter by applying techniques directly on the data managed by each team, and then both teams continue to work on the data overview and data preparation under our supervision. I explain to the teams what kind of results we expect, the reasons why they are needed, and how to achieve them. Afterwards we review and explain the results, and continue with new instructions, until we resolve all known problems. Simultaneously with the data preparation the data overview is performed. The logic behind this task is the same – again I show to the teams involved the expected results, how to achieve them and what they mean. This is also done in multiple cycles as is the case with data preparation, because, quite frankly, both tasks are completely interleaved. A specific objective of the data overview is of principal importance – it is represented by a simple star schema and a simple OLAP cube that will first of all simplify data discovery and interpretation of the results, and will also prove useful in the following tasks. The presence of the customer’s SME is the key to resolving possible issues with the actual meaning of the data. We can always replace the IT part of the team with another database developer; however, we cannot conduct this kind of a project without the customer’s SME. After the data preparation and when the data overview is available, we begin the scientific part of the project. I assist the team in developing a variety of models, and in interpreting the results. The results are presented graphically, in an intuitive way. While it is possible to interpret the results on the fly, a much more appropriate alternative is possible if the initial training was also performed, because it allows the customer’s personnel to interpret the results by themselves, with only some guidance from me. The models are evaluated immediately by using several different techniques. One of the techniques includes evaluation over time, where we use an OLAP cube. After evaluating the models, we select the most appropriate model to be deployed for a production test; this allows the team to understand the deployment process. There are many possibilities of deploying data mining models into production; at the POC stage, we select the one that can be completed quickly. Typically, this means that we add the mining model as an additional dimension to an existing DW or OLAP cube, or to the OLAP cube developed during the data overview phase. Finally, we spend some time presenting the results of the POC project to the stakeholders and managers. Even from a POC, the customer will receive lots of benefits, all at the sole risk of spending money and time for a single 5 to 10 day project: The customer learns the basic patterns of frauds and fraud detection The customer learns how to do the entire cycle with their own people, only relying on me for the most complex problems The customer’s analysts learn how to perform much more in-depth analyses than they ever thought possible The customer’s IT experts learn how to perform data extraction and preparation much more efficiently than they did before All of the attendees of this training learn how to use their own creativity to implement further improvements of the process and procedures, even after the solution has been deployed to production The POC output for a smaller company or for a subsidiary of a larger company can actually be considered a finished, production-ready solution It is possible to utilize the results of the POC project at subsidiary level, as a finished POC project for the entire enterprise Typically, the project results in several important “side effects” Improved data quality Improved employee job satisfaction, as they are able to proactively contribute to the central knowledge about fraud patterns in the organization Because eventually more minds get to be involved in the enterprise, the company should expect more and better fraud detection patterns After the POC project is completed as described above, the actual project would not need months of engagement from my side. This is possible due to our preference to transfer the knowledge onto the customer’s employees: typically, the customer will use the results of the POC project for some time, and only engage me again to complete the project, or to ask for additional expertise if the complexity of the problem increases significantly. I usually expect to perform the following tasks: Establish the final infrastructure to measure the efficiency of the deployed models Deploy the models in additional scenarios Through reports By including Data Mining Extensions (DMX) queries in OLTP applications to support real-time early warnings Include data mining models as dimensions in OLAP cubes, if this was not done already during the POC project Create smart ETL applications that divert suspicious data for immediate or later inspection I would also offer to investigate how the outcome could be transferred automatically to the central system; for instance, if the POC project was performed in a subsidiary whereas a central system is available as well Of course, for the actual project, I would repeat the data and model preparation as needed It is virtually impossible to tell in advance how much time the deployment would take, before we decide together with customer what exactly the deployment process should cover. Without considering the deployment part, and with the POC project conducted as suggested above (including the transfer of knowledge), the actual project should still only take additional 5 to 10 days. The approximate timeline for the POC project is, as follows: 1-2 days of training 2-3 days for data preparation and data overview 2 days for creating and evaluating the models 1 day for initial preparation of the continuous learning infrastructure 1 day for presentation of the results and discussion of further actions Quite frequently I receive the following question: are we going to find the best possible model during the POC project, or during the actual project? My answer is always quite simple: I do not know. Maybe, if we would spend just one hour more for data preparation, or create just one more model, we could get better patterns and predictions. However, we simply must stop somewhere, and the best possible way to do this, according to my experience, is to restrict the time spent on the project in advance, after an agreement with the customer. You must also never forget that, because we build the complete learning infrastructure and transfer the knowledge, the customer will be capable of doing further investigations independently and improve the models and predictions over time without the need for a constant engagement with me.

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  • ASP.NET WebAPI Security 3: Extensible Authentication Framework

    - by Your DisplayName here!
    In my last post, I described the identity architecture of ASP.NET Web API. The short version was, that Web API (beta 1) does not really have an authentication system on its own, but inherits the client security context from its host. This is fine in many situations (e.g. AJAX style callbacks with an already established logon session). But there are many cases where you don’t use the containing web application for authentication, but need to do it yourself. Examples of that would be token based authentication and clients that don’t run in the context of the web application (e.g. desktop clients / mobile). Since Web API provides a nice extensibility model, it is easy to implement whatever security framework you want on top of it. My design goals were: Easy to use. Extensible. Claims-based. ..and of course, this should always behave the same, regardless of the hosting environment. In the rest of the post I am outlining some of the bits and pieces, So you know what you are dealing with, in case you want to try the code. At the very heart… is a so called message handler. This is a Web API extensibility point that gets to see (and modify if needed) all incoming and outgoing requests. Handlers run after the conversion from host to Web API, which means that handler code deals with HttpRequestMessage and HttpResponseMessage. See Pedro’s post for more information on the processing pipeline. This handler requires a configuration object for initialization. Currently this is very simple, it contains: Settings for the various authentication and credential types Settings for claims transformation Ability to block identity inheritance from host The most important part here is the credential type support, but I will come back to that later. The logic of the message handler is simple: Look at the incoming request. If the request contains an authorization header, try to authenticate the client. If this is successful, create a claims principal and populate the usual places. If not, return a 401 status code and set the Www-Authenticate header. Look at outgoing response, if the status code is 401, set the Www-Authenticate header. Credential type support Under the covers I use the WIF security token handler infrastructure to validate credentials and to turn security tokens into claims. The idea is simple: an authorization header consists of two pieces: the schema and the actual “token”. My configuration object allows to associate a security token handler with a scheme. This way you only need to implement support for a specific credential type, and map that to the incoming scheme value. The current version supports HTTP Basic Authentication as well as SAML and SWT tokens. (I needed to do some surgery on the standard security token handlers, since WIF does not directly support string-ified tokens. The next version of .NET will fix that, and the code should become simpler then). You can e.g. use this code to hook up a username/password handler to the Basic scheme (the default scheme name for Basic Authentication). config.Handler.AddBasicAuthenticationHandler( (username, password) => username == password); You simply have to provide a password validation function which could of course point back to your existing password library or e.g. membership. The following code maps a token handler for Simple Web Tokens (SWT) to the Bearer scheme (the currently favoured scheme name for OAuth2). You simply have to specify the issuer name, realm and shared signature key: config.Handler.AddSimpleWebTokenHandler(     "Bearer",     http://identity.thinktecture.com/trust,     Constants.Realm,     "Dc9Mpi3jaaaUpBQpa/4R7XtUsa3D/ALSjTVvK8IUZbg="); For certain integration scenarios it is very useful if your Web API can consume SAML tokens. This is also easily accomplishable. The following code uses the standard WIF API to configure the usual SAMLisms like issuer, audience, service certificate and certificate validation. Both SAML 1.1 and 2.0 are supported. var registry = new ConfigurationBasedIssuerNameRegistry(); registry.AddTrustedIssuer( "d1 c5 b1 25 97 d0 36 94 65 1c e2 64 fe 48 06 01 35 f7 bd db", "ADFS"); var adfsConfig = new SecurityTokenHandlerConfiguration(); adfsConfig.AudienceRestriction.AllowedAudienceUris.Add( new Uri(Constants.Realm)); adfsConfig.IssuerNameRegistry = registry; adfsConfig.CertificateValidator = X509CertificateValidator.None; // token decryption (read from configuration section) adfsConfig.ServiceTokenResolver = FederatedAuthentication.ServiceConfiguration.CreateAggregateTokenResolver(); config.Handler.AddSaml11SecurityTokenHandler("SAML", adfsConfig); Claims Transformation After successful authentication, if configured, the standard WIF ClaimsAuthenticationManager is called to run claims transformation and validation logic. This stage is used to transform the “technical” claims from the security token into application claims. You can either have a separate transformation logic, or share on e.g. with the containing web application. That’s just a matter of configuration. Adding the authentication handler to a Web API application In the spirit of Web API this is done in code, e.g. global.asax for web hosting: protected void Application_Start() {     AreaRegistration.RegisterAllAreas();     ConfigureApis(GlobalConfiguration.Configuration);     RegisterGlobalFilters(GlobalFilters.Filters);     RegisterRoutes(RouteTable.Routes);     BundleTable.Bundles.RegisterTemplateBundles(); } private void ConfigureApis(HttpConfiguration configuration) {     configuration.MessageHandlers.Add( new AuthenticationHandler(ConfigureAuthentication())); } private AuthenticationConfiguration ConfigureAuthentication() {     var config = new AuthenticationConfiguration     {         // sample claims transformation for consultants sample, comment out to see raw claims         ClaimsAuthenticationManager = new ApiClaimsTransformer(),         // value of the www-authenticate header, // if not set, the first scheme added to the handler collection is used         DefaultAuthenticationScheme = "Basic"     };     // add token handlers - see above     return config; } You can find the full source code and some samples here. In the next post I will describe some of the samples in the download, and then move on to authorization. HTH

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  • Full-text Indexing Books Online

    - by Most Valuable Yak (Rob Volk)
    While preparing for a recent SQL Saturday presentation, I was struck by a crazy idea (shocking, I know): Could someone import the content of SQL Server Books Online into a database and apply full-text indexing to it?  The answer is yes, and it's really quite easy to do. The first step is finding the installed help files.  If you have SQL Server 2012, BOL is installed under the Microsoft Help Library.  You can find the install location by opening SQL Server Books Online and clicking the gear icon for the Help Library Manager.  When the new window pops up click the Settings link, you'll get the following: You'll see the path under Library Location. Once you navigate to that path you'll have to drill down a little further, to C:\ProgramData\Microsoft\HelpLibrary\content\Microsoft\store.  This is where the help file content is kept if you downloaded it for offline use. Depending on which products you've downloaded help for, you may see a few hundred files.  Fortunately they're named well and you can easily find the "SQL_Server_Denali_Books_Online_" files.  We are interested in the .MSHC files only, and can skip the Installation and Developer Reference files. Despite the .MHSC extension, these files are compressed with the standard Zip format, so your favorite archive utility (WinZip, 7Zip, WinRar, etc.) can open them.  When you do, you'll see a few thousand files in the archive.  We are only interested in the .htm files, but there's no harm in extracting all of them to a folder.  7zip provides a command-line utility and the following will extract to a D:\SQLHelp folder previously created: 7z e –oD:\SQLHelp "C:\ProgramData\Microsoft\HelpLibrary\content\Microsoft\store\SQL_Server_Denali_Books_Online_B780_SQL_110_en-us_1.2.mshc" *.htm Well that's great Rob, but how do I put all those files into a full-text index? I'll tell you in a second, but first we have to set up a few things on the database side.  I'll be using a database named Explore (you can certainly change that) and the following setup is a fragment of the script I used in my presentation: USE Explore; GO CREATE SCHEMA help AUTHORIZATION dbo; GO -- Create default fulltext catalog for later FT indexes CREATE FULLTEXT CATALOG FTC AS DEFAULT; GO CREATE TABLE help.files(file_id int not null IDENTITY(1,1) CONSTRAINT PK_help_files PRIMARY KEY, path varchar(256) not null CONSTRAINT UNQ_help_files_path UNIQUE, doc_type varchar(6) DEFAULT('.xml'), content varbinary(max) not null); CREATE FULLTEXT INDEX ON help.files(content TYPE COLUMN doc_type LANGUAGE 1033) KEY INDEX PK_help_files; This will give you a table, default full-text catalog, and full-text index on that table for the content you're going to insert.  I'll be using the command line again for this, it's the easiest method I know: for %a in (D:\SQLHelp\*.htm) do sqlcmd -S. -E -d Explore -Q"set nocount on;insert help.files(path,content) select '%a', cast(c as varbinary(max)) from openrowset(bulk '%a', SINGLE_CLOB) as c(c)" You'll need to copy and run that as one line in a command prompt.  I'll explain what this does while you run it and watch several thousand files get imported: The "for" command allows you to loop over a collection of items.  In this case we want all the .htm files in the D:\SQLHelp folder.  For each file it finds, it will assign the full path and file name to the %a variable.  In the "do" clause, we'll specify another command to be run for each iteration of the loop.  I make a call to "sqlcmd" in order to run a SQL statement.  I pass in the name of the server (-S.), where "." represents the local default instance. I specify -d Explore as the database, and -E for trusted connection.  I then use -Q to run a query that I enclose in double quotes. The query uses OPENROWSET(BULK…SINGLE_CLOB) to open the file as a data source, and to treat it as a single character large object.  In order for full-text indexing to work properly, I have to convert the text content to varbinary. I then INSERT these contents along with the full path of the file into the help.files table created earlier.  This process continues for each file in the folder, creating one new row in the table. And that's it! 5 SQL Statements and 2 command line statements to unzip and import SQL Server Books Online!  In case you're wondering why I didn't use FILESTREAM or FILETABLE, it's simply because I haven't learned them…yet. I may return to this blog after I figure that out and update it with the steps to do so.  I believe that will make it even easier. In the spirit of exploration, I'll leave you to work on some fulltext queries of this content.  I also recommend playing around with the sys.dm_fts_xxxx DMVs (I particularly like sys.dm_fts_index_keywords, it's pretty interesting).  There are additional example queries in the download material for my presentation linked above. Many thanks to Kevin Boles (t) for his advice on (re)checking the content of the help files.  Don't let that .htm extension fool you! The 2012 help files are actually XML, and you'd need to specify '.xml' in your document type column in order to extract the full-text keywords.  (You probably noticed this in the default definition for the doc_type column.)  You can query sys.fulltext_document_types to get a complete list of the types that can be full-text indexed. I also need to thank Hilary Cotter for giving me the original idea. I believe he used MSDN content in a full-text index for an article from waaaaaaaaaaay back, that I can't find now, and had forgotten about until just a few days ago.  He is also co-author of Pro Full-Text Search in SQL Server 2008, which I highly recommend.  He also has some FTS articles on Simple Talk: http://www.simple-talk.com/sql/learn-sql-server/sql-server-full-text-search-language-features/ http://www.simple-talk.com/sql/learn-sql-server/sql-server-full-text-search-language-features,-part-2/

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  • CodePlex Daily Summary for Sunday, September 02, 2012

    CodePlex Daily Summary for Sunday, September 02, 2012Popular ReleasesThisismyusername's codeplex page.: HTML5 Multitouch Example - Fruit Ninja in HTML5: This is an example of how you could create a game such as Fruit Ninja using HTML5's multitouch capabilities. This example isn't responsive enough, so I will be working on that, and it doesn't have great graphics, either. If I had my own webpage, I could store some graphics and upload the game there and it might look halfway decent, but here the fruits are just circles. I hope you enjoy reading the source code anyway.GmailDefaultMaker: GmailDefaultMaker 3.0.0.2: Add QQ Mail BugfixRuminate XNA 4.0 GUI: Release 1.1.1: Fixed bugs with Slider and TextBox. Added ComboBox.Confuser: Confuser build 76542: This is a build of changeset 76542.SharePoint Column & View Permission: SharePoint Column and View Permission v1.2: Version 1.2 of this project. If you will find any bugs please let me know at enti@zoznam.sk or post your findings in Issue TrackerMihmojsos OS: Mihmojsos OS 3 (Smart Rabbit): !Mihmojsos OS 3 Smart Rabbit Mihmojsos Smart Rabbit is now availableDotNetNuke Translator: 01.00.00 Beta: First release of the project.YNA: YNA 0.2 alpha: Wath's new since 0.1 alpha ? A lot of changes but there are the most interresting : StateManager is now better and faster Mouse events for all YnObjects (Sprites, Images, texts) A really big improvement for YnGroup Gamepad support And the news : Tiled Map support (need refactoring) Isometric tiled map support (need refactoring) Transition effect like "FadeIn" and "FadeOut" (YnTransition) Timers (YnTimer) Path management (YnPath, need more refactoring) Downloads All downloads...Audio Pitch & Shift: Audio Pitch And Shift 5.1.0.2: fixed several issues with streaming modeUrlPager: UrlPager 1.2: Fixed bug in which url parameters will lost after paging; ????????url???bug;Sofire Suite: Sofire v1.5.0.0: Sofire v1.5.0.0 ?? ???????? ?????: 1、?? 2、????EntLib.com????????: EntLib.com???????? v3.0: EntLib eCommerce Solution ???Microsoft .Net Framework?????????????????????。Coevery - Free CRM: Coevery 1.0.0.24: Add a sample database, and installation instructions.Math.NET Numerics: Math.NET Numerics v2.2.1: Major linear algebra rework since v2.1, now available on Codeplex as well (previous versions were only available via NuGet). Since v2.2.0: Student-T density more robust for very large degrees of freedom Sparse Kronecker product much more efficient (now leverages sparsity) Direct access to raw matrix storage implementations for advanced extensibility Now also separate package for signed core library with a strong name (we dropped strong names in v2.2.0) Also available as NuGet packages...Microsoft SQL Server Product Samples: Database: AdventureWorks Databases – 2012, 2008R2 and 2008: About this release This release consolidates AdventureWorks databases for SQL Server 2012, 2008R2 and 2008 versions to one page. Each zip file contains an mdf database file and ldf log file. This should make it easier to find and download AdventureWorks databases since all OLTP versions are on one page. There are no database schema changes. For each release of the product, there is a light-weight and full version of the AdventureWorks sample database. The light-weight version is denoted by ...Christoc's DotNetNuke Module Development Template: DotNetNuke Project Templates V1.1 for VS2012: This release is specifically for Visual Studio 2012 Support, distributed through the Visual Studio Extensions gallery at http://visualstudiogallery.msdn.microsoft.com/ After you build in Release mode the installable packages (source/install) can be found in the INSTALL folder now, within your module's folder, not the packages folder anymore Check out the blog post for all of the details about this release. http://www.dotnetnuke.com/Resources/Blogs/EntryId/3471/New-Visual-Studio-2012-Projec...Home Access Plus+: v8.0: v8.0.0901.1830 RELEASE CHANGED TO BETA Any issues, please log them on http://www.edugeek.net/forums/home-access-plus/ This is full release, NO upgrade ZIP will be provided as most files require replacing. To upgrade from a previous version, delete everything but your AppData folder, extract all but the AppData folder and run your HAP+ install Documentation is supplied in the Web Zip The Quota Services require executing a script to register the service, this can be found in there install ...Phalanger - The PHP Language Compiler for the .NET Framework: 3.0.0.3406 (September 2012): New features: Extended ReflectionClass libxml error handling, constants DateTime::modify(), DateTime::getOffset() TreatWarningsAsErrors MSBuild option OnlyPrecompiledCode configuration option; allows to use only compiled code Fixes: ArgsAware exception fix accessing .NET properties bug fix ASP.NET session handler fix for OutOfProc mode DateTime methods (WordPress posting fix) Phalanger Tools for Visual Studio: Visual Studio 2010 & 2012 New debugger engine, PHP-like debugging ...MabiCommerce: MabiCommerce 1.0.1: What's NewSetup now creates shortcuts Fix spelling errors Minor enhancement to the Map window.ScintillaNET: ScintillaNET 2.5.2: This release has been built from the 2.5 branch. Version 2.5.2 is functionally identical to the 2.5.1 release but also includes the XML documentation comments file generated by Visual Studio. It is not 100% comprehensive but it will give you Visual Studio IntelliSense for a large part of the API. Just make sure the ScintillaNET.xml file is in the same folder as the ScintillaNET.dll reference you're using in your projects. (The XML file does not need to be distributed with your application)....New ProjectsATSV: this is a student project for making a new silverlight UI Bookmark Collector: This project is a best practice example of how to use content items in DotNetNuke. It allows you to quickly and easily manage a listing of external links.BPVotingmachine: BP Vote SystemClean My Space: Sort your files in a fun and fast! With Clean My Space you can!CutePlatform: CutePlatform is a platform game based around the PlanetCute graphics pack from Daniel cook, make him a visit in www.lostgardem.comDancTeX: This project is targeting the integration of LaTeX into VisusalStudio. Epi Info™ Companion for Android: A mobile companion to the Epi Info™ 7 desktop tool for epidemiologic data collection and analysis.Flucene: Object Document Mapper for Lucene.Netfluentserializer: FluentSerializer is a library for .NET usable to create serialize/deserialize data through its fluent interface. The methods it creates are compiled.hongjiapp: hongjiappidealthings educational comprehensive administration system: ?????????????????????????????????????????????.Java Accounting Library: The project aims at providing a Financial Accounting Java Library which may be integrated to any other Java Application independent of its Backend Database.mycnblogs: mycnblogsNETPack: Lightweight and flexible packer for .NETRandom Useful Code: This project is where I will store various useful classes I have built over time. Only the code will be provided, no Library or the like.Suleymaniye Tavimi: Namaz vakitleri hesaplama uygulamasidir. Istenilen yer için hesaplama yapar.

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  • Refactoring a Single Rails Model with large methods & long join queries trying to do everything

    - by Kelseydh
    I have a working Ruby on Rails Model that I suspect is inefficient, hard to maintain, and full of unnecessary SQL join queries. I want to optimize and refactor this Model (Quiz.rb) to comply with Rails best practices, but I'm not sure how I should do it. The Rails app is a game that has Missions with many Stages. Users complete Stages by answering Questions that have correct or incorrect Answers. When a User tries to complete a stage by answering questions, the User gets a Quiz entry with many Attempts. Each Attempt records an Answer submitted for that Question within the Stage. A user completes a stage or mission by getting every Attempt correct, and their progress is tracked by adding a new entry to the UserMission & UserStage join tables. All of these features work, but unfortunately the Quiz.rb Model has been twisted to handle almost all of it exclusively. The callbacks began at 'Quiz.rb', and because I wasn't sure how to leave the Quiz Model during a multi-model update, I resorted to using Rails Console to have the @quiz instance variable via self.some_method do all the heavy lifting to retrieve every data value for the game's business logic; resulting in large extended join queries that "dance" all around the Database schema. The Quiz.rb Model that Smells: class Quiz < ActiveRecord::Base belongs_to :user has_many :attempts, dependent: :destroy before_save :check_answer before_save :update_user_mission_and_stage accepts_nested_attributes_for :attempts, :reject_if => lambda { |a| a[:answer_id].blank? }, :allow_destroy => true #Checks every answer within each quiz, adding +1 for each correct answer #within a stage quiz, and -1 for each incorrect answer def check_answer stage_score = 0 self.attempts.each do |attempt| if attempt.answer.correct? == true stage_score += 1 elsif attempt.answer.correct == false stage_score - 1 end end stage_score end def winner return true end def update_user_mission_and_stage ####### #Step 1: Checks if UserMission exists, finds or creates one. #if no UserMission for the current mission exists, creates a new UserMission if self.user_has_mission? == false @user_mission = UserMission.new(user_id: self.user.id, mission_id: self.current_stage.mission_id, available: true) @user_mission.save else @user_mission = self.find_user_mission end ####### #Step 2: Checks if current UserStage exists, stops if true to prevent duplicate entry if self.user_has_stage? @user_mission.save return true else ####### ##Step 3: if step 2 returns false: ##Initiates UserStage creation instructions #checks for winner (winner actions need to be defined) if they complete last stage of last mission for a given orientation if self.passed? && self.is_last_stage? && self.is_last_mission? create_user_stage_and_update_user_mission self.winner #NOTE: The rest are the same, but specify conditions that are available to add badges or other actions upon those conditions occurring: ##if user completes first stage of a mission elsif self.passed? && self.is_first_stage? && self.is_first_mission? create_user_stage_and_update_user_mission #creates user badge for finishing first stage of first mission self.user.add_badge(5) self.user.activity_logs.create(description: "granted first-stage badge", type_event: "badge", value: "first-stage") #If user completes last stage of a given mission, creates a new UserMission elsif self.passed? && self.is_last_stage? && self.is_first_mission? create_user_stage_and_update_user_mission #creates user badge for finishing first mission self.user.add_badge(6) self.user.activity_logs.create(description: "granted first-mission badge", type_event: "badge", value: "first-mission") elsif self.passed? create_user_stage_and_update_user_mission else self.passed? == false return true end end end #Creates a new UserStage record in the database for a successful Quiz question passing def create_user_stage_and_update_user_mission @nu_stage = @user_mission.user_stages.new(user_id: self.user.id, stage_id: self.current_stage.id) @nu_stage.save @user_mission.save self.user.add_points(50) end #Boolean that defines passing a stage as answering every question in that stage correct def passed? self.check_answer >= self.number_of_questions end #Returns the number of questions asked for that stage's quiz def number_of_questions self.attempts.first.answer.question.stage.questions.count end #Returns the current_stage for the Quiz, routing through 1st attempt in that Quiz def current_stage self.attempts.first.answer.question.stage end #Gives back the position of the stage relative to its mission. def stage_position self.attempts.first.answer.question.stage.position end #will find the user_mission for the current user and stage if it exists def find_user_mission self.user.user_missions.find_by_mission_id(self.current_stage.mission_id) end #Returns true if quiz was for the last stage within that mission #helpful for triggering actions related to a user completing a mission def is_last_stage? self.stage_position == self.current_stage.mission.stages.last.position end #Returns true if quiz was for the first stage within that mission #helpful for triggering actions related to a user completing a mission def is_first_stage? self.stage_position == self.current_stage.mission.stages_ordered.first.position end #Returns true if current user has a UserMission for the current stage def user_has_mission? self.user.missions.ids.include?(self.current_stage.mission.id) end #Returns true if current user has a UserStage for the current stage def user_has_stage? self.user.stages.include?(self.current_stage) end #Returns true if current user is on the last mission based on position within a given orientation def is_first_mission? self.user.missions.first.orientation.missions.by_position.first.position == self.current_stage.mission.position end #Returns true if current user is on the first stage & mission of a given orientation def is_last_mission? self.user.missions.first.orientation.missions.by_position.last.position == self.current_stage.mission.position end end My Question Currently my Rails server takes roughly 500ms to 1 sec to process single @quiz.save action. I am confident that the slowness here is due to sloppy code, not bad Database ERD design. What does a better solution look like? And specifically: Should I use join queries to retrieve values like I did here, or is it better to instantiate new objects within the model instead? Or am I missing a better solution? How should update_user_mission_and_stage be refactored to follow best practices? Relevant Code for Reference: quizzes_controller.rb w/ Controller Route Initiating Callback: class QuizzesController < ApplicationController before_action :find_stage_and_mission before_action :find_orientation before_action :find_question def show end def create @user = current_user @quiz = current_user.quizzes.new(quiz_params) if @quiz.save if @quiz.passed? if @mission.next_mission.nil? && @stage.next_stage.nil? redirect_to root_path, notice: "Congratulations, you have finished the last mission!" elsif @stage.next_stage.nil? redirect_to [@mission.next_mission, @mission.first_stage], notice: "Correct! Time for Mission #{@mission.next_mission.position}", info: "Starting next mission" else redirect_to [@mission, @stage.next_stage], notice: "Answer Correct! You passed the stage!" end else redirect_to [@mission, @stage], alert: "You didn't get every question right, please try again." end else redirect_to [@mission, @stage], alert: "Sorry. We were unable to save your answer. Please contact the admministrator." end @questions = @stage.questions.all end private def find_stage_and_mission @stage = Stage.find(params[:stage_id]) @mission = @stage.mission end def find_question @question = @stage.questions.find_by_id params[:id] end def quiz_params params.require(:quiz).permit(:user_id, :attempt_id, {attempts_attributes: [:id, :quiz_id, :answer_id]}) end def find_orientation @orientation = @mission.orientation @missions = @orientation.missions.by_position end end Overview of Relevant ERD Database Relationships: Mission - Stage - Question - Answer - Attempt <- Quiz <- User Mission - UserMission <- User Stage - UserStage <- User Other Models: Mission.rb class Mission < ActiveRecord::Base belongs_to :orientation has_many :stages has_many :user_missions, dependent: :destroy has_many :users, through: :user_missions #SCOPES scope :by_position, -> {order(position: :asc)} def stages_ordered stages.order(:position) end def next_mission self.orientation.missions.find_by_position(self.position.next) end def first_stage next_mission.stages_ordered.first end end Stage.rb: class Stage < ActiveRecord::Base belongs_to :mission has_many :questions, dependent: :destroy has_many :user_stages, dependent: :destroy has_many :users, through: :user_stages accepts_nested_attributes_for :questions, reject_if: :all_blank, allow_destroy: true def next_stage self.mission.stages.find_by_position(self.position.next) end end Question.rb class Question < ActiveRecord::Base belongs_to :stage has_many :answers, dependent: :destroy accepts_nested_attributes_for :answers, :reject_if => lambda { |a| a[:body].blank? }, :allow_destroy => true end Answer.rb: class Answer < ActiveRecord::Base belongs_to :question has_many :attempts, dependent: :destroy end Attempt.rb: class Attempt < ActiveRecord::Base belongs_to :answer belongs_to :quiz end User.rb: class User < ActiveRecord::Base belongs_to :school has_many :activity_logs has_many :user_missions, dependent: :destroy has_many :missions, through: :user_missions has_many :user_stages, dependent: :destroy has_many :stages, through: :user_stages has_many :orientations, through: :school has_many :quizzes, dependent: :destroy has_many :attempts, through: :quizzes def latest_stage_position self.user_missions.last.user_stages.last.stage.position end end UserMission.rb class UserMission < ActiveRecord::Base belongs_to :user belongs_to :mission has_many :user_stages, dependent: :destroy end UserStage.rb class UserStage < ActiveRecord::Base belongs_to :user belongs_to :stage belongs_to :user_mission end

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  • SQL University: What and why of database refactoring

    - by Mladen Prajdic
    This is a post for a great idea called SQL University started by Jorge Segarra also famously known as SqlChicken on Twitter. It’s a collection of blog posts on different database related topics contributed by several smart people all over the world. So this week is mine and we’ll be talking about database testing and refactoring. In 3 posts we’ll cover: SQLU part 1 - What and why of database testing SQLU part 2 - What and why of database refactoring SQLU part 3 - Tools of the trade This is a second part of the series and in it we’ll take a look at what database refactoring is and why do it. Why refactor a database To know why refactor we first have to know what refactoring actually is. Code refactoring is a process where we change module internals in a way that does not change that module’s input/output behavior. For successful refactoring there is one crucial thing we absolutely must have: Tests. Automated unit tests are the only guarantee we have that we haven’t broken the input/output behavior before refactoring. If you haven’t go back ad read my post on the matter. Then start writing them. Next thing you need is a code module. Those are views, UDFs and stored procedures. By having direct table access we can kiss fast and sweet refactoring good bye. One more point to have a database abstraction layer. And no, ORM’s don’t fall into that category. But also know that refactoring is NOT adding new functionality to your code. Many have fallen into this trap. Don’t be one of them and resist the lure of the dark side. And it’s a strong lure. We developers in general love to add new stuff to our code, but hate fixing our own mistakes or changing existing code for no apparent reason. To be a good refactorer one needs discipline and focus. Now we know that refactoring is all about changing inner workings of existing code. This can be due to performance optimizations, changing internal code workflows or some other reason. This is a typical black box scenario to the outside world. If we upgrade the car engine it still has to drive on the road (preferably faster) and not fly (no matter how cool that would be). Also be aware that white box tests will break when we refactor. What to refactor in a database Refactoring databases doesn’t happen that often but when it does it can include a lot of stuff. Let us look at a few common cases. Adding or removing database schema objects Adding, removing or changing table columns in any way, adding constraints, keys, etc… All of these can be counted as internal changes not visible to the data consumer. But each of these carries a potential input/output behavior change. Dropping a column can result in views not working anymore or stored procedure logic crashing. Adding a unique constraint shows duplicated data that shouldn’t exist. Foreign keys break a truncate table command executed from an application that runs once a month. All these scenarios are very real and can happen. With the proper database abstraction layer fully covered with black box tests we can make sure something like that does not happen (hopefully at all). Changing physical structures Physical structures include heaps, indexes and partitions. We can pretty much add or remove those without changing the data returned by the database. But the performance can be affected. So here we use our performance tests. We do have them, right? Just by adding a single index we can achieve orders of magnitude performance improvement. Won’t that make users happy? But what if that index causes our write operations to crawl to a stop. again we have to test this. There are a lot of things to think about and have tests for. Without tests we can’t do successful refactoring! Fixing bad code We all have some bad code in our systems. We usually refer to that code as code smell as they violate good coding practices. Examples of such code smells are SQL injection, use of SELECT *, scalar UDFs or cursors, etc… Each of those is huge code smell and can result in major code changes. Take SELECT * from example. If we remove a column from a table the client using that SELECT * statement won’t have a clue about that until it runs. Then it will gracefully crash and burn. Not to mention the widely unknown SELECT * view refresh problem that Tomas LaRock (@SQLRockstar on Twitter) and Colin Stasiuk (@BenchmarkIT on Twitter) talk about in detail. Go read about it, it’s informative. Refactoring this includes replacing the * with column names and most likely change to application using the database. Breaking apart huge stored procedures Have you ever seen seen a stored procedure that was 2000 lines long? I have. It’s not pretty. It hurts the eyes and sucks the will to live the next 10 minutes. They are a maintenance nightmare and turn into things no one dares to touch. I’m willing to bet that 100% of time they don’t have a single test on them. Large stored procedures (and functions) are a clear sign that they contain business logic. General opinion on good database coding practices says that business logic has no business in the database. That’s the applications part. Refactoring such behemoths requires writing lots of edge case tests for the stored procedure input/output behavior and then start to refactor it. First we split the logic inside into smaller parts like new stored procedures and UDFs. Those then get called from the master stored procedure. Once we’ve successfully modularized the database code it’s best to transfer that logic into the applications consuming it. This only leaves the stored procedure with common data manipulation logic. Of course this isn’t always possible so having a plethora of performance and behavior unit tests is absolutely necessary to confirm we’ve actually improved the codebase in some way.   Refactoring is not a popular chore amongst developers or managers. The former don’t like fixing old code, the latter can’t see the financial benefit. Remember how we talked about being lousy at estimating future costs in the previous post? But there comes a time when it must be done. Hopefully I’ve given you some ideas how to get started. In the last post of the series we’ll take a look at the tools to use and an example of testing and refactoring.

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  • How-to delete a tree node using the context menu

    - by frank.nimphius
    Hierarchical trees in Oracle ADF make use of View Accessors, which means that only the top level node needs to be exposed as a View Object instance on the ADF Business Components Data Model. This also means that only the top level node has a representation in the PageDef file as a tree binding and iterator binding reference. Detail nodes are accessed through tree rule definitions that use the accessor mentioned above (or nested collections in the case of POJO or EJB business services). The tree component is configured for single node selection, which however can be declaratively changed for users to press the ctrl key and selecting multiple nodes. In the following, I explain how to create a context menu on the tree for users to delete the selected tree nodes. For this, the context menu item will access a managed bean, which then determines the selected node(s), the internal ADF node bindings and the rows they represent. As mentioned, the ADF Business Components Data Model only needs to expose the top level node data sources, which in this example is an instance of the Locations View Object. For the tree to work, you need to have associations defined between entities, which usually is done for you by Oracle JDeveloper if the database tables have foreign keys defined Note: As a general hint of best practices and to simplify your life: Make sure your database schema is well defined and designed before starting your development project. Don't treat the database as something organic that grows and changes with the requirements as you proceed in your project. Business service refactoring in response to database changes is possible, but should be treated as an exception, not the rule. Good database design is a necessity – even for application developers – and nothing evil. To create the tree component, expand the Data Controls panel and drag the View Object collection to the view. From the context menu, select the tree component entry and continue with defining the tree rules that make up the hierarchical structure. As you see, when pressing the green plus icon  in the Edit Tree Binding  dialog, the data structure, Locations -  Departments – Employees in my sample, shows without you having created a View Object instance for each of the nodes in the ADF Business Components Data Model. After you configured the tree structure in the Edit Tree Binding dialog, you press OK and the tree is created. Select the tree in the page editor and open the Structure Window (ctrl+shift+S). In the Structure window, expand the tree node to access the conextMenu facet. Use the right mouse button to insert a Popup  into the facet. Repeat the same steps to insert a Menu and a Menu Item into the Popup you created. The Menu item text should be changed to something meaningful like "Delete". Note that the custom menu item later is added to the context menu together with the default context menu options like expand and expand all. To define the action that is executed when the menu item is clicked on, you select the Action Listener property in the Property Inspector and click the arrow icon followed by the Edit menu option. Create or select a managed bean and define a method name for the action handler. Next, select the tree component and browse to its binding property in the Property Inspector. Again, use the arrow icon | Edit option to create a component binding in the same managed bean that has the action listener defined. The tree handle is used in the action listener code, which is shown below: public void onTreeNodeDelete(ActionEvent actionEvent) {   //access the tree from the JSF component reference created   //using the af:tree "binding" property. The "binding" property   //creates a pair of set/get methods to access the RichTree instance   RichTree tree = this.getTreeHandler();   //get the list of selected row keys   RowKeySet rks = tree.getSelectedRowKeys();   //access the iterator to loop over selected nodes   Iterator rksIterator = rks.iterator();          //The CollectionModel represents the tree model and is   //accessed from the tree "value" property   CollectionModel model = (CollectionModel) tree.getValue();   //The CollectionModel is a wrapper for the ADF tree binding   //class, which is JUCtrlHierBinding   JUCtrlHierBinding treeBinding =                  (JUCtrlHierBinding) model.getWrappedData();          //loop over the selected nodes and delete the rows they   //represent   while(rksIterator.hasNext()){     List nodeKey = (List) rksIterator.next();     //find the ADF node binding using the node key     JUCtrlHierNodeBinding node =                       treeBinding.findNodeByKeyPath(nodeKey);     //delete the row.     Row rw = node.getRow();       rw.remove();   }          //only refresh the tree if tree nodes have been selected   if(rks.size() > 0){     AdfFacesContext adfFacesContext =                          AdfFacesContext.getCurrentInstance();     adfFacesContext.addPartialTarget(tree);   } } Note: To enable multi node selection for a tree, select the tree and change the row selection setting from "single" to "multiple". Note: a fully pictured version of this post will become available at the end of the month in a PDF summary on ADF Code Corner : http://www.oracle.com/technetwork/developer-tools/adf/learnmore/index-101235.html 

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  • BizTalk: Internals: the Partner Direct Ports and the Orchestration Chains

    - by Leonid Ganeline
    Partner Direct Port is one of the BizTalk hidden gems. It opens simple ways to the several messaging patterns. This article based on the Kevin Lam’s blog article. The article is pretty detailed but it still leaves several unclear pieces. So I have created a sample and will show how it works from different perspectives. Requirements We should create an orchestration chain where the messages should be routed from the first stage to the second stage. The messages should not be modified. All messages has the same message type. Common artifacts Source code can be downloaded here. It is interesting but all orchestrations use only one port type. It is possible because all ports are one-way ports and use only one operation. I have added a B orchestration. It helps to test the sample, showing all test messages in channel. The Receive shape Filter is empty. A Receive Port (R_Shema1Direct) is a plain Direct Port. As you can see, a subscription expression of this direct port has only one part, the MessageType for our test schema: A Filer is empty but, as you know, a link from the Receive shape to the Port creates this MessageType expression. I use only one Physical Receive File port to send a message to all processes. Each orchestration outputs a Trace.WriteLine(“<Orchestration Name>”). Forward Binding This sample has three orchestrations: A_1, A_21 and A_22. A_1 is a sender, A_21 and A_22 are receivers. Here is a subscription of the A_1 orchestration: It has two parts A MessageType. The same was for the B orchestration. A ReceivePortID. There was no such parameter for the B orchestration. It was created because I have bound the orchestration port with Physical Receive File port. This binding means the PortID parameter is added to the subscription. How to set up the ports? All ports involved in the message exchange should be the same port type. It forces us to use the same operation and the same message type for the bound ports. This step as absolutely contra-intuitive. We have to choose a Partner Orchestration parameter for the sending orchestration, A_1. The first strange thing is it is not a partner orchestration we have to choose but an orchestration port. But the most strange thing is we have to choose exactly this orchestration and exactly this port.It is not a port from the partner, receive orchestrations, A_21 or A_22, but it is A_1 orchestration and S_SentFromA_1 port. Now we have to choose a Partner Orchestration parameter for the received orchestrations, A_21 and A_22. Nothing strange is here except a parameter name. We choose the port of the sender, A_1 orchestration and S_SentFromA_1 port. As you can see the Partner Orchestration parameter for the sender and receiver orchestrations is the same. Testing I dropped a test file in a file folder. There we go: A dropped file was received by B and by A_1 A_1 sent a message forward. A message was received by B, A_21, A_22 Let’s look at a context of a message sent by A_1 on the second step: A MessageType part. It is quite expected. A PartnerService, a ParnerPort, an Operation. All those parameters were set up in the Partner Orchestration parameter on both bound ports.     Now let’s see a subscription of the A_21 and A_22 orchestrations. Now it makes sense. That’s why we have chosen such a strange value for the Partner Orchestration parameter of the sending orchestration. Inverse Binding This sample has three orchestrations: A_11, A_12 and A_2. A_11 and A_12 are senders, A_2 is receiver. How to set up the ports? All ports involved in the message exchange should be the same port type. It forces us to use the same operation and the same message type for the bound ports. This step as absolutely contra-intuitive. We have to choose a Partner Orchestration parameter for a receiving orchestration, A_2. The first strange thing is it is not a partner orchestration we have to choose but an orchestration port. But the most strange thing is we have to choose exactly this orchestration and exactly this port.It is not a port from the partner, sent orchestrations, A_11 or A_12, but it is A_2 orchestration and R_SentToA_2 port. Now we have to choose a Partner Orchestration parameter for the sending orchestrations, A_11 and A_12. Nothing strange is here except a parameter name. We choose the port of the sender, A_2 orchestration and R_SentToA_2 port. Testing I dropped a test file in a file folder. There we go: A dropped file was received by B, A_11 and by A_12 A_11 and A_12 sent two messages forward. The messages were received by B, A_2 Let’s see what was a context of a message sent by A_1 on the second step: A MessageType part. It is quite expected. A PartnerService, a ParnerPort, an Operation. All those parameters were set up in the Partner Orchestration parameter on both bound ports. Here is a subscription of the A_2 orchestration. Models I had a hard time trying to explain the Partner Direct Ports in simple terms. I have finished with this model: Forward Binding Receivers know a Sender. Sender doesn’t know Receivers. Publishers know a Subscriber. Subscriber doesn’t know Publishers. 1 –> 1 1 –> M Inverse Binding Senders know a Receiver. Receiver doesn’t know Senders. Subscribers know a Publisher. Publisher doesn’t know Subscribers. 1 –> 1 M –> 1 Notes   Orchestration chain It’s worth to note, the Partner Direct Port Binding creates a chain opened from one side and closed from another. The Forward Binding: A new Receiver can be added at run-time. The Sender can not be changed without design-time changes in Receivers. The Inverse Binding: A new Sender can be added at run-time. The Receiver can not be changed without design-time changes in Senders.

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  • Augmenting your Social Efforts via Data as a Service (DaaS)

    - by Mike Stiles
    The following is the 3rd in a series of posts on the value of leveraging social data across your enterprise by Oracle VP Product Development Don Springer and Oracle Cloud Data and Insight Service Sr. Director Product Management Niraj Deo. In this post, we will discuss the approach and value of integrating additional “public” data via a cloud-based Data-as-as-Service platform (or DaaS) to augment your Socially Enabled Big Data Analytics and CX Management. Let’s assume you have a functional Social-CRM platform in place. You are now successfully and continuously listening and learning from your customers and key constituents in Social Media, you are identifying relevant posts and following up with direct engagement where warranted (both 1:1, 1:community, 1:all), and you are starting to integrate signals for communication into your appropriate Customer Experience (CX) Management systems as well as insights for analysis in your business intelligence application. What is the next step? Augmenting Social Data with other Public Data for More Advanced Analytics When we say advanced analytics, we are talking about understanding causality and correlation from a wide variety, volume and velocity of data to Key Performance Indicators (KPI) to achieve and optimize business value. And in some cases, to predict future performance to make appropriate course corrections and change the outcome to your advantage while you can. The data to acquire, process and analyze this is very nuanced: It can vary across structured, semi-structured, and unstructured data It can span across content, profile, and communities of profiles data It is increasingly public, curated and user generated The key is not just getting the data, but making it value-added data and using it to help discover the insights to connect to and improve your KPIs. As we spend time working with our larger customers on advanced analytics, we have seen a need arise for more business applications to have the ability to ingest and use “quality” curated, social, transactional reference data and corresponding insights. The challenge for the enterprise has been getting this data inline into an easily accessible system and providing the contextual integration of the underlying data enriched with insights to be exported into the enterprise’s business applications. The following diagram shows the requirements for this next generation data and insights service or (DaaS): Some quick points on these requirements: Public Data, which in this context is about Common Business Entities, such as - Customers, Suppliers, Partners, Competitors (all are organizations) Contacts, Consumers, Employees (all are people) Products, Brands This data can be broadly categorized incrementally as - Base Utility data (address, industry classification) Public Master Reference data (trade style, hierarchy) Social/Web data (News, Feeds, Graph) Transactional Data generated by enterprise process, workflows etc. This Data has traits of high-volume, variety, velocity etc., and the technology needed to efficiently integrate this data for your needs includes - Change management of Public Reference Data across all categories Applied Big Data to extract statics as well as real-time insights Knowledge Diagnostics and Data Mining As you consider how to deploy this solution, many of our customers will be using an online “cloud” service that provides quality data and insights uniformly to all their necessary applications. In addition, they are requesting a service that is: Agile and Easy to Use: Applications integrated with the service can obtain data on-demand, quickly and simply Cost-effective: Pre-integrated into applications so customers don’t have to Has High Data Quality: Single point access to reference data for data quality and linkages to transactional, curated and social data Supports Data Governance: Becomes more manageable and cost-effective since control of data privacy and compliance can be enforced in a centralized place Data-as-a-Service (DaaS) Just as the cloud has transformed and now offers a better path for how an enterprise manages its IT from their infrastructure, platform, and software (IaaS, PaaS, and SaaS), the next step is data (DaaS). Over the last 3 years, we have seen the market begin to offer a cloud-based data service and gain initial traction. On one side of the DaaS continuum, we see an “appliance” type of service that provides a single, reliable source of accurate business data plus social information about accounts, leads, contacts, etc. On the other side of the continuum we see more of an online market “exchange” approach where ISVs and Data Publishers can publish and sell premium datasets within the exchange, with the exchange providing a rich set of web interfaces to improve the ease of data integration. Why the difference? It depends on the provider’s philosophy on how fast the rate of commoditization of certain data types will occur. How do you decide the best approach? Our perspective, as shown in the diagram below, is that the enterprise should develop an elastic schema to support multi-domain applicability. This allows the enterprise to take the most flexible approach to harness the speed and breadth of public data to achieve value. The key tenet of the proposed approach is that an enterprise carefully federates common utility, master reference data end points, mobility considerations and content processing, so that they are pervasively available. One way you may already be familiar with this approach is in how you do Address Verification treatments for accounts, contacts etc. If you design and revise this service in such a way that it is also easily available to social analytic needs, you could extend this to launch geo-location based social use cases (marketing, sales etc.). Our fundamental belief is that value-added data achieved through enrichment with specialized algorithms, as well as applying business “know-how” to weight-factor KPIs based on innovative combinations across an ever-increasing variety, volume and velocity of data, will be where real value is achieved. Essentially, Data-as-a-Service becomes a single entry point for the ever-increasing richness and volume of public data, with enrichment and combined capabilities to extract and integrate the right data from the right sources with the right factoring at the right time for faster decision-making and action within your core business applications. As more data becomes available (and in many cases commoditized), this value-added data processing approach will provide you with ongoing competitive advantage. Let’s look at a quick example of creating a master reference relationship that could be used as an input for a variety of your already existing business applications. In phase 1, a simple master relationship is achieved between a company (e.g. General Motors) and a variety of car brands’ social insights. The reference data allows for easy sort, export and integration into a set of CRM use cases for analytics, sales and marketing CRM. In phase 2, as you create more data relationships (e.g. competitors, contacts, other brands) to have broader and deeper references (social profiles, social meta-data) for more use cases across CRM, HCM, SRM, etc. This is just the tip of the iceberg, as the amount of master reference relationships is constrained only by your imagination and the availability of quality curated data you have to work with. DaaS is just now emerging onto the marketplace as the next step in cloud transformation. For some of you, this may be the first you have heard about it. Let us know if you have questions, or perspectives. In the meantime, we will continue to share insights as we can.Photo: Erik Araujo, stock.xchng

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  • SQL Server Developer Tools &ndash; Codename Juneau vs. Red-Gate SQL Source Control

    - by Ajarn Mark Caldwell
    So how do the new SQL Server Developer Tools (previously code-named Juneau) stack up against SQL Source Control?  Read on to find out. At the PASS Community Summit a couple of weeks ago, it was announced that the previously code-named Juneau software would be released under the name of SQL Server Developer Tools with the release of SQL Server 2012.  This replacement for Database Projects in Visual Studio (also known in a former life as Data Dude) has some great new features.  I won’t attempt to describe them all here, but I will applaud Microsoft for making major improvements.  One of my favorite changes is the way database elements are broken down.  Previously every little thing was in its own file.  For example, indexes were each in their own file.  I always hated that.  Now, SSDT uses a pattern similar to Red-Gate’s and puts the indexes and keys into the same file as the overall table definition. Of course there are really cool features to keep your database model in sync with the actual source scripts, and the rename refactoring feature is now touted as being more than just a search and replace, but rather a “semantic-aware” search and replace.  Funny, it reminds me of SQL Prompt’s Smart Rename feature.  But I’m not writing this just to criticize Microsoft and argue that they are late to the party with this feature set.  Instead, I do see it as a viable alternative for folks who want all of their source code to be version controlled, but there are a couple of key trade-offs that you need to know about when you choose which tool set to use. First, the basics Both tool sets integrate with a wide variety of source control systems including the most popular: Subversion, GIT, Vault, and Team Foundation Server.  Both tools have integrated functionality to produce objects to upgrade your target database when you are ready (DACPACs in SSDT, integration with SQL Compare for SQL Source Control).  If you regularly live in Visual Studio or the Business Intelligence Development Studio (BIDS) then SSDT will likely be comfortable for you.  Like BIDS, SSDT is a Visual Studio Project Type that comes with SQL Server, and if you don’t already have Visual Studio installed, it will install the shell for you.  If you already have Visual Studio 2010 installed, then it will just add this as an available project type.  On the other hand, if you regularly live in SQL Server Management Studio (SSMS) then you will really enjoy the SQL Source Control integration from within SSMS.  Both tool sets store their database model in script files.  In SSDT, these are on your file system like other source files; in SQL Source Control, these are stored in the folder structure in your source control system, and you can always GET them to your file system if you want to browse them directly. For me, the key differentiating factors are 1) a single, unified check-in, and 2) migration scripts.  How you value those two features will likely make your decision for you. Unified Check-In If you do a continuous-integration (CI) style of development that triggers an automated build with unit testing on every check-in of source code, and you use Visual Studio for the rest of your development, then you will want to really consider SSDT.  Because it is just another project in Visual Studio, it can be added to your existing Solution, and you can then do a complete, or unified single check-in of all changes whether they are application or database changes.  This is simply not possible with SQL Source Control because it is in a different development tool (SSMS instead of Visual Studio) and there is no way to do one unified check-in between the two.  You CAN do really fast back-to-back check-ins, but there is the possibility that the automated build that is triggered from the first check-in will cause your unit tests to fail and the CI tool to report that you broke the build.  Of course, the automated build that is triggered from the second check-in which contains the “other half” of your changes should pass and so the amount of time that the build was broken may be very, very short, but if that is very, very important to you, then SQL Source Control just won’t work; you’ll have to use SSDT. Refactoring and Migrations If you work on a mature system, or on a not-so-mature but also not-so-well-designed system, where you want to refactor the database schema as you go along, but you can’t have data suddenly disappearing from your target system, then you’ll probably want to go with SQL Source Control.  As I wrote previously, there are a number of changes which you can make to your database that the comparison tools (both from Microsoft and Red Gate) simply cannot handle without the possibility (or probability) of data loss.  Currently, SSDT only offers you the ability to inject PRE and POST custom deployment scripts.  There is no way to insert your own script in the middle to override the default behavior of the tool.  In version 3.0 of SQL Source Control (Early Access version now available) you have that ability to create your own custom migration script to take the place of the commands that the tool would have done, and ensure the preservation of your data.  Or, even if the default tool behavior would have worked, but you simply know a better way then you can take control and do things your way instead of theirs. You Decide In the environment I work in, our automated builds are not triggered off of check-ins, but off of the clock (currently once per night) and so there is no point at which the automated build and unit tests will be triggered without having both sides of the development effort already checked-in.  Therefore having a unified check-in, while handy, is not critical for us.  As for migration scripts, these are critically important to us.  We do a lot of new development on systems that have already been in production for years, and it is not uncommon for us to need to do a refactoring of the database.  Because of the maturity of the existing system, that often involves data migrations or other additional SQL tasks that the comparison tools just can’t detect on their own.  Therefore, the ability to create a custom migration script to override the tool’s default behavior is very important to us.  And so, you can see why we will continue to use Red Gate SQL Source Control for the foreseeable future.

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  • Create Auto Customization Criteria OAF Search Page

    - by PRajkumar
    1. Create a New Workspace and Project Right click Workspaces and click create new OAworkspace and name it as PRajkumarCustSearch. Automatically a new OA Project will also be created. Name the project as CustSearchDemo and package as prajkumar.oracle.apps.fnd.custsearchdemo   2. Create a New Application Module (AM) Right Click on CustSearchDemo > New > ADF Business Components > Application Module Name -- CustSearchAM Package -- prajkumar.oracle.apps.fnd.custsearchdemo.server   3. Enable Passivation for the Root UI Application Module (AM) Right Click on CustSearchAM > Edit SearchAM > Custom Properties > Name – RETENTION_LEVEL Value – MANAGE_STATE Click add > Apply > OK   4. Create Test Table and insert data some data in it (For Testing Purpose)   CREATE TABLE xx_custsearch_demo (   -- ---------------------     -- Data Columns     -- ---------------------     column1                  VARCHAR2(100),     column2                  VARCHAR2(100),     column3                  VARCHAR2(100),     column4                  VARCHAR2(100),     -- ---------------------     -- Who Columns     -- ---------------------     last_update_date    DATE         NOT NULL,     last_updated_by     NUMBER   NOT NULL,     creation_date          DATE         NOT NULL,     created_by               NUMBER   NOT NULL,     last_update_login   NUMBER  );   INSERT INTO xx_custsearch_demo VALUES('v1','v2','v3','v4',SYSDATE,0,SYSDATE,0,0); INSERT INTO xx_custsearch_demo VALUES('v1','v3','v4','v5',SYSDATE,0,SYSDATE,0,0); INSERT INTO xx_custsearch_demo VALUES('v2','v3','v4','v5',SYSDATE,0,SYSDATE,0,0); INSERT INTO xx_custsearch_demo VALUES('v3','v4','v5','v6',SYSDATE,0,SYSDATE,0,0); Now we have 4 records in our custom table   5. Create a New Entity Object (EO) Right click on SearchDemo > New > ADF Business Components > Entity Object Name – CustSearchEO Package -- prajkumar.oracle.apps.fnd.custsearchdemo.schema.server Database Objects -- XX_CUSTSEARCH_DEMO   Note – By default ROWID will be the primary key if we will not make any column to be primary key   Check the Accessors, Create Method, Validation Method and Remove Method   6. Create a New View Object (VO) Right click on CustSearchDemo > New > ADF Business Components > View Object Name -- CustSearchVO Package -- prajkumar.oracle.apps.fnd.custsearchdemo.server   In Step2 in Entity Page select CustSearchEO and shuttle them to selected list   In Step3 in Attributes Window select columns Column1, Column2, Column3, Column4, and shuttle them to selected list   In Java page deselect Generate Java file for View Object Class: CustSearchVOImpl and Select Generate Java File for View Row Class: CustSearchVORowImpl   7. Add Your View Object to Root UI Application Module Select Right click on CustSearchAM > Application Modules > Data Model Select CustSearchVO and shuttle to Data Model list   8. Create a New Page Right click on CustSearchDemo > New > Web Tier > OA Components > Page Name -- CustSearchPG Package -- prajkumar.oracle.apps.fnd.custsearchdemo.webui   9. Select the CustSearchPG and go to the strcuture pane where a default region has been created   10. Select region1 and set the following properties: ID -- PageLayoutRN Region Style -- PageLayout AM Definition -- prajkumar.oracle.apps.fnd.custsearchdemo.server.CustSearchAM Window Title – AutoCustomize Search Page Window Title – AutoCustomization Search Page Auto Footer -- True   11. Add a Query Bean to Your Page Right click on PageLayoutRN > New > Region Select new region region1 and set following properties ID – QueryRN Region Style – query Construction Mode – autoCustomizationCriteria Include Simple Panel – False Include Views Panel – False Include Advanced Panel – False   12. Create a New Region of style table Right Click on QueryRN > New > Region Using Wizard Application Module – prajkumar.oracle.apps.fnd.custsearchdemo.server.CustSearchAM Available View Usages – CustSearchVO1   In Step2 in Region Properties set following properties Region ID – CustSearchTable Region Style – Table   In Step3 in View Attributes shuttle all the items (Column1, Column2, Column3, Column4) available in “Available View Attributes” to Selected View Attributes: In Step4 in Region Items page set style to “messageStyledText” for all items   13. Select CustSearchTable in Structure Panel and set property Width to 100%   14. Include Simple Search Panel Right Click on QueryRN > New > simpleSearchPanel Automatically region2 (header Region) and region1 (MessageComponentLayout Region) created Set Following Properties for region2 Id – SimpleSearchHeader Text -- Simple Search   15. Now right click on message Component Layout Region (SimpleSearchMappings) and create two message text input beans and set the below properties to each   Message TextInputBean1 Id – SearchColumn1 Search Allowed – True Data Type – VARCHAR2 Maximum Length – CSS Class – OraFieldText Prompt – Column1   Message TextInputBean2 Id – SearchColumn2 Search Allowed -- True Data Type – VARCHAR2 Maximum Length – 100 CSS Class – OraFieldText Prompt – Column2   16. Now Right Click on query Components and create simple Search Mappings. Then automatically SimpleSearchMappings and QueryCriteriaMap1 created   17.  Now select the QueryCriteriaMap1 and set the below properties Id – SearchColumn1Map Search Item – SearchColumn1 Result Item – Column1   18. Now again right click on simpleSearchMappings -> New -> queryCriteriaMap, and then set the below properties Id – SearchColumn2Map Search Item – SearchColumn2 Result Item – Column2   19. Congratulation you have successfully finished Auto Customization Search page. Run Your CustSearchPG page and Test Your Work            

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