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• Jquery ajax get - how to output data based on condition?

  - by arunas_t

  Hello, there, I have a such piece of code: $("#choose").change(function(){ $.get("get_results.php", {name: $("#choose").val()}, function(data){ if(data !== ""){ $("#results").html(data); }else{ $("#results").html('<strong>Sorry, no records.</strong>'); } }); }); Now the problem is that the first condition ( if(data !== "") ) is always evaluated correctly and executed, but the else clause ('Sorry, no records') never shows up. Can anyone spot the error? Data passed for the else clause is specifically "". Thank You.

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• how to store data with many categories and many properties efficiently?

  - by Mickey Shine

  We have a large number of data in many categories with many properties, e.g. category 1: Book properties: BookID, BookName, BookType, BookAuthor, BookPrice category 2: Fruit properties: FruitID, FruitName, FruitShape, FruitColor, FruitPrice We have many categories like book and fruit. Obviously we can create many tables for them (MySQL e.g.), and each category a table. But this will have to create too many tables and we have to write many "adapters" to unify manipulating data. The difficulties are: 1) Every category has different properties and this results in a different data structure. 2) The properties of every categoriy may have to be changed at anytime. 3) Hard to manipulate data if each category a table (too many tables) How do you store such kind of data?

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• Which approach to create the data access layer has the highest performance?

  - by pooyakhamooshi

  I have to create a very high performance application. Currently, I am using Entity Framework for my data access layer. My application has to insert some communication data almost every second. I found that Entity Framework is slow; it has about 2 seconds delay to finish the SaveChanges() method. I was thinking I have the following options: 1. Create the data access layer myself using ADO.NET; using stored procedures or ad-hoc queries 2. Use Enterprise Library Data access Layer 3. Use NHibernate 4. Use Repository Factory: http://pooyakhamooshi.blogspot.com/search?q=repository What do you think? which one is quicker for inserting data? Which one is quicker to set up?

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• PHP: HOw to store and retrieve the data entered by a user in a text field from a file?

  - by kishore

  HI all, I want to Store the data entered by user in a file. If a user enters his description in a text field, Then i Have to store the data in a file. All the users data will go to the same file with their user name and description. And I have to retrieve The Data from that file for a particular user. For example if there are two users with their descriptions in the file, Then I have to retrieve a particular users description and print it on the users page. How can I store and retrieve The data from a file?

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• Create macro to move data in a column UP?

  - by user1786695

  I have an excel sheet of which the data was jumbled: for example, the data that should have been in Columns AB and AC were instead in Columns B and C, but on the row after. I have the following written which moved the data from B and C to AB and AC respectively: Dim rCell As Range Dim rRng As Range Set rRng = Sheet1.Range("A:A") i = 1 lastRow = ActiveSheet.Cells(Rows.Count, "A").End(xlUp).Row For Each rCell In rRng.Cells If rCell.Value = "" Then Range("AB" & i) = rCell.Offset(0, 1).Value rCell.Offset(0, 1).ClearContents End If i = i + 1 If i = lastRow + 1 Then Exit Sub End If Next rCell End Sub However, it doesn't fix the problem of the data being on the row BELOW the appropriate row now that they are in the right columns. I am new to VBA Macros so I would appreciate any help to make the data now align. I tried toggling the Offset parameter (-1,0) but it's not working.

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• Using jQuery to Insert a New Database Record

  - by Stephen Walther

  The goal of this blog entry is to explore the easiest way of inserting a new record into a database using jQuery and .NET. I’m going to explore two approaches: using Generic Handlers and using a WCF service (In a future blog entry I’ll take a look at OData and WCF Data Services). Create the ASP.NET Project I’ll start by creating a new empty ASP.NET application with Visual Studio 2010. Select the menu option File, New Project and select the ASP.NET Empty Web Application project template. Setup the Database and Data Model I’ll use my standard MoviesDB.mdf movies database. This database contains one table named Movies that looks like this: I’ll use the ADO.NET Entity Framework to represent my database data: Select the menu option Project, Add New Item and select the ADO.NET Entity Data Model project item. Name the data model MoviesDB.edmx and click the Add button. In the Choose Model Contents step, select Generate from database and click the Next button. In the Choose Your Data Connection step, leave all of the defaults and click the Next button. In the Choose Your Data Objects step, select the Movies table and click the Finish button. Unfortunately, Visual Studio 2010 cannot spell movie correctly :) You need to click on Movy and change the name of the class to Movie. In the Properties window, change the Entity Set Name to Movies. Using a Generic Handler In this section, we’ll use jQuery with an ASP.NET generic handler to insert a new record into the database. A generic handler is similar to an ASP.NET page, but it does not have any of the overhead. It consists of one method named ProcessRequest(). Select the menu option Project, Add New Item and select the Generic Handler project item. Name your new generic handler InsertMovie.ashx and click the Add button. Modify your handler so it looks like Listing 1: Listing 1 – InsertMovie.ashx using System.Web; namespace WebApplication1 { /// <summary> /// Inserts a new movie into the database /// </summary> public class InsertMovie : IHttpHandler { private MoviesDBEntities _dataContext = new MoviesDBEntities(); public void ProcessRequest(HttpContext context) { context.Response.ContentType = "text/plain"; // Extract form fields var title = context.Request["title"]; var director = context.Request["director"]; // Create movie to insert var movieToInsert = new Movie { Title = title, Director = director }; // Save new movie to DB _dataContext.AddToMovies(movieToInsert); _dataContext.SaveChanges(); // Return success context.Response.Write("success"); } public bool IsReusable { get { return true; } } } } In Listing 1, the ProcessRequest() method is used to retrieve a title and director from form parameters. Next, a new Movie is created with the form values. Finally, the new movie is saved to the database and the string “success” is returned. Using jQuery with the Generic Handler We can call the InsertMovie.ashx generic handler from jQuery by using the standard jQuery post() method. The following HTML page illustrates how you can retrieve form field values and post the values to the generic handler: Listing 2 – Default.htm <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Add Movie</title> <script src="http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js" type="text/javascript"></script> </head> <body> <form> <label>Title:</label> <input name="title" /> <br /> <label>Director:</label> <input name="director" /> </form> <button id="btnAdd">Add Movie</button> <script type="text/javascript"> $("#btnAdd").click(function () { $.post("InsertMovie.ashx", $("form").serialize(), insertCallback); }); function insertCallback(result) { if (result == "success") { alert("Movie added!"); } else { alert("Could not add movie!"); } } </script> </body> </html>     When you open the page in Listing 2 in a web browser, you get a simple HTML form: Notice that the page in Listing 2 includes the jQuery library. The jQuery library is included with the following SCRIPT tag: <script src="http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js" type="text/javascript"></script> The jQuery library is included on the Microsoft Ajax CDN so you can always easily include the jQuery library in your applications. You can learn more about the CDN at this website: http://www.asp.net/ajaxLibrary/cdn.ashx When you click the Add Movie button, the jQuery post() method is called to post the form data to the InsertMovie.ashx generic handler. Notice that the form values are serialized into a URL encoded string by calling the jQuery serialize() method. The serialize() method uses the name attribute of form fields and not the id attribute. Notes on this Approach This is a very low-level approach to interacting with .NET through jQuery – but it is simple and it works! And, you don’t need to use any JavaScript libraries in addition to the jQuery library to use this approach. The signature for the jQuery post() callback method looks like this: callback(data, textStatus, XmlHttpRequest) The second parameter, textStatus, returns the HTTP status code from the server. I tried returning different status codes from the generic handler with an eye towards implementing server validation by returning a status code such as 400 Bad Request when validation fails (see http://www.w3.org/Protocols/rfc2616/rfc2616-sec10.html ). I finally figured out that the callback is not invoked when the textStatus has any value other than “success”. Using a WCF Service As an alternative to posting to a generic handler, you can create a WCF service. You create a new WCF service by selecting the menu option Project, Add New Item and selecting the Ajax-enabled WCF Service project item. Name your WCF service InsertMovie.svc and click the Add button. Modify the WCF service so that it looks like Listing 3: Listing 3 – InsertMovie.svc using System.ServiceModel; using System.ServiceModel.Activation; namespace WebApplication1 { [ServiceBehavior(IncludeExceptionDetailInFaults=true)] [ServiceContract(Namespace = "")] [AspNetCompatibilityRequirements(RequirementsMode = AspNetCompatibilityRequirementsMode.Allowed)] public class MovieService { private MoviesDBEntities _dataContext = new MoviesDBEntities(); [OperationContract] public bool Insert(string title, string director) { // Create movie to insert var movieToInsert = new Movie { Title = title, Director = director }; // Save new movie to DB _dataContext.AddToMovies(movieToInsert); _dataContext.SaveChanges(); // Return movie (with primary key) return true; } } }   The WCF service in Listing 3 uses the Entity Framework to insert a record into the Movies database table. The service always returns the value true. Notice that the service in Listing 3 includes the following attribute: [ServiceBehavior(IncludeExceptionDetailInFaults=true)] You need to include this attribute if you want to get detailed error information back to the client. When you are building an application, you should always include this attribute. When you are ready to release your application, you should remove this attribute for security reasons. Using jQuery with the WCF Service Calling a WCF service from jQuery requires a little more work than calling a generic handler from jQuery. Here are some good blog posts on some of the issues with using jQuery with WCF: http://encosia.com/2008/06/05/3-mistakes-to-avoid-when-using-jquery-with-aspnet-ajax/ http://encosia.com/2008/03/27/using-jquery-to-consume-aspnet-json-web-services/ http://weblogs.asp.net/scottgu/archive/2007/04/04/json-hijacking-and-how-asp-net-ajax-1-0-mitigates-these-attacks.aspx http://www.west-wind.com/Weblog/posts/896411.aspx http://www.west-wind.com/weblog/posts/324917.aspx http://professionalaspnet.com/archive/tags/WCF/default.aspx The primary requirement when calling WCF from jQuery is that the request use JSON: The request must include a content-type:application/json header. Any parameters included with the request must be JSON encoded. Unfortunately, jQuery does not include a method for serializing JSON (Although, oddly, jQuery does include a parseJSON() method for deserializing JSON). Therefore, we need to use an additional library to handle the JSON serialization. The page in Listing 4 illustrates how you can call a WCF service from jQuery. Listing 4 – Default2.aspx <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <title>Add Movie</title> <script src="http://ajax.microsoft.com/ajax/jquery/jquery-1.4.2.js" type="text/javascript"></script> <script src="Scripts/json2.js" type="text/javascript"></script> </head> <body> <form> <label>Title:</label> <input id="title" /> <br /> <label>Director:</label> <input id="director" /> </form> <button id="btnAdd">Add Movie</button> <script type="text/javascript"> $("#btnAdd").click(function () { // Convert the form into an object var data = { title: $("#title").val(), director: $("#director").val() }; // JSONify the data data = JSON.stringify(data); // Post it $.ajax({ type: "POST", contentType: "application/json; charset=utf-8", url: "MovieService.svc/Insert", data: data, dataType: "json", success: insertCallback }); }); function insertCallback(result) { // unwrap result result = result["d"]; if (result === true) { alert("Movie added!"); } else { alert("Could not add movie!"); } } </script> </body> </html> There are several things to notice about Listing 4. First, notice that the page includes both the jQuery library and Douglas Crockford’s JSON2 library: <script src="Scripts/json2.js" type="text/javascript"></script> You need to include the JSON2 library to serialize the form values into JSON. You can download the JSON2 library from the following location: http://www.json.org/js.html When you click the button to submit the form, the form data is converted into a JavaScript object: // Convert the form into an object var data = { title: $("#title").val(), director: $("#director").val() }; Next, the data is serialized into JSON using the JSON2 library: // JSONify the data var data = JSON.stringify(data); Finally, the form data is posted to the WCF service by calling the jQuery ajax() method: // Post it $.ajax({   type: "POST",   contentType: "application/json; charset=utf-8",   url: "MovieService.svc/Insert",   data: data,   dataType: "json",   success: insertCallback }); You can’t use the standard jQuery post() method because you must set the content-type of the request to be application/json. Otherwise, the WCF service will reject the request for security reasons. For details, see the Scott Guthrie blog post: http://weblogs.asp.net/scottgu/archive/2007/04/04/json-hijacking-and-how-asp-net-ajax-1-0-mitigates-these-attacks.aspx The insertCallback() method is called when the WCF service returns a response. This method looks like this: function insertCallback(result) {   // unwrap result   result = result["d"];   if (result === true) {       alert("Movie added!");   } else {     alert("Could not add movie!");   } } When we called the jQuery ajax() method, we set the dataType to JSON. That causes the jQuery ajax() method to deserialize the response from the WCF service from JSON into a JavaScript object automatically. The following value is passed to the insertCallback method: {"d":true} For security reasons, a WCF service always returns a response with a “d” wrapper. The following line of code removes the “d” wrapper: // unwrap result result = result["d"]; To learn more about the “d” wrapper, I recommend that you read the following blog posts: http://encosia.com/2009/02/10/a-breaking-change-between-versions-of-aspnet-ajax/ http://encosia.com/2009/06/29/never-worry-about-asp-net-ajaxs-d-again/ Summary In this blog entry, I explored two methods of inserting a database record using jQuery and .NET. First, we created a generic handler and called the handler from jQuery. This is a very low-level approach. However, it is a simple approach that works. Next, we looked at how you can call a WCF service using jQuery. This approach required a little more work because you need to serialize objects into JSON. We used the JSON2 library to perform the serialization. In the next blog post, I want to explore how you can use jQuery with OData and WCF Data Services.

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• Working with PivotTables in Excel

  - by Mark Virtue

  PivotTables are one of the most powerful features of Microsoft Excel.  They allow large amounts of data to be analyzed and summarized in just a few mouse clicks. In this article, we explore PivotTables, understand what they are, and learn how to create and customize them. Note:  This article is written using Excel 2010 (Beta).  The concept of a PivotTable has changed little over the years, but the method of creating one has changed in nearly every iteration of Excel.  If you are using a version of Excel that is not 2010, expect different screens from the ones you see in this article. A Little History In the early days of spreadsheet programs, Lotus 1-2-3 ruled the roost.  Its dominance was so complete that people thought it was a waste of time for Microsoft to bother developing their own spreadsheet software (Excel) to compete with Lotus.  Flash-forward to 2010, and Excel’s dominance of the spreadsheet market is greater than Lotus’s ever was, while the number of users still running Lotus 1-2-3 is approaching zero.  How did this happen?  What caused such a dramatic reversal of fortunes? Industry analysts put it down to two factors:  Firstly, Lotus decided that this fancy new GUI platform called “Windows” was a passing fad that would never take off.  They declined to create a Windows version of Lotus 1-2-3 (for a few years, anyway), predicting that their DOS version of the software was all anyone would ever need.  Microsoft, naturally, developed Excel exclusively for Windows.  Secondly, Microsoft developed a feature for Excel that Lotus didn’t provide in 1-2-3, namely PivotTables.  The PivotTables feature, exclusive to Excel, was deemed so staggeringly useful that people were willing to learn an entire new software package (Excel) rather than stick with a program (1-2-3) that didn’t have it.  This one feature, along with the misjudgment of the success of Windows, was the death-knell for Lotus 1-2-3, and the beginning of the success of Microsoft Excel. Understanding PivotTables So what is a PivotTable, exactly? Put simply, a PivotTable is a summary of some data, created to allow easy analysis of said data.  But unlike a manually created summary, Excel PivotTables are interactive.  Once you have created one, you can easily change it if it doesn’t offer the exact insights into your data that you were hoping for.  In a couple of clicks the summary can be “pivoted” – rotated in such a way that the column headings become row headings, and vice versa.  There’s a lot more that can be done, too.  Rather than try to describe all the features of PivotTables, we’ll simply demonstrate them… The data that you analyze using a PivotTable can’t be just any data – it has to be raw data, previously unprocessed (unsummarized) – typically a list of some sort.  An example of this might be the list of sales transactions in a company for the past six months. Examine the data shown below: Notice that this is not raw data.  In fact, it is already a summary of some sort.  In cell B3 we can see $30,000, which apparently is the total of James Cook’s sales for the month of January.  So where is the raw data?  How did we arrive at the figure of $30,000?  Where is the original list of sales transactions that this figure was generated from?  It’s clear that somewhere, someone must have gone to the trouble of collating all of the sales transactions for the past six months into the summary we see above.  How long do you suppose this took?  An hour?  Ten?  Probably. If we were to track down the original list of sales transactions, it might look something like this: You may be surprised to learn that, using the PivotTable feature of Excel, we can create a monthly sales summary similar to the one above in a few seconds, with only a few mouse clicks.  We can do this – and a lot more too! How to Create a PivotTable First, ensure that you have some raw data in a worksheet in Excel.  A list of financial transactions is typical, but it can be a list of just about anything:  Employee contact details, your CD collection, or fuel consumption figures for your company’s fleet of cars. So we start Excel… …and we load such a list… Once we have the list open in Excel, we’re ready to start creating the PivotTable. Click on any one single cell within the list: Then, from the Insert tab, click the PivotTable icon: The Create PivotTable box appears, asking you two questions:  What data should your new PivotTable be based on, and where should it be created?  Because we already clicked on a cell within the list (in the step above), the entire list surrounding that cell is already selected for us ($A$1:$G$88 on the Payments sheet, in this example).  Note that we could select a list in any other region of any other worksheet, or even some external data source, such as an Access database table, or even a MS-SQL Server database table.  We also need to select whether we want our new PivotTable to be created on a new worksheet, or on an existing one.  In this example we will select a new one: The new worksheet is created for us, and a blank PivotTable is created on that worksheet: Another box also appears:  The PivotTable Field List.  This field list will be shown whenever we click on any cell within the PivotTable (above): The list of fields in the top part of the box is actually the collection of column headings from the original raw data worksheet.  The four blank boxes in the lower part of the screen allow us to choose the way we would like our PivotTable to summarize the raw data.  So far, there is nothing in those boxes, so the PivotTable is blank.  All we need to do is drag fields down from the list above and drop them in the lower boxes.  A PivotTable is then automatically created to match our instructions.  If we get it wrong, we only need to drag the fields back to where they came from and/or drag new fields down to replace them. The Values box is arguably the most important of the four.  The field that is dragged into this box represents the data that needs to be summarized in some way (by summing, averaging, finding the maximum, minimum, etc).  It is almost always numerical data.  A perfect candidate for this box in our sample data is the “Amount” field/column.  Let’s drag that field into the Values box: Notice that (a) the “Amount” field in the list of fields is now ticked, and “Sum of Amount” has been added to the Values box, indicating that the amount column has been summed. If we examine the PivotTable itself, we indeed find the sum of all the “Amount” values from the raw data worksheet: We’ve created our first PivotTable!  Handy, but not particularly impressive.  It’s likely that we need a little more insight into our data than that. Referring to our sample data, we need to identify one or more column headings that we could conceivably use to split this total.  For example, we may decide that we would like to see a summary of our data where we have a row heading for each of the different salespersons in our company, and a total for each.  To achieve this, all we need to do is to drag the “Salesperson” field into the Row Labels box: Now, finally, things start to get interesting!  Our PivotTable starts to take shape….   With a couple of clicks we have created a table that would have taken a long time to do manually. So what else can we do?  Well, in one sense our PivotTable is complete.  We’ve created a useful summary of our source data.  The important stuff is already learned!  For the rest of the article, we will examine some ways that more complex PivotTables can be created, and ways that those PivotTables can be customized. First, we can create a two-dimensional table.  Let’s do that by using “Payment Method” as a column heading.  Simply drag the “Payment Method” heading to the Column Labels box: Which looks like this: Starting to get very cool! Let’s make it a three-dimensional table.  What could such a table possibly look like?  Well, let’s see… Drag the “Package” column/heading to the Report Filter box: Notice where it ends up…. This allows us to filter our report based on which “holiday package” was being purchased.  For example, we can see the breakdown of salesperson vs payment method for all packages, or, with a couple of clicks, change it to show the same breakdown for the “Sunseekers” package: And so, if you think about it the right way, our PivotTable is now three-dimensional.  Let’s keep customizing… If it turns out, say, that we only want to see cheque and credit card transactions (i.e. no cash transactions), then we can deselect the “Cash” item from the column headings.  Click the drop-down arrow next to Column Labels, and untick “Cash”: Let’s see what that looks like…As you can see, “Cash” is gone. Formatting This is obviously a very powerful system, but so far the results look very plain and boring.  For a start, the numbers that we’re summing do not look like dollar amounts – just plain old numbers.  Let’s rectify that. A temptation might be to do what we’re used to doing in such circumstances and simply select the whole table (or the whole worksheet) and use the standard number formatting buttons on the toolbar to complete the formatting.  The problem with that approach is that if you ever change the structure of the PivotTable in the future (which is 99% likely), then those number formats will be lost.  We need a way that will make them (semi-)permanent. First, we locate the “Sum of Amount” entry in the Values box, and click on it.  A menu appears.  We select Value Field Settings… from the menu: The Value Field Settings box appears. Click the Number Format button, and the standard Format Cells box appears: From the Category list, select (say) Accounting, and drop the number of decimal places to 0.  Click OK a few times to get back to the PivotTable… As you can see, the numbers have been correctly formatted as dollar amounts. While we’re on the subject of formatting, let’s format the entire PivotTable.  There are a few ways to do this.  Let’s use a simple one… Click the PivotTable Tools/Design tab: Then drop down the arrow in the bottom-right of the PivotTable Styles list to see a vast collection of built-in styles: Choose any one that appeals, and look at the result in your PivotTable:   Other Options We can work with dates as well.  Now usually, there are many, many dates in a transaction list such as the one we started with.  But Excel provides the option to group data items together by day, week, month, year, etc.  Let’s see how this is done. First, let’s remove the “Payment Method” column from the Column Labels box (simply drag it back up to the field list), and replace it with the “Date Booked” column: As you can see, this makes our PivotTable instantly useless, giving us one column for each date that a transaction occurred on – a very wide table! To fix this, right-click on any date and select Group… from the context-menu: The grouping box appears.  We select Months and click OK: Voila!  A much more useful table: (Incidentally, this table is virtually identical to the one shown at the beginning of this article – the original sales summary that was created manually.) Another cool thing to be aware of is that you can have more than one set of row headings (or column headings): …which looks like this…. You can do a similar thing with column headings (or even report filters). Keeping things simple again, let’s see how to plot averaged values, rather than summed values. First, click on “Sum of Amount”, and select Value Field Settings… from the context-menu that appears: In the Summarize value field by list in the Value Field Settings box, select Average: While we’re here, let’s change the Custom Name, from “Average of Amount” to something a little more concise.  Type in something like “Avg”: Click OK, and see what it looks like.  Notice that all the values change from summed totals to averages, and the table title (top-left cell) has changed to “Avg”: If we like, we can even have sums, averages and counts (counts = how many sales there were) all on the same PivotTable! Here are the steps to get something like that in place (starting from a blank PivotTable): Drag “Salesperson” into the Column Labels Drag “Amount” field down into the Values box three times For the first “Amount” field, change its custom name to “Total” and it’s number format to Accounting (0 decimal places) For the second “Amount” field, change its custom name to “Average”, its function to Average and it’s number format to Accounting (0 decimal places) For the third “Amount” field, change its name to “Count” and its function to Count Drag the automatically created field from Column Labels to Row Labels Here’s what we end up with: Total, average and count on the same PivotTable! Conclusion There are many, many more features and options for PivotTables created by Microsoft Excel – far too many to list in an article like this.  To fully cover the potential of PivotTables, a small book (or a large website) would be required.  Brave and/or geeky readers can explore PivotTables further quite easily:  Simply right-click on just about everything, and see what options become available to you.  There are also the two ribbon-tabs: PivotTable Tools/Options and Design.  It doesn’t matter if you make a mistake – it’s easy to delete the PivotTable and start again – a possibility old DOS users of Lotus 1-2-3 never had. We’ve included an Excel that should work with most versions of Excel, so you can download to practice your PivotTable skills. Download Our Practice Excel File Similar Articles Productive Geek Tips Magnify Selected Cells In Excel 2007Share Access Data with Excel in Office 2010Make Excel 2007 Print Gridlines In Workbook FileMake Excel 2007 Always Save in Excel 2003 FormatConvert Older Excel Documents to Excel 2007 Format TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional Ben & Jerry’s Free Cone Day, 3/23/10 New Stinger from McAfee Helps Remove ‘FakeAlert’ Threats Google Apps Marketplace: Tools & Services For Google Apps Users Get News Quick and Precise With Newser Scan for Viruses in Ubuntu using ClamAV Replace Your Windows Task Manager With System Explorer

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• MySQL for Excel 1.3.0 Beta has been released

  - by Javier Treviño

  The MySQL Windows Experience Team is proud to announce the release of MySQL for Excel version 1.3.0.  This is a beta release for 1.3.x. MySQL for Excel is an application plug-in enabling data analysts to very easily access and manipulate MySQL data within Microsoft Excel. It enables you to directly work with a MySQL database from within Microsoft Excel so you can easily do tasks such as: Importing MySQL data into Excel Exporting Excel data directly into MySQL to a new or existing table Editing MySQL data directly within Excel As this is a beta version the MySQL for Excel product can be downloaded only by using the product standalone installer at this link http://dev.mysql.com/downloads/windows/excel/ Your feedback on this beta version is very well appreciated, you can raise bugs on the MySQL bugs page or give us your comments on the MySQL for Excel forum. Changes in MySQL for Excel 1.3.0 (2014-06-06, Beta) This section documents all changes and bug fixes applied to MySQL for Excel since the release of 1.2.1. Several new features were added, for more information see What Is New In MySQL for Excel (http://dev.mysql.com/doc/refman/5.6/en/mysql-for-excel-what-is-new.html). Known limitations: Upgrading from versions MySQL for Excel 1.2.0 and lower is not possible due to a bug fixed in MySQL for Excel 1.2.1. In that scenario, the old version (MySQL for Excel 1.2.0 or lower) must be uninstalled first. Upgrading from version 1.2.1 works correctly. <CTRL> + <A> cannot be used to select all database objects. Either <SHIFT> + <Arrow Key> or <CTRL> + click must be used instead. PivotTables are normally placed to the right (skipping one column) of the imported data, they will not be created if there is another existing Excel object at that position. Functionality Added or Changed Imported data can now be refreshed by using the native Refresh feature. Fields in the imported data sheet are then updated against the live MySQL database using the saved connection ID. Functionality was added to import data directly into PivotTables, which can be created from any Import operation. Multiple objects (tables and views) can now be imported into Excel, when before only one object could be selected. Relational information is also utilized when importing multiple objects. All options now have descriptive tooltips. Hovering over an option/preference displays helpful information about its use. A new Export Data, Advanced Options option was added that shows all available data types in the Data Type combo box, instead of only showing a subset of the most popular data types. The option dialogs now include a Refresh to Defaults button that resets the dialog's options to their defaults values. Each option dialog is set individually. A new Add Summary Fields for Numeric Columns option was added to the Import Data dialog that automatically adds summary fields for numeric data after the last row of the imported data. The specific summary function is selectable from many options, such as "Total" and "Average." A new collation option was added for the schema and table creation wizards. The default schema collation is "Server Default", and the default table collation is "Schema Default". Collation options may be selected from a drop-down list of all available collations. Quick links: MySQL for Excel documentation: http://dev.mysql.com/doc/en/mysql-for-excel.html. MySQL on Windows blog: http://blogs.oracle.com/MySQLOnWindows. MySQL for Excel forum: http://forums.mysql.com/list.php?172. MySQL YouTube channel: http://www.youtube.com/user/MySQLChannel. Enjoy and thanks for the support! 

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• Get XML from Server for Use on Windows Phone

  - by psheriff

  When working with mobile devices you always need to take into account bandwidth usage and power consumption. If you are constantly connecting to a server to retrieve data for an input screen, then you might think about moving some of that data down to the phone and cache the data on the phone. An example would be a static list of US State Codes that you are asking the user to select from. Since this is data that does not change very often, this is one set of data that would be great to cache on the phone. Since the Windows Phone does not have an embedded database, you can just use an XML string stored in Isolated Storage. Of course, then you need to figure out how to get data down to the phone. You can either ship it with the application, or connect and retrieve the data from your server one time and thereafter cache it and retrieve it from the cache. In this blog post you will see how to create a WCF service to retrieve data from a Product table in a database and send that data as XML to the phone and store it in Isolated Storage. You will then read that data from Isolated Storage using LINQ to XML and display it in a ListBox. Step 1: Create a Windows Phone Application The first step is to create a Windows Phone application called WP_GetXmlFromDataSet (or whatever you want to call it). On the MainPage.xaml add the following XAML within the “ContentPanel” grid: <StackPanel>  <Button Name="btnGetXml"          Content="Get XML"          Click="btnGetXml_Click" />  <Button Name="btnRead"          Content="Read XML"          IsEnabled="False"          Click="btnRead_Click" />  <ListBox Name="lstData"            Height="430"            ItemsSource="{Binding}"            DisplayMemberPath="ProductName" /></StackPanel> Now it is time to create the WCF Service Application that you will call to get the XML from a table in a SQL Server database. Step 2: Create a WCF Service Application Add a new project to your solution called WP_GetXmlFromDataSet.Services. Delete the IService1.* and Service1.* files and the App_Data folder, as you don’t generally need these items. Add a new WCF Service class called ProductService. In the IProductService class modify the void DoWork() method with the following code: [OperationContract]string GetProductXml(); Open the code behind in the ProductService.svc and create the GetProductXml() method. This method (shown below) will connect up to a database and retrieve data from a Product table. public string GetProductXml(){  string ret = string.Empty;  string sql = string.Empty;  SqlDataAdapter da;  DataSet ds = new DataSet();   sql = "SELECT ProductId, ProductName,";  sql += " IntroductionDate, Price";  sql += " FROM Product";   da = new SqlDataAdapter(sql,    ConfigurationManager.ConnectionStrings["Sandbox"].ConnectionString);   da.Fill(ds);   // Create Attribute based XML  foreach (DataColumn col in ds.Tables[0].Columns)  {    col.ColumnMapping = MappingType.Attribute;  }   ds.DataSetName = "Products";  ds.Tables[0].TableName = "Product";  ret = ds.GetXml();   return ret;} After retrieving the data from the Product table using a DataSet, you will want to set each column’s ColumnMapping property to Attribute. Using attribute based XML will make the data transferred across the wire a little smaller. You then set the DataSetName property to the top-level element name you want to assign to the XML. You then set the TableName property on the DataTable to the name you want each element to be in your XML. The last thing you need to do is to call the GetXml() method on the DataSet object which will return an XML string of the data in your DataSet object. This is the value that you will return from the service call. The XML that is returned from the above call looks like the following: <Products>  <Product ProductId="1"           ProductName="PDSA .NET Productivity Framework"           IntroductionDate="9/3/2010"           Price="5000" />  <Product ProductId="3"           ProductName="Haystack Code Generator for .NET"           IntroductionDate="7/1/2010"           Price="599.00" />  ...  ...  ... </Products> The GetProductXml() method uses a connection string from the Web.Config file, so add a <connectionStrings> element to the Web.Config file in your WCF Service application. Modify the settings shown below as needed for your server and database name. <connectionStrings>  <add name="Sandbox"        connectionString="Server=Localhost;Database=Sandbox;                         Integrated Security=Yes"/></connectionStrings> The Product Table You will need a Product table that you can read data from. I used the following structure for my product table. Add any data you want to this table after you create it in your database. CREATE TABLE Product(  ProductId int PRIMARY KEY IDENTITY(1,1) NOT NULL,  ProductName varchar(50) NOT NULL,  IntroductionDate datetime NULL,  Price money NULL) Step 3: Connect to WCF Service from Windows Phone Application Back in your Windows Phone application you will now need to add a Service Reference to the WCF Service application you just created. Right-mouse click on the Windows Phone Project and choose Add Service Reference… from the context menu. Click on the Discover button. In the Namespace text box enter “ProductServiceRefrence”, then click the OK button. If you entered everything correctly, Visual Studio will generate some code that allows you to connect to your Product service. On the MainPage.xaml designer window double click on the Get XML button to generate the Click event procedure for this button. In the Click event procedure make a call to a GetXmlFromServer() method. This method will also need a “Completed” event procedure to be written since all communication with a WCF Service from Windows Phone must be asynchronous.  Write these two methods as follows: private const string KEY_NAME = "ProductData"; private void GetXmlFromServer(){  ProductServiceClient client = new ProductServiceClient();   client.GetProductXmlCompleted += new     EventHandler<GetProductXmlCompletedEventArgs>      (client_GetProductXmlCompleted);   client.GetProductXmlAsync();  client.CloseAsync();} void client_GetProductXmlCompleted(object sender,                                   GetProductXmlCompletedEventArgs e){  // Store XML data in Isolated Storage  IsolatedStorageSettings.ApplicationSettings[KEY_NAME] = e.Result;   btnRead.IsEnabled = true;} As you can see, this is a fairly standard call to a WCF Service. In the Completed event you get the Result from the event argument, which is the XML, and store it into Isolated Storage using the IsolatedStorageSettings.ApplicationSettings class. Notice the constant that I added to specify the name of the key. You will use this constant later to read the data from Isolated Storage. Step 4: Create a Product Class Even though you stored XML data into Isolated Storage when you read that data out you will want to convert each element in the XML file into an actual Product object. This means that you need to create a Product class in your Windows Phone application. Add a Product class to your project that looks like the code below: public class Product{  public string ProductName{ get; set; }  public int ProductId{ get; set; }  public DateTime IntroductionDate{ get; set; }  public decimal Price{ get; set; }} Step 5: Read Settings from Isolated Storage Now that you have the XML data stored in Isolated Storage, it is time to use it. Go back to the MainPage.xaml design view and double click on the Read XML button to generate the Click event procedure. From the Click event procedure call a method named ReadProductXml().Create this method as shown below: private void ReadProductXml(){  XElement xElem = null;   if (IsolatedStorageSettings.ApplicationSettings.Contains(KEY_NAME))  {    xElem = XElement.Parse(     IsolatedStorageSettings.ApplicationSettings[KEY_NAME].ToString());     // Create a list of Product objects    var products =         from prod in xElem.Descendants("Product")        orderby prod.Attribute("ProductName").Value        select new Product        {          ProductId = Convert.ToInt32(prod.Attribute("ProductId").Value),          ProductName = prod.Attribute("ProductName").Value,          IntroductionDate =             Convert.ToDateTime(prod.Attribute("IntroductionDate").Value),          Price = Convert.ToDecimal(prod.Attribute("Price").Value)        };     lstData.DataContext = products;  }} The ReadProductXml() method checks to make sure that the key name that you saved your XML as exists in Isolated Storage prior to trying to open it. If the key name exists, then you retrieve the value as a string. Use the XElement’s Parse method to convert the XML string to a XElement object. LINQ to XML is used to iterate over each element in the XElement object and create a new Product object from each attribute in your XML file. The LINQ to XML code also orders the XML data by the ProductName. After the LINQ to XML code runs you end up with an IEnumerable collection of Product objects in the variable named “products”. You assign this collection of product data to the DataContext of the ListBox you created in XAML. The DisplayMemberPath property of the ListBox is set to “ProductName” so it will now display the product name for each row in your products collection. Summary In this article you learned how to retrieve an XML string from a table in a database, return that string across a WCF Service and store it into Isolated Storage on your Windows Phone. You then used LINQ to XML to create a collection of Product objects from the data stored and display that data in a Windows Phone list box. This same technique can be used in Silverlight or WPF applications too. NOTE: You can download the complete sample code at my website. http://www.pdsa.com/downloads. Choose Tips & Tricks, then "Get XML From Server for Use on Windows Phone" from the drop-down. Good Luck with your Coding,Paul Sheriff ** SPECIAL OFFER FOR MY BLOG READERS **Visit http://www.pdsa.com/Event/Blog for a free video on Silverlight entitled Silverlight XAML for the Complete Novice - Part 1.  

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• If the model is validating the data, shouldn't it throw exceptions on bad input?

  - by Carlos Campderrós

  Reading this SO question it seems that throwing exceptions for validating user input is frowned upon. But who should validate this data? In my applications, all validations are done in the business layer, because only the class itself really knows which values are valid for each one of its properties. If I were to copy the rules for validating a property to the controller, it is possible that the validation rules change and now there are two places where the modification should be made. Is my premise that validation should be done on the business layer wrong? What I do So my code usually ends up like this: <?php class Person { private $name; private $age; public function setName($n) { $n = trim($n); if (mb_strlen($n) == 0) { throw new ValidationException("Name cannot be empty"); } $this->name = $n; } public function setAge($a) { if (!is_int($a)) { if (!ctype_digit(trim($a))) { throw new ValidationException("Age $a is not valid"); } $a = (int)$a; } if ($a < 0 || $a > 150) { throw new ValidationException("Age $a is out of bounds"); } $this->age = $a; } // other getters, setters and methods } In the controller, I just pass the input data to the model, and catch thrown exceptions to show the error(s) to the user: <?php $person = new Person(); $errors = array(); // global try for all exceptions other than ValidationException try { // validation and process (if everything ok) try { $person->setAge($_POST['age']); } catch (ValidationException $e) { $errors['age'] = $e->getMessage(); } try { $person->setName($_POST['name']); } catch (ValidationException $e) { $errors['name'] = $e->getMessage(); } ... } catch (Exception $e) { // log the error, send 500 internal server error to the client // and finish the request } if (count($errors) == 0) { // process } else { showErrorsToUser($errors); } Is this a bad methodology? Alternate method Should maybe I create methods for isValidAge($a) that return true/false and then call them from the controller? <?php class Person { private $name; private $age; public function setName($n) { $n = trim($n); if ($this->isValidName($n)) { $this->name = $n; } else { throw new Exception("Invalid name"); } } public function setAge($a) { if ($this->isValidAge($a)) { $this->age = $a; } else { throw new Exception("Invalid age"); } } public function isValidName($n) { $n = trim($n); if (mb_strlen($n) == 0) { return false; } return true; } public function isValidAge($a) { if (!is_int($a)) { if (!ctype_digit(trim($a))) { return false; } $a = (int)$a; } if ($a < 0 || $a > 150) { return false; } return true; } // other getters, setters and methods } And the controller will be basically the same, just instead of try/catch there are now if/else: <?php $person = new Person(); $errors = array(); if ($person->isValidAge($age)) { $person->setAge($age); } catch (Exception $e) { $errors['age'] = "Invalid age"; } if ($person->isValidName($name)) { $person->setName($name); } catch (Exception $e) { $errors['name'] = "Invalid name"; } ... if (count($errors) == 0) { // process } else { showErrorsToUser($errors); } So, what should I do? I'm pretty happy with my original method, and my colleagues to whom I have showed it in general have liked it. Despite this, should I change to the alternate method? Or am I doing this terribly wrong and I should look for another way?

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• Cloud – the forecast is improving

  - by Rob Farley

  There is a lot of discussion about “the cloud”, and how that affects people’s data stories. Today the discussion enters the realm of T-SQL Tuesday, hosted this month by Jorge Segarra. Over the years, companies have invested a lot in making sure that their data is good, and I mean every aspect of it – the quality of it, the security of it, the performance of it, and more. Experts such as those of us at LobsterPot Solutions have helped these companies with this, and continue to work with clients to make sure that data is a strong part of their business, not an oversight. Whether business intelligence systems are being utilised or not, every business needs to be able to rely on its data, and have the confidence in it. Data should be a foundation upon which a business is built. In the past, data had been stored in paper-based systems. Filing cabinets stored vital information. Today, people have server rooms with storage of various kinds, recognising that filing cabinets don’t necessarily scale particularly well. It’s easy to ‘lose’ data in a filing cabinet, when you have people who need to make sure that the sheets of paper are in the right spot, and that you know how things are stored. Databases help solve that problem, but still the idea of a large filing cabinet continues, it just doesn’t involve paper. If something happens to the physical ‘filing cabinet’, then the problems are larger still. Then the data itself is under threat. Many clients have generators in case the power goes out, redundant cables in case the connectivity dies, and spare servers in other buildings just in case they’re required. But still they’re maintaining filing cabinets. You see, people like filing cabinets. There’s something to be said for having your data ‘close’. Even if the data is not in readable form, living as bits on a disk somewhere, the idea that its home is ‘in the building’ is comforting to many people. They simply don’t want to move their data anywhere else. The cloud offers an alternative to this, and the human element is an obstacle. By leveraging the cloud, companies can have someone else look after their filing cabinet. A lot of people really don’t like the idea of this, partly because the administrators of the data, those people who could potentially log in with escalated rights and see more than they should be allowed to, who need to be trusted to respond if there’s a problem, are now a faceless entity in the cloud. But this doesn’t mean that the cloud is bad – this is simply a concern that some people may have. In new functionality that’s on its way, we see other hybrid mechanisms that mean that people can leverage parts of the cloud with less fear. Companies can use cloud storage to hold their backup data, for example, backups that have been encrypted and are therefore not able to be read by anyone (including administrators) who don’t have the right password. Companies can have a database instance that runs locally, but which has its data files in the cloud, complete with Transparent Data Encryption if needed. There can be a higher level of control, making the change easier to accept. Hybrid options allow people who have had fears (potentially very justifiable) to take a new look at the cloud, and to start embracing some of the benefits of the cloud (such as letting someone else take care of storage, high availability, and more) without losing the feeling of the data being close. @rob_farley

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• Asynchrony in C# 5 (Part II)

  - by javarg

  This article is a continuation of the series of asynchronous features included in the new Async CTP preview for next versions of C# and VB. Check out Part I for more information. So, let’s continue with TPL Dataflow: Asynchronous functions TPL Dataflow Task based asynchronous Pattern Part II: TPL Dataflow Definition (by quote of Async CTP doc): “TPL Dataflow (TDF) is a new .NET library for building concurrent applications. It promotes actor/agent-oriented designs through primitives for in-process message passing, dataflow, and pipelining. TDF builds upon the APIs and scheduling infrastructure provided by the Task Parallel Library (TPL) in .NET 4, and integrates with the language support for asynchrony provided by C#, Visual Basic, and F#.” This means: data manipulation processed asynchronously. “TPL Dataflow is focused on providing building blocks for message passing and parallelizing CPU- and I/O-intensive applications”. Data manipulation is another hot area when designing asynchronous and parallel applications: how do you sync data access in a parallel environment? how do you avoid concurrency issues? how do you notify when data is available? how do you control how much data is waiting to be consumed? etc.  Dataflow Blocks TDF provides data and action processing blocks. Imagine having preconfigured data processing pipelines to choose from, depending on the type of behavior you want. The most basic block is the BufferBlock<T>, which provides an storage for some kind of data (instances of <T>). So, let’s review data processing blocks available. Blocks a categorized into three groups: Buffering Blocks Executor Blocks Joining Blocks Think of them as electronic circuitry components :).. 1. BufferBlock<T>: it is a FIFO (First in First Out) queue. You can Post data to it and then Receive it synchronously or asynchronously. It synchronizes data consumption for only one receiver at a time (you can have many receivers but only one will actually process it). 2. BroadcastBlock<T>: same FIFO queue for messages (instances of <T>) but link the receiving event to all consumers (it makes the data available for consumption to N number of consumers). The developer can provide a function to make a copy of the data if necessary. 3. WriteOnceBlock<T>: it stores only one value and once it’s been set, it can never be replaced or overwritten again (immutable after being set). As with BroadcastBlock<T>, all consumers can obtain a copy of the value. 4. ActionBlock<TInput>: this executor block allows us to define an operation to be executed when posting data to the queue. Thus, we must pass in a delegate/lambda when creating the block. Posting data will result in an execution of the delegate for each data in the queue. You could also specify how many parallel executions to allow (degree of parallelism). 5. TransformBlock<TInput, TOutput>: this is an executor block designed to transform each input, that is way it defines an output parameter. It ensures messages are processed and delivered in order. 6. TransformManyBlock<TInput, TOutput>: similar to TransformBlock but produces one or more outputs from each input. 7. BatchBlock<T>: combines N single items into one batch item (it buffers and batches inputs). 8. JoinBlock<T1, T2, …>: it generates tuples from all inputs (it aggregates inputs). Inputs could be of any type you want (T1, T2, etc.). 9. BatchJoinBlock<T1, T2, …>: aggregates tuples of collections. It generates collections for each type of input and then creates a tuple to contain each collection (Tuple<IList<T1>, IList<T2>>). Next time I will show some examples of usage for each TDF block. * Images taken from Microsoft’s Async CTP documentation.

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• Selenium &ndash; Use Data Driven tests to run in multiple browsers and sizes

  - by Aligned

  Originally posted on: http://geekswithblogs.net/Aligned/archive/2013/11/04/selenium-ndash-use-data-driven-tests-to-run-in-multiple.aspxSelenium uses WebDriver (or is it the same? I’m still learning how it is connected) to run Automated UI tests in many different browsers. For example, you can run the same test in Chrome and Firefox and in a smaller sized Chrome browser. The permutations can grow quickly. One way to get them to run in MStest is to create  a test method for each test (ie ChromeDeleteItem_Small, ChromeDeleteItem_Large, FFDeleteItem_Small, FFDeleteItem_Large) that each call  the same base method, passing in the browser and size you’d like. This approach was causing a lot of duplicate code, so I decided to use the data driven approach, common to Coded UI or Unit test methods. 1. Create a class with a test method. 2. Create a csv with two columns: BrowserType, BrowserSize 3. Add rows for each permutation: Chrome, Large | Chrome, Small | Firefox, Large | Firefox, Small | IE, Large | IE, Small | *** 4. Add the csv to the Visual Studio Project. 5. Set the Copy to output directory to Copy always 6. Add the attribute: [DataSource("Microsoft.VisualStudio.TestTools.DataSource.CSV", "|DataDirectory|\\TestMatrix.csv", "TestMatrix#csv", DataAccessMethod.Sequential), DeploymentItem("TestMatrix.csv")] 7. Run the test in the test explorer Example:[CodedUITest] public class AllTasksTests : TasksTestBase { [TestMethod] [TestCategory("Tasks")] [DataSource("Microsoft.VisualStudio.TestTools.DataSource.CSV", "|DataDirectory|\\TestMatrix.csv", "TestMatrix#csv", DataAccessMethod.Sequential), DeploymentItem("TestMatrix.csv")] public void CreateTask() { this.PrepForDataDrivenTest(); base.CreateTaskTest("New Task"); } } protected void PrepForDataDrivenTest() { var browserType = this.ParseBrowserType(Context.DataRow["BrowserType"].ToString()); var browserSize = this.ParseBrowserSize(Context.DataRow["BrowserSize"].ToString()); this.BrowserType = browserType; this.BrowserSize = browserSize; Trace.WriteLine("browser: " + browserType.ToString()); Trace.WriteLine("browser size: " + browserSize.ToString()); } /// <summary> /// Get the enum value from the string /// </summary> /// <param name="browserType">Chrome, Firefox, or IE</param> /// <returns>The browser type.</returns> private BrowserType ParseBrowserType(string browserType) { return (UITestFramework.BrowserType)Enum.Parse(typeof(UITestFramework.BrowserType), browserType, true); } /// <summary> /// Get the browser size enum value from the string /// </summary> /// <param name="browserSize">Small, Medium, Large</param> /// <returns>the browser size</returns> private BrowserSizeEnum ParseBrowserSize(string browserSize) { return (BrowserSizeEnum)Enum.Parse(typeof(BrowserSizeEnum), browserSize, true); }/// <summary> /// Change the browser to the size based on the enum. /// </summary> /// <param name="browserSize">The BrowserSizeEnum value to resize the window to.</param> private void ResizeBrowser(BrowserSizeEnum browserSize) { switch (browserSize) { case BrowserSizeEnum.Large: this.driver.Manage().Window.Maximize(); break; case BrowserSizeEnum.Medium: this.driver.Manage().Window.Size = new Size(800, this.driver.Manage().Window.Size.Height); break; case BrowserSizeEnum.Small: this.driver.Manage().Window.Size = new Size(500, this.driver.Manage().Window.Size.Height); break; default: break; } }/// <summary> /// Browser sizes for automation testing /// </summary> public enum BrowserSizeEnum { /// <summary> /// Large size, Maximized to the desktop /// </summary> Large, /// <summary> /// Similar to tablets /// </summary> Medium, /// <summary> /// Phone sizes... 610px and smaller /// </summary> Small } Hope it helps!

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• How can I get the data from the json one by one by using javascript/jquery? [on hold]

  - by sandhus

  I have the working code which fetches all the records from the json, but how can I make it available one by one on the click of the button or link? The following code is working to fetch all the records: <!doctype html> <html> <head> <meta charset="utf-8"> <title>jQuery PHP Json Response</title> <style type="text/css"> div { text-align:center; padding:10px; } #msg { width: 500px; margin: 0px auto; } .members { width: 500px ; background-color: beige; } </style> </head> <body> <div id="msg"> <table id="userdata" border="1"> <thead> <th>Email</th> <th>Sex</th> <th>Location</th> <th>Picture</th> <th>audio</th> <th>video</th> </thead> <tbody></tbody> </table> </div> <script type="text/javascript" src="https://ajax.googleapis.com/ajax/libs/jquery/1/jquery.min.js"> </script> <script type="text/javascript"> $(document).ready(function(){ var url="json.php"; $("#userdata tbody").html(""); $.getJSON(url,function(data){ $.each(data.members, function(i,user){ var tblRow = "<tr>" +"<td>"+user.email+"</td>" +"<td>"+user.sex+"</td>" +"<td>"+user.location+"</td>" +"<td>"+"<img src="+user.image+">"+"</td>" +"<td>"+"<audio src="+user.video+" controls>"+"</td>" +"<td>"+"<video src="+user.video+" controls>"+"</td>" +"</tr>" ; $(tblRow).appendTo("#userdata tbody"); }); }); }); </script> </body> </html> I used the json_encode function in the php file to encode the sql db. How can i achieve this?

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• Is this spaghetti code already? [migrated]

  - by hephestos

  I post the following code writen all by hand. Why I have the feeling that it is a western spaghetti on its own. Second, could that be written better? <div id="form-board" class="notice" style="height: 200px; min-height: 109px; width: auto;display: none;"> <script type="text/javascript"> jQuery(document).ready(function(){ $(".form-button-slide").click(function(){ $( "#form-board" ).dialog(); return false; }); }); </script> <?php echo $this->Form->create('mysubmit'); echo $this->Form->input('inputs', array('type' => 'select', 'id' => 'inputs', 'options' => $inputs)); echo $this->Form->input('Fields', array('type' => 'select', 'id' => 'fields', 'empty' => '-- Pick a state first --')); echo $this->Form->input('inputs2', array('type' => 'select', 'id' => 'inputs2', 'options' => $inputs2)); echo $this->Form->input('Fields2', array('type' => 'select', 'id' => 'fields2', 'empty' => '-- Pick a state first --')); echo $this->Form->end("Submit"); ?> </div> <div style="width:100%"></div> <div class="form-button-slide" style="float:left;display:block;"> <?php echo $this->Html->link("Error Results", "#"); ?> </div> <script type="text/javascript"> jQuery(document).ready(function(){ $("#mysubmitIndexForm").submit(function() { // we want to store the values from the form input box, then send via ajax below jQuery.post("Staffs/view", { data1: $("#inputs").attr('value'), data2:$("#inputs2").attr('value'),data3:$("#fields").attr('value'), data4:$("#fields2").attr('value') } ); //Close the dialog $( "#form-board" ).dialog('close') return false; }); $("#inputs").change(function() { // we want to store the values from the form input box, then send via ajax below var input_id = $('#inputs').attr('value'); $.ajax({ type: "POST", //The controller who listens to our request url: "Inputs/getFieldsFromOneInput/"+input_id, data: "input_id="+ input_id, //+"&amp; lname="+ lname, success: function(data){//function on success with returned data $('form#mysubmit').hide(function(){}); data = $.parseJSON(data); var sel = $("#fields"); sel.empty(); for (var i=0; i<data.length; i++) { sel.append('<option value="' + data[i].id + '">' + data[i].name + '</option>'); } } }); return false; }); $("#inputs2").change(function() { // we want to store the values from the form input box, then send via ajax below var input_id = $('#inputs2').attr('value'); $.ajax({ type: "POST", //The controller who listens to our request url: "Inputs/getFieldsFromOneInput/"+input_id, data: "input_id="+ input_id, //+"&amp; lname="+ lname, success: function(data){//function on success with returned data $('form#mysubmit').hide(function(){}); data = $.parseJSON(data); var sel = $("#fields2"); sel.empty(); for (var i=0; i<data.length; i++) { sel.append('<option value="' + data[i].id + '">' + data[i].name + '</option>'); } } }); return false; }); }); </script>

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• SQL Server 2012 - AlwaysOn

  - by Claus Jandausch

  Ich war nicht nur irritiert, ich war sogar regelrecht schockiert - und für einen kurzen Moment sprachlos (was nur selten der Fall ist). Gerade eben hatte mich jemand gefragt "Wann Oracle denn etwas Vergleichbares wie AlwaysOn bieten würde - und ob überhaupt?" War ich hier im falschen Film gelandet? Ich konnte nicht anders, als meinen Unmut kundzutun und zu erklären, dass die Fragestellung normalerweise anders herum läuft. Zugegeben - es mag vielleicht strittige Punkte geben im Vergleich zwischen Oracle und SQL Server - bei denen nicht unbedingt immer Oracle die Nase vorn haben muss - aber das Thema Clustering für Hochverfügbarkeit (HA), Disaster Recovery (DR) und Skalierbarkeit gehört mit Sicherheit nicht dazu. Dieses Erlebnis hakte ich am Nachgang als Einzelfall ab, der so nie wieder vorkommen würde. Bis ich kurz darauf eines Besseren belehrt wurde und genau die selbe Frage erneut zu hören bekam. Diesmal sogar im Exadata-Umfeld und einem Oracle Stretch Cluster. Einmal ist keinmal, doch zweimal ist einmal zu viel... Getreu diesem alten Motto war mir klar, dass man das so nicht länger stehen lassen konnte. Ich habe keine Ahnung, wie die Microsoft Marketing Abteilung es geschafft hat, unter dem AlwaysOn Brading eine innovative Technologie vermuten zu lassen - aber sie hat ihren Job scheinbar gut gemacht. Doch abgesehen von einem guten Marketing, stellt sich natürlich die Frage, was wirklich dahinter steckt und wie sich das Ganze mit Oracle vergleichen lässt - und ob überhaupt? Damit wären wir wieder bei der ursprünglichen Frage angelangt.  So viel zum Hintergrund dieses Blogbeitrags - von meiner Antwort handelt der restliche Blog. "Windows was the God ..." Um den wahren Unterschied zwischen Oracle und Microsoft verstehen zu können, muss man zunächst das bedeutendste Microsoft Dogma kennen. Es lässt sich schlicht und einfach auf den Punkt bringen: "Alles muss auf Windows basieren." Die Überschrift dieses Absatzes ist kein von mir erfundener Ausspruch, sondern ein Zitat. Konkret stammt es aus einem längeren Artikel von Kurt Eichenwald in der Vanity Fair aus dem August 2012. Er lautet Microsoft's Lost Decade und sei jedem ans Herz gelegt, der die "Microsoft-Maschinerie" unter Steve Ballmer und einige ihrer Kuriositäten besser verstehen möchte. "YOU TALKING TO ME?" Microsoft C.E.O. Steve Ballmer bei seiner Keynote auf der 2012 International Consumer Electronics Show in Las Vegas am 9. Januar   Manche Dinge in diesem Artikel mögen überspitzt dargestellt erscheinen - sind sie aber nicht. Vieles davon kannte ich bereits aus eigener Erfahrung und kann es nur bestätigen. Anderes hat sich mir erst so richtig erschlossen. Insbesondere die folgenden Passagen führten zum Aha-Erlebnis: “Windows was the god—everything had to work with Windows,” said Stone... “Every little thing you want to write has to build off of Windows (or other existing roducts),” one software engineer said. “It can be very confusing, …” Ich habe immer schon darauf hingewiesen, dass in einem SQL Server Failover Cluster die Microsoft Datenbank eigentlich nichts Nenneswertes zum Geschehen beiträgt, sondern sich voll und ganz auf das Windows Betriebssystem verlässt. Deshalb muss man auch die Windows Server Enterprise Edition installieren, soll ein Failover Cluster für den SQL Server eingerichtet werden. Denn hier werden die Cluster Services geliefert - nicht mit dem SQL Server. Er ist nur lediglich ein weiteres Server Produkt, für das Windows in Ausfallszenarien genutzt werden kann - so wie Microsoft Exchange beispielsweise, oder Microsoft SharePoint, oder irgendein anderes Server Produkt das auf Windows gehostet wird. Auch Oracle kann damit genutzt werden. Das Stichwort lautet hier: Oracle Failsafe. Nur - warum sollte man das tun, wenn gleichzeitig eine überlegene Technologie wie die Oracle Real Application Clusters (RAC) zur Verfügung steht, die dann auch keine Windows Enterprise Edition voraussetzen, da Oracle die eigene Clusterware liefert. Welche darüber hinaus für kürzere Failover-Zeiten sorgt, da diese Cluster-Technologie Datenbank-integriert ist und sich nicht auf "Dritte" verlässt. Wenn man sich also schon keine technischen Vorteile mit einem SQL Server Failover Cluster erkauft, sondern zusätzlich noch versteckte Lizenzkosten durch die Lizenzierung der Windows Server Enterprise Edition einhandelt, warum hat Microsoft dann in den vergangenen Jahren seit SQL Server 2000 nicht ebenfalls an einer neuen und innovativen Lösung gearbeitet, die mit Oracle RAC mithalten kann? Entwickler hat Microsoft genügend? Am Geld kann es auch nicht liegen? Lesen Sie einfach noch einmal die beiden obenstehenden Zitate und sie werden den Grund verstehen. Anders lässt es sich ja auch gar nicht mehr erklären, dass AlwaysOn aus zwei unterschiedlichen Technologien besteht, die beide jedoch wiederum auf dem Windows Server Failover Clustering (WSFC) basieren. Denn daraus ergeben sich klare Nachteile - aber dazu später mehr. Um AlwaysOn zu verstehen, sollte man sich zunächst kurz in Erinnerung rufen, was Microsoft bisher an HA/DR (High Availability/Desaster Recovery) Lösungen für SQL Server zur Verfügung gestellt hat. Replikation Basiert auf logischer Replikation und Pubisher/Subscriber Architektur Transactional Replication Merge Replication Snapshot Replication Microsoft's Replikation ist vergleichbar mit Oracle GoldenGate. Oracle GoldenGate stellt jedoch die umfassendere Technologie dar und bietet High Performance. Log Shipping Microsoft's Log Shipping stellt eine einfache Technologie dar, die vergleichbar ist mit Oracle Managed Recovery in Oracle Version 7. Das Log Shipping besitzt folgende Merkmale: Transaction Log Backups werden von Primary nach Secondary/ies geschickt Einarbeitung (z.B. Restore) auf jedem Secondary individuell Optionale dritte Server Instanz (Monitor Server) für Überwachung und Alarm Log Restore Unterbrechung möglich für Read-Only Modus (Secondary) Keine Unterstützung von Automatic Failover Database Mirroring Microsoft's Database Mirroring wurde verfügbar mit SQL Server 2005, sah aus wie Oracle Data Guard in Oracle 9i, war funktional jedoch nicht so umfassend. Für ein HA/DR Paar besteht eine 1:1 Beziehung, um die produktive Datenbank (Principle DB) abzusichern. Auf der Standby Datenbank (Mirrored DB) werden alle Insert-, Update- und Delete-Operationen nachgezogen. Modi Synchron (High-Safety Modus) Asynchron (High-Performance Modus) Automatic Failover Unterstützt im High-Safety Modus (synchron) Witness Server vorausgesetzt     Zur Frage der Kontinuität Es stellt sich die Frage, wie es um diesen Technologien nun im Zusammenhang mit SQL Server 2012 bestellt ist. Unter Fanfaren seinerzeit eingeführt, war Database Mirroring das erklärte Mittel der Wahl. Ich bin kein Produkt Manager bei Microsoft und kann hierzu nur meine Meinung äußern, aber zieht man den SQL AlwaysOn Team Blog heran, so sieht es nicht gut aus für das Database Mirroring - zumindest nicht langfristig. "Does AlwaysOn Availability Group replace Database Mirroring going forward?” “The short answer is we recommend that you migrate from the mirroring configuration or even mirroring and log shipping configuration to using Availability Group. Database Mirroring will still be available in the Denali release but will be phased out over subsequent releases. Log Shipping will continue to be available in future releases.” Damit wären wir endlich beim eigentlichen Thema angelangt. Was ist eine sogenannte Availability Group und was genau hat es mit der vielversprechend klingenden Bezeichnung AlwaysOn auf sich?   SQL Server 2012 - AlwaysOn Zwei HA-Features verstekcne sich hinter dem “AlwaysOn”-Branding. Einmal das AlwaysOn Failover Clustering aka SQL Server Failover Cluster Instances (FCI) - zum Anderen die AlwaysOn Availability Groups. Failover Cluster Instances (FCI) Entspricht ungefähr dem Stretch Cluster Konzept von Oracle Setzt auf Windows Server Failover Clustering (WSFC) auf Bietet HA auf Instanz-Ebene AlwaysOn Availability Groups (Verfügbarkeitsgruppen) Ähnlich der Idee von Consistency Groups, wie in Storage-Level Replikations-Software von z.B. EMC SRDF Abhängigkeiten zu Windows Server Failover Clustering (WSFC) Bietet HA auf Datenbank-Ebene   Hinweis: Verwechseln Sie nicht eine SQL Server Datenbank mit einer Oracle Datenbank. Und auch nicht eine Oracle Instanz mit einer SQL Server Instanz. Die gleichen Begriffe haben hier eine andere Bedeutung - nicht selten ein Grund, weshalb Oracle- und Microsoft DBAs schnell aneinander vorbei reden. Denken Sie bei einer SQL Server Datenbank eher an ein Oracle Schema, das kommt der Sache näher. So etwas wie die SQL Server Northwind Datenbank ist vergleichbar mit dem Oracle Scott Schema. Wenn Sie die genauen Unterschiede kennen möchten, finden Sie eine detaillierte Beschreibung in meinem Buch "Oracle10g Release 2 für Windows und .NET", erhältich bei Lehmanns, Amazon, etc.   Windows Server Failover Clustering (WSFC) Wie man sieht, basieren beide AlwaysOn Technologien wiederum auf dem Windows Server Failover Clustering (WSFC), um einerseits Hochverfügbarkeit auf Ebene der Instanz zu gewährleisten und andererseits auf der Datenbank-Ebene. Deshalb nun eine kurze Beschreibung der WSFC. Die WSFC sind ein mit dem Windows Betriebssystem geliefertes Infrastruktur-Feature, um HA für Server Anwendungen, wie Microsoft Exchange, SharePoint, SQL Server, etc. zu bieten. So wie jeder andere Cluster, besteht ein WSFC Cluster aus einer Gruppe unabhängiger Server, die zusammenarbeiten, um die Verfügbarkeit einer Applikation oder eines Service zu erhöhen. Falls ein Cluster-Knoten oder -Service ausfällt, kann der auf diesem Knoten bisher gehostete Service automatisch oder manuell auf einen anderen im Cluster verfügbaren Knoten transferriert werden - was allgemein als Failover bekannt ist. Unter SQL Server 2012 verwenden sowohl die AlwaysOn Avalability Groups, als auch die AlwaysOn Failover Cluster Instances die WSFC als Plattformtechnologie, um Komponenten als WSFC Cluster-Ressourcen zu registrieren. Verwandte Ressourcen werden in eine Ressource Group zusammengefasst, die in Abhängigkeit zu anderen WSFC Cluster-Ressourcen gebracht werden kann. Der WSFC Cluster Service kann jetzt die Notwendigkeit zum Neustart der SQL Server Instanz erfassen oder einen automatischen Failover zu einem anderen Server-Knoten im WSFC Cluster auslösen.   Failover Cluster Instances (FCI) Eine SQL Server Failover Cluster Instanz (FCI) ist eine einzelne SQL Server Instanz, die in einem Failover Cluster betrieben wird, der aus mehreren Windows Server Failover Clustering (WSFC) Knoten besteht und so HA (High Availability) auf Ebene der Instanz bietet. Unter Verwendung von Multi-Subnet FCI kann auch Remote DR (Disaster Recovery) unterstützt werden. Eine weitere Option für Remote DR besteht darin, eine unter FCI gehostete Datenbank in einer Availability Group zu betreiben. Hierzu später mehr. FCI und WSFC Basis FCI, das für lokale Hochverfügbarkeit der Instanzen genutzt wird, ähnelt der veralteten Architektur eines kalten Cluster (Aktiv-Passiv). Unter SQL Server 2008 wurde diese Technologie SQL Server 2008 Failover Clustering genannt. Sie nutzte den Windows Server Failover Cluster. In SQL Server 2012 hat Microsoft diese Basistechnologie unter der Bezeichnung AlwaysOn zusammengefasst. Es handelt sich aber nach wie vor um die klassische Aktiv-Passiv-Konfiguration. Der Ablauf im Failover-Fall ist wie folgt: Solange kein Hardware-oder System-Fehler auftritt, werden alle Dirty Pages im Buffer Cache auf Platte geschrieben Alle entsprechenden SQL Server Services (Dienste) in der Ressource Gruppe werden auf dem aktiven Knoten gestoppt Die Ownership der Ressource Gruppe wird auf einen anderen Knoten der FCI transferriert Der neue Owner (Besitzer) der Ressource Gruppe startet seine SQL Server Services (Dienste) Die Connection-Anforderungen einer Client-Applikation werden automatisch auf den neuen aktiven Knoten mit dem selben Virtuellen Network Namen (VNN) umgeleitet Abhängig vom Zeitpunkt des letzten Checkpoints, kann die Anzahl der Dirty Pages im Buffer Cache, die noch auf Platte geschrieben werden müssen, zu unvorhersehbar langen Failover-Zeiten führen. Um diese Anzahl zu drosseln, besitzt der SQL Server 2012 eine neue Fähigkeit, die Indirect Checkpoints genannt wird. Indirect Checkpoints ähnelt dem Fast-Start MTTR Target Feature der Oracle Datenbank, das bereits mit Oracle9i verfügbar war.   SQL Server Multi-Subnet Clustering Ein SQL Server Multi-Subnet Failover Cluster entspricht vom Konzept her einem Oracle RAC Stretch Cluster. Doch dies ist nur auf den ersten Blick der Fall. Im Gegensatz zu RAC ist in einem lokalen SQL Server Failover Cluster jeweils nur ein Knoten aktiv für eine Datenbank. Für die Datenreplikation zwischen geografisch entfernten Sites verlässt sich Microsoft auf 3rd Party Lösungen für das Storage Mirroring.     Die Verbesserung dieses Szenario mit einer SQL Server 2012 Implementierung besteht schlicht darin, dass eine VLAN-Konfiguration (Virtual Local Area Network) nun nicht mehr benötigt wird, so wie dies bisher der Fall war. Das folgende Diagramm stellt dar, wie der Ablauf mit SQL Server 2012 gehandhabt wird. In Site A und Site B wird HA jeweils durch einen lokalen Aktiv-Passiv-Cluster sichergestellt.     Besondere Aufmerksamkeit muss hier der Konfiguration und dem Tuning geschenkt werden, da ansonsten völlig inakzeptable Failover-Zeiten resultieren. Dies liegt darin begründet, weil die Downtime auf Client-Seite nun nicht mehr nur von der reinen Failover-Zeit abhängt, sondern zusätzlich von der Dauer der DNS Replikation zwischen den DNS Servern. (Rufen Sie sich in Erinnerung, dass wir gerade von Multi-Subnet Clustering sprechen). Außerdem ist zu berücksichtigen, wie schnell die Clients die aktualisierten DNS Informationen abfragen. Spezielle Konfigurationen für Node Heartbeat, HostRecordTTL (Host Record Time-to-Live) und Intersite Replication Frequeny für Active Directory Sites und Services werden notwendig. Default TTL für Windows Server 2008 R2: 20 Minuten Empfohlene Einstellung: 1 Minute DNS Update Replication Frequency in Windows Umgebung: 180 Minuten Empfohlene Einstellung: 15 Minuten (minimaler Wert)   Betrachtet man diese Werte, muss man feststellen, dass selbst eine optimale Konfiguration die rigiden SLAs (Service Level Agreements) heutiger geschäftskritischer Anwendungen für HA und DR nicht erfüllen kann. Denn dies impliziert eine auf der Client-Seite erlebte Failover-Zeit von insgesamt 16 Minuten. Hierzu ein Auszug aus der SQL Server 2012 Online Dokumentation: Cons: If a cross-subnet failover occurs, the client recovery time could be 15 minutes or longer, depending on your HostRecordTTL setting and the setting of your cross-site DNS/AD replication schedule.    Wir sind hier an einem Punkt unserer Überlegungen angelangt, an dem sich erklärt, weshalb ich zuvor das "Windows was the God ..." Zitat verwendet habe. Die unbedingte Abhängigkeit zu Windows wird zunehmend zum Problem, da sie die Komplexität einer Microsoft-basierenden Lösung erhöht, anstelle sie zu reduzieren. Und Komplexität ist das Letzte, was sich CIOs heutzutage wünschen.  Zur Ehrenrettung des SQL Server 2012 und AlwaysOn muss man sagen, dass derart lange Failover-Zeiten kein unbedingtes "Muss" darstellen, sondern ein "Kann". Doch auch ein "Kann" kann im unpassenden Moment unvorhersehbare und kostspielige Folgen haben. Die Unabsehbarkeit ist wiederum Ursache vieler an der Implementierung beteiligten Komponenten und deren Abhängigkeiten, wie beispielsweise drei Cluster-Lösungen (zwei von Microsoft, eine 3rd Party Lösung). Wie man die Sache auch dreht und wendet, kommt man an diesem Fakt also nicht vorbei - ganz unabhängig von der Dauer einer Downtime oder Failover-Zeiten. Im Gegensatz zu AlwaysOn und der hier vorgestellten Version eines Stretch-Clusters, vermeidet eine entsprechende Oracle Implementierung eine derartige Komplexität, hervorgerufen duch multiple Abhängigkeiten. Den Unterschied machen Datenbank-integrierte Mechanismen, wie Fast Application Notification (FAN) und Fast Connection Failover (FCF). Für Oracle MAA Konfigurationen (Maximum Availability Architecture) sind Inter-Site Failover-Zeiten im Bereich von Sekunden keine Seltenheit. Wenn Sie dem Link zur Oracle MAA folgen, finden Sie außerdem eine Reihe an Customer Case Studies. Auch dies ist ein wichtiges Unterscheidungsmerkmal zu AlwaysOn, denn die Oracle Technologie hat sich bereits zigfach in höchst kritischen Umgebungen bewährt.   Availability Groups (Verfügbarkeitsgruppen) Die sogenannten Availability Groups (Verfügbarkeitsgruppen) sind - neben FCI - der weitere Baustein von AlwaysOn.   Hinweis: Bevor wir uns näher damit beschäftigen, sollten Sie sich noch einmal ins Gedächtnis rufen, dass eine SQL Server Datenbank nicht die gleiche Bedeutung besitzt, wie eine Oracle Datenbank, sondern eher einem Oracle Schema entspricht. So etwas wie die SQL Server Northwind Datenbank ist vergleichbar mit dem Oracle Scott Schema.   Eine Verfügbarkeitsgruppe setzt sich zusammen aus einem Set mehrerer Benutzer-Datenbanken, die im Falle eines Failover gemeinsam als Gruppe behandelt werden. Eine Verfügbarkeitsgruppe unterstützt ein Set an primären Datenbanken (primäres Replikat) und einem bis vier Sets von entsprechenden sekundären Datenbanken (sekundäre Replikate).       Es können jedoch nicht alle SQL Server Datenbanken einer AlwaysOn Verfügbarkeitsgruppe zugeordnet werden. Der SQL Server Spezialist Michael Otey zählt in seinem SQL Server Pro Artikel folgende Anforderungen auf: Verfügbarkeitsgruppen müssen mit Benutzer-Datenbanken erstellt werden. System-Datenbanken können nicht verwendet werden Die Datenbanken müssen sich im Read-Write Modus befinden. Read-Only Datenbanken werden nicht unterstützt Die Datenbanken in einer Verfügbarkeitsgruppe müssen Multiuser Datenbanken sein Sie dürfen nicht das AUTO_CLOSE Feature verwenden Sie müssen das Full Recovery Modell nutzen und es muss ein vollständiges Backup vorhanden sein Eine gegebene Datenbank kann sich nur in einer einzigen Verfügbarkeitsgruppe befinden und diese Datenbank düerfen nicht für Database Mirroring konfiguriert sein Microsoft empfiehl außerdem, dass der Verzeichnispfad einer Datenbank auf dem primären und sekundären Server identisch sein sollte Wie man sieht, eignen sich Verfügbarkeitsgruppen nicht, um HA und DR vollständig abzubilden. Die Unterscheidung zwischen der Instanzen-Ebene (FCI) und Datenbank-Ebene (Availability Groups) ist von hoher Bedeutung. Vor kurzem wurde mir gesagt, dass man mit den Verfügbarkeitsgruppen auf Shared Storage verzichten könne und dadurch Kosten spart. So weit so gut ... Man kann natürlich eine Installation rein mit Verfügbarkeitsgruppen und ohne FCI durchführen - aber man sollte sich dann darüber bewusst sein, was man dadurch alles nicht abgesichert hat - und dies wiederum für Desaster Recovery (DR) und SLAs (Service Level Agreements) bedeutet. Kurzum, um die Kombination aus beiden AlwaysOn Produkten und der damit verbundene Komplexität kommt man wohl in der Praxis nicht herum.    Availability Groups und WSFC AlwaysOn hängt von Windows Server Failover Clustering (WSFC) ab, um die aktuellen Rollen der Verfügbarkeitsreplikate einer Verfügbarkeitsgruppe zu überwachen und zu verwalten, und darüber zu entscheiden, wie ein Failover-Ereignis die Verfügbarkeitsreplikate betrifft. Das folgende Diagramm zeigt de Beziehung zwischen Verfügbarkeitsgruppen und WSFC:   Der Verfügbarkeitsmodus ist eine Eigenschaft jedes Verfügbarkeitsreplikats. Synychron und Asynchron können also gemischt werden: Availability Modus (Verfügbarkeitsmodus) Asynchroner Commit-Modus Primäres replikat schließt Transaktionen ohne Warten auf Sekundäres Synchroner Commit-Modus Primäres Replikat wartet auf Commit von sekundärem Replikat Failover Typen Automatic Manual Forced (mit möglichem Datenverlust) Synchroner Commit-Modus Geplanter, manueller Failover ohne Datenverlust Automatischer Failover ohne Datenverlust Asynchroner Commit-Modus Nur Forced, manueller Failover mit möglichem Datenverlust   Der SQL Server kennt keinen separaten Switchover Begriff wie in Oracle Data Guard. Für SQL Server werden alle Role Transitions als Failover bezeichnet. Tatsächlich unterstützt der SQL Server keinen Switchover für asynchrone Verbindungen. Es gibt nur die Form des Forced Failover mit möglichem Datenverlust. Eine ähnliche Fähigkeit wie der Switchover unter Oracle Data Guard ist so nicht gegeben.   SQL Sever FCI mit Availability Groups (Verfügbarkeitsgruppen) Neben den Verfügbarkeitsgruppen kann eine zweite Failover-Ebene eingerichtet werden, indem SQL Server FCI (auf Shared Storage) mit WSFC implementiert wird. Ein Verfügbarkeitesreplikat kann dann auf einer Standalone Instanz gehostet werden, oder einer FCI Instanz. Zum Verständnis: Die Verfügbarkeitsgruppen selbst benötigen kein Shared Storage. Diese Kombination kann verwendet werden für lokale HA auf Ebene der Instanz und DR auf Datenbank-Ebene durch Verfügbarkeitsgruppen. Das folgende Diagramm zeigt dieses Szenario:   Achtung! Hier handelt es sich nicht um ein Pendant zu Oracle RAC plus Data Guard, auch wenn das Bild diesen Eindruck vielleicht vermitteln mag - denn alle sekundären Knoten im FCI sind rein passiv. Es existiert außerdem eine weitere und ernsthafte Einschränkung: SQL Server Failover Cluster Instanzen (FCI) unterstützen nicht das automatische AlwaysOn Failover für Verfügbarkeitsgruppen. Jedes unter FCI gehostete Verfügbarkeitsreplikat kann nur für manuelles Failover konfiguriert werden.   Lesbare Sekundäre Replikate Ein oder mehrere Verfügbarkeitsreplikate in einer Verfügbarkeitsgruppe können für den lesenden Zugriff konfiguriert werden, wenn sie als sekundäres Replikat laufen. Dies ähnelt Oracle Active Data Guard, jedoch gibt es Einschränkungen. Alle Abfragen gegen die sekundäre Datenbank werden automatisch auf das Snapshot Isolation Level abgebildet. Es handelt sich dabei um eine Versionierung der Rows. Microsoft versuchte hiermit die Oracle MVRC (Multi Version Read Consistency) nachzustellen. Tatsächlich muss man die SQL Server Snapshot Isolation eher mit Oracle Flashback vergleichen. Bei der Implementierung des Snapshot Isolation Levels handelt sich um ein nachträglich aufgesetztes Feature und nicht um einen inhärenten Teil des Datenbank-Kernels, wie im Falle Oracle. (Ich werde hierzu in Kürze einen weiteren Blogbeitrag verfassen, wenn ich mich mit der neuen SQL Server 2012 Core Lizenzierung beschäftige.) Für die Praxis entstehen aus der Abbildung auf das Snapshot Isolation Level ernsthafte Restriktionen, derer man sich für den Betrieb in der Praxis bereits vorab bewusst sein sollte: Sollte auf der primären Datenbank eine aktive Transaktion zu dem Zeitpunkt existieren, wenn ein lesbares sekundäres Replikat in die Verfügbarkeitsgruppe aufgenommen wird, werden die Row-Versionen auf der korrespondierenden sekundären Datenbank nicht sofort vollständig verfügbar sein. Eine aktive Transaktion auf dem primären Replikat muss zuerst abgeschlossen (Commit oder Rollback) und dieser Transaktions-Record auf dem sekundären Replikat verarbeitet werden. Bis dahin ist das Isolation Level Mapping auf der sekundären Datenbank unvollständig und Abfragen sind temporär geblockt. Microsoft sagt dazu: "This is needed to guarantee that row versions are available on the secondary replica before executing the query under snapshot isolation as all isolation levels are implicitly mapped to snapshot isolation." (SQL Storage Engine Blog: AlwaysOn: I just enabled Readable Secondary but my query is blocked?)  Grundlegend bedeutet dies, dass ein aktives lesbares Replikat nicht in die Verfügbarkeitsgruppe aufgenommen werden kann, ohne das primäre Replikat vorübergehend stillzulegen. Da Leseoperationen auf das Snapshot Isolation Transaction Level abgebildet werden, kann die Bereinigung von Ghost Records auf dem primären Replikat durch Transaktionen auf einem oder mehreren sekundären Replikaten geblockt werden - z.B. durch eine lang laufende Abfrage auf dem sekundären Replikat. Diese Bereinigung wird auch blockiert, wenn die Verbindung zum sekundären Replikat abbricht oder der Datenaustausch unterbrochen wird. Auch die Log Truncation wird in diesem Zustant verhindert. Wenn dieser Zustand längere Zeit anhält, empfiehlt Microsoft das sekundäre Replikat aus der Verfügbarkeitsgruppe herauszunehmen - was ein ernsthaftes Downtime-Problem darstellt. Die Read-Only Workload auf den sekundären Replikaten kann eingehende DDL Änderungen blockieren. Obwohl die Leseoperationen aufgrund der Row-Versionierung keine Shared Locks halten, führen diese Operatioen zu Sch-S Locks (Schemastabilitätssperren). DDL-Änderungen durch Redo-Operationen können dadurch blockiert werden. Falls DDL aufgrund konkurrierender Lese-Workload blockiert wird und der Schwellenwert für 'Recovery Interval' (eine SQL Server Konfigurationsoption) überschritten wird, generiert der SQL Server das Ereignis sqlserver.lock_redo_blocked, welches Microsoft zum Kill der blockierenden Leser empfiehlt. Auf die Verfügbarkeit der Anwendung wird hierbei keinerlei Rücksicht genommen.   Keine dieser Einschränkungen existiert mit Oracle Active Data Guard.   Backups auf sekundären Replikaten  Über die sekundären Replikate können Backups (BACKUP DATABASE via Transact-SQL) nur als copy-only Backups einer vollständigen Datenbank, Dateien und Dateigruppen erstellt werden. Das Erstellen inkrementeller Backups ist nicht unterstützt, was ein ernsthafter Rückstand ist gegenüber der Backup-Unterstützung physikalischer Standbys unter Oracle Data Guard. Hinweis: Ein möglicher Workaround via Snapshots, bleibt ein Workaround. Eine weitere Einschränkung dieses Features gegenüber Oracle Data Guard besteht darin, dass das Backup eines sekundären Replikats nicht ausgeführt werden kann, wenn es nicht mit dem primären Replikat kommunizieren kann. Darüber hinaus muss das sekundäre Replikat synchronisiert sein oder sich in der Synchronisation befinden, um das Beackup auf dem sekundären Replikat erstellen zu können.   Vergleich von Microsoft AlwaysOn mit der Oracle MAA Ich komme wieder zurück auf die Eingangs erwähnte, mehrfach an mich gestellte Frage "Wann denn - und ob überhaupt - Oracle etwas Vergleichbares wie AlwaysOn bieten würde?" und meine damit verbundene (kurze) Irritation. Wenn Sie diesen Blogbeitrag bis hierher gelesen haben, dann kennen Sie jetzt meine darauf gegebene Antwort. Der eine oder andere Punkt traf dabei nicht immer auf Jeden zu, was auch nicht der tiefere Sinn und Zweck meiner Antwort war. Wenn beispielsweise kein Multi-Subnet mit im Spiel ist, sind alle diesbezüglichen Kritikpunkte zunächst obsolet. Was aber nicht bedeutet, dass sie nicht bereits morgen schon wieder zum Thema werden könnten (Sag niemals "Nie"). In manch anderes Fettnäpfchen tritt man wiederum nicht unbedingt in einer Testumgebung, sondern erst im laufenden Betrieb. Erst recht nicht dann, wenn man sich potenzieller Probleme nicht bewusst ist und keine dedizierten Tests startet. Und wer AlwaysOn erfolgreich positionieren möchte, wird auch gar kein Interesse daran haben, auf mögliche Schwachstellen und den besagten Teufel im Detail aufmerksam zu machen. Das ist keine Unterstellung - es ist nur menschlich. Außerdem ist es verständlich, dass man sich in erster Linie darauf konzentriert "was geht" und "was gut läuft", anstelle auf das "was zu Problemen führen kann" oder "nicht funktioniert". Wer will schon der Miesepeter sein? Für mich selbst gesprochen, kann ich nur sagen, dass ich lieber vorab von allen möglichen Einschränkungen wissen möchte, anstelle sie dann nach einer kurzen Zeit der heilen Welt schmerzhaft am eigenen Leib erfahren zu müssen. Ich bin davon überzeugt, dass es Ihnen nicht anders geht. Nachfolgend deshalb eine Zusammenfassung all jener Punkte, die ich im Vergleich zur Oracle MAA (Maximum Availability Architecture) als unbedingt Erwähnenswert betrachte, falls man eine Evaluierung von Microsoft AlwaysOn in Betracht zieht. 1. AlwaysOn ist eine komplexe Technologie Der SQL Server AlwaysOn Stack ist zusammengesetzt aus drei verschiedenen Technlogien: Windows Server Failover Clustering (WSFC) SQL Server Failover Cluster Instances (FCI) SQL Server Availability Groups (Verfügbarkeitsgruppen) Man kann eine derartige Lösung nicht als nahtlos bezeichnen, wofür auch die vielen von Microsoft dargestellten Einschränkungen sprechen. Während sich frühere SQL Server Versionen in Richtung eigener HA/DR Technologien entwickelten (wie Database Mirroring), empfiehlt Microsoft nun die Migration. Doch weshalb dieser Schwenk? Er führt nicht zu einem konsisten und robusten Angebot an HA/DR Technologie für geschäftskritische Umgebungen.  Liegt die Antwort in meiner These begründet, nach der "Windows was the God ..." noch immer gilt und man die Nachteile der allzu engen Kopplung mit Windows nicht sehen möchte? Entscheiden Sie selbst ... 2. Failover Cluster Instanzen - Kein RAC-Pendant Die SQL Server und Windows Server Clustering Technologie basiert noch immer auf dem veralteten Aktiv-Passiv Modell und führt zu einer Verschwendung von Systemressourcen. In einer Betrachtung von lediglich zwei Knoten erschließt sich auf Anhieb noch nicht der volle Mehrwert eines Aktiv-Aktiv Clusters (wie den Real Application Clusters), wie er von Oracle bereits vor zehn Jahren entwickelt wurde. Doch kennt man die Vorzüge der Skalierbarkeit durch einfaches Hinzufügen weiterer Cluster-Knoten, die dann alle gemeinsam als ein einziges logisches System zusammenarbeiten, versteht man was hinter dem Motto "Pay-as-you-Grow" steckt. In einem Aktiv-Aktiv Cluster geht es zwar auch um Hochverfügbarkeit - und ein Failover erfolgt zudem schneller, als in einem Aktiv-Passiv Modell - aber es geht eben nicht nur darum. An dieser Stelle sei darauf hingewiesen, dass die Oracle 11g Standard Edition bereits die Nutzung von Oracle RAC bis zu vier Sockets kostenfrei beinhaltet. Möchten Sie dazu Windows nutzen, benötigen Sie keine Windows Server Enterprise Edition, da Oracle 11g die eigene Clusterware liefert. Sie kommen in den Genuss von Hochverfügbarkeit und Skalierbarkeit und können dazu die günstigere Windows Server Standard Edition nutzen. 3. SQL Server Multi-Subnet Clustering - Abhängigkeit zu 3rd Party Storage Mirroring  Die SQL Server Multi-Subnet Clustering Architektur unterstützt den Aufbau eines Stretch Clusters, basiert dabei aber auf dem Aktiv-Passiv Modell. Das eigentlich Problematische ist jedoch, dass man sich zur Absicherung der Datenbank auf 3rd Party Storage Mirroring Technologie verlässt, ohne Integration zwischen dem Windows Server Failover Clustering (WSFC) und der darunterliegenden Mirroring Technologie. Wenn nun im Cluster ein Failover auf Instanzen-Ebene erfolgt, existiert keine Koordination mit einem möglichen Failover auf Ebene des Storage-Array. 4. Availability Groups (Verfügbarkeitsgruppen) - Vier, oder doch nur Zwei? Ein primäres Replikat erlaubt bis zu vier sekundäre Replikate innerhalb einer Verfügbarkeitsgruppe, jedoch nur zwei im Synchronen Commit Modus. Während dies zwar einen Vorteil gegenüber dem stringenten 1:1 Modell unter Database Mirroring darstellt, fällt der SQL Server 2012 damit immer noch weiter zurück hinter Oracle Data Guard mit bis zu 30 direkten Stanbdy Zielen - und vielen weiteren durch kaskadierende Ziele möglichen. Damit eignet sich Oracle Active Data Guard auch für die Bereitstellung einer Reader-Farm Skalierbarkeit für Internet-basierende Unternehmen. Mit AwaysOn Verfügbarkeitsgruppen ist dies nicht möglich. 5. Availability Groups (Verfügbarkeitsgruppen) - kein asynchrones Switchover  Die Technologie der Verfügbarkeitsgruppen wird auch als geeignetes Mittel für administrative Aufgaben positioniert - wie Upgrades oder Wartungsarbeiten. Man muss sich jedoch einem gravierendem Defizit bewusst sein: Im asynchronen Verfügbarkeitsmodus besteht die einzige Möglichkeit für Role Transition im Forced Failover mit Datenverlust! Um den Verlust von Daten durch geplante Wartungsarbeiten zu vermeiden, muss man den synchronen Verfügbarkeitsmodus konfigurieren, was jedoch ernstzunehmende Auswirkungen auf WAN Deployments nach sich zieht. Spinnt man diesen Gedanken zu Ende, kommt man zu dem Schluss, dass die Technologie der Verfügbarkeitsgruppen für geplante Wartungsarbeiten in einem derartigen Umfeld nicht effektiv genutzt werden kann. 6. Automatisches Failover - Nicht immer möglich Sowohl die SQL Server FCI, als auch Verfügbarkeitsgruppen unterstützen automatisches Failover. Möchte man diese jedoch kombinieren, wird das Ergebnis kein automatisches Failover sein. Denn ihr Zusammentreffen im Failover-Fall führt zu Race Conditions (Wettlaufsituationen), weshalb diese Konfiguration nicht länger das automatische Failover zu einem Replikat in einer Verfügbarkeitsgruppe erlaubt. Auch hier bestätigt sich wieder die tiefere Problematik von AlwaysOn, mit einer Zusammensetzung aus unterschiedlichen Technologien und der Abhängigkeit zu Windows. 7. Problematische RTO (Recovery Time Objective) Microsoft postioniert die SQL Server Multi-Subnet Clustering Architektur als brauchbare HA/DR Architektur. Bedenkt man jedoch die Problematik im Zusammenhang mit DNS Replikation und den möglichen langen Wartezeiten auf Client-Seite von bis zu 16 Minuten, sind strenge RTO Anforderungen (Recovery Time Objectives) nicht erfüllbar. Im Gegensatz zu Oracle besitzt der SQL Server keine Datenbank-integrierten Technologien, wie Oracle Fast Application Notification (FAN) oder Oracle Fast Connection Failover (FCF). 8. Problematische RPO (Recovery Point Objective) SQL Server ermöglicht Forced Failover (erzwungenes Failover), bietet jedoch keine Möglichkeit zur automatischen Übertragung der letzten Datenbits von einem alten zu einem neuen primären Replikat, wenn der Verfügbarkeitsmodus asynchron war. Oracle Data Guard hingegen bietet diese Unterstützung durch das Flush Redo Feature. Dies sichert "Zero Data Loss" und beste RPO auch in erzwungenen Failover-Situationen. 9. Lesbare Sekundäre Replikate mit Einschränkungen Aufgrund des Snapshot Isolation Transaction Level für lesbare sekundäre Replikate, besitzen diese Einschränkungen mit Auswirkung auf die primäre Datenbank. Die Bereinigung von Ghost Records auf der primären Datenbank, wird beeinflusst von lang laufenden Abfragen auf der lesabaren sekundären Datenbank. Die lesbare sekundäre Datenbank kann nicht in die Verfügbarkeitsgruppe aufgenommen werden, wenn es aktive Transaktionen auf der primären Datenbank gibt. Zusätzlich können DLL Änderungen auf der primären Datenbank durch Abfragen auf der sekundären blockiert werden. Und imkrementelle Backups werden hier nicht unterstützt.   Keine dieser Restriktionen existiert unter Oracle Data Guard.

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• This web part does not have a valid XSLT stylesheet: There is no XSL property available for presenting the data.

  - by Patrick Olurotimi Ige

  I have been thinking for a while how i can reuse my code when building custom dataview webparts in sharepoint designer 2010.So i decided to use the XslLink which is one of the properties when you edit a sharepoint webpart.I started by creating a xsl file that i can use but after adding the link to the file like so:<XslLink>sites/server/mycustomtemplate.xsl</XslLink>I get the error : This web part does not have  a valid XSLT stylesheet: There is no XSL property available for presenting the data.So after some debugging i noticed it was the directory path for the link to the XSL style shee gets broken.So i changed it to  the full URL  http://mysite/sites/server/mycustomtemplate.xsl it works Enjoy

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• How to find and fix performance problems in ORM powered applications

  - by FransBouma

  Once in a while we get requests about how to fix performance problems with our framework. As it comes down to following the same steps and looking into the same things every single time, I decided to write a blogpost about it instead, so more people can learn from this and solve performance problems in their O/R mapper powered applications. In some parts it's focused on LLBLGen Pro but it's also usable for other O/R mapping frameworks, as the vast majority of performance problems in O/R mapper powered applications are not specific for a certain O/R mapper framework. Too often, the developer looks at the wrong part of the application, trying to fix what isn't a problem in that part, and getting frustrated that 'things are so slow with <insert your favorite framework X here>'. I'm in the O/R mapper business for a long time now (almost 10 years, full time) and as it's a small world, we O/R mapper developers know almost all tricks to pull off by now: we all know what to do to make task ABC faster and what compromises (because there are almost always compromises) to deal with if we decide to make ABC faster that way. Some O/R mapper frameworks are faster in X, others in Y, but you can be sure the difference is mainly a result of a compromise some developers are willing to deal with and others aren't. That's why the O/R mapper frameworks on the market today are different in many ways, even though they all fetch and save entities from and to a database. I'm not suggesting there's no room for improvement in today's O/R mapper frameworks, there always is, but it's not a matter of 'the slowness of the application is caused by the O/R mapper' anymore. Perhaps query generation can be optimized a bit here, row materialization can be optimized a bit there, but it's mainly coming down to milliseconds. Still worth it if you're a framework developer, but it's not much compared to the time spend inside databases and in user code: if a complete fetch takes 40ms or 50ms (from call to entity object collection), it won't make a difference for your application as that 10ms difference won't be noticed. That's why it's very important to find the real locations of the problems so developers can fix them properly and don't get frustrated because their quest to get a fast, performing application failed. Performance tuning basics and rules Finding and fixing performance problems in any application is a strict procedure with four prescribed steps: isolate, analyze, interpret and fix, in that order. It's key that you don't skip a step nor make assumptions: these steps help you find the reason of a problem which seems to be there, and how to fix it or leave it as-is. Skipping a step, or when you assume things will be bad/slow without doing analysis will lead to the path of premature optimization and won't actually solve your problems, only create new ones. The most important rule of finding and fixing performance problems in software is that you have to understand what 'performance problem' actually means. Most developers will say "when a piece of software / code is slow, you have a performance problem". But is that actually the case? If I write a Linq query which will aggregate, group and sort 5 million rows from several tables to produce a resultset of 10 rows, it might take more than a couple of milliseconds before that resultset is ready to be consumed by other logic. If I solely look at the Linq query, the code consuming the resultset of the 10 rows and then look at the time it takes to complete the whole procedure, it will appear to me to be slow: all that time taken to produce and consume 10 rows? But if you look closer, if you analyze and interpret the situation, you'll see it does a tremendous amount of work, and in that light it might even be extremely fast. With every performance problem you encounter, always do realize that what you're trying to solve is perhaps not a technical problem at all, but a perception problem. The second most important rule you have to understand is based on the old saying "Penny wise, Pound Foolish": the part which takes e.g. 5% of the total time T for a given task isn't worth optimizing if you have another part which takes a much larger part of the total time T for that same given task. Optimizing parts which are relatively insignificant for the total time taken is not going to bring you better results overall, even if you totally optimize that part away. This is the core reason why analysis of the complete set of application parts which participate in a given task is key to being successful in solving performance problems: No analysis -> no problem -> no solution. One warning up front: hunting for performance will always include making compromises. Fast software can be made maintainable, but if you want to squeeze as much performance out of your software, you will inevitably be faced with the dilemma of compromising one or more from the group {readability, maintainability, features} for the extra performance you think you'll gain. It's then up to you to decide whether it's worth it. In almost all cases it's not. The reason for this is simple: the vast majority of performance problems can be solved by implementing the proper algorithms, the ones with proven Big O-characteristics so you know the performance you'll get plus you know the algorithm will work. The time taken by the algorithm implementing code is inevitable: you already implemented the best algorithm. You might find some optimizations on the technical level but in general these are minor. Let's look at the four steps to see how they guide us through the quest to find and fix performance problems. Isolate The first thing you need to do is to isolate the areas in your application which are assumed to be slow. For example, if your application is a web application and a given page is taking several seconds or even minutes to load, it's a good candidate to check out. It's important to start with the isolate step because it allows you to focus on a single code path per area with a clear begin and end and ignore the rest. The rest of the steps are taken per identified problematic area. Keep in mind that isolation focuses on tasks in an application, not code snippets. A task is something that's started in your application by either another task or the user, or another program, and has a beginning and an end. You can see a task as a piece of functionality offered by your application.  Analyze Once you've determined the problem areas, you have to perform analysis on the code paths of each area, to see where the performance problems occur and which areas are not the problem. This is a multi-layered effort: an application which uses an O/R mapper typically consists of multiple parts: there's likely some kind of interface (web, webservice, windows etc.), a part which controls the interface and business logic, the O/R mapper part and the RDBMS, all connected with either a network or inter-process connections provided by the OS or other means. Each of these parts, including the connectivity plumbing, eat up a part of the total time it takes to complete a task, e.g. load a webpage with all orders of a given customer X. To understand which parts participate in the task / area we're investigating and how much they contribute to the total time taken to complete the task, analysis of each participating task is essential. Start with the code you wrote which starts the task, analyze the code and track the path it follows through your application. What does the code do along the way, verify whether it's correct or not. Analyze whether you have implemented the right algorithms in your code for this particular area. Remember we're looking at one area at a time, which means we're ignoring all other code paths, just the code path of the current problematic area, from begin to end and back. Don't dig in and start optimizing at the code level just yet. We're just analyzing. If your analysis reveals big architectural stupidity, it's perhaps a good idea to rethink the architecture at this point. For the rest, we're analyzing which means we collect data about what could be wrong, for each participating part of the complete application. Reviewing the code you wrote is a good tool to get deeper understanding of what is going on for a given task but ultimately it lacks precision and overview what really happens: humans aren't good code interpreters, computers are. We therefore need to utilize tools to get deeper understanding about which parts contribute how much time to the total task, triggered by which other parts and for example how many times are they called. There are two different kind of tools which are necessary: .NET profilers and O/R mapper / RDBMS profilers. .NET profiling .NET profilers (e.g. dotTrace by JetBrains or Ants by Red Gate software) show exactly which pieces of code are called, how many times they're called, and the time it took to run that piece of code, at the method level and sometimes even at the line level. The .NET profilers are essential tools for understanding whether the time taken to complete a given task / area in your application is consumed by .NET code, where exactly in your code, the path to that code, how many times that code was called by other code and thus reveals where hotspots are located: the areas where a solution can be found. Importantly, they also reveal which areas can be left alone: remember our penny wise pound foolish saying: if a profiler reveals that a group of methods are fast, or don't contribute much to the total time taken for a given task, ignore them. Even if the code in them is perhaps complex and looks like a candidate for optimization: you can work all day on that, it won't matter.  As we're focusing on a single area of the application, it's best to start profiling right before you actually activate the task/area. Most .NET profilers support this by starting the application without starting the profiling procedure just yet. You navigate to the particular part which is slow, start profiling in the profiler, in your application you perform the actions which are considered slow, and afterwards you get a snapshot in the profiler. The snapshot contains the data collected by the profiler during the slow action, so most data is produced by code in the area to investigate. This is important, because it allows you to stay focused on a single area. O/R mapper and RDBMS profiling .NET profilers give you a good insight in the .NET side of things, but not in the RDBMS side of the application. As this article is about O/R mapper powered applications, we're also looking at databases, and the software making it possible to consume the database in your application: the O/R mapper. To understand which parts of the O/R mapper and database participate how much to the total time taken for task T, we need different tools. There are two kind of tools focusing on O/R mappers and database performance profiling: O/R mapper profilers and RDBMS profilers. For O/R mapper profilers, you can look at LLBLGen Prof by hibernating rhinos or the Linq to Sql/LLBLGen Pro profiler by Huagati. Hibernating rhinos also have profilers for other O/R mappers like NHibernate (NHProf) and Entity Framework (EFProf) and work the same as LLBLGen Prof. For RDBMS profilers, you have to look whether the RDBMS vendor has a profiler. For example for SQL Server, the profiler is shipped with SQL Server, for Oracle it's build into the RDBMS, however there are also 3rd party tools. Which tool you're using isn't really important, what's important is that you get insight in which queries are executed during the task / area we're currently focused on and how long they took. Here, the O/R mapper profilers have an advantage as they collect the time it took to execute the query from the application's perspective so they also collect the time it took to transport data across the network. This is important because a query which returns a massive resultset or a resultset with large blob/clob/ntext/image fields takes more time to get transported across the network than a small resultset and a database profiler doesn't take this into account most of the time. Another tool to use in this case, which is more low level and not all O/R mappers support it (though LLBLGen Pro and NHibernate as well do) is tracing: most O/R mappers offer some form of tracing or logging system which you can use to collect the SQL generated and executed and often also other activity behind the scenes. While tracing can produce a tremendous amount of data in some cases, it also gives insight in what's going on. Interpret After we've completed the analysis step it's time to look at the data we've collected. We've done code reviews to see whether we've done anything stupid and which parts actually take place and if the proper algorithms have been implemented. We've done .NET profiling to see which parts are choke points and how much time they contribute to the total time taken to complete the task we're investigating. We've performed O/R mapper profiling and RDBMS profiling to see which queries were executed during the task, how many queries were generated and executed and how long they took to complete, including network transportation. All this data reveals two things: which parts are big contributors to the total time taken and which parts are irrelevant. Both aspects are very important. The parts which are irrelevant (i.e. don't contribute significantly to the total time taken) can be ignored from now on, we won't look at them. The parts which contribute a lot to the total time taken are important to look at. We now have to first look at the .NET profiler results, to see whether the time taken is consumed in our own code, in .NET framework code, in the O/R mapper itself or somewhere else. For example if most of the time is consumed by DbCommand.ExecuteReader, the time it took to complete the task is depending on the time the data is fetched from the database. If there was just 1 query executed, according to tracing or O/R mapper profilers / RDBMS profilers, check whether that query is optimal, uses indexes or has to deal with a lot of data. Interpret means that you follow the path from begin to end through the data collected and determine where, along the path, the most time is contributed. It also means that you have to check whether this was expected or is totally unexpected. My previous example of the 10 row resultset of a query which groups millions of rows will likely reveal that a long time is spend inside the database and almost no time is spend in the .NET code, meaning the RDBMS part contributes the most to the total time taken, the rest is compared to that time, irrelevant. Considering the vastness of the source data set, it's expected this will take some time. However, does it need tweaking? Perhaps all possible tweaks are already in place. In the interpret step you then have to decide that further action in this area is necessary or not, based on what the analysis results show: if the analysis results were unexpected and in the area where the most time is contributed to the total time taken is room for improvement, action should be taken. If not, you can only accept the situation and move on. In all cases, document your decision together with the analysis you've done. If you decide that the perceived performance problem is actually expected due to the nature of the task performed, it's essential that in the future when someone else looks at the application and starts asking questions you can answer them properly and new analysis is only necessary if situations changed. Fix After interpreting the analysis results you've concluded that some areas need adjustment. This is the fix step: you're actively correcting the performance problem with proper action targeted at the real cause. In many cases related to O/R mapper powered applications it means you'll use different features of the O/R mapper to achieve the same goal, or apply optimizations at the RDBMS level. It could also mean you apply caching inside your application (compromise memory consumption over performance) to avoid unnecessary re-querying data and re-consuming the results. After applying a change, it's key you re-do the analysis and interpretation steps: compare the results and expectations with what you had before, to see whether your actions had any effect or whether it moved the problem to a different part of the application. Don't fall into the trap to do partly analysis: do the full analysis again: .NET profiling and O/R mapper / RDBMS profiling. It might very well be that the changes you've made make one part faster but another part significantly slower, in such a way that the overall problem hasn't changed at all. Performance tuning is dealing with compromises and making choices: to use one feature over the other, to accept a higher memory footprint, to go away from the strict-OO path and execute queries directly onto the RDBMS, these are choices and compromises which will cross your path if you want to fix performance problems with respect to O/R mappers or data-access and databases in general. In most cases it's not a big issue: alternatives are often good choices too and the compromises aren't that hard to deal with. What is important is that you document why you made a choice, a compromise: which analysis data, which interpretation led you to the choice made. This is key for good maintainability in the years to come. Most common performance problems with O/R mappers Below is an incomplete list of common performance problems related to data-access / O/R mappers / RDBMS code. It will help you with fixing the hotspots you found in the interpretation step. SELECT N+1: (Lazy-loading specific). Lazy loading triggered performance bottlenecks. Consider a list of Orders bound to a grid. You have a Field mapped onto a related field in Order, Customer.CompanyName. Showing this column in the grid will make the grid fetch (indirectly) for each row the Customer row. This means you'll get for the single list not 1 query (for the orders) but 1+(the number of orders shown) queries. To solve this: use eager loading using a prefetch path to fetch the customers with the orders. SELECT N+1 is easy to spot with an O/R mapper profiler or RDBMS profiler: if you see a lot of identical queries executed at once, you have this problem. Prefetch paths using many path nodes or sorting, or limiting. Eager loading problem. Prefetch paths can help with performance, but as 1 query is fetched per node, it can be the number of data fetched in a child node is bigger than you think. Also consider that data in every node is merged on the client within the parent. This is fast, but it also can take some time if you fetch massive amounts of entities. If you keep fetches small, you can use tuning parameters like the ParameterizedPrefetchPathThreshold setting to get more optimal queries. Deep inheritance hierarchies of type Target Per Entity/Type. If you use inheritance of type Target per Entity / Type (each type in the inheritance hierarchy is mapped onto its own table/view), fetches will join subtype- and supertype tables in many cases, which can lead to a lot of performance problems if the hierarchy has many types. With this problem, keep inheritance to a minimum if possible, or switch to a hierarchy of type Target Per Hierarchy, which means all entities in the inheritance hierarchy are mapped onto the same table/view. Of course this has its own set of drawbacks, but it's a compromise you might want to take. Fetching massive amounts of data by fetching large lists of entities. LLBLGen Pro supports paging (and limiting the # of rows returned), which is often key to process through large sets of data. Use paging on the RDBMS if possible (so a query is executed which returns only the rows in the page requested). When using paging in a web application, be sure that you switch server-side paging on on the datasourcecontrol used. In this case, paging on the grid alone is not enough: this can lead to fetching a lot of data which is then loaded into the grid and paged there. Keep note that analyzing queries for paging could lead to the false assumption that paging doesn't occur, e.g. when the query contains a field of type ntext/image/clob/blob and DISTINCT can't be applied while it should have (e.g. due to a join): the datareader will do DISTINCT filtering on the client. this is a little slower but it does perform paging functionality on the data-reader so it won't fetch all rows even if the query suggests it does. Fetch massive amounts of data because blob/clob/ntext/image fields aren't excluded. LLBLGen Pro supports field exclusion for queries. You can exclude fields (also in prefetch paths) per query to avoid fetching all fields of an entity, e.g. when you don't need them for the logic consuming the resultset. Excluding fields can greatly reduce the amount of time spend on data-transport across the network. Use this optimization if you see that there's a big difference between query execution time on the RDBMS and the time reported by the .NET profiler for the ExecuteReader method call. Doing client-side aggregates/scalar calculations by consuming a lot of data. If possible, try to formulate a scalar query or group by query using the projection system or GetScalar functionality of LLBLGen Pro to do data consumption on the RDBMS server. It's far more efficient to process data on the RDBMS server than to first load it all in memory, then traverse the data in-memory to calculate a value. Using .ToList() constructs inside linq queries. It might be you use .ToList() somewhere in a Linq query which makes the query be run partially in-memory. Example: var q = from c in metaData.Customers.ToList() where c.Country=="Norway" select c; This will actually fetch all customers in-memory and do an in-memory filtering, as the linq query is defined on an IEnumerable<T>, and not on the IQueryable<T>. Linq is nice, but it can often be a bit unclear where some parts of a Linq query might run. Fetching all entities to delete into memory first. To delete a set of entities it's rather inefficient to first fetch them all into memory and then delete them one by one. It's more efficient to execute a DELETE FROM ... WHERE query on the database directly to delete the entities in one go. LLBLGen Pro supports this feature, and so do some other O/R mappers. It's not always possible to do this operation in the context of an O/R mapper however: if an O/R mapper relies on a cache, these kind of operations are likely not supported because they make it impossible to track whether an entity is actually removed from the DB and thus can be removed from the cache. Fetching all entities to update with an expression into memory first. Similar to the previous point: it is more efficient to update a set of entities directly with a single UPDATE query using an expression instead of fetching the entities into memory first and then updating the entities in a loop, and afterwards saving them. It might however be a compromise you don't want to take as it is working around the idea of having an object graph in memory which is manipulated and instead makes the code fully aware there's a RDBMS somewhere. Conclusion Performance tuning is almost always about compromises and making choices. It's also about knowing where to look and how the systems in play behave and should behave. The four steps I provided should help you stay focused on the real problem and lead you towards the solution. Knowing how to optimally use the systems participating in your own code (.NET framework, O/R mapper, RDBMS, network/services) is key for success as well as knowing what's going on inside the application you built. I hope you'll find this guide useful in tracking down performance problems and dealing with them in a useful way.  

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• SQLAuthority News – Download Microsoft SQL Server 2012 RTM Now

  - by pinaldave

  SQL Server 2012 enables a cloud-ready information platform that will help organizations unlock breakthrough insights across the organization as well as quickly build solutions and extend data across on-premises and public cloud backed by capabilities for mission critical confidence: Deliver required uptime and data protection with AlwaysOn Gain breakthrough & predictable performance with ColumnStore Index Help enable security and compliance with new User-defined Roles and Default Schema for Groups Enable rapid data discovery for deeper insights across the organization with ColumnStore Index Ensure more credible, consistent data with SSIS improvements, a Master Data Services add-in for Excel, and new Data Quality Services Optimize IT and developer productivity across server and cloud with Data-tier Application Component (DAC) parity with SQL Azure and SQL Server Data Tools for a unified dev experience across database, BI, and cloud functions Download SQL Server 2012 RTM Download Microsoft SQL Server 2012 Feature Pack Download SQL Server Data Tools Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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• What is a name for a job where you do system analysis, project management and data diagramming?

  - by David Archer

  In the last 4 months I've been able to manage a team and step away from the coding for a bit. I've been planning the system in full (both System Analysis and project managing, alongside action and data diagramming) writing the technical documentation, the code's architecture, keeping track of the other guys doing the actual coding, QA, bug reports and dealing with clients. I had to take two days' training on node.js just to see if it would be suitable for a project we were considering. Is there a name for this job? Project Manager and Systems Architect don't quite seem to have the same stuff, and IT manager seems way off. I only want to know so that I can get some qualification towards it and try to move into this kind of work full-time.

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• What resources will help me understand the data model for QC 10.0 in order to write my SQL queries?

  - by srihari

  I am a fresher in Quality Center 10.0 HP software testing tool. As per my understanding in order to generate reports from QC and to troubleshoot the scenarios, we need to write SQL queries in the QC back end database. In my case it is SQL db. I downloaded the database reference help file but I could not understand from where I can start. It just gave the table name and its information. For a starter like me are there any online tutorials or helpful websites,hands on exercises,scenario's where I can better understand how to write queries for the QC data model? I am very confident about the SQL coding itself, what I want to know is how to query on the QC database tables based on the scenarios that occur in QC tool. Please suggest. Thanks, Srihari

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• Securing data inside Azure SQL? Any good libraries or DIY?

  - by Sid

  Azure SQL doesn't support many of the encryption features found in SQL Server (Table and Column encryption). We need to store some sensitive information that needs to be encrypted and we've rolled our own using AesCryptoServiceProvider to encrypt/decrypt data to/from the database. This solves the immediate issue (no cleartext in db) but poses other problems like Key rotation (we have to roll our own code for this, walking through the db converting old cipher text into new cipher text) metadata mapping of which tables and which columns are encrypted. This is simple with it's a few but quickly gets out of hand ... So are there any libraries out there that do this well? Any other resources or design patterns I can be pointed to?

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• How do multi-platform games usually store save data?

  - by PixelPerfect3

  I realize this is a bit of a broad question, but I was wondering if there is a "standard" in the industry when it comes to storing save data for games (and is it different across platforms - Xbox/PS/PC/Mac/Android/iOS?) For example for a game like Assassin's Creed or The Walking Dead: They are on multiple platforms and they usually have to save enough information about the player and their actions. Do they use something like XML files, databases, or just straight binary dumps? How much does it differ from platform to platform? I would appreciate it if someone with experience in the game industry would answer this.

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• rails fake data, considering switch from faker to forgery, any advantages or pitfalls?

  - by Michael Durrant

  With Ruby on Rails I've usually used Forgery for generating dummy data for testing. I've noticed recently that several clients and tutorials are using Faker They both seem fairly similar in use and popularity: Faker 128 forks, 418 watchers. Forgery 59 forks, 399 watchers. They both seem similar in how current they are: Faker Most updates are from 6 and 9 months ago. Forgery Most updates are from 4 and 9 months ago. The one distinguishing factor I've found so far is that Forgery seems like it has better instructions. Are there any particular benefits or disadvantages to using one over the other? Have you ever needed to switch from one to another for a particular reason?

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• Can I install ubuntu on usb hdd without loosing data on it?

  - by Radek

  I have live-usb stick that I can boot latest live Ubuntu from. Then I have 160GB external WD hdd with few GB free of space. My notebook can't have any internal hdd so I was wondering if I can use my external one to install and boot Ubuntu and install new programs, save settings etc. without loosing (or moving around) any data on this external hdd. The best would be if I can somehow use the live-usb. I'm traveling so any "complicated" solution might be bit hard to implement. I do have an access to the Internet.

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