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  • In Java, is there a performance gain in using interfaces for complex models?

    - by Gnoupi
    The title is hardly understandable, but I'm not sure how to summarize that another way. Any edit to clarify is welcome. I have been told, and recommended to use interfaces to improve performances, even in a case which doesn't especially call for the regular "interface" role. In this case, the objects are big models (in a MVC meaning), with many methods and fields. The "good use" that has been recommended to me is to create an interface, with its unique implementation. There won't be any other class implementing this interface, for sure. I have been told that this is better to do so, because it "exposes less" (or something close) to the other classes which will use methods from this class, as these objects are referring to the object from its interface (all public methods from the implementation being reproduced in the interface). This seems quite strange to me, as it seems like a C++ use to me (with header files). There I see the point, but in Java? Is there really a point in making an interface for such unique implementation? I would really appreciate some clarifications on the topic, so I could justify not following such kind of behavior, and the hassle it creates from duplicating all declarations. Edit: Plenty of valid points in most answers, I'm wondering if I won't switch this question for a community wiki, so we can regroup these points in more structured answers.

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  • Why one loop is performing better than other memory wise as well as performance wise?

    - by Mohit
    I have following two loops in C#, and I am running these loops for a collection with 10,000 records being downloaded with paging using "yield return" First foreach(var k in collection) { repo.Save(k); } Second var collectionEnum = collection.GetEnumerator(); while (collectionEnum.MoveNext()) { var k = collectionEnum.Current; repo.Save(k); k = null; } Seems like that the second loop consumes less memory and it faster than the first loop. Memory I understand may be because of k being set to null(Even though I am not sure). But how come it is faster than for each. Following is the actual code [Test] public void BechmarkForEach_Test() { bool isFirstTimeSync = true; Func<Contact, bool> afterProcessing = contactItem => { return true; }; var contactService = CreateSerivce("/administrator/components/com_civicrm"); var contactRepo = new ContactRepository(new Mock<ILogger>().Object); contactRepo.Drop(); contactRepo = new ContactRepository(new Mock<ILogger>().Object); Profile("For Each Profiling",1,()=>{ var localenumertaor=contactService.Download(); foreach (var item in localenumertaor) { if (isFirstTimeSync) item.StateFlag = 1; item.ClientTimeStamp = DateTime.UtcNow; if (item.StateFlag == 1) contactRepo.Insert(item); else contactRepo.Update(item); afterProcessing(item); } contactRepo.DeleteAll(); }); } [Test] public void BechmarkWhile_Test() { bool isFirstTimeSync = true; Func<Contact, bool> afterProcessing = contactItem => { return true; }; var contactService = CreateSerivce("/administrator/components/com_civicrm"); var contactRepo = new ContactRepository(new Mock<ILogger>().Object); contactRepo.Drop(); contactRepo = new ContactRepository(new Mock<ILogger>().Object); var itemsCollection = contactService.Download().GetEnumerator(); Profile("While Profiling", 1, () => { while (itemsCollection.MoveNext()) { var item = itemsCollection.Current; //if First time sync then ignore and overwrite the stateflag if (isFirstTimeSync) item.StateFlag = 1; item.ClientTimeStamp = DateTime.UtcNow; if (item.StateFlag == 1) contactRepo.Insert(item); else contactRepo.Update(item); afterProcessing(item); item = null; } contactRepo.DeleteAll(); }); } static void Profile(string description, int iterations, Action func) { // clean up GC.Collect(); GC.WaitForPendingFinalizers(); GC.Collect(); // warm up func(); var watch = Stopwatch.StartNew(); for (int i = 0; i < iterations; i++) { func(); } watch.Stop(); Console.Write(description); Console.WriteLine(" Time Elapsed {0} ms", watch.ElapsedMilliseconds); } I m using the micro bench marking, from a stackoverflow question itself benchmarking-small-code The time taken is For Each Profiling Time Elapsed 5249 ms While Profiling Time Elapsed 116 ms

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  • Which one has a faster runtime performance: WPF or Winforms?

    - by Joan Venge
    I know WPF is more complex an flexible so could be thought to do more calculations. But since the rendering is done on the GPU, wouldn't it be faster than Winforms for the same application (functionally and visually)? I mean when you are not running any games or heavy 3d rendering, the GPU isn't doing heavy work, right? Whereas the CPU is always busy. Is this a valid assumption or is the GPU utilization of WPF a very minor operation in its pipeline?

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  • When does code bloat start having a noticeable effect on performance?

    - by Kyle
    I am looking to make a hefty shift towards templates in one of my OpenGL projects, mainly for fun and the learning experience. I plan on watching the size of the executable carefully as I do this, to see just how much of the notorious bloat happens. Currently, the size of my Release build is around 580 KB when I favor speed and 440 KB when I favor size. Yes, it's a tiny project, and in fact even if my executable bloats 10 x its size, it's still going to be 5 MB or so, which hardly seems large by today's standards... or is it? This brings me to my question. Is speed proportional to size, or are there leaps and plateaus at certain thresholds, thresholds which I should be aiming to stay below? (And if so, what are the thresholds specifically?)

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  • How can I compare the performance of log() and fp division in C++?

    - by Ventzi Zhechev
    Hi, I’m using a log-based class in C++ to store very small floating-point values (as the values otherwise go beyond the scope of double). As I’m performing a large number of multiplications, this has the added benefit of converting the multiplications to sums. However, at a certain point in my algorithm, I need to divide a standard double value by an integer value and than do a *= to a log-based value. I have overloaded the *= operator for my log-based class and the right-hand side value is first converted to a log-based value by running log() and than added to the left-hand side value. Thus the operations actually performed are floating-point division, log() and floating-point summation. My question whether it would be faster to first convert the denominator to a log-based value, which would replace the floating-point division with floating-point subtraction, yielding the following chain of operations: twice log(), floating-point subtraction, floating-point summation. In the end, this boils down to whether floating-point division is faster or slower than log(). I suspect that a common answer would be that this is compiler and architecture dependent, so I’ll say that I use gcc 4.2 from Apple on darwin 10.3.0. Still, I hope to get an answer with a general remark on the speed of these two operators and/or an idea on how to measure the difference myself, as there might be more going on here, e.g. executing the constructors that do the type conversion etc. Cheers!

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  • What's the fastest lookup algorithm for a key, pair data structure (i.e, a map)?

    - by truncheon
    In the following example a std::map structure is filled with 26 values from A - Z (for key) and 0 – 26 for value. The time taken (on my system) to lookup the last entry (10000000 times) is roughly 250 ms for the vector, and 125 ms for the map. (I compiled using release mode, with O3 option turned on for g++ 4.4) But if for some odd reason I wanted better performance than the std::map, what data structures and functions would I need to consider using? I apologize if the answer seems obvious to you, but I haven't had much experience in the performance critical aspects of C++ programming. #include <ctime> #include <map> #include <vector> #include <iostream> struct mystruct { char key; int value; mystruct(char k = 0, int v = 0) : key(k), value(v) { } }; int find(const std::vector<mystruct>& ref, char key) { for (std::vector<mystruct>::const_iterator i = ref.begin(); i != ref.end(); ++i) if (i->key == key) return i->value; return -1; } int main() { std::map<char, int> mymap; std::vector<mystruct> myvec; for (int i = 'a'; i < 'a' + 26; ++i) { mymap[i] = i - 'a'; myvec.push_back(mystruct(i, i - 'a')); } int pre = clock(); for (int i = 0; i < 10000000; ++i) { find(myvec, 'z'); } std::cout << "linear scan: milli " << clock() - pre << "\n"; pre = clock(); for (int i = 0; i < 10000000; ++i) { mymap['z']; } std::cout << "map scan: milli " << clock() - pre << "\n"; return 0; }

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  • .htaccess redirect noticably increasing load time

    - by GTCrais
    I set up a SEF link via .htaccess RewriteRule to one of the articles on my website just to see how that works, and it does work but it considerably increases the load time of that particular page. On average the articles (including the one I'm talking about, when not using the rewrite rule) load in about 1.3 seconds. With the rewrite rule, the load time is 3.3 seconds on average until the page displays, and the loader thingy in the firefox tab keeps spinning for another 2 seconds. I have WAMP setup on my computer, and the website is being accessed through no-ip.com. Here is the .htaccess config (very simple, as you can see): Options +FollowSymLinks RewriteEngine On RewriteCond %{REQUEST_FILENAME} !-f RewriteCond %{REQUEST_FILENAME} !-d RewriteRule ^o-sw-liji /NewSWL/o-nama.php?body=o-sw-liji In httpd.conf I have this (somewhere I read this might affect the load time for some reason - searching for files through all the directories or something, I don't remember exactly what I read): <Directory /> Options None AllowOverride None Order deny,allow Deny from all </Directory> DocumentRoot "Z:/Program Files (x86)/wamp/www/" <Directory "Z:/Program Files (x86)/wamp/www/"> Options None AllowOverride All Order allow,deny Allow from all </Directory> Any ideas why .htaccess redirect increases the load time by so much? UPDATE: so I put a session based counter in the "o-nama.php" script. Apparently when I access the web via the 'normal' link i.e. 'o-nama.php?body=o-sw-liji', the counter increases by one, as it should - it's one page load. But when the page is accessed through the redirected link, i.e. 'o-nama/o-sharewood-liji' the counter increases by 6-8, which naturally makes the load time a lot longer, since it's loading the same page for 6-8 times. I have no idea why this is happening. Any help is appreciated.

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  • Why do dicts of defaultdict(int)'s use so much memory? (and other simple python performance question

    - by dukhat
    import numpy as num from collections import defaultdict topKeys = range(16384) keys = range(8192) table = dict((k,defaultdict(int)) for k in topKeys) dat = num.zeros((16384,8192), dtype="int32") print "looping begins" #how much memory should this use? I think it shouldn't use more that a few #times the memory required to hold (16384*8192) int32's (512 mb), but #it uses 11 GB! for k in topKeys: for j in keys: dat[k,j] = table[k][j] print "done" What is going on here? Furthermore, this similar script takes eons to run compared to the first one, and also uses an absurd quantity of memory. topKeys = range(16384) keys = range(8192) table = [(j,0) for k in topKeys for j in keys] I guess python ints might be 64 bit ints, which would account for some of this, but do these relatively natural and simple constructions really produce such a massive overhead? I guess these scripts show that they do, so my question is: what exactly is causing the high memory usage in the first script and the long runtime and high memory usage of the second script and is there any way to avoid these costs?

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  • When is a SQL function not a function?

    - by Rob Farley
    Should SQL Server even have functions? (Oh yeah – this is a T-SQL Tuesday post, hosted this month by Brad Schulz) Functions serve an important part of programming, in almost any language. A function is a piece of code that is designed to return something, as opposed to a piece of code which isn’t designed to return anything (which is known as a procedure). SQL Server is no different. You can call stored procedures, even from within other stored procedures, and you can call functions and use these in other queries. Stored procedures might query something, and therefore ‘return data’, but a function in SQL is considered to have the type of the thing returned, and can be used accordingly in queries. Consider the internal GETDATE() function. SELECT GETDATE(), SomeDatetimeColumn FROM dbo.SomeTable; There’s no logical difference between the field that is being returned by the function and the field that’s being returned by the table column. Both are the datetime field – if you didn’t have inside knowledge, you wouldn’t necessarily be able to tell which was which. And so as developers, we find ourselves wanting to create functions that return all kinds of things – functions which look up values based on codes, functions which do string manipulation, and so on. But it’s rubbish. Ok, it’s not all rubbish, but it mostly is. And this isn’t even considering the SARGability impact. It’s far more significant than that. (When I say the SARGability aspect, I mean “because you’re unlikely to have an index on the result of some function that’s applied to a column, so try to invert the function and query the column in an unchanged manner”) I’m going to consider the three main types of user-defined functions in SQL Server: Scalar Inline Table-Valued Multi-statement Table-Valued I could also look at user-defined CLR functions, including aggregate functions, but not today. I figure that most people don’t tend to get around to doing CLR functions, and I’m going to focus on the T-SQL-based user-defined functions. Most people split these types of function up into two types. So do I. Except that most people pick them based on ‘scalar or table-valued’. I’d rather go with ‘inline or not’. If it’s not inline, it’s rubbish. It really is. Let’s start by considering the two kinds of table-valued function, and compare them. These functions are going to return the sales for a particular salesperson in a particular year, from the AdventureWorks database. CREATE FUNCTION dbo.FetchSales_inline(@salespersonid int, @orderyear int) RETURNS TABLE AS  RETURN (     SELECT e.LoginID as EmployeeLogin, o.OrderDate, o.SalesOrderID     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101') ) ; GO CREATE FUNCTION dbo.FetchSales_multi(@salespersonid int, @orderyear int) RETURNS @results TABLE (     EmployeeLogin nvarchar(512),     OrderDate datetime,     SalesOrderID int     ) AS BEGIN     INSERT @results (EmployeeLogin, OrderDate, SalesOrderID)     SELECT e.LoginID, o.OrderDate, o.SalesOrderID     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101')     ;     RETURN END ; GO You’ll notice that I’m being nice and responsible with the use of the DATEADD function, so that I have SARGability on the OrderDate filter. Regular readers will be hoping I’ll show what’s going on in the execution plans here. Here I’ve run two SELECT * queries with the “Show Actual Execution Plan” option turned on. Notice that the ‘Query cost’ of the multi-statement version is just 2% of the ‘Batch cost’. But also notice there’s trickery going on. And it’s nothing to do with that extra index that I have on the OrderDate column. Trickery. Look at it – clearly, the first plan is showing us what’s going on inside the function, but the second one isn’t. The second one is blindly running the function, and then scanning the results. There’s a Sequence operator which is calling the TVF operator, and then calling a Table Scan to get the results of that function for the SELECT operator. But surely it still has to do all the work that the first one is doing... To see what’s actually going on, let’s look at the Estimated plan. Now, we see the same plans (almost) that we saw in the Actuals, but we have an extra one – the one that was used for the TVF. Here’s where we see the inner workings of it. You’ll probably recognise the right-hand side of the TVF’s plan as looking very similar to the first plan – but it’s now being called by a stack of other operators, including an INSERT statement to be able to populate the table variable that the multi-statement TVF requires. And the cost of the TVF is 57% of the batch! But it gets worse. Let’s consider what happens if we don’t need all the columns. We’ll leave out the EmployeeLogin column. Here, we see that the inline function call has been simplified down. It doesn’t need the Employee table. The join is redundant and has been eliminated from the plan, making it even cheaper. But the multi-statement plan runs the whole thing as before, only removing the extra column when the Table Scan is performed. A multi-statement function is a lot more powerful than an inline one. An inline function can only be the result of a single sub-query. It’s essentially the same as a parameterised view, because views demonstrate this same behaviour of extracting the definition of the view and using it in the outer query. A multi-statement function is clearly more powerful because it can contain far more complex logic. But a multi-statement function isn’t really a function at all. It’s a stored procedure. It’s wrapped up like a function, but behaves like a stored procedure. It would be completely unreasonable to expect that a stored procedure could be simplified down to recognise that not all the columns might be needed, but yet this is part of the pain associated with this procedural function situation. The biggest clue that a multi-statement function is more like a stored procedure than a function is the “BEGIN” and “END” statements that surround the code. If you try to create a multi-statement function without these statements, you’ll get an error – they are very much required. When I used to present on this kind of thing, I even used to call it “The Dangers of BEGIN and END”, and yes, I’ve written about this type of thing before in a similarly-named post over at my old blog. Now how about scalar functions... Suppose we wanted a scalar function to return the count of these. CREATE FUNCTION dbo.FetchSales_scalar(@salespersonid int, @orderyear int) RETURNS int AS BEGIN     RETURN (         SELECT COUNT(*)         FROM Sales.SalesOrderHeader AS o         LEFT JOIN HumanResources.Employee AS e         ON e.EmployeeID = o.SalesPersonID         WHERE o.SalesPersonID = @salespersonid         AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')         AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101')     ); END ; GO Notice the evil words? They’re required. Try to remove them, you just get an error. That’s right – any scalar function is procedural, despite the fact that you wrap up a sub-query inside that RETURN statement. It’s as ugly as anything. Hopefully this will change in future versions. Let’s have a look at how this is reflected in an execution plan. Here’s a query, its Actual plan, and its Estimated plan: SELECT e.LoginID, y.year, dbo.FetchSales_scalar(p.SalesPersonID, y.year) AS NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID; We see here that the cost of the scalar function is about twice that of the outer query. Nicely, the query optimizer has worked out that it doesn’t need the Employee table, but that’s a bit of a red herring here. There’s actually something way more significant going on. If I look at the properties of that UDF operator, it tells me that the Estimated Subtree Cost is 0.337999. If I just run the query SELECT dbo.FetchSales_scalar(281,2003); we see that the UDF cost is still unchanged. You see, this 0.0337999 is the cost of running the scalar function ONCE. But when we ran that query with the CROSS JOIN in it, we returned quite a few rows. 68 in fact. Could’ve been a lot more, if we’d had more salespeople or more years. And so we come to the biggest problem. This procedure (I don’t want to call it a function) is getting called 68 times – each one between twice as expensive as the outer query. And because it’s calling it in a separate context, there is even more overhead that I haven’t considered here. The cheek of it, to say that the Compute Scalar operator here costs 0%! I know a number of IT projects that could’ve used that kind of costing method, but that’s another story that I’m not going to go into here. Let’s look at a better way. Suppose our scalar function had been implemented as an inline one. Then it could have been expanded out like a sub-query. It could’ve run something like this: SELECT e.LoginID, y.year, (SELECT COUNT(*)     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = p.SalesPersonID     AND o.OrderDate >= DATEADD(year,y.year-2000,'20000101')     AND o.OrderDate < DATEADD(year,y.year-2000+1,'20000101')     ) AS NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID; Don’t worry too much about the Scan of the SalesOrderHeader underneath a Nested Loop. If you remember from plenty of other posts on the matter, execution plans don’t push the data through. That Scan only runs once. The Index Spool sucks the data out of it and populates a structure that is used to feed the Stream Aggregate. The Index Spool operator gets called 68 times, but the Scan only once (the Number of Executions property demonstrates this). Here, the Query Optimizer has a full picture of what’s being asked, and can make the appropriate decision about how it accesses the data. It can simplify it down properly. To get this kind of behaviour from a function, we need it to be inline. But without inline scalar functions, we need to make our function be table-valued. Luckily, that’s ok. CREATE FUNCTION dbo.FetchSales_inline2(@salespersonid int, @orderyear int) RETURNS table AS RETURN (SELECT COUNT(*) as NumSales     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101') ); GO But we can’t use this as a scalar. Instead, we need to use it with the APPLY operator. SELECT e.LoginID, y.year, n.NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID OUTER APPLY dbo.FetchSales_inline2(p.SalesPersonID, y.year) AS n; And now, we get the plan that we want for this query. All we’ve done is tell the function that it’s returning a table instead of a single value, and removed the BEGIN and END statements. We’ve had to name the column being returned, but what we’ve gained is an actual inline simplifiable function. And if we wanted it to return multiple columns, it could do that too. I really consider this function to be superior to the scalar function in every way. It does need to be handled differently in the outer query, but in many ways it’s a more elegant method there too. The function calls can be put amongst the FROM clause, where they can then be used in the WHERE or GROUP BY clauses without fear of calling the function multiple times (another horrible side effect of functions). So please. If you see BEGIN and END in a function, remember it’s not really a function, it’s a procedure. And then fix it. @rob_farley

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  • Synchronize Data between a Silverlight ListBox and a User Control

    - by psheriff
    One of the great things about XAML is the powerful data-binding capabilities. If you load up a list box with a collection of objects, you can display detail data about each object without writing any C# or VB.NET code. Take a look at Figure 1 that shows a collection of Product objects in a list box. When you click on a list box you bind the current Product object selected in the list box to a set of controls in a user control with just a very simple Binding statement in XAML.  Figure 1: Synchronizing a ListBox to a User Control is easy with Data Binding Product and Products Classes To illustrate this data binding feature I am going to just create some local data instead of using a WCF service. The code below shows a Product class that has three properties, namely, ProductId, ProductName and Price. This class also has a constructor that takes 3 parameters and allows us to set the 3 properties in an instance of our Product class. C#public class Product{  public Product(int productId, string productName, decimal price)  {    ProductId = productId;    ProductName = productName;    Price = price;  }   public int ProductId { get; set; }  public string ProductName { get; set; }  public decimal Price { get; set; }} VBPublic Class Product  Public Sub New(ByVal _productId As Integer, _                 ByVal _productName As String, _                 ByVal _price As Decimal)    ProductId = _productId    ProductName = _productName    Price = _price  End Sub   Private mProductId As Integer  Private mProductName As String  Private mPrice As Decimal   Public Property ProductId() As Integer    Get      Return mProductId    End Get    Set(ByVal value As Integer)      mProductId = value    End Set  End Property   Public Property ProductName() As String    Get      Return mProductName    End Get    Set(ByVal value As String)      mProductName = value    End Set  End Property   Public Property Price() As Decimal    Get      Return mPrice    End Get    Set(ByVal value As Decimal)      mPrice = value    End Set  End PropertyEnd Class To fill up a list box you need a collection class of Product objects. The code below creates a generic collection class of Product objects. In the constructor of the Products class I have hard-coded five product objects and added them to the collection. In a real-world application you would get your data through a call to service to fill the list box, but for simplicity and just to illustrate the data binding, I am going to just hard code the data. C#public class Products : List<Product>{  public Products()  {    this.Add(new Product(1, "Microsoft VS.NET 2008", 1000));    this.Add(new Product(2, "Microsoft VS.NET 2010", 1000));    this.Add(new Product(3, "Microsoft Silverlight 4", 1000));    this.Add(new Product(4, "Fundamentals of N-Tier eBook", 20));    this.Add(new Product(5, "ASP.NET Security eBook", 20));  }} VBPublic Class Products  Inherits List(Of Product)   Public Sub New()    Me.Add(New Product(1, "Microsoft VS.NET 2008", 1000))    Me.Add(New Product(2, "Microsoft VS.NET 2010", 1000))    Me.Add(New Product(3, "Microsoft Silverlight 4", 1000))    Me.Add(New Product(4, "Fundamentals of N-Tier eBook", 20))    Me.Add(New Product(5, "ASP.NET Security eBook", 20))  End SubEnd Class The Product Detail User Control Below is a user control (named ucProduct) that is used to display the product detail information seen in the bottom portion of Figure 1. This is very basic XAML that just creates a text block and a text box control for each of the three properties in the Product class. Notice the {Binding Path=[PropertyName]} on each of the text box controls. This means that if the DataContext property of this user control is set to an instance of a Product class, then the data in the properties of that Product object will be displayed in each of the text boxes. <UserControl x:Class="SL_SyncListBoxAndUserControl_CS.ucProduct"  xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation"  xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"  HorizontalAlignment="Left"  VerticalAlignment="Top">  <Grid Margin="4">    <Grid.RowDefinitions>      <RowDefinition Height="Auto" />      <RowDefinition Height="Auto" />      <RowDefinition Height="Auto" />    </Grid.RowDefinitions>    <Grid.ColumnDefinitions>      <ColumnDefinition MinWidth="120" />      <ColumnDefinition />    </Grid.ColumnDefinitions>    <TextBlock Grid.Row="0"               Grid.Column="0"               Text="Product Id" />    <TextBox Grid.Row="0"             Grid.Column="1"             Text="{Binding Path=ProductId}" />    <TextBlock Grid.Row="1"               Grid.Column="0"               Text="Product Name" />    <TextBox Grid.Row="1"             Grid.Column="1"             Text="{Binding Path=ProductName}" />    <TextBlock Grid.Row="2"               Grid.Column="0"               Text="Price" />    <TextBox Grid.Row="2"             Grid.Column="1"             Text="{Binding Path=Price}" />  </Grid></UserControl> Synchronize ListBox with User Control You are now ready to fill the list box with the collection class of Product objects and then bind the SelectedItem of the list box to the Product detail user control. The XAML below is the complete code for Figure 1. <UserControl x:Class="SL_SyncListBoxAndUserControl_CS.MainPage"  xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation"  xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"  xmlns:src="clr-namespace:SL_SyncListBoxAndUserControl_CS"  VerticalAlignment="Top"  HorizontalAlignment="Left">  <UserControl.Resources>    <src:Products x:Key="productCollection" />  </UserControl.Resources>  <Grid x:Name="LayoutRoot"        Margin="4"        Background="White">    <Grid.RowDefinitions>      <RowDefinition Height="Auto" />      <RowDefinition Height="*" />    </Grid.RowDefinitions>    <ListBox x:Name="lstData"             Grid.Row="0"             BorderBrush="Black"             BorderThickness="1"             ItemsSource="{Binding                   Source={StaticResource productCollection}}"             DisplayMemberPath="ProductName" />    <src:ucProduct x:Name="prodDetail"                   Grid.Row="1"                   DataContext="{Binding ElementName=lstData,                                          Path=SelectedItem}" />  </Grid></UserControl> The first step to making this happen is to reference the Silverlight project (SL_SyncListBoxAndUserControl_CS) where the Product and Products classes are located. I added this namespace and assigned it a namespace prefix of “src” as shown in the line below: xmlns:src="clr-namespace:SL_SyncListBoxAndUserControl_CS" Next, to use the data from an instance of the Products collection, you create a UserControl.Resources section in the XAML and add a tag that creates an instance of the Products class and assigns it a key of “productCollection”.   <UserControl.Resources>    <src:Products x:Key="productCollection" />  </UserControl.Resources> Next, you bind the list box to this productCollection object using the ItemsSource property. You bind the ItemsSource of the list box to the static resource named productCollection. You can then set the DisplayMemberPath attribute of the list box to any property of the Product class that you want. In the XAML below I used the ProductName property. <ListBox x:Name="lstData"         ItemsSource="{Binding             Source={StaticResource productCollection}}"         DisplayMemberPath="ProductName" /> You now need to create an instance of the ucProduct user contol below the list box. You do this by once again referencing the “src” namespace and typing in the name of the user control. You then set the DataContext property on this user control to a binding. The binding uses the ElementName attribute to bind to the list box name, in this case “lstData”. The Path of the data is SelectedItem. These two attributes together tell Silverlight to bind the DataContext to the selected item of the list box. That selected item is a Product object. So, once this is bound, the bindings on each text box in the user control are updated and display the current product information. <src:ucProduct x:Name="prodDetail"               DataContext="{Binding ElementName=lstData,                                      Path=SelectedItem}" /> Summary Once you understand the basics of data binding in XAML, you eliminate a lot code that is otherwise needed to move data into controls and out of controls back into an object. Connecting two controls together is easy by just binding using the ElementName and Path properties of the Binding markup extension. Another good tip out of this blog is use user controls and set the DataContext of the user control to have all of the data on the user control update through the bindings. NOTE: You can download the complete sample code (in both VB and C#) at my website. http://www.pdsa.com/downloads. Choose Tips & Tricks, then "SL – Synchronize List Box Data with User Control" 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 eBook on "Fundamentals of N-Tier".

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  • Basics of Join Factorization

    - by Hong Su
    We continue our series on optimizer transformations with a post that describes the Join Factorization transformation. The Join Factorization transformation was introduced in Oracle 11g Release 2 and applies to UNION ALL queries. Union all queries are commonly used in database applications, especially in data integration applications. In many scenarios the branches in a UNION All query share a common processing, i.e, refer to the same tables. In the current Oracle execution strategy, each branch of a UNION ALL query is evaluated independently, which leads to repetitive processing, including data access and join. The join factorization transformation offers an opportunity to share the common computations across the UNION ALL branches. Currently, join factorization only factorizes common references to base tables only, i.e, not views. Consider a simple example of query Q1. Q1:    select t1.c1, t2.c2    from t1, t2, t3    where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c2 = 2 and t2.c2 = t3.c2   union all    select t1.c1, t2.c2    from t1, t2, t4    where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c3 = t4.c3; Table t1 appears in both the branches. As does the filter predicates on t1 (t1.c1 > 1) and the join predicates involving t1 (t1.c1 = t2.c1). Nevertheless, without any transformation, the scan (and the filtering) on t1 has to be done twice, once per branch. Such a query may benefit from join factorization which can transform Q1 into Q2 as follows: Q2:    select t1.c1, VW_JF_1.item_2    from t1, (select t2.c1 item_1, t2.c2 item_2                   from t2, t3                    where t2.c2 = t3.c2 and t2.c2 = 2                                  union all                   select t2.c1 item_1, t2.c2 item_2                   from t2, t4                    where t2.c3 = t4.c3) VW_JF_1    where t1.c1 = VW_JF_1.item_1 and t1.c1 > 1; In Q2, t1 is "factorized" and thus the table scan and the filtering on t1 is done only once (it's shared). If t1 is large, then avoiding one extra scan of t1 can lead to a huge performance improvement. Another benefit of join factorization is that it can open up more join orders. Let's look at query Q3. Q3:    select *    from t5, (select t1.c1, t2.c2                  from t1, t2, t3                  where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c2 = 2 and t2.c2 = t3.c2                 union all                  select t1.c1, t2.c2                  from t1, t2, t4                  where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c3 = t4.c3) V;   where t5.c1 = V.c1 In Q3, view V is same as Q1. Before join factorization, t1, t2 and t3 must be joined first before they can be joined with t5. But if join factorization factorizes t1 from view V, t1 can then be joined with t5. This opens up new join orders. That being said, join factorization imposes certain join orders. For example, in Q2, t2 and t3 appear in the first branch of the UNION ALL query in view VW_JF_1. T2 must be joined with t3 before it can be joined with t1 which is outside of the VW_JF_1 view. The imposed join order may not necessarily be the best join order. For this reason, join factorization is performed under cost-based transformation framework; this means that we cost the plans with and without join factorization and choose the cheapest plan. Note that if the branches in UNION ALL have DISTINCT clauses, join factorization is not valid. For example, Q4 is NOT semantically equivalent to Q5.   Q4:     select distinct t1.*      from t1, t2      where t1.c1 = t2.c1  union all      select distinct t1.*      from t1, t2      where t1.c1 = t2.c1 Q5:    select distinct t1.*     from t1, (select t2.c1 item_1                   from t2                union all                   select t2.c1 item_1                  from t2) VW_JF_1     where t1.c1 = VW_JF_1.item_1 Q4 might return more rows than Q5. Q5's results are guaranteed to be duplicate free because of the DISTINCT key word at the top level while Q4's results might contain duplicates.   The examples given so far involve inner joins only. Join factorization is also supported in outer join, anti join and semi join. But only the right tables of outer join, anti join and semi joins can be factorized. It is not semantically correct to factorize the left table of outer join, anti join or semi join. For example, Q6 is NOT semantically equivalent to Q7. Q6:     select t1.c1, t2.c2    from t1, t2    where t1.c1 = t2.c1(+) and t2.c2 (+) = 2  union all    select t1.c1, t2.c2    from t1, t2      where t1.c1 = t2.c1(+) and t2.c2 (+) = 3 Q7:     select t1.c1, VW_JF_1.item_2    from t1, (select t2.c1 item_1, t2.c2 item_2                  from t2                  where t2.c2 = 2                union all                  select t2.c1 item_1, t2.c2 item_2                  from t2                                                                                                    where t2.c2 = 3) VW_JF_1       where t1.c1 = VW_JF_1.item_1(+)                                                                  However, the right side of an outer join can be factorized. For example, join factorization can transform Q8 to Q9 by factorizing t2, which is the right table of an outer join. Q8:    select t1.c2, t2.c2    from t1, t2      where t1.c1 = t2.c1 (+) and t1.c1 = 1 union all    select t1.c2, t2.c2    from t1, t2    where t1.c1 = t2.c1(+) and t1.c1 = 2 Q9:   select VW_JF_1.item_2, t2.c2   from t2,             (select t1.c1 item_1, t1.c2 item_2            from t1            where t1.c1 = 1           union all            select t1.c1 item_1, t1.c2 item_2            from t1            where t1.c1 = 2) VW_JF_1   where VW_JF_1.item_1 = t2.c1(+) All of the examples in this blog show factorizing a single table from two branches. This is just for ease of illustration. Join factorization can factorize multiple tables and from more than two UNION ALL branches.  SummaryJoin factorization is a cost-based transformation. It can factorize common computations from branches in a UNION ALL query which can lead to huge performance improvement. 

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  • getting database connectivity issue from only one part of my ASP.net project?

    - by Greg
    Hi, Something weird has started happening to my project with Dynamic Data. Suddenly I am now getting connection errors when going to the DD navigation pages, but things work fine on the default DD main page, and also other MVC pages I've added in myself work fine to the database. Any ideas? So in summary if I go to the following web pages: custom URL for my custom controller - this works fine, including getting database data main DD page from root URL - this works fine click on a link to a table maintenance page from the main DD page - GET DATABASE CONNECTIVITY ERROR Some items: * I'm using SQL Server Express 2008 * Doesn't seem to be any debug/error info in VS2010 at all I can see * Web config entry: <add name="Model1Container" connectionString="metadata=res://*/Model1.csdl|res://*/Model1.ssdl|res://*/Model1.msl;provider=System.Data.SqlClient;provider connection string=&quot;Data Source=GREG\SQLEXPRESS_2008;Initial Catalog=greg_development;Integrated Security=True;MultipleActiveResultSets=True&quot;" providerName="System.Data.EntityClient"/> Error: Server Error in '/' Application. A network-related or instance-specific error occurred while establishing a connection to SQL Server. The server was not found or was not accessible. Verify that the instance name is correct and that SQL Server is configured to allow remote connections. (provider: SQL Network Interfaces, error: 26 - Error Locating Server/Instance Specified) Description: An unhandled exception occurred during the execution of the current web request. Please review the stack trace for more information about the error and where it originated in the code. Exception Details: System.Data.SqlClient.SqlException: A network-related or instance-specific error occurred while establishing a connection to SQL Server. The server was not found or was not accessible. Verify that the instance name is correct and that SQL Server is configured to allow remote connections. (provider: SQL Network Interfaces, error: 26 - Error Locating Server/Instance Specified) Source Error: Line 39: DropDownList1.Items.Add(new ListItem("[Not Set]", NullValueString)); Line 40: } Line 41: PopulateListControl(DropDownList1); Line 42: // Set the initial value if there is one Line 43: string initialValue = DefaultValue; Source File: U:\My Dropbox\source\ToplogyLibrary\Topology_Web_Dynamic\DynamicData\Filters\ForeignKey.ascx.cs Line: 41 Stack Trace: [SqlException (0x80131904): A network-related or instance-specific error occurred while establishing a connection to SQL Server. The server was not found or was not accessible. Verify that the instance name is correct and that SQL Server is configured to allow remote connections. (provider: SQL Network Interfaces, error: 26 - Error Locating Server/Instance Specified)] System.Data.SqlClient.SqlInternalConnection.OnError(SqlException exception, Boolean breakConnection) +5009598 System.Data.SqlClient.TdsParser.ThrowExceptionAndWarning() +234 System.Data.SqlClient.TdsParser.Connect(ServerInfo serverInfo, SqlInternalConnectionTds connHandler, Boolean ignoreSniOpenTimeout, Int64 timerExpire, Boolean encrypt, Boolean trustServerCert, Boolean integratedSecurity) +341 System.Data.SqlClient.SqlInternalConnectionTds.AttemptOneLogin(ServerInfo serverInfo, String newPassword, Boolean ignoreSniOpenTimeout, TimeoutTimer timeout, SqlConnection owningObject) +129 System.Data.SqlClient.SqlInternalConnectionTds.LoginNoFailover(ServerInfo serverInfo, String newPassword, Boolean redirectedUserInstance, SqlConnection owningObject, SqlConnectionString connectionOptions, TimeoutTimer timeout) +239 System.Data.SqlClient.SqlInternalConnectionTds.OpenLoginEnlist(SqlConnection owningObject, TimeoutTimer timeout, SqlConnectionString connectionOptions, String newPassword, Boolean redirectedUserInstance) +195 System.Data.SqlClient.SqlInternalConnectionTds..ctor(DbConnectionPoolIdentity identity, SqlConnectionString connectionOptions, Object providerInfo, String newPassword, SqlConnection owningObject, Boolean redirectedUserInstance) +232 System.Data.SqlClient.SqlConnectionFactory.CreateConnection(DbConnectionOptions options, Object poolGroupProviderInfo, DbConnectionPool pool, DbConnection owningConnection) +185 System.Data.ProviderBase.DbConnectionFactory.CreatePooledConnection(DbConnection owningConnection, DbConnectionPool pool, DbConnectionOptions options) +33 System.Data.ProviderBase.DbConnectionPool.CreateObject(DbConnection owningObject) +524 System.Data.ProviderBase.DbConnectionPool.UserCreateRequest(DbConnection owningObject) +66 System.Data.ProviderBase.DbConnectionPool.GetConnection(DbConnection owningObject) +479 System.Data.ProviderBase.DbConnectionFactory.GetConnection(DbConnection owningConnection) +108 System.Data.ProviderBase.DbConnectionClosed.OpenConnection(DbConnection outerConnection, DbConnectionFactory connectionFactory) +126 System.Data.SqlClient.SqlConnection.Open() +125 System.Data.EntityClient.EntityConnection.OpenStoreConnectionIf(Boolean openCondition, DbConnection storeConnectionToOpen, DbConnection originalConnection, String exceptionCode, String attemptedOperation, Boolean& closeStoreConnectionOnFailure) +52 [EntityException: The underlying provider failed on Open.] System.Data.EntityClient.EntityConnection.OpenStoreConnectionIf(Boolean openCondition, DbConnection storeConnectionToOpen, DbConnection originalConnection, String exceptionCode, String attemptedOperation, Boolean& closeStoreConnectionOnFailure) +161 System.Data.EntityClient.EntityConnection.Open() +98 System.Data.Objects.ObjectContext.EnsureConnection() +81 System.Data.Objects.ObjectQuery`1.GetResults(Nullable`1 forMergeOption) +46 System.Data.Objects.ObjectQuery`1.System.Collections.Generic.IEnumerable<T>.GetEnumerator() +44 System.Data.Objects.ObjectQuery`1.GetEnumeratorInternal() +36 System.Data.Objects.ObjectQuery.System.Collections.IEnumerable.GetEnumerator() +10 System.Web.DynamicData.Misc.FillListItemCollection(IMetaTable table, ListItemCollection listItemCollection) +50 System.Web.DynamicData.QueryableFilterUserControl.PopulateListControl(ListControl listControl) +85 Topology_Web_Dynamic.ForeignKeyFilter.Page_Init(Object sender, EventArgs e) in U:\My Dropbox\source\ToplogyLibrary\Topology_Web_Dynamic\DynamicData\Filters\ForeignKey.ascx.cs:41 System.Web.Util.CalliHelper.EventArgFunctionCaller(IntPtr fp, Object o, Object t, EventArgs e) +14 System.Web.Util.CalliEventHandlerDelegateProxy.Callback(Object sender, EventArgs e) +35 System.Web.UI.Control.OnInit(EventArgs e) +91 System.Web.UI.UserControl.OnInit(EventArgs e) +83 System.Web.UI.Control.InitRecursive(Control namingContainer) +140 System.Web.UI.Control.AddedControl(Control control, Int32 index) +197 System.Web.UI.ControlCollection.Add(Control child) +79 System.Web.DynamicData.DynamicFilter.EnsureInit(IQueryableDataSource dataSource) +200 System.Web.DynamicData.QueryableFilterRepeater.<Page_InitComplete>b__1(DynamicFilter f) +11 System.Collections.Generic.List`1.ForEach(Action`1 action) +145 System.Web.DynamicData.QueryableFilterRepeater.Page_InitComplete(Object sender, EventArgs e) +607 System.EventHandler.Invoke(Object sender, EventArgs e) +0 System.Web.UI.Page.OnInitComplete(EventArgs e) +8871862 System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) +604 Version Information: Microsoft .NET Framework Version:4.0.30319; ASP.NET Version:4.0.30319.1

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  • SQL SERVER – How to Recover SQL Database Data Deleted by Accident

    - by Pinal Dave
    In Repair a SQL Server database using a transaction log explorer, I showed how to use ApexSQL Log, a SQL Server transaction log viewer, to recover a SQL Server database after a disaster. In this blog, I’ll show you how to use another SQL Server disaster recovery tool from ApexSQL in a situation when data is accidentally deleted. You can download ApexSQL Recover here, install, and play along. With a good SQL Server disaster recovery strategy, data recovery is not a problem. You have a reliable full database backup with valid data, a full database backup and subsequent differential database backups, or a full database backup and a chain of transaction log backups. But not all situations are ideal. Here we’ll address some sub-optimal scenarios, where you can still successfully recover data. If you have only a full database backup This is the least optimal SQL Server disaster recovery strategy, as it doesn’t ensure minimal data loss. For example, data was deleted on Wednesday. Your last full database backup was created on Sunday, three days before the records were deleted. By using the full database backup created on Sunday, you will be able to recover SQL database records that existed in the table on Sunday. If there were any records inserted into the table on Monday or Tuesday, they will be lost forever. The same goes for records modified in this period. This method will not bring back modified records, only the old records that existed on Sunday. If you restore this full database backup, all your changes (intentional and accidental) will be lost and the database will be reverted to the state it had on Sunday. What you have to do is compare the records that were in the table on Sunday to the records on Wednesday, create a synchronization script, and execute it against the Wednesday database. If you have a full database backup followed by differential database backups Let’s say the situation is the same as in the example above, only you create a differential database backup every night. Use the full database backup created on Sunday, and the last differential database backup (created on Tuesday). In this scenario, you will lose only the data inserted and updated after the differential backup created on Tuesday. If you have a full database backup and a chain of transaction log backups This is the SQL Server disaster recovery strategy that provides minimal data loss. With a full chain of transaction logs, you can recover the SQL database to an exact point in time. To provide optimal results, you have to know exactly when the records were deleted, because restoring to a later point will not bring back the records. This method requires restoring the full database backup first. If you have any differential log backup created after the last full database backup, restore the most recent one. Then, restore transaction log backups, one by one, it the order they were created starting with the first created after the restored differential database backup. Now, the table will be in the state before the records were deleted. You have to identify the deleted records, script them and run the script against the original database. Although this method is reliable, it is time-consuming and requires a lot of space on disk. How to easily recover deleted records? The following solution enables you to recover SQL database records even if you have no full or differential database backups and no transaction log backups. To understand how ApexSQL Recover works, I’ll explain what happens when table data is deleted. Table data is stored in data pages. When you delete table records, they are not immediately deleted from the data pages, but marked to be overwritten by new records. Such records are not shown as existing anymore, but ApexSQL Recover can read them and create undo script for them. How long will deleted records stay in the MDF file? It depends on many factors, as time passes it’s less likely that the records will not be overwritten. The more transactions occur after the deletion, the more chances the records will be overwritten and permanently lost. Therefore, it’s recommended to create a copy of the database MDF and LDF files immediately (if you cannot take your database offline until the issue is solved) and run ApexSQL Recover on them. Note that a full database backup will not help here, as the records marked for overwriting are not included in the backup. First, I’ll delete some records from the Person.EmailAddress table in the AdventureWorks database.   I can delete these records in SQL Server Management Studio, or execute a script such as DELETE FROM Person.EmailAddress WHERE BusinessEntityID BETWEEN 70 AND 80 Then, I’ll start ApexSQL Recover and select From DELETE operation in the Recovery tab.   In the Select the database to recover step, first select the SQL Server instance. If it’s not shown in the drop-down list, click the Server icon right to the Server drop-down list and browse for the SQL Server instance, or type the instance name manually. Specify the authentication type and select the database in the Database drop-down list.   In the next step, you’re prompted to add additional data sources. As this can be a tricky step, especially for new users, ApexSQL Recover offers help via the Help me decide option.   The Help me decide option guides you through a series of questions about the database transaction log and advises what files to add. If you know that you have no transaction log backups or detached transaction logs, or the online transaction log file has been truncated after the data was deleted, select No additional transaction logs are available. If you know that you have transaction log backups that contain the delete transactions you want to recover, click Add transaction logs. The online transaction log is listed and selected automatically.   Click Add if to add transaction log backups. It would be best if you have a full transaction log chain, as explained above. The next step for this option is to specify the time range.   Selecting a small time range for the time of deletion will create the recovery script just for the accidentally deleted records. A wide time range might script the records deleted on purpose, and you don’t want that. If needed, you can check the script generated and manually remove such records. After that, for all data sources options, the next step is to select the tables. Be careful here, if you deleted some data from other tables on purpose, and don’t want to recover them, don’t select all tables, as ApexSQL Recover will create the INSERT script for them too.   The next step offers two options: to create a recovery script that will insert the deleted records back into the Person.EmailAddress table, or to create a new database, create the Person.EmailAddress table in it, and insert the deleted records. I’ll select the first one.   The recovery process is completed and 11 records are found and scripted, as expected.   To see the script, click View script. ApexSQL Recover has its own script editor, where you can review, modify, and execute the recovery script. The insert into statements look like: INSERT INTO Person.EmailAddress( BusinessEntityID, EmailAddressID, EmailAddress, rowguid, ModifiedDate) VALUES( 70, 70, N'[email protected]' COLLATE SQL_Latin1_General_CP1_CI_AS, 'd62c5b4e-c91f-403f-b630-7b7e0fda70ce', '20030109 00:00:00.000' ); To execute the script, click Execute in the menu.   If you want to check whether the records are really back, execute SELECT * FROM Person.EmailAddress WHERE BusinessEntityID BETWEEN 70 AND 80 As shown, ApexSQL Recover recovers SQL database data after accidental deletes even without the database backup that contains the deleted data and relevant transaction log backups. ApexSQL Recover reads the deleted data from the database data file, so this method can be used even for databases in the Simple recovery model. Besides recovering SQL database records from a DELETE statement, ApexSQL Recover can help when the records are lost due to a DROP TABLE, or TRUNCATE statement, as well as repair a corrupted MDF file that cannot be attached to as SQL Server instance. You can find more information about how to recover SQL database lost data and repair a SQL Server database on ApexSQL Solution center. There are solutions for various situations when data needs to be recovered. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Introduction to Rollup Clause

    - by pinaldave
    In this article we will go over basic understanding of Rollup clause in SQL Server. ROLLUP clause is used to do aggregate operation on multiple levels in hierarchy. Let us understand how it works by using an example. Consider a table with the following structure and data: CREATE TABLE tblPopulation ( Country VARCHAR(100), [State] VARCHAR(100), City VARCHAR(100), [Population (in Millions)] INT ) GO INSERT INTO tblPopulation VALUES('India', 'Delhi','East Delhi',9 [...]

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  • How to improve Windows Aero desktop performance?

    - by Click Ok
    Sincerely I don't understand why in Windows Experience ratings, the "Game Graphics" in my pc is 5.0 and "Graphic Elements" (windows aero desktop performance) is 3.9. How it is possible? My VGA is nice for games but bad for Windows Desktop? What I can do to improve windows aero desktop performance?

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  • How to Always Load Internet Explorer 9 in Full Screen Mode

    - by Lori Kaufman
    Internet Explorer 9 has a minimal interface by default, with the tab bar and the toolbar and address bar on the same line. However, you can gain even more viewable space by pressing F11 to go to full screen mode. If you like full screen mode and want to use it most of the time, you can have Internet Explorer open in that mode automatically, by editing a setting in the registry. To begin, enter “regedit” (without the quotes) in the Search box on the Start menu. When the results display, click regedit.exe or press Enter when it’s highlighted. NOTE: Before making changes to the registry, be sure you back it up. We also recommend creating a restore point you can use to restore your system if something goes wrong. HTG Explains: Learn How Websites Are Tracking You Online Here’s How to Download Windows 8 Release Preview Right Now HTG Explains: Why Linux Doesn’t Need Defragmenting

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  • SQL SERVER – Index Created on View not Used Often – Observation of the View – Part 2

    - by pinaldave
    Earlier, I have written an article about SQL SERVER – Index Created on View not Used Often – Observation of the View. I received an email from one of the readers, asking if there would no problems when we create the Index on the base table. Well, we need to discuss this situation in two different cases. Before proceeding to the discussion, I strongly suggest you read my earlier articles. To avoid the duplication, I am not going to repeat the code and explanation over here. In all the earlier cases, I have explained in detail how Index created on the View is not utilized. SQL SERVER – Index Created on View not Used Often – Limitation of the View 12 SQL SERVER – Index Created on View not Used Often – Observation of the View SQL SERVER – Indexed View always Use Index on Table As per earlier blog posts, so far we have done the following: Create a Table Create a View Create Index On View Write SELECT with ORDER BY on View However, the blog reader who emailed me suggests the extension of the said logic, which is as follows: Create a Table Create a View Create Index On View Write SELECT with ORDER BY on View Create Index on the Base Table Write SELECT with ORDER BY on View After doing the last two steps, the question is “Will the query on the View utilize the Index on the View, or will it still use the Index of the base table?“ Let us first run the Create example. USE tempdb GO IF EXISTS (SELECT * FROM sys.views WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[SampleView]')) DROP VIEW [dbo].[SampleView] GO IF EXISTS (SELECT * FROM sys.objects WHERE OBJECT_ID = OBJECT_ID(N'[dbo].[mySampleTable]') AND TYPE IN (N'U')) DROP TABLE [dbo].[mySampleTable] GO -- Create SampleTable CREATE TABLE mySampleTable (ID1 INT, ID2 INT, SomeData VARCHAR(100)) INSERT INTO mySampleTable (ID1,ID2,SomeData) SELECT TOP 100000 ROW_NUMBER() OVER (ORDER BY o1.name), ROW_NUMBER() OVER (ORDER BY o2.name), o2.name FROM sys.all_objects o1 CROSS JOIN sys.all_objects o2 GO -- Create View CREATE VIEW SampleView WITH SCHEMABINDING AS SELECT ID1,ID2,SomeData FROM dbo.mySampleTable GO -- Create Index on View CREATE UNIQUE CLUSTERED INDEX [IX_ViewSample] ON [dbo].[SampleView] ( ID2 ASC ) GO -- Select from view SELECT ID1,ID2,SomeData FROM SampleView ORDER BY ID2 GO -- Create Index on Original Table -- On Column ID1 CREATE UNIQUE CLUSTERED INDEX [IX_OriginalTable] ON mySampleTable ( ID1 ASC ) GO -- On Column ID2 CREATE UNIQUE NONCLUSTERED INDEX [IX_OriginalTable_ID2] ON mySampleTable ( ID2 ) GO -- Select from view SELECT ID1,ID2,SomeData FROM SampleView ORDER BY ID2 GO Now let us see the execution plans for both of the SELECT statement. Before Index on Base Table (with Index on View): After Index on Base Table (with Index on View): Looking at both executions, it is very clear that with or without, the View is using Indexes. Alright, I have written 11 disadvantages of the Views. Now I have written one case where the View is using Indexes. Anybody who says that I am being harsh on Views can say now that I found one place where Index on View can be helpful. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL View, SQLServer, T SQL, Technology

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