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  • Which of Your Stored Procedures are Using the Most Resources?

    Dynamic Management Views and Functions aren't always easy to understand. However, they are the easiest way of finding out which of your stored procedures are using up the most resources. Greg takes the time to explain how and why these DMVs and DMFs get their information. Suddenly, it all gets clearer. Join SQL Backup’s 35,000+ customers to compress and strengthen your backups "SQL Backup will be a REAL boost to any DBA lucky enough to use it." Jonathan Allen. Download a free trial now.

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  • Swichable Graphics

    - by user67291
    Im having a bit of a problem with my 2 graphic card in my laptop. laptop: Acer Aspire 5553g Graphic Cards: Performance: ATI Mobility Radeon HD 5650 Power saving: ATI Radeon HD 4200. On this laptop i have used ubuntu 11.04, then upgraded to 11.11, and now upgraded to 12.04 the other day. The problem is that sins i upgraded to 12.04 im unable to switch to my performance graphic card using the Catalyst Control Center. Under 11.04 and 11.11 it was no problem. I open the Catalyst Control Center and select the performance option then apply, it tels me that it will be applied after reboot, I reboot and nothing has changed. Im able to "force" it by changing in BIOS, so i know there is nothing wrong with the card. Thanks /Daan

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  • LINQ Lycanthropy: Transformations into LINQ

    LINQ is one of the few technologies that you can start to use without a lot of preliminary learning. Also, it lends itself to learning by trying out examples. With Michael Sorens' help, you can watch as your conventional C# code changes to ravenous LINQ before your very eyes. Join SQL Backup’s 35,000+ customers to compress and strengthen your backups "SQL Backup will be a REAL boost to any DBA lucky enough to use it." Jonathan Allen. Download a free trial now.

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  • Existing Instance, Shiny New Disks

    - by merrillaldrich
    Migrating an Instance of SQL Server to New Disks I get to do something pretty entertaining this week – migrate SQL instances on a 2008 cluster from one disk array to another! Zut alors! I am so excited I can hardly contain myself, so let’s get started. (Only a DBA could love this stuff, am I right? I know.) Anyway, here’s one method of many to migrate your data. Assumption : this is a host-based migration, which just means I’m using the Windows file system to push the data from one set of SAN disks...(read more)

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  • Did You Know: What do you know that isn't so?

    - by Kalen Delaney
    You know what they say… it's not what you don't know that will hurt you, it's what you know that isn't so! In other words, your misconceptions. Or, as Paul Nielson calls them in his SQL Server Bible … MYTHconceptions. Some misconceptions come from misunderstanding of complex information, or from misinterpreting your own results, and assuming we can generalize behavior from one particular situation. Since I teach advanced classes to students with lots of SQL Server experience, I actually see a lot...(read more)

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  • How to Create Effective Error Reports

    - by John Paul Cook
    This post demonstrates some generic problem reporting steps that I encourage all users, whether developers or nontechnical end users, to follow. SQL Server has a feature that can help. So does Windows in some cases. More on those in Step 3. Step 1: Is the problem caused by a particular action undertaken on a gui? If so, you should get a screen capture. But if it is caused by executing some T-SQL code in a query window, just copy/paste the offending code as text. There are several ways to get a screen...(read more)

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  • StreamInsight 2.1, meet LINQ

    - by Roman Schindlauer
    Someone recently called LINQ “magic” in my hearing. I leapt to LINQ’s defense immediately. Turns out some people don’t realize “magic” is can be a pejorative term. I thought LINQ needed demystification. Here’s your best demystification resource: http://blogs.msdn.com/b/mattwar/archive/2008/11/18/linq-links.aspx. I won’t repeat much of what Matt Warren says in his excellent series, but will talk about some core ideas and how they affect the 2.1 release of StreamInsight. Let’s tell the story of a LINQ query. Compile time It begins with some code: IQueryable<Product> products = ...; var query = from p in products             where p.Name == "Widget"             select p.ProductID; foreach (int id in query) {     ... When the code is compiled, the C# compiler (among other things) de-sugars the query expression (see C# spec section 7.16): ... var query = products.Where(p => p.Name == "Widget").Select(p => p.ProductID); ... Overload resolution subsequently binds the Queryable.Where<Product> and Queryable.Select<Product, int> extension methods (see C# spec sections 7.5 and 7.6.5). After overload resolution, the compiler knows something interesting about the anonymous functions (lambda syntax) in the de-sugared code: they must be converted to expression trees, i.e.,“an object structure that represents the structure of the anonymous function itself” (see C# spec section 6.5). The conversion is equivalent to the following rewrite: ... var prm1 = Expression.Parameter(typeof(Product), "p"); var prm2 = Expression.Parameter(typeof(Product), "p"); var query = Queryable.Select<Product, int>(     Queryable.Where<Product>(         products,         Expression.Lambda<Func<Product, bool>>(Expression.Property(prm1, "Name"), prm1)),         Expression.Lambda<Func<Product, int>>(Expression.Property(prm2, "ProductID"), prm2)); ... If the “products” expression had type IEnumerable<Product>, the compiler would have chosen the Enumerable.Where and Enumerable.Select extension methods instead, in which case the anonymous functions would have been converted to delegates. At this point, we’ve reduced the LINQ query to familiar code that will compile in C# 2.0. (Note that I’m using C# snippets to illustrate transformations that occur in the compiler, not to suggest a viable compiler design!) Runtime When the above program is executed, the Queryable.Where method is invoked. It takes two arguments. The first is an IQueryable<> instance that exposes an Expression property and a Provider property. The second is an expression tree. The Queryable.Where method implementation looks something like this: public static IQueryable<T> Where<T>(this IQueryable<T> source, Expression<Func<T, bool>> predicate) {     return source.Provider.CreateQuery<T>(     Expression.Call(this method, source.Expression, Expression.Quote(predicate))); } Notice that the method is really just composing a new expression tree that calls itself with arguments derived from the source and predicate arguments. Also notice that the query object returned from the method is associated with the same provider as the source query. By invoking operator methods, we’re constructing an expression tree that describes a query. Interestingly, the compiler and operator methods are colluding to construct a query expression tree. The important takeaway is that expression trees are built in one of two ways: (1) by the compiler when it sees an anonymous function that needs to be converted to an expression tree, and; (2) by a query operator method that constructs a new queryable object with an expression tree rooted in a call to the operator method (self-referential). Next we hit the foreach block. At this point, the power of LINQ queries becomes apparent. The provider is able to determine how the query expression tree is evaluated! The code that began our story was intentionally vague about the definition of the “products” collection. Maybe it is a queryable in-memory collection of products: var products = new[]     { new Product { Name = "Widget", ProductID = 1 } }.AsQueryable(); The in-memory LINQ provider works by rewriting Queryable method calls to Enumerable method calls in the query expression tree. It then compiles the expression tree and evaluates it. It should be mentioned that the provider does not blindly rewrite all Queryable calls. It only rewrites a call when its arguments have been rewritten in a way that introduces a type mismatch, e.g. the first argument to Queryable.Where<Product> being rewritten as an expression of type IEnumerable<Product> from IQueryable<Product>. The type mismatch is triggered initially by a “leaf” expression like the one associated with the AsQueryable query: when the provider recognizes one of its own leaf expressions, it replaces the expression with the original IEnumerable<> constant expression. I like to think of this rewrite process as “type irritation” because the rewritten leaf expression is like a foreign body that triggers an immune response (further rewrites) in the tree. The technique ensures that only those portions of the expression tree constructed by a particular provider are rewritten by that provider: no type irritation, no rewrite. Let’s consider the behavior of an alternative LINQ provider. If “products” is a collection created by a LINQ to SQL provider: var products = new NorthwindDataContext().Products; the provider rewrites the expression tree as a SQL query that is then evaluated by your favorite RDBMS. The predicate may ultimately be evaluated using an index! In this example, the expression associated with the Products property is the “leaf” expression. StreamInsight 2.1 For the in-memory LINQ to Objects provider, a leaf is an in-memory collection. For LINQ to SQL, a leaf is a table or view. When defining a “process” in StreamInsight 2.1, what is a leaf? To StreamInsight a leaf is logic: an adapter, a sequence, or even a query targeting an entirely different LINQ provider! How do we represent the logic? Remember that a standing query may outlive the client that provisioned it. A reference to a sequence object in the client application is therefore not terribly useful. But if we instead represent the code constructing the sequence as an expression, we can host the sequence in the server: using (var server = Server.Connect(...)) {     var app = server.Applications["my application"];     var source = app.DefineObservable(() => Observable.Range(0, 10, Scheduler.NewThread));     var query = from i in source where i % 2 == 0 select i; } Example 1: defining a source and composing a query Let’s look in more detail at what’s happening in example 1. We first connect to the remote server and retrieve an existing app. Next, we define a simple Reactive sequence using the Observable.Range method. Notice that the call to the Range method is in the body of an anonymous function. This is important because it means the source sequence definition is in the form of an expression, rather than simply an opaque reference to an IObservable<int> object. The variation in Example 2 fails. Although it looks similar, the sequence is now a reference to an in-memory observable collection: var local = Observable.Range(0, 10, Scheduler.NewThread); var source = app.DefineObservable(() => local); // can’t serialize ‘local’! Example 2: error referencing unserializable local object The Define* methods support definitions of operator tree leaves that target the StreamInsight server. These methods all have the same basic structure. The definition argument is a lambda expression taking between 0 and 16 arguments and returning a source or sink. The method returns a proxy for the source or sink that can then be used for the usual style of LINQ query composition. The “define” methods exploit the compile-time C# feature that converts anonymous functions into translatable expression trees! Query composition exploits the runtime pattern that allows expression trees to be constructed by operators taking queryable and expression (Expression<>) arguments. The practical upshot: once you’ve Defined a source, you can compose LINQ queries in the familiar way using query expressions and operator combinators. Notably, queries can be composed using pull-sequences (LINQ to Objects IQueryable<> inputs), push sequences (Reactive IQbservable<> inputs), and temporal sequences (StreamInsight IQStreamable<> inputs). You can even construct processes that span these three domains using “bridge” method overloads (ToEnumerable, ToObservable and To*Streamable). Finally, the targeted rewrite via type irritation pattern is used to ensure that StreamInsight computations can leverage other LINQ providers as well. Consider the following example (this example depends on Interactive Extensions): var source = app.DefineEnumerable((int id) =>     EnumerableEx.Using(() =>         new NorthwindDataContext(), context =>             from p in context.Products             where p.ProductID == id             select p.ProductName)); Within the definition, StreamInsight has no reason to suspect that it ‘owns’ the Queryable.Where and Queryable.Select calls, and it can therefore defer to LINQ to SQL! Let’s use this source in the context of a StreamInsight process: var sink = app.DefineObserver(() => Observer.Create<string>(Console.WriteLine)); var query = from name in source(1).ToObservable()             where name == "Widget"             select name; using (query.Bind(sink).Run("process")) {     ... } When we run the binding, the source portion which filters on product ID and projects the product name is evaluated by SQL Server. Outside of the definition, responsibility for evaluation shifts to the StreamInsight server where we create a bridge to the Reactive Framework (using ToObservable) and evaluate an additional predicate. It’s incredibly easy to define computations that span multiple domains using these new features in StreamInsight 2.1! Regards, The StreamInsight Team

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  • The case against INFORMATION_SCHEMA views

    - by AaronBertrand
    In SQL Server 2000, INFORMATION_SCHEMA was the way I derived all of my metadata information - table names, procedure names, column names and data types, relationships... the list goes on and on. I used the system tables like sysindexes from time to time, but I tried to stay away from them when I could. In SQL Server 2005, this all changed with the introduction of catalog views. For one thing, they're a lot easier to type. sys.tables vs. INFORMATION_SCHEMA.TABLES? Come on; no contest there - even...(read more)

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  • Meet @marcorus and @ferrarialberto at TechEd Europe 2012 #tee2012

    - by Marco Russo (SQLBI)
    I and Alberto are in Amsterdam this week at TechEd Europe 2012. If you are here at the conference, you can meet us here: Wed, Jun 27 10:15 AM - 11:30 AM – Room G106 DBI319 - BISM: Multidimensional vs. Tabular Wed, Jun 27 02:15 PM – 02:30 PM – Microsoft Press Booth in the TechExpo area PowerPivot for Excel 2010 Book Signing Thu, Jun 28 8:30 AM - 9:45 AM – Room E107 Many-to-Many Relationships in BISM Tabular Fri, Jun 29 1:00 PM - 2:45 PM – Breakthrough Insight at Microsoft SQL Server Booth – TechExpo area Staff and Q&A We’ll try to visit the Microsoft Booth very often and we’ll be in the area Breakthrough Insight of SQL Server zone (see the picture to identify it). And don’t miss the PowerPivot for Excel 2010 book signing event:

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  • Point-in-time restore of database backup?

    - by TiborKaraszi
    SQL Server 2005 added the STOPAT option for the RESTORE DATABASE command. This sounds great - we can stop at some point in time during the database backup process was running! Or? No, we can't. Here follows some tech stuff why not, and then what the option is really meant for: A database backup includes all used extents and also all log records that were produced while the backup process was running (possibly older as well, to handle open transactions). When you restore such a backup, SQL Server...(read more)

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  • Meet @marcorus and @ferrarialberto at TechEd Europe 2012 #tee2012

    - by Marco Russo (SQLBI)
    I and Alberto are in Amsterdam this week at TechEd Europe 2012. If you are here at the conference, you can meet us here: Wed, Jun 27 10:15 AM - 11:30 AM – Room G106 DBI319 - BISM: Multidimensional vs. Tabular Wed, Jun 27 02:15 PM – 02:30 PM – Microsoft Press Booth in the TechExpo area PowerPivot for Excel 2010 Book Signing Thu, Jun 28 8:30 AM - 9:45 AM – Room E107 Many-to-Many Relationships in BISM Tabular Fri, Jun 29 1:00 PM - 2:45 PM – Breakthrough Insight at Microsoft SQL Server Booth – TechExpo area Staff and Q&A We’ll try to visit the Microsoft Booth very often and we’ll be in the area Breakthrough Insight of SQL Server zone (see the picture to identify it). And don’t miss the PowerPivot for Excel 2010 book signing event:

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  • Google I/O 2012 - Breaking the JavaScript Speed Limit with V8

    Google I/O 2012 - Breaking the JavaScript Speed Limit with V8 Daniel Clifford Are you are interested in making JavaScript run blazingly fast in Chrome? This talk takes a look under the hood in V8 to help you identify how to optimize your JavaScript code. We'll show you how to leverage V8's sampling profiler to eliminate performance bottlenecks and optimize JavaScript programs, and we'll expose how V8 uses hidden classes and runtime type feedback to generate efficient JIT code. Attendees will leave the session with solid optimization guidelines for their JavaScript app and a good understanding on how to best use performance tools and JavaScript idioms to maximize the performance of their application with V8. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 3049 113 ratings Time: 47:35 More in Science & Technology

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  • Cloud Computing Forces Better Design Practices

    - by Herve Roggero
    Is cloud computing simply different than on premise development, or is cloud computing actually forcing you to create better applications than you normally would? In other words, is cloud computing merely imposing different design principles, or forcing better design principles?  A little while back I got into a discussion with a developer in which I was arguing that cloud computing, and specifically Windows Azure in his case, was forcing developers to adopt better design principles. His opinion was that cloud computing was not yielding better systems; just different systems. In this blog, I will argue that cloud computing does force developers to use better design practices, and hence better applications. So the first thing to define, of course, is the word “better”, in the context of application development. Looking at a few definitions online, better means “superior quality”. As it relates to this discussion then, I stipulate that cloud computing can yield higher quality applications in terms of scalability, everything else being equal. Before going further I need to also outline the difference between performance and scalability. Performance and scalability are two related concepts, but they don’t mean the same thing. Scalability is the measure of system performance given various loads. So when developers design for performance, they usually give higher priority to a given load and tend to optimize for the given load. When developers design for scalability, the actual performance at a given load is not as important; the ability to ensure reasonable performance regardless of the load becomes the objective. This can lead to very different design choices. For example, if your objective is to obtains the fastest response time possible for a service you are building, you may choose the implement a TCP connection that never closes until the client chooses to close the connection (in other words, a tightly coupled service from a connectivity standpoint), and on which a connection session is established for faster processing on the next request (like SQL Server or other database systems for example). If you objective is to scale, you may implement a service that answers to requests without keeping session state, so that server resources are released as quickly as possible, like a REST service for example. This alternate design would likely have a slower response time than the TCP service for any given load, but would continue to function at very large loads because of its inherently loosely coupled design. An example of a REST service is the NO-SQL implementation in the Microsoft cloud called Azure Tables. Now, back to cloud computing… Cloud computing is designed to help you scale your applications, specifically when you use Platform as a Service (PaaS) offerings. However it’s not automatic. You can design a tightly-coupled TCP service as discussed above, and as you can imagine, it probably won’t scale even if you place the service in the cloud because it isn’t using a connection pattern that will allow it to scale [note: I am not implying that all TCP systems do not scale; I am just illustrating the scalability concepts with an imaginary TCP service that isn’t designed to scale for the purpose of this discussion]. The other service, using REST, will have a better chance to scale because, by design, it minimizes resource consumption for individual requests and doesn’t tie a client connection to a specific endpoint (which means you can easily deploy this service to hundreds of machines without much trouble, as long as your pockets are deep enough). The TCP and REST services discussed above are both valid designs; the TCP service is faster and the REST service scales better. So is it fair to say that one service is fundamentally better than the other? No; not unless you need to scale. And if you don’t need to scale, then you don’t need the cloud in the first place. However, it is interesting to note that if you do need to scale, then a loosely coupled system becomes a better design because it can almost always scale better than a tightly-coupled system. And because most applications grow overtime, with an increasing user base, new functional requirements, increased data and so forth, most applications eventually do need to scale. So in my humble opinion, I conclude that a loosely coupled system is not just different than a tightly coupled system; it is a better design, because it will stand the test of time. And in my book, if a system stands the test of time better than another, it is of superior quality. Because cloud computing demands loosely coupled systems so that its underlying service architecture can be leveraged, developers ultimately have no choice but to design loosely coupled systems for the cloud. And because loosely coupled systems are better… … the cloud forces better design practices. My 2 cents.

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  • Power View Infrastructure Configuration and Installation: Step-by-Step and Scripts

    This document contains step-by-step instructions for installing and testing the Microsoft Business Intelligence infrastructure based on SQL Server 2012 and SharePoint 2010, focused on SQL Server 2012 Reporting Services with Power View. This document describes how to completely install the following scenarios: a standalone instance of SharePoint and Power View with all required components; a new SharePoint farm with the Power View infrastructure; a server with the Power View infrastructure joined to an existing SharePoint farm; installation on a separate computer of client tools; installation of a tabular instance of Analysis Services on a separate instance; and configuration of single sign-on access for double-hop scenarios with and without Kerberos. Scripts are provided for all/most scenarios.

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  • The Com.PASS Feeds

    A new set of RSS feeds, hosted by PASS, bring you a large quantity of SQL Server content from various sites, including SQLServerCentral.

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  • Learning PostgreSql: Embracing Change With Copying Types and VARCHAR(NO_SIZE_NEEDED)

    - by Alexander Kuznetsov
    PostgreSql 9.3 allows us to declare parameter types to match column types, aka Copying Types. Also it allows us to omit the length of VARCHAR fields, without any performance penalty. These two features make PostgreSql a great back end for agile development, because they make PL/PgSql more resilient to changes. Both features are not in SQL Server 2008 R2. I am not sure about later releases of SQL Server. Let us discuss them in more detail and see why they are so useful. Using Copying Types Suppose...(read more)

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  • Linqpad and Autocompletion

    I have mentioned before about doing development for StreamInsight in Linqpad. I have it installed on two separate PCs and I have enabled autocompletion on only one of them. Whilst both versions are an excellent tool, the one with autocompletion enabled is so much easier to use. After enabling autocompletion you can see I now get parameter listing Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • Contiguous Time Periods

    It is always more efficient to maintain referential integrity by using constraints rather than triggers. Sometimes it isn't obvious how to do this. Until a recent idea by Alex Kuznetsov, the history table presented problems for checking data that were difficult to solve with constraints. Joe Celko explains. Free trial of SQL Backup™“SQL Backup was able to cut down my backup time significantly AND achieved a 90% compression at the same time!” Joe Cheng. Download a free trial now.

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  • SPARC T5-4 Engineering Simulation Solution

    - by Mike Mulkey-Oracle
    A recent Oracle internal performance evaluation for computer-based product design demonstrated that Oracle's SPARC T5-4 server running MSC's SimManager simulation software with Oracle Database 12c consolidates the work of multiple x86 servers while delivering better overall performance.   Engineering simulation solutions have taken the center stage in helping companies design and develop innovative products while reducing physical prototyping costs, and exploring a larger design space, resulting in more design possibilities. For this solution, a single SPARC T5-4 server running Oracle Solaris 11 was deployed to consolidate the MSC SimManager server, the Oracle Database 12c server, and the web application server onto a single platform. An automotive design workload was deployed to demonstrate how the SPARC T5-4 server can be used to consolidate the work of multiple x86 servers and deliver better overall performance while reducing complexity and achieving optimal product designs.  A joint Oracle/MSC Software solution brief describes this in more detail:  A Simplified Solution for Product Lifecycle Management —MSC SimManager on a SPARC T5-4 Server

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  • Could it be more efficient for systems in general to do away with Stacks and just use Heap for memory management?

    - by Dark Templar
    It seems to me that everything that can be done with a stack can be done with the heap, but not everything that can be done with the heap can be done with the stack. Is that correct? Then for simplicity's sake, and even if we do lose a little amount of performance with certain workloads, couldn't it be better to just go with one standard (ie, the heap)? Think of the trade-off between modularity and performance. I know that isn't the best way to describe this scenario, but in general it seems that simplicity of understanding and design could be a better option even if there is a potential for better performance.

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  • Should I keep separate client codebases and databases for a software-as-a-service application?

    - by John
    My question is about the architecture of my application. I have a Rails application where companies can administrate all things related to their clients. Companies would buy a subscription and their users can access the application online. Hopefully I will get multiple companies subscribing to my application/service. What should I do with my code and database? Seperate app code base and database per company One app code base but seperate database per company One app code base and one database The decision involves security (e.g. a user from company X should not see any data from company Y) performance (let's suppose it becomes successful, it should have a good performance) and scalability (again, if successful, it should have a good performance but also easy for me to handle all the companies, code changes, etc). For the sake of maintainability, I tend to opt for the one code base, but for the database I really don't know. What do you think is the best option?

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