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  • SQL. Sorting by a field

    - by strakastroukas
    I have created a simple view consisting of 3 tables in SQL. By right clicking and selecting Design, in the Object explorer table, i modified my custom view. I just added sortby asc in a field. The problem is that the changes are not reflected in the outout of the View. After saving the view, and selecting Open view the sort is not displayed in output. So what is going on here?

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  • An XEvent a Day (10 of 31) – Targets Week – etw_classic_sync_target

    - by Jonathan Kehayias
    Yesterday’s post, Targets Week – pair_matching , looked at the pair_matching Target in Extended Events and how it could be used to find unmatched Events.  Today’s post will cover the etw_classic_sync_target Target, which can be used to track Events starting in SQL Server, out to the Windows Server OS Kernel, and then back to the Event completion in SQL Server. What is the etw_classic_sync_target Target? The etw_classic_sync_target Target is the target that hooks Extended Events in SQL Server...(read more)

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  • An XEvent a Day (17 of 31) – A Look at Backup Internals and How to Track Backup and Restore Throughput (Part 1)

    - by Jonathan Kehayias
    Today’s post is a continuation of yesterday’s post How Many Checkpoints are Issued During a Full Backup? and the investigation of Database Engine Internals with Extended Events.  In today’s post we’ll look at how Backup’s work inside of SQL Server and how to track the throughput of Backup and Restore operations.  This post is not going to cover Backups in SQL Server as a topic; if that is what you are looking for see Paul Randal’s TechNet Article Understanding SQL Server Backups . Yesterday...(read more)

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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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  • What’s new in SQL Prompt 6.3?

    - by Tom Crossman
    This post describes some of the improvements we’ve made in the latest version of SQL Prompt. Code suggestions In recent months, the focus of the SQL Prompt development team has been to remove annoyances and improve code suggestions. Here’s just a few of the improvements to code suggestions we’ve made in SQL Prompt 6.3: The suggestions box is no longer shown when there are no suggestions Suggestions are now shown if you continue to type a half-completed word More suggestions for new SQL Server 2014 syntax Improvements to partial match suggestions Improved suggestion ordering As well as improving suggestions, we’ve also added some new features. Select in Object Explorer You can now use SQL Prompt to select an object in the Object Explorer from a query window. This is useful because many SSMS features are available from an object’s Object Explorer context menu (eg select top 1000 rows, design, script as). To select an object in the Object Explorer, place the cursor over the object you want to select and press Ctrl + F12: Here’s a short video of the feature in action. $SELECTIONSTART$ and $SELECTIONEND$ placeholders You can now use $SELECTIONSTART$ and $SELECTIONEND$ placeholders in your snippet code. The code between these placeholders is selected when you insert the snippet. For example, the following snippet: $SELECTIONSTART$SELECT TOP 100 * FROM Table1$SELECTIONEND$ is inserted as: You can then press F5 to run the selected snippet code. For the full list of snippet placeholders you can use, see the documentation. Highlighting matching parentheses If your cursor is next to an opening or closing parenthesis in a query, SQL Prompt now automatically highlights the matching parenthesis: You can then use the SSMS and Visual Studio shortcut Ctrl + ] to move between parentheses. More improvements Those are just a few of the improvements in SQL Prompt 6.3. For the full list of features and bug fixes, see the release notes.

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  • [Update] RedGate SQL Source Control and TFSPreview

    - by andyleonard
    31 Oct 2012 Update: SQL Source Control 3.1 is available! - Andy 12 Oct 2012 Update: The SQL Source Control 3.1 update is currently unavailable. I will provide additional updates when this version is re-released. - Andy I am excited that RedGate ’s SQL Source Control now supports connectivity to TFSPreview , Microsoft ’s cloud-based Application Life Cycle Management portal. Buck Woody ( Blog | @buckwoody ) and I have written about TFSPreview at SQLBlog already: Team Foundation Server (TFS) in the...(read more)

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  • An XEvent a Day (22 of 31) – The Future – fn_dblog() No More? Tracking Transaction Log Activity in Denali

    - by Jonathan Kehayias
    I bet that made you look didn’t it?  Worry not, fn_dblog() still exists in SQL Server Denali, and I plan on using it to validate the information being returned by a new Event in SQL Server Denali CTP1, sqlerver.transaction_log, which brings with it the ability to correlate specific transaction log entries to the operations that actually caused them to occur. There is no greater source of information about the transaction log in SQL Server than Paul Randal’s blog category Transaction Log . ...(read more)

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  • T-SQL Tuesday 24: Ode to Composable Code

    - by merrillaldrich
    I love the T-SQL Tuesday tradition, started by Adam Machanic and hosted this month by Brad Shulz . I am a little pressed for time this month, so today’s post is a short ode to how I love saving time with Composable Code in SQL. Composability is one of the very best features of SQL, but sometimes gets picked on due to both real and imaginary performance worries. I like to pick composable solutions when I can, while keeping the perf issues in mind, because they are just so handy and eliminate so much...(read more)

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  • An XEvent a Day (28 of 31) – Tracking Page Compression Operations

    - by Jonathan Kehayias
    The Database Compression feature in SQL Server 2008 Enterprise Edition can provide some significant reductions in storage requirements for SQL Server databases, and in the right implementations and scenarios performance improvements as well.  There isn’t really a whole lot of information about the operations of database compression that is documented as being available in the DMV’s or SQL Trace.  Paul Randal pointed out on Twitter today that sys.dm_db_index_operational_stats() provides...(read more)

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  • October 2012 Cumulative Updates are available - SQL Server 2008 R2 & SQL Server 2012

    - by AaronBertrand
    Microsoft released new cumulative updates for SQL Server; they announced them on their blog several hours ago . SQL Server 2012 RTM Cumulative Update # 4 KB Article: KB #2758687 25 fixes are listed at the time of publication Build number is 11.0.2383 Relevant for @@VERSION 11.0.2100 through 11.0.2382 SQL Server 2008 R2 Service Pack 1 Cumulative Update # 9 KB Article: KB #2756574 14 fixes are listed at the time of publication Build number is 10.50.2866 Relevant for @@VERSION 10.50.2500 through 10.50.2865...(read more)

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  • Scream if you want to go faster

    - by simonsabin
    My session for 24hrs of pass on High Performance functions will be starting at 11:00 GMT thats migdnight for folks in the UK. To attend follow this link https://www.livemeeting.com/cc/8000181573/join?id=N5Q8S7&role=attend&pw=d2%28_KmN3r The rest of the sessions can be found here http://www.sqlpass.org/24hours/2010/Sessions/ChronologicalOrder.aspx So far the sessions have been great so no pressure :( See you there in 4.5 hrs...(read more)

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  • Group SQL tables in SQL Server Management Studio object explorer

    - by MainMa
    I have a table which has approximately sixty tables, and other tables are added constantly. Each table is a part of a schema. A such quantity of tables makes it difficult to use Microsoft SQL Server Management Studio 2008. For example, I must scroll up in object explorer to access database related functions, or scroll down each time I need to access Views or Security features. Is it possible to group several tables to be able to expand or collapse them in Object Explorer? Maybe a folder may be displayed for each schema, letting collapse the folders I don't need to use?

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  • How do I filter one of the columns in a SQL Server SQL Query

    - by Kent S. Clarkson
    I have a table (that relates to a number of other tables) where I would like to filter ONE of the columns (RequesterID) - that column will be a combobox where only people that are not sales people should be selectable. Here is the "unfiltered" query, lets call it QUERY 1: SELECT RequestsID, RequesterID, ProductsID FROM dbo.Requests If using a separate query, lets call it QUERY 2, to filter RequesterID (which is a People related column, connected to People.PeopleID), it would look like this: SELECT People.PeopleID FROM People INNER JOIN Roles ON People.RolesID = Roles.RolesID INNER JOIN Requests ON People.PeopleID = Requests.RequesterID WHERE (Roles.Role <> N'SalesGuy') ORDER BY Requests.RequestsID Now, is there a way of "merging" the QUERY 2 into QUERY 1? (dbo.Requests in QUERY 1 has RequesterID populated as a Foreign Key from dbo.People, so no problem there... The connections are all right, just not know how to write the SQL query!)

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  • Auto Increment feature of SQL Server

    - by Rahul Tripathi
    I have created a table named as ABC. It has three columns which are as follows:- The column number_pk (int) is the primary key of my table in which I have made the auto increment feature on for that column. Now I have deleted two rows from that table say Number_pk= 5 and Number_pk =6. The table which I get now is like this:- Now if I again enter two new rows in this table with the same value I get the two new Number_pk starting from 7 and 8 i.e, My question is that what is the logic behind this since I have deleted the two rows from the table. I know that a simple answer is because I have set the auto increment on for the primary key of my table. But I want to know is there any way that I can insert the two new entries starting from the last Number_pk without changing the design of my table? And how the SQL Server manage this record since I have deleted the rows from the database??

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  • SQL 2005 - Search stored procedures for text (Not all text is being searched)

    - by hamlin11
    The following bits of code do not seem to be searching the entire routine definition. Code block 1: select top 50 * from information_schema.routines where routine_definition like '%09/01/2008%' and specific_Name like '%NET' Code Block 2: SELECT ROUTINE_NAME, ROUTINE_DEFINITION FROM INFORMATION_SCHEMA.ROUTINES WHERE ROUTINE_DEFINITION LIKE '%EffectiveDate%' AND ROUTINE_TYPE='PROCEDURE' and ROUTINE_NAME like '%NET' I know for a fact that these bits of SQL work under most circumstances. The problem is this: When I run this for "EffectiveDate" which is buried at line ~800 in a few stored procedures, these stored procedures never show up in the results. It's as if "like" only searches so deep. Any tips on fixing this? I want to search the ENTIRE stored procedure for the specified text. Thanks!

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  • SQL Server not releasing Memory

    - by noob2487
    I am using SQL Server 2005. I am running a job which processes around 100 K records. Job runs fine, it takes are 45 mins to execute, which is good. But after that job is processed, I can see instance of SQL Server 2005 still there with around 900 MB of Memory. I waited for around 2 hrs but that memory was not released. Is there any process which takes care of memory here, something like GC (unpredictable) Or am I doing something wrong???

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  • SQL Query for generating matrix like output querying related table in SQL Server

    - by Nagesh
    I have three tables: Product ProductID ProductName 1 Cycle 2 Scooter 3 Car Customer CustomerID CustomerName 101 Ronald 102 Michelle 103 Armstrong 104 Schmidt 105 Peterson Transactions TID ProductID CustomerID TranDate Amount 10001 1 101 01-Jan-11 25000.00 10002 2 101 02-Jan-11 98547.52 10003 1 102 03-Feb-11 15000.00 10004 3 102 07-Jan-11 36571.85 10005 2 105 09-Feb-11 82658.23 10006 2 104 10-Feb-11 54000.25 10007 3 103 20-Feb-11 80115.50 10008 3 104 22-Feb-11 45000.65 I have written a query to group the transactions like this: SELECT P.ProductName AS Product, C.CustName AS Customer, SUM(T.Amount) AS Amount FROM Transactions AS T INNER JOIN Product AS P ON T.ProductID = P.ProductID INNER JOIN Customer AS C ON T.CustomerID = C.CustomerID WHERE T.TranDate BETWEEN '2011-01-01' AND '2011-03-31' GROUP BY P.ProductName, C.CustName ORDER BY P.ProductName which gives the result like this: Product Customer Amount Car Armstrong 80115.50 Car Michelle 36571.85 Car Schmidt 45000.65 Cycle Michelle 15000.00 Cycle Ronald 25000.00 Scooter Peterson 82658.23 Scooter Ronald 98547.52 Scooter Schmidt 54000.25 I need result of query in MATRIX form like this: Customer |------------ Amounts --------------- Name |Car Cycle Scooter Totals Armstrong 80115.50 0.00 0.00 80115.50 Michelle 36571.85 15000.00 0.00 51571.85 Ronald 0.00 25000.00 98547.52 123547.52 Peterson 0.00 0.00 82658.23 82658.23 Schmidt 45000.65 0.00 54000.25 99000.90 Please help me to acheive the above result in SQL Server 2005. Using mulitple views or even temporory tables is fine for me.

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  • SSIS Design Patterns Training in London 8-11 Sep!

    - by andyleonard
    A few seats remain for my course SQL Server Integration Services 2012 Design Patterns to be delivered in London 8-11 Sep 2014. Register today to learn more about: New features in SSIS 2012 and 2014 Advanced patterns for loading data warehouses Error handling The (new) Project Deployment Model Scripting in SSIS The (new) SSIS Catalog Designing custom SSIS tasks Executing, managing, monitoring, and administering SSIS in the enterprise Business Intelligence Markup Language (Biml) BimlScript ETL Instrumentation...(read more)

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  • Idera SQL Doctor 3.0 and MS SQL Changes

    New features worth mentioning in SQL doctor 3.0 begin with a new server dashboard that not only gives a comprehensive overview of a SQL Server instance's current health, but also several key details to help database administrators. Some of the details include recommendations on how to optimize server configuration, how to fix certain security issues, and how to get rid of performance bottlenecks. The latest version of SQL doctor also supplies users with key server information. The status of system parameters known to affect SQL Server performance, such as processes, disk partitions, cache, m...

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  • Where should the partitioning column go in the primary key on SQL Server?

    - by Bialecki
    Using SQL Server 2005 and 2008. I've got a potentially very large table (potentially hundreds of millions of rows) consisting of the following columns: CREATE TABLE ( date SMALLDATETIME, id BIGINT, value FLOAT ) which is being partitioned on column date in daily partitions. The question then is should the primary key be on date, id or value, id? I can imagine that SQL Server is smart enough to know that it's already partitioning on date and therefore, if I'm always querying for whole chunks of days, then I can have it second in the primary key. Or I can imagine that SQL Server will need that column to be first in the primary key to get the benefit of partitioning. Can anyone lend some insight into which way the table should be keyed?

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  • SQL Spatial: Getting “nearest” calculations working properly

    - by Rob Farley
    If you’ve ever done spatial work with SQL Server, I hope you’ve come across the ‘nearest’ problem. You have five thousand stores around the world, and you want to identify the one that’s closest to a particular place. Maybe you want the store closest to the LobsterPot office in Adelaide, at -34.925806, 138.605073. Or our new US office, at 42.524929, -87.858244. Or maybe both! You know how to do this. You don’t want to use an aggregate MIN or MAX, because you want the whole row, telling you which store it is. You want to use TOP, and if you want to find the closest store for multiple locations, you use APPLY. Let’s do this (but I’m going to use addresses in AdventureWorks2012, as I don’t have a list of stores). Oh, and before I do, let’s make sure we have a spatial index in place. I’m going to use the default options. CREATE SPATIAL INDEX spin_Address ON Person.Address(SpatialLocation); And my actual query: WITH MyLocations AS (SELECT * FROM (VALUES ('LobsterPot Adelaide', geography::Point(-34.925806, 138.605073, 4326)),                        ('LobsterPot USA', geography::Point(42.524929, -87.858244, 4326))                ) t (Name, Geo)) SELECT l.Name, a.AddressLine1, a.City, s.Name AS [State], c.Name AS Country FROM MyLocations AS l CROSS APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a JOIN Person.StateProvince AS s     ON s.StateProvinceID = a.StateProvinceID JOIN Person.CountryRegion AS c     ON c.CountryRegionCode = s.CountryRegionCode ; Great! This is definitely working. I know both those City locations, even if the AddressLine1s don’t quite ring a bell. I’m sure I’ll be able to find them next time I’m in the area. But of course what I’m concerned about from a querying perspective is what’s happened behind the scenes – the execution plan. This isn’t pretty. It’s not using my index. It’s sucking every row out of the Address table TWICE (which sucks), and then it’s sorting them by the distance to find the smallest one. It’s not pretty, and it takes a while. Mind you, I do like the fact that it saw an indexed view it could use for the State and Country details – that’s pretty neat. But yeah – users of my nifty website aren’t going to like how long that query takes. The frustrating thing is that I know that I can use the index to find locations that are within a particular distance of my locations quite easily, and Microsoft recommends this for solving the ‘nearest’ problem, as described at http://msdn.microsoft.com/en-au/library/ff929109.aspx. Now, in the first example on this page, it says that the query there will use the spatial index. But when I run it on my machine, it does nothing of the sort. I’m not particularly impressed. But what we see here is that parallelism has kicked in. In my scenario, it’s split the data up into 4 threads, but it’s still slow, and not using my index. It’s disappointing. But I can persuade it with hints! If I tell it to FORCESEEK, or use my index, or even turn off the parallelism with MAXDOP 1, then I get the index being used, and it’s a thing of beauty! Part of the plan is here: It’s massive, and it’s ugly, and it uses a TVF… but it’s quick. The way it works is to hook into the GeodeticTessellation function, which is essentially finds where the point is, and works out through the spatial index cells that surround it. This then provides a framework to be able to see into the spatial index for the items we want. You can read more about it at http://msdn.microsoft.com/en-us/library/bb895265.aspx#tessellation – including a bunch of pretty diagrams. One of those times when we have a much more complex-looking plan, but just because of the good that’s going on. This tessellation stuff was introduced in SQL Server 2012. But my query isn’t using it. When I try to use the FORCESEEK hint on the Person.Address table, I get the friendly error: Msg 8622, Level 16, State 1, Line 1 Query processor could not produce a query plan because of the hints defined in this query. Resubmit the query without specifying any hints and without using SET FORCEPLAN. And I’m almost tempted to just give up and move back to the old method of checking increasingly large circles around my location. After all, I can even leverage multiple OUTER APPLY clauses just like I did in my recent Lookup post. WITH MyLocations AS (SELECT * FROM (VALUES ('LobsterPot Adelaide', geography::Point(-34.925806, 138.605073, 4326)),                        ('LobsterPot USA', geography::Point(42.524929, -87.858244, 4326))                ) t (Name, Geo)) SELECT     l.Name,     COALESCE(a1.AddressLine1,a2.AddressLine1,a3.AddressLine1),     COALESCE(a1.City,a2.City,a3.City),     s.Name AS [State],     c.Name AS Country FROM MyLocations AS l OUTER APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     WHERE l.Geo.STDistance(ad.SpatialLocation) < 1000     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a1 OUTER APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     WHERE l.Geo.STDistance(ad.SpatialLocation) < 5000     AND a1.AddressID IS NULL     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a2 OUTER APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     WHERE l.Geo.STDistance(ad.SpatialLocation) < 20000     AND a2.AddressID IS NULL     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a3 JOIN Person.StateProvince AS s     ON s.StateProvinceID = COALESCE(a1.StateProvinceID,a2.StateProvinceID,a3.StateProvinceID) JOIN Person.CountryRegion AS c     ON c.CountryRegionCode = s.CountryRegionCode ; But this isn’t friendly-looking at all, and I’d use the method recommended by Isaac Kunen, who uses a table of numbers for the expanding circles. It feels old-school though, when I’m dealing with SQL 2012 (and later) versions. So why isn’t my query doing what it’s supposed to? Remember the query... WITH MyLocations AS (SELECT * FROM (VALUES ('LobsterPot Adelaide', geography::Point(-34.925806, 138.605073, 4326)),                        ('LobsterPot USA', geography::Point(42.524929, -87.858244, 4326))                ) t (Name, Geo)) SELECT l.Name, a.AddressLine1, a.City, s.Name AS [State], c.Name AS Country FROM MyLocations AS l CROSS APPLY (     SELECT TOP (1) *     FROM Person.Address AS ad     ORDER BY l.Geo.STDistance(ad.SpatialLocation)     ) AS a JOIN Person.StateProvince AS s     ON s.StateProvinceID = a.StateProvinceID JOIN Person.CountryRegion AS c     ON c.CountryRegionCode = s.CountryRegionCode ; Well, I just wasn’t reading http://msdn.microsoft.com/en-us/library/ff929109.aspx properly. The following requirements must be met for a Nearest Neighbor query to use a spatial index: A spatial index must be present on one of the spatial columns and the STDistance() method must use that column in the WHERE and ORDER BY clauses. The TOP clause cannot contain a PERCENT statement. The WHERE clause must contain a STDistance() method. If there are multiple predicates in the WHERE clause then the predicate containing STDistance() method must be connected by an AND conjunction to the other predicates. The STDistance() method cannot be in an optional part of the WHERE clause. The first expression in the ORDER BY clause must use the STDistance() method. Sort order for the first STDistance() expression in the ORDER BY clause must be ASC. All the rows for which STDistance returns NULL must be filtered out. Let’s start from the top. 1. Needs a spatial index on one of the columns that’s in the STDistance call. Yup, got the index. 2. No ‘PERCENT’. Yeah, I don’t have that. 3. The WHERE clause needs to use STDistance(). Ok, but I’m not filtering, so that should be fine. 4. Yeah, I don’t have multiple predicates. 5. The first expression in the ORDER BY is my distance, that’s fine. 6. Sort order is ASC, because otherwise we’d be starting with the ones that are furthest away, and that’s tricky. 7. All the rows for which STDistance returns NULL must be filtered out. But I don’t have any NULL values, so that shouldn’t affect me either. ...but something’s wrong. I do actually need to satisfy #3. And I do need to make sure #7 is being handled properly, because there are some situations (eg, differing SRIDs) where STDistance can return NULL. It says so at http://msdn.microsoft.com/en-us/library/bb933808.aspx – “STDistance() always returns null if the spatial reference IDs (SRIDs) of the geography instances do not match.” So if I simply make sure that I’m filtering out the rows that return NULL… …then it’s blindingly fast, I get the right results, and I’ve got the complex-but-brilliant plan that I wanted. It just wasn’t overly intuitive, despite being documented. @rob_farley

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  • Improving VPN performance - stronger encryption = more performance?

    - by Seth
    I have a site-to-site VPN set up with two SonicWall's (a TZ170 and a Pro1260). It was suggested to me that turning off encryption (so the VPN is tunneling only) would improve performance. (I'm not concerned with security, because the VPN is running over a trusted line.) Using FTP and HTTP transfers, I measured my baseline performance at about 130±10 kB/s. The Ipsec (Phase 2) Encryption was set to 3DES, so I set it to "none". However, the effect was opposite -- the performance dropped to 60±30 kB/s, and the transfers stall for about 25 seconds before any data comes down the line. I tried AES-128 and the throughput went UP to 160±5 kB/s. The rated speed of my line is 193 kB/s (it's a T1). Contrary to what I would think, stronger Ipsec encryption seems to improve throughput. Can anyone explain what might be going on here? Why would no encryption cause poor and highly variable performance, and cause transfers to stall? Why does AES-128 improve performance?

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  • Scripting a database copy from MS Sql 2005 to 2008 without detach/backup/RDP

    - by James Santiago
    My goal is to move a single SQL 2005 database to a seperate 2008 server. The issue is my level of access to both servers. On each I can only access the database and nothing else. I cant create a backup file or detach the database because I don't have access to the file system or to create a proxy. I've tried using the generate script function of sql 2005 management studio express to restore the schema but receive command not supported errors when attempting to execute the sql on the new database. Similarly I tried using EMS SQL Manager 2005 Lite to script a backup of the schema and data but ran into similar problems. How do I go about acomplishing this? I can't seem to find any solutions outside of using the detach and backup functions.

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  • Validate a string in a table in SQL Server - CLR function or T-SQL

    - by Ashish Gupta
    I need to check If a column value (string) in SQL server table starts with a small letter and can only contain '_', '-', numbers and alphabets. I know I can use a SQL server CLR function for that. However, I am trying to implement that validation using a scalar UDF and could make very little here...I can use 'NOT LIKE', but I am not sure how to make sure I validate the string irrespective of the order of characters or in other words write a pattern in SQL for this. Am I better off using a SQL CLR function? Any help will be appreciated.. Thanks in advance Thank you everyone for their comments. This morning, I chose to go CLR function way. For the purpose of what I was trying to achieve, I created one CLR function which does the validation of an input string and have that called from a SQL UDF and It works well. Just to measure the performance of t-SQL UDF using SQL CLR function vs t- SQL UDF, I created a SQL CLR function which will just check if the input string contains only small letters, it should return true else false and have that called from a UDF (IsLowerCaseCLR). After that I also created a regular t-SQL UDF(IsLowerCaseTSQL) which does the same thing using the 'NOT LIKE'. Then I created a table (Person) with columns Name(varchar) and IsValid(bit) columns and populate that with names to test. Data :- 1000 records with 'Ashish' as value for Name column 1000 records with 'ashish' as value for Name column then I ran the following :- UPDATE Person Set IsValid=1 WHERE dbo.IsLowerCaseTSQL (Name) Above updated 1000 records (with Isvalid=1) and took less than a second. I deleted all the data in the table and repopulated the same with same data. Then updated the same table using Sql CLR UDF (with Isvalid=1) and this took 3 seconds! If update happens for 5000 records, regular UDF takes 0 seconds compared to CLR UDF which takes 16 seconds! I am very less knowledgeable on t-SQL regular expression or I could have tested my actual more complex validation criteria. But I just wanted to know, even I could have written that, would that have been faster than the SQL CLR function considering the example above. Are we using SQL CLR because we can implement we can implement lot richer logic which would have been difficult otherwise If we write in regular SQL. Sorry for this long post. I just want to know from the experts. Please feel free to ask if you could not understand anything here. Thank you again for your time.

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