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  • SQL SERVER – Example of Performance Tuning for Advanced Users with DB Optimizer

    - by Pinal Dave
    Performance tuning is such a subject that everyone wants to master it. In beginning everybody is at a novice level and spend lots of time learning how to master the art of performance tuning. However, as we progress further the tuning of the system keeps on getting very difficult. I have understood in my early career there should be no need of ego in the technology field. There are always better solutions and better ideas out there and we should not resist them. Instead of resisting the change and new wave I personally adopt it. Here is a similar example, as I personally progress to the master level of performance tuning, I face that it is getting harder to come up with optimal solutions. In such scenarios I rely on various tools to teach me how I can do things better. Once I learn about tools, I am often able to come up with better solutions when I face the similar situation next time. A few days ago I had received a query where the user wanted to tune it further to get the maximum out of the performance. I have re-written the similar query with the help of AdventureWorks sample database. SELECT * FROM HumanResources.Employee e INNER JOIN HumanResources.EmployeeDepartmentHistory edh ON e.BusinessEntityID = edh.BusinessEntityID INNER JOIN HumanResources.Shift s ON edh.ShiftID = s.ShiftID; User had similar query to above query was used in very critical report and wanted to get best out of the query. When I looked at the query – here were my initial thoughts Use only column in the select statements as much as you want in the application Let us look at the query pattern and data workload and find out the optimal index for it Before I give further solutions I was told by the user that they need all the columns from all the tables and creating index was not allowed in their system. He can only re-write queries or use hints to further tune this query. Now I was in the constraint box – I believe * was not a great idea but if they wanted all the columns, I believe we can’t do much besides using *. Additionally, if I cannot create a further index, I must come up with some creative way to write this query. I personally do not like to use hints in my application but there are cases when hints work out magically and gives optimal solutions. Finally, I decided to use Embarcadero’s DB Optimizer. It is a fantastic tool and very helpful when it is about performance tuning. I have previously explained how it works over here. First open DBOptimizer and open Tuning Job from File >> New >> Tuning Job. Once you open DBOptimizer Tuning Job follow the various steps indicates in the following diagram. Essentially we will take our original script and will paste that into Step 1: New SQL Text and right after that we will enable Step 2 for Generating Various cases, Step 3 for Detailed Analysis and Step 4 for Executing each generated case. Finally we will click on Analysis in Step 5 which will generate the report detailed analysis in the result pan. The detailed pan looks like. It generates various cases of T-SQL based on the original query. It applies various hints and available hints to the query and generate various execution plans of the query and displays them in the resultant. You can clearly notice that original query had a cost of 0.0841 and logical reads about 607 pages. Whereas various options which are just following it has different execution cost as well logical read. There are few cases where we have higher logical read and there are few cases where as we have very low logical read. If we pay attention the very next row to original query have Merge_Join_Query in description and have lowest execution cost value of 0.044 and have lowest Logical Reads of 29. This row contains the query which is the most optimal re-write of the original query. Let us double click over it. Here is the query: SELECT * FROM HumanResources.Employee e INNER JOIN HumanResources.EmployeeDepartmentHistory edh ON e.BusinessEntityID = edh.BusinessEntityID INNER JOIN HumanResources.Shift s ON edh.ShiftID = s.ShiftID OPTION (MERGE JOIN) If you notice above query have additional hint of Merge Join. With the help of this Merge Join query hint this query is now performing much better than before. The entire process takes less than 60 seconds. Please note that it the join hint Merge Join was optimal for this query but it is not necessary that the same hint will be helpful in all the queries. Additionally, if the workload or data pattern changes the query hint of merge join may be no more optimal join. In that case, we will have to redo the entire exercise once again. This is the reason I do not like to use hints in my queries and I discourage all of my users to use the same. However, if you look at this example, this is a great case where hints are optimizing the performance of the query. It is humanly not possible to test out various query hints and index options with the query to figure out which is the most optimal solution. Sometimes, we need to depend on the efficiency tools like DB Optimizer to guide us the way and select the best option from the suggestion provided. Let me know what you think of this article as well your experience with DB Optimizer. Please leave a comment. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Joins, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • How to get full query string parameters not UrlDecoded

    - by developerit
    Introduction While developing Developer IT’s website, we came across a problem when the user search keywords containing special character like the plus ‘+’ char. We found it while looking for C++ in our search engine. The request parameter output in ASP.NET was “c “. I found it strange that it removed the ‘++’ and replaced it with a space… Analysis After a bit of Googling and Reflection, it turns out that ASP.NET calls UrlDecode on each parameters retreived by the Request(“item”) method. The Request.Params property is affected by this two since it mashes all QueryString, Forms and other collections into a single one. Workaround Finally, I solve the puzzle usign the Request.RawUrl property and parsing it with the same RegEx I use in my url re-writter. The RawUrl not affected by anything. As its name say it, it’s raw. Published on http://www.developerit.com/

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  • SQLAuthority News – Statistics Used by the Query Optimizer in Microsoft SQL Server 2008 – Microsoft Whitepaper

    - by pinaldave
    I recently presented session on Statistics and Best Practices in Virtual Tech Days on Nov 22, 2010. The sessions was very popular and I got many questions right after the sessions. The number question I had received was where everybody can get the further information. I am very much happy that my sessions created some curiosity for one of the most important feature of the SQL Server. Statistics are the heart of the SQL Server. Microsoft has published a white paper on the subject how statistics are useful to Query Optimizer. Here is the abstract of the same white paper from Microsoft. Statistics Used by the Query Optimizer in Microsoft SQL Server 2008 Writer: Eric N. Hanson and Yavor Angelov Microsoft SQL Server 2008 collects statistical information about indexes and column data stored in the database. These statistics are used by the SQL Server query optimizer to choose the most efficient plan for retrieving or updating data. This paper describes what data is collected, where it is stored, and which commands create, update, and delete statistics. By default, SQL Server 2008 also creates and updates statistics automatically, when such an operation is considered to be useful. This paper also outlines how these defaults can be changed on different levels (column, table, and database). In addition, it presents how certain query language features, such as Transact-SQL variables, interact with use of statistics by the optimizer, and it provides guidance for using these features when writing queries so you can obtain good query performance. Link to white paper Statistics Used by the Query Optimizer in Microsoft SQL Server 2008 ?Reference: Pinal Dave (http://blog.SQLAuthority.com)   Filed under: Pinal Dave, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology

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  • Alternatives to Google Website Optimizer

    - by yahelc
    What (affordable) alternatives are there to Google Website Optimizer for A/B and multivariate tests? The pro's with GWO are basically that its free and that it integrates with Google Analytics. The cons: The relative high time cost of setting up a test. Some alternatives I've seen so far: Optimizely.com VisualWebsiteOptimizer.com Genetify (wiki.github.com/gregdingle/genetify/) Free, open-source, but seems like there's no developer community committed to the project.

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  • Wierd Results A/B Test in Google Website Optimizer

    - by Yisroel
    I set up a test in Google Website Optimizer that has a 3 variations - original (A), B, and C. In order to further validate the results of the test, I added a variation C that is exactly the same as the original. And thats where the results get weird. 6 days in to the test, the best performing variation is C. It outperforms the original by 18.4%! How is that possible? Do I now discount the results of this test entirely?

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  • Wierd Results A/B Test in Google Website Optimizer

    - by Yisroel
    I set up a test in Google Website Optimizer that has a 3 variations - original (A), B, and C. In order to further validate the results of the test, I added a variation C that is exactly the same as the original. And thats where the results get weird. 6 days in to the test, the best performing variation is C. It outperforms the original by 18.4%! How is that possible? Do I now discount the results of this test entirely?

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  • Weird Results A/B Test in Google Website Optimizer

    - by Yisroel
    I set up a test in Google Website Optimizer that has a 3 variations - original (A), B, and C. In order to further validate the results of the test, I added a variation C that is exactly the same as the original. And thats where the results get weird. 6 days into the test, the best performing variation is C. It outperforms the original by 18.4%! How is that possible? Do I now discount the results of this test entirely?

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  • SQL SERVER – Maximize Database Performance with DB Optimizer – SQL in Sixty Seconds #054

    - by Pinal Dave
    Performance tuning is an interesting concept and everybody evaluates it differently. Every developer and DBA have different opinion about how one can do performance tuning. I personally believe performance tuning is a three step process Understanding the Query Identifying the Bottleneck Implementing the Fix While, we are working with large database application and it suddenly starts to slow down. We are all under stress about how we can get back the database back to normal speed. Most of the time we do not have enough time to do deep analysis of what is going wrong as well what will fix the problem. Our primary goal at that time is to just fix the database problem as fast as we can. However, here is one very important thing which we need to keep in our mind is that when we do quick fix, it should not create any further issue with other parts of the system. When time is essence and we want to do deep analysis of our system to give us the best solution we often tend to make mistakes. Sometimes we make mistakes as we do not have proper time to analysis the entire system. Here is what I do when I face such a situation – I take the help of DB Optimizer. It is a fantastic tool and does superlative performance tuning of the system. Everytime when I talk about performance tuning tool, the initial reaction of the people is that they do not want to try this as they believe it requires lots of the learning of the tool before they use it. It is absolutely not true with the case of the DB optimizer. It is a very easy to use and self intuitive tool. Once can get going with the product, in no time. Here is a quick video I have build where I demonstrate how we can identify what index is missing for query and how we can quickly create the index. Entire three steps of the query tuning are completed in less than 60 seconds. If you are into performance tuning and query optimization you should download DB Optimizer and give it a go. Let us see the same concept in following SQL in Sixty Seconds Video: You can Download DB Optimizer and reproduce the same Sixty Seconds experience. Related Tips in SQL in Sixty Seconds: Performance Tuning – Part 1 of 2 – Getting Started and Configuration Performance Tuning – Part 2 of 2 – Analysis, Detection, Tuning and Optimizing What would you like to see in the next SQL in Sixty Seconds video? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Interview Questions and Answers, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Identity

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  • SQL SERVER – DMV – sys.dm_exec_query_optimizer_info – Statistics of Optimizer

    - by pinaldave
    Incredibly, SQL Server has so much information to share with us. Every single day, I am amazed with this SQL Server technology. Sometimes I find several interesting information by just querying few of the DMV. And when I present this info in front of my client during performance tuning consultancy, they are surprised with my findings. Today, I am going to share one of the hidden gems of DMV with you, the one which I frequently use to understand what’s going on under the hood of SQL Server. SQL Server keeps the record of most of the operations of the Query Optimizer. We can learn many interesting details about the optimizer which can be utilized to improve the performance of server. SELECT * FROM sys.dm_exec_query_optimizer_info WHERE counter IN ('optimizations', 'elapsed time','final cost', 'insert stmt','delete stmt','update stmt', 'merge stmt','contains subquery','tables', 'hints','order hint','join hint', 'view reference','remote query','maximum DOP', 'maximum recursion level','indexed views loaded', 'indexed views matched','indexed views used', 'indexed views updated','dynamic cursor request', 'fast forward cursor request') All occurrence values are cumulative and are set to 0 at system restart. All values for value fields are set to NULL at system restart. I have removed a few of the internal counters from the script above, and kept only documented details. Let us check the result of the above query. As you can see, there is so much vital information that is revealed in above query. I can easily say so many things about how many times Optimizer was triggered and what the average time taken by it to optimize my queries was. Additionally, I can also determine how many times update, insert or delete statements were optimized. I was able to quickly figure out that my client was overusing the Query Hints using this dynamic management view. If you have been reading my blog, I am sure you are aware of my series related to SQL Server Views SQL SERVER – The Limitations of the Views – Eleven and more…. With this, I can take a quick look and figure out how many times Views were used in various solutions within the query. Moreover, you can easily know what fraction of the optimizations has been involved in tuning server. For example, the following query would tell me, in total optimizations, what the fraction of time View was “reference“. As this View also includes system Views and DMVs, the number is a bit higher on my machine. SELECT (SELECT CAST (occurrence AS FLOAT) FROM sys.dm_exec_query_optimizer_info WHERE counter = 'view reference') / (SELECT CAST (occurrence AS FLOAT) FROM sys.dm_exec_query_optimizer_info WHERE counter = 'optimizations') AS ViewReferencedFraction Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Sub query pass through

    - by SQL and the like
    Occasionally in forums and on client sites I see conditional subqueries in statements. This is where the developer has decided that it is only necessary to process some data under a certain condition.  By way of example, something like this : Create Procedure GetOrder @SalesOrderId integer, @CountDetails tinyint as Select SOH.salesorderid , case when @CountDetails = 1 then (Select count(*) from Sales.SalesOrderDetail SOD where SOH.SalesOrderID = SOD.SalesOrderID) end from sales.SalesOrderHeader...(read more)

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  • SQL Server Optimizer Malfunction?

    - by Tony Davis
    There was a sharp intake of breath from the audience when Adam Machanic declared the SQL Server optimizer to be essentially "stuck in 1997". It was during his fascinating "Query Tuning Mastery: Manhandling Parallelism" session at the recent PASS SQL Summit. Paraphrasing somewhat, Adam (blog | @AdamMachanic) offered a convincing argument that the optimizer often delivers flawed plans based on assumptions that are no longer valid with today’s hardware. In 1997, when Microsoft engineers re-designed the database engine for SQL Server 7.0, SQL Server got its initial implementation of a cost-based optimizer. Up to SQL Server 2000, the developer often had to deploy a steady stream of hints in SQL statements to combat the occasionally wilful plan choices made by the optimizer. However, with each successive release, the optimizer has evolved and improved in its decision-making. It is still prone to the occasional stumble when we tackle difficult problems, join large numbers of tables, perform complex aggregations, and so on, but for most of us, most of the time, the optimizer purrs along efficiently in the background. Adam, however, challenged further any assumption that the current optimizer is competent at providing the most efficient plans for our more complex analytical queries, and in particular of offering up correctly parallelized plans. He painted a picture of a present where complex analytical queries have become ever more prevalent; where disk IO is ever faster so that reads from disk come into buffer cache faster than ever; where the improving RAM-to-data ratio means that we have a better chance of finding our data in cache. Most importantly, we have more CPUs at our disposal than ever before. To get these queries to perform, we not only need to have the right indexes, but also to be able to split the data up into subsets and spread its processing evenly across all these available CPUs. Improvements such as support for ColumnStore indexes are taking things in the right direction, but, unfortunately, deficiencies in the current Optimizer mean that SQL Server is yet to be able to exploit properly all those extra CPUs. Adam’s contention was that the current optimizer uses essentially the same costing model for many of its core operations as it did back in the days of SQL Server 7, based on assumptions that are no longer valid. One example he gave was a "slow disk" bias that may have been valid back in 1997 but certainly is not on modern disk systems. Essentially, the optimizer assesses the relative cost of serial versus parallel plans based on the assumption that there is no IO cost benefit from parallelization, only CPU. It assumes that a single request will saturate the IO channel, and so a query would not run any faster if we parallelized IO because the disk system simply wouldn’t be able to handle the extra pressure. As such, the optimizer often decides that a serial plan is lower cost, often in cases where a parallel plan would improve performance dramatically. It was challenging and thought provoking stuff, as were his techniques for driving parallelism through query logic based on subsets of rows that define the "grain" of the query. I highly recommend you catch the session if you missed it. I’m interested to hear though, when and how often people feel the force of the optimizer’s shortcomings. Barring mistakes, such as stale statistics, how often do you feel the Optimizer fails to find the plan you think it should, and what are the most common causes? Is it fighting to induce it toward parallelism? Combating unexpected plans, arising from table partitioning? Something altogether more prosaic? Cheers, Tony.

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  • Oracle tuning optimizer index cost adj and optimizer index caching

    - by Darryl Braaten
    What is the correct way to set the optimizer index cost adj parameter for Oracle. As a developer I have observed huge performance improvements as this parameter is lowered. Common queries are reduced from 2 seconds to 200ms. There are lots of warnings on the net that lowering this value will cause dire issues with the database, but no detail is given on what will start going wrong. I am currently only seeing only an upside, much improved application performance and no downside. I need to better understand the possible negative repercussions of adjusting these parameters.

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  • MySQL Connect 9 Days Away – Optimizer Sessions

    - by Bertrand Matthelié
    72 1024x768 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Following my previous blog post focusing on InnoDB talks at MySQL Connect, let us review today the sessions focusing on the MySQL Optimizer: Saturday, 11.30 am, Room Golden Gate 6: MySQL Optimizer Overview—Olav Sanstå, Oracle The goal of MySQL optimizer is to take a SQL query as input and produce an optimal execution plan for the query. This session presents an overview of the main phases of the MySQL optimizer and the primary optimizations done to the query. These optimizations are based on a combination of logical transformations and cost-based decisions. Examples of optimization strategies the presentation covers are the main query transformations, the join optimizer, the data access selection strategies, and the range optimizer. For the cost-based optimizations, an overview of the cost model and the data used for doing the cost estimations is included. Saturday, 1.00 pm, Room Golden Gate 6: Overview of New Optimizer Features in MySQL 5.6—Manyi Lu, Oracle Many optimizer features have been added into MySQL 5.6. This session provides an introduction to these great features. Multirange read, index condition pushdown, and batched key access will yield huge performance improvements on large data volumes. Structured explain, explain for update/delete/insert, and optimizer tracing will help users analyze and speed up queries. And last but not least, the session covers subquery optimizations in Release 5.6. Saturday, 7.00 pm, Room Golden Gate 4: BoF: Query Optimizations: What Is New and What Is Coming? This BoF presents common techniques for query optimization, covers what is new in MySQL 5.6, and provides a discussion forum in which attendees can tell the MySQL optimizer team which optimizations they would like to see in the future. Sunday, 1.15 pm, Room Golden Gate 8: Query Performance Comparison of MySQL 5.5 and MySQL 5.6—Øystein Grøvlen, Oracle MySQL Release 5.6 contains several improvements in the query optimizer that create improved performance for complex queries. This presentation looks at how MySQL 5.6 improves the performance of many of the queries in the DBT-3 benchmark. Based on the observed improvements, the presentation discusses what makes the specific queries perform better in Release 5.6. It describes the relevant new optimization techniques and gives examples of the types of queries that will benefit from these techniques. Sunday, 4.15 pm, Room Golden Gate 4: Powerful EXPLAIN in MySQL 5.6—Evgeny Potemkin, Oracle The EXPLAIN command of MySQL has long been a very useful tool for understanding how MySQL will execute a query. Release 5.6 of the MySQL database offers several new additions that give more-detailed information about the query plan and make it easier to understand at the same time. This presentation gives an overview of new EXPLAIN features: structured EXPLAIN in JSON format, EXPLAIN for INSERT/UPDATE/DELETE, and optimizer tracing. Examples in the session give insights into how you can take advantage of the new features. They show how these features supplement and relate to each other and to classical EXPLAIN and how and why the MySQL server chooses a particular query plan. You can check out the full program here as well as in the September edition of the MySQL newsletter. Not registered yet? You can still save US$ 300 over the on-site fee – Register Now!

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  • SQL University: Parallelism Week - Part 2, Query Processing

    - by Adam Machanic
    Welcome back for the second part of Parallelism Week here at SQL University . Get your pencils ready, and make sure to raise your hand if you have a question. Last time we covered the necessary background material to help you understand how the SQL Server Operating System schedules its many active threads, and the differences between its behavior and that of the Windows operating system's scheduler. We also discussed some of the variations on the theme of parallel processing. Today we'll take a look...(read more)

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  • "Zend Optimizer not installed" after I updated to Ubuntu 10.04

    - by Eugene
    Hi guys, I've just updated from 9.10 to 10.04. Everything seems to run fine except for zend optimizer which is throwing "Zend Optimizer not installed" error. I went to php.ini and the following line is still there Code: zend_extension=/etc/php5/ZendOptimizer.so Also I checked that the file does exist and that the php.ini I am looking at is in fact the php.ini file that is being used by the server. Please let me know if you have any ideas about how to fix or debug this. Thanks, Eugene

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  • Complex query making site extremely slow

    - by Basit
    select SQL_CALC_FOUND_ROWS DISTINCT media.*, username from album as album, album_permission as permission, user as user, media as media , word_tag as word_tag, tag as tag where ((media.album_id = album.album_id and album.private = 'yes' and album.album_id = permission.album_id and (permission.email = '' or permission.user_id = '') ) or (media.album_id = album.album_id and album.private = 'no' ) or media.album_id = '0' ) and media.status = '1' and media.user_id = user.user_id and word_tag.media_id = media.media_id and word_tag.tag_id = tag.tag_id and tag.name in ('justin','bieber','malfunction','katherine','heigl','wardrobe','cinetube') and media.media_type = 'video' and media.media_id not in ('YHL6a5z8MV4') group by media.media_id order by RAND() #there is limit too, by 20 rows.. i dont know where to begin explaining about this query, but please forgive me and ask me if you have any question. following is the explanation. SQL_CALC_FOUND_ROWS is calculating how many rows are there and will be using for pagination, so it counts total records, even tho only 20 is showing. DISTINCT will stop the repeated row to display. username is from user table. album, album_permission. its checking if album is private and if it is, then check if user has permission, by user_id. i think rest is easy to understand, but if you need to know more about it, then please ask. im really frustrated by this query and site is very slow or not opening sometimes cause of this query. please help

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  • SQL SERVER – SSMS Automatically Generates TOP (100) PERCENT in Query Designer

    - by pinaldave
    Earlier this week, I was surfing various SQL forums to see what kind of help developer need in the SQL Server world. One of the question indeed caught my attention. I am here regenerating complete question as well scenario to illustrate the point in a precise manner. Additionally, I have added added second part of the question to give completeness. Question: I am trying to create a view in Query Designer (not in the New Query Window). Every time I am trying to create a view it always adds  TOP (100) PERCENT automatically on the T-SQL script. No matter what I do, it always automatically adds the TOP (100) PERCENT to the script. I have attempted to copy paste from notepad, build a query and a few other things – there is no success. I am really not sure what I am doing wrong with Query Designer. Here is my query script: (I use AdventureWorks as a sample database) SELECT Person.Address.AddressID FROM Person.Address INNER JOIN Person.AddressType ON Person.Address.AddressID = Person.AddressType.AddressTypeID ORDER BY Person.Address.AddressID This script automatically replaces by following query: SELECT TOP (100) PERCENT Person.Address.AddressID FROM Person.Address INNER JOIN Person.AddressType ON Person.Address.AddressID = Person.AddressType.AddressTypeID ORDER BY Person.Address.AddressID However, when I try to do the same from New Query Window it works totally fine. However, when I attempt to create a view of the same query it gives following error. Msg 1033, Level 15, State 1, Procedure myView, Line 6 The ORDER BY clause is invalid in views, inline functions, derived tables, subqueries, and common table expressions, unless TOP, OFFSET or FOR XML is also specified. It is pretty clear to me now that the script which I have written seems to need TOP (100) PERCENT, so Query . Why do I need it? Is there any work around to this issue. I particularly find this question pretty interesting as it really touches the fundamentals of the T-SQL query writing. Please note that the query which is automatically changed is not in New Query Editor but opened from SSMS using following way. Database >> Views >> Right Click >> New View (see the image below) Answer: The answer to the above question can be very long but I will keep it simple and to the point. There are three things to discuss in above script 1) Reason for Error 2) Reason for Auto generates TOP (100) PERCENT and 3) Potential solutions to the above error. Let us quickly see them in detail. 1) Reason for Error The reason for error is already given in the error. ORDER BY is invalid in the views and a few other objects. One has to use TOP or other keywords along with it. The way semantics of the query works where optimizer only follows(honors) the ORDER BY in the same scope or the same SELECT/UPDATE/DELETE statement. There is a possibility that one can order after the scope of the view again the efforts spend to order view will be wasted. The final resultset of the query always follows the final ORDER BY or outer query’s order and due to the same reason optimizer follows the final order of the query and not of the views (as view will be used in another query for further processing e.g. in SELECT statement). Due to same reason ORDER BY is now allowed in the view. For further accuracy and clear guidance I suggest you read this blog post by Query Optimizer Team. They have explained it very clear manner the same subject. 2) Reason for Auto Generated TOP (100) PERCENT One of the most popular workaround to above error is to use TOP (100) PERCENT in the view. Now TOP (100) PERCENT allows user to use ORDER BY in the query and allows user to overcome above error which we discussed. This gives the impression to the user that they have resolved the error and successfully able to use ORDER BY in the View. Well, this is incorrect as well. The way this works is when TOP (100) PERCENT is used the result is not guaranteed as well it is ignored in our the query where the view is used. Here is the blog post on this subject: Interesting Observation – TOP 100 PERCENT and ORDER BY. Now when you create a new view in the SSMS and build a query with ORDER BY to avoid the error automatically it adds the TOP 100 PERCENT. Here is the connect item for the same issue. I am sure there will be more connect items as well but I could not find them. 3) Potential Solutions If you are reading this post from the beginning in that case, it is clear by now that ORDER BY should not be used in the View as it does not serve any purpose unless there is a specific need of it. If you are going to use TOP 100 PERCENT with ORDER BY there is absolutely no need of using ORDER BY rather avoid using it all together. Here is another blog post of mine which describes the same subject ORDER BY Does Not Work – Limitation of the Views Part 1. It is valid to use ORDER BY in a view if there is a clear business need of using TOP with any other percentage lower than 100 (for example TOP 10 PERCENT or TOP 50 PERCENT etc). In most of the cases ORDER BY is not needed in the view and it should be used in the most outer query for present result in desired order. User can remove TOP 100 PERCENT and ORDER BY from the view before using the view in any query or procedure. In the most outer query there should be ORDER BY as per the business need. I think this sums up the concept in a few words. This is a very long topic and not easy to illustrate in one single blog post. I welcome your comments and suggestions. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, SQL View, T SQL, Technology

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  • Cardinality Estimation Bug with Lookups in SQL Server 2008 onward

    - by Paul White
    Cost-based optimization stands or falls on the quality of cardinality estimates (expected row counts).  If the optimizer has incorrect information to start with, it is quite unlikely to produce good quality execution plans except by chance.  There are many ways we can provide good starting information to the optimizer, and even more ways for cardinality estimation to go wrong.  Good database people know this, and work hard to write optimizer-friendly queries with a schema and metadata (e.g. statistics) that reduce the chances of poor cardinality estimation producing a sub-optimal plan.  Today, I am going to look at a case where poor cardinality estimation is Microsoft’s fault, and not yours. SQL Server 2005 SELECT th.ProductID, th.TransactionID, th.TransactionDate FROM Production.TransactionHistory AS th WHERE th.ProductID = 1 AND th.TransactionDate BETWEEN '20030901' AND '20031231'; The query plan on SQL Server 2005 is as follows (if you are using a more recent version of AdventureWorks, you will need to change the year on the date range from 2003 to 2007): There is an Index Seek on ProductID = 1, followed by a Key Lookup to find the Transaction Date for each row, and finally a Filter to restrict the results to only those rows where Transaction Date falls in the range specified.  The cardinality estimate of 45 rows at the Index Seek is exactly correct.  The table is not very large, there are up-to-date statistics associated with the index, so this is as expected. The estimate for the Key Lookup is also exactly right.  Each lookup into the Clustered Index to find the Transaction Date is guaranteed to return exactly one row.  The plan shows that the Key Lookup is expected to be executed 45 times.  The estimate for the Inner Join output is also correct – 45 rows from the seek joining to one row each time, gives 45 rows as output. The Filter estimate is also very good: the optimizer estimates 16.9951 rows will match the specified range of transaction dates.  Eleven rows are produced by this query, but that small difference is quite normal and certainly nothing to worry about here.  All good so far. SQL Server 2008 onward The same query executed against an identical copy of AdventureWorks on SQL Server 2008 produces a different execution plan: The optimizer has pushed the Filter conditions seen in the 2005 plan down to the Key Lookup.  This is a good optimization – it makes sense to filter rows out as early as possible.  Unfortunately, it has made a bit of a mess of the cardinality estimates. The post-Filter estimate of 16.9951 rows seen in the 2005 plan has moved with the predicate on Transaction Date.  Instead of estimating one row, the plan now suggests that 16.9951 rows will be produced by each clustered index lookup – clearly not right!  This misinformation also confuses SQL Sentry Plan Explorer: Plan Explorer shows 765 rows expected from the Key Lookup (it multiplies a rounded estimate of 17 rows by 45 expected executions to give 765 rows total). Workarounds One workaround is to provide a covering non-clustered index (avoiding the lookup avoids the problem of course): CREATE INDEX nc1 ON Production.TransactionHistory (ProductID) INCLUDE (TransactionDate); With the Transaction Date filter applied as a residual predicate in the same operator as the seek, the estimate is again as expected: We could also force the use of the ultimate covering index (the clustered one): SELECT th.ProductID, th.TransactionID, th.TransactionDate FROM Production.TransactionHistory AS th WITH (INDEX(1)) WHERE th.ProductID = 1 AND th.TransactionDate BETWEEN '20030901' AND '20031231'; Summary Providing a covering non-clustered index for all possible queries is not always practical, and scanning the clustered index will rarely be optimal.  Nevertheless, these are the best workarounds we have today. In the meantime, watch out for poor cardinality estimates when a predicate is applied as part of a lookup. The worst thing is that the estimate after the lookup join in the 2008+ plans is wrong.  It’s not hopelessly wrong in this particular case (45 versus 16.9951 is not the end of the world) but it easily can be much worse, and there’s not much you can do about it.  Any decisions made by the optimizer after such a lookup could be based on very wrong information – which can only be bad news. If you think this situation should be improved, please vote for this Connect item. © 2012 Paul White – All Rights Reserved twitter: @SQL_Kiwi email: [email protected]

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  • How to optimize this MySQL query

    - by James Simpson
    This query was working fine when the database was small, but now that there are millions of rows in the database, I am realizing I should have looked at optimizing this earlier. It is looking at over 600,000 rows and is Using where; Using temporary; Using filesort (which leads to an execution time of 5-10 seconds). It is using an index on the field 'battle_type.' SELECT username, SUM( outcome ) AS wins, COUNT( * ) - SUM( outcome ) AS losses FROM tblBattleHistory WHERE battle_type = '0' && outcome < '2' GROUP BY username ORDER BY wins DESC , losses ASC , username ASC LIMIT 0 , 50

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  • need recommendation for running PHP/Zend based optimizer

    - by senorsmile
    Firstly, I must admit that I don't know much about setting up PHP beyond the basics. I have an Ubuntu 10.04 server system (hosted) running primarily as an FTP store for a commercial store software. The server that the commercial store is installed on is unfortunately not very reliable, and would like to move that to this Ubuntu 10.04 server. (We've already received permission from the store vendor to do this.) My problem is that they use Zend optimizer which is only compatible with PHP 5.2. I have tried a couple of "hacks" to downgrade PHP to 5.2, but it breaks so many other things that it doesn't seem worth it. My idea is to install some sort of container of Ubuntu 8.04 (like OpenVZ) on the server to house a native install of PHP 5.2 to meet the dependency of the store software. However, it appears that OpenVZ is no longer supported on Ubuntu. Is there another solution similar that I could run on a hosted server to installed a separate "container-like" 8.04 system?

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  • SQL SERVER – Quiz and Video – Introduction to Basics of a Query Hint

    - by pinaldave
    This blog post is inspired from SQL Architecture Basics Joes 2 Pros: Core Architecture concepts – SQL Exam Prep Series 70-433 – Volume 3. [Amazon] | [Flipkart] | [Kindle] | [IndiaPlaza] This is follow up blog post of my earlier blog post on the same subject - SQL SERVER – Introduction to Basics of a Query Hint – A Primer. In the article we discussed various basics terminology of the query hints. The article further covers following important concepts of query hints. Expecting Seek and getting a Scan Creating an index for improved optimization Implementing the query hint Above three are the most important concepts related to query hint and SQL Server.  There are many more things one has to learn but without beginners fundamentals one can’t learn the advanced  concepts. Let us have small quiz and check how many of you get the fundamentals right. Quiz 1) You have the following query: DECLARE @UlaChoice TinyInt SET @Type = 1 SELECT * FROM LegalActivity WHERE UlaChoice = @UlaChoice You have a nonclustered index named IX_Legal_Ula on the UlaChoice field. The Primary key is on the ID field and called PK_Legal_ID 99% of the time the value of the @UlaChoice is set to ‘YP101′. What query will achieve the best optimization for this query? SELECT * FROM LegalActivity WHERE UlaChoice = @UlaChoice WITH(INDEX(X_Legal_Ula)) SELECT * FROM LegalActivity WHERE UlaChoice = @UlaChoice WITH(INDEX(PK_Legal_ID)) SELECT * FROM LegalActivity WHERE UlaChoice = @UlaChoice OPTION (Optimize FOR(@UlaChoice = ‘YP101′)) 2) You have the following query: SELECT * FROM CurrentProducts WHERE ShortName = ‘Yoga Trip’ You have a nonclustered index on the ShortName field and the query runs an efficient index seek. You change your query to use a variable for ShortName and now you are using a slow index scan. What query hint can you use to get the same execution time as before? WITH LOCK FAST OPTIMIZE FOR MAXDOP READONLY Now make sure that you write down all the answers on the piece of paper. Watch following video and read earlier article over here. If you want to change the answer you still have chance. Solution 1) 3 2) 4 Now compare let us check the answers and compare your answers to following answers. I am very confident you will get them correct. Available at USA: Amazon India: Flipkart | IndiaPlaza Volume: 1, 2, 3, 4, 5 Please leave your feedback in the comment area for the quiz and video. Did you know all the answers of the quiz? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Joes 2 Pros, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Discard Results After Query Execution – SSMS

    - by pinaldave
    The first thing I do any day is to turn on the computer. Today I woke up and as soon as I turned on the computer I saw a chat message from a friend. He was a bit confused and wanted me to help him. Just as usual I am keeping the relevant conversation in focus and documenting our conversation as chat. Let us call him Ajit. Ajit: Pinal, every time I run a query there is no result displayed in the SSMS but when I run the query in my application it works and returns an appropriate result. Pinal:  Have you tried with different parameters? Ajit: Same thing. However, it works from another computer when I connect to the same server with the same query parameters? Pinal: What? That is new and I believe it is something to do with SSMS and not with the server. Send me screenshot please. Ajit: I believe so, let me send you a screenshot, Pinal: (looking at the screenshot) Oh man, there is no result-tab at all. Ajit: That is what the problem is. It does not have the tab which displays the result. This works just fine from another computer. Pinal: Have you referred Nakul’s blog post – SSMS – Query result options – Discard result after query executes, that talks about setting which can discard the query results after execution. (After a while) Ajit: I think it seems like on the computer where I am running the query my SSMS seems to have the option enabled related to discarding results. I fixed it by following Nakul’s blog post. Pinal: Great! Quite often I get the question what is the importance of the feature. Let us first see how to turn on or turn off this feature in SQL Server Management Studio 2012. In SSMS 2012 go to Tools >> Options >> Query Results > SQL Server >> Results to Grid >> Discard Results After Query Execution. When enabled this option will discard results after the execution. The advantage of disabling the option is that it will improve the performance by using less memory. However the real question is why would someone enable or disable the option. What are the cases when someone wants to run the query but do not care about the result? Matter of the fact, it does not make sense at all to run query and not care about the result. The matter of the fact, I can see quite a few reasons for using this option. I often enable this option when I am doing performance tuning exercise. During performance tuning exercise when I am working with execution plans and do not need results to verify every time or when I am tuning Indexes and its effect on execution plan I do not need the results. In this kind of situations I do keep this option on and discard the results. It always helps me big time as in most of the performance tuning exercise I am dealing with huge amount of the data and dealing with this data can be expensive. Nakul’s has done the experiment here already but I am going to repeat the same again using AdventureWorks Database. Run following T-SQL Script with and without enabling the option to discard the results. USE AdventureWorks2012 GO SELECT * FROM Sales.SalesOrderDetail GO 10 After enabling Discard Results After Query Execution After disabling Discard Results After Query Execution Well, this is indeed a good option when someone is debugging the execution plan or does not want the result to be displayed. Please note that this option does not reduce IO or CPU usage for SQL Server. It just discards the results after execution and a good help for debugging on the development server. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology

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  • MERGE Bug with Filtered Indexes

    - by Paul White
    A MERGE statement can fail, and incorrectly report a unique key violation when: The target table uses a unique filtered index; and No key column of the filtered index is updated; and A column from the filtering condition is updated; and Transient key violations are possible Example Tables Say we have two tables, one that is the target of a MERGE statement, and another that contains updates to be applied to the target.  The target table contains three columns, an integer primary key, a single character alternate key, and a status code column.  A filtered unique index exists on the alternate key, but is only enforced where the status code is ‘a’: CREATE TABLE #Target ( pk integer NOT NULL, ak character(1) NOT NULL, status_code character(1) NOT NULL,   PRIMARY KEY (pk) );   CREATE UNIQUE INDEX uq1 ON #Target (ak) INCLUDE (status_code) WHERE status_code = 'a'; The changes table contains just an integer primary key (to identify the target row to change) and the new status code: CREATE TABLE #Changes ( pk integer NOT NULL, status_code character(1) NOT NULL,   PRIMARY KEY (pk) ); Sample Data The sample data for the example is: INSERT #Target (pk, ak, status_code) VALUES (1, 'A', 'a'), (2, 'B', 'a'), (3, 'C', 'a'), (4, 'A', 'd');   INSERT #Changes (pk, status_code) VALUES (1, 'd'), (4, 'a');          Target                     Changes +-----------------------+    +------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦ ¦  1 ¦ A  ¦ a           ¦    ¦  1 ¦ d           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+ ¦  4 ¦ A  ¦ d           ¦ +-----------------------+ The target table’s alternate key (ak) column is unique, for rows where status_code = ‘a’.  Applying the changes to the target will change row 1 from status ‘a’ to status ‘d’, and row 4 from status ‘d’ to status ‘a’.  The result of applying all the changes will still satisfy the filtered unique index, because the ‘A’ in row 1 will be deleted from the index and the ‘A’ in row 4 will be added. Merge Test One Let’s now execute a MERGE statement to apply the changes: MERGE #Target AS t USING #Changes AS c ON c.pk = t.pk WHEN MATCHED AND c.status_code <> t.status_code THEN UPDATE SET status_code = c.status_code; The MERGE changes the two target rows as expected.  The updated target table now contains: +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦ ¦  1 ¦ A  ¦ d           ¦ <—changed from ‘a’ ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ a           ¦ <—changed from ‘d’ +-----------------------+ Merge Test Two Now let’s repopulate the changes table to reverse the updates we just performed: TRUNCATE TABLE #Changes;   INSERT #Changes (pk, status_code) VALUES (1, 'a'), (4, 'd'); This will change row 1 back to status ‘a’ and row 4 back to status ‘d’.  As a reminder, the current state of the tables is:          Target                        Changes +-----------------------+    +------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦ ¦  1 ¦ A  ¦ d           ¦    ¦  1 ¦ a           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ d           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+ ¦  4 ¦ A  ¦ a           ¦ +-----------------------+ We execute the same MERGE statement: MERGE #Target AS t USING #Changes AS c ON c.pk = t.pk WHEN MATCHED AND c.status_code <> t.status_code THEN UPDATE SET status_code = c.status_code; However this time we receive the following message: Msg 2601, Level 14, State 1, Line 1 Cannot insert duplicate key row in object 'dbo.#Target' with unique index 'uq1'. The duplicate key value is (A). The statement has been terminated. Applying the changes using UPDATE Let’s now rewrite the MERGE to use UPDATE instead: UPDATE t SET status_code = c.status_code FROM #Target AS t JOIN #Changes AS c ON t.pk = c.pk WHERE c.status_code <> t.status_code; This query succeeds where the MERGE failed.  The two rows are updated as expected: +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦ ¦  1 ¦ A  ¦ a           ¦ <—changed back to ‘a’ ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ d           ¦ <—changed back to ‘d’ +-----------------------+ What went wrong with the MERGE? In this test, the MERGE query execution happens to apply the changes in the order of the ‘pk’ column. In test one, this was not a problem: row 1 is removed from the unique filtered index by changing status_code from ‘a’ to ‘d’ before row 4 is added.  At no point does the table contain two rows where ak = ‘A’ and status_code = ‘a’. In test two, however, the first change was to change row 1 from status ‘d’ to status ‘a’.  This change means there would be two rows in the filtered unique index where ak = ‘A’ (both row 1 and row 4 meet the index filtering criteria ‘status_code = a’). The storage engine does not allow the query processor to violate a unique key (unless IGNORE_DUP_KEY is ON, but that is a different story, and doesn’t apply to MERGE in any case).  This strict rule applies regardless of the fact that if all changes were applied, there would be no unique key violation (row 4 would eventually be changed from ‘a’ to ‘d’, removing it from the filtered unique index, and resolving the key violation). Why it went wrong The query optimizer usually detects when this sort of temporary uniqueness violation could occur, and builds a plan that avoids the issue.  I wrote about this a couple of years ago in my post Beware Sneaky Reads with Unique Indexes (you can read more about the details on pages 495-497 of Microsoft SQL Server 2008 Internals or in Craig Freedman’s blog post on maintaining unique indexes).  To summarize though, the optimizer introduces Split, Filter, Sort, and Collapse operators into the query plan to: Split each row update into delete followed by an inserts Filter out rows that would not change the index (due to the filter on the index, or a non-updating update) Sort the resulting stream by index key, with deletes before inserts Collapse delete/insert pairs on the same index key back into an update The effect of all this is that only net changes are applied to an index (as one or more insert, update, and/or delete operations).  In this case, the net effect is a single update of the filtered unique index: changing the row for ak = ‘A’ from pk = 4 to pk = 1.  In case that is less than 100% clear, let’s look at the operation in test two again:          Target                     Changes                   Result +-----------------------+    +------------------+    +-----------------------+ ¦ pk ¦ ak ¦ status_code ¦    ¦ pk ¦ status_code ¦    ¦ pk ¦ ak ¦ status_code ¦ ¦----+----+-------------¦    ¦----+-------------¦    ¦----+----+-------------¦ ¦  1 ¦ A  ¦ d           ¦    ¦  1 ¦ d           ¦    ¦  1 ¦ A  ¦ a           ¦ ¦  2 ¦ B  ¦ a           ¦    ¦  4 ¦ a           ¦    ¦  2 ¦ B  ¦ a           ¦ ¦  3 ¦ C  ¦ a           ¦    +------------------+    ¦  3 ¦ C  ¦ a           ¦ ¦  4 ¦ A  ¦ a           ¦                            ¦  4 ¦ A  ¦ d           ¦ +-----------------------+                            +-----------------------+ From the filtered index’s point of view (filtered for status_code = ‘a’ and shown in nonclustered index key order) the overall effect of the query is:   Before           After +---------+    +---------+ ¦ pk ¦ ak ¦    ¦ pk ¦ ak ¦ ¦----+----¦    ¦----+----¦ ¦  4 ¦ A  ¦    ¦  1 ¦ A  ¦ ¦  2 ¦ B  ¦    ¦  2 ¦ B  ¦ ¦  3 ¦ C  ¦    ¦  3 ¦ C  ¦ +---------+    +---------+ The single net change there is a change of pk from 4 to 1 for the nonclustered index entry ak = ‘A’.  This is the magic performed by the split, sort, and collapse.  Notice in particular how the original changes to the index key (on the ‘ak’ column) have been transformed into an update of a non-key column (pk is included in the nonclustered index).  By not updating any nonclustered index keys, we are guaranteed to avoid transient key violations. The Execution Plans The estimated MERGE execution plan that produces the incorrect key-violation error looks like this (click to enlarge in a new window): The successful UPDATE execution plan is (click to enlarge in a new window): The MERGE execution plan is a narrow (per-row) update.  The single Clustered Index Merge operator maintains both the clustered index and the filtered nonclustered index.  The UPDATE plan is a wide (per-index) update.  The clustered index is maintained first, then the Split, Filter, Sort, Collapse sequence is applied before the nonclustered index is separately maintained. There is always a wide update plan for any query that modifies the database. The narrow form is a performance optimization where the number of rows is expected to be relatively small, and is not available for all operations.  One of the operations that should disallow a narrow plan is maintaining a unique index where intermediate key violations could occur. Workarounds The MERGE can be made to work (producing a wide update plan with split, sort, and collapse) by: Adding all columns referenced in the filtered index’s WHERE clause to the index key (INCLUDE is not sufficient); or Executing the query with trace flag 8790 set e.g. OPTION (QUERYTRACEON 8790). Undocumented trace flag 8790 forces a wide update plan for any data-changing query (remember that a wide update plan is always possible).  Either change will produce a successfully-executing wide update plan for the MERGE that failed previously. Conclusion The optimizer fails to spot the possibility of transient unique key violations with MERGE under the conditions listed at the start of this post.  It incorrectly chooses a narrow plan for the MERGE, which cannot provide the protection of a split/sort/collapse sequence for the nonclustered index maintenance. The MERGE plan may fail at execution time depending on the order in which rows are processed, and the distribution of data in the database.  Worse, a previously solid MERGE query may suddenly start to fail unpredictably if a filtered unique index is added to the merge target table at any point. Connect bug filed here Tests performed on SQL Server 2012 SP1 CUI (build 11.0.3321) x64 Developer Edition © 2012 Paul White – All Rights Reserved Twitter: @SQL_Kiwi Email: [email protected]

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  • How to prevent Google Website Optimizer from making Google Analytics spike Direct Traffic and lower Bounce Rate?

    - by Scott
    I am using Google Website Optimizer (GWO) and Google Analytics. Whenever a person (Google Website Optimizer) does a javascript redirect, Google Analytics will change the referrer. When the referrer changes, the traffic source becomes yourself and is changed to Direct Traffic. For Example: A visitor goes to google: searches for my great service. Clicks the link that goes to website page: /home/ At this point, Google Analytics tracks the referrer as Google. However, /home/ has a GWO javacript redirect to a battery of A/B tests. /home-1/ or /home-2/ or /home-3/ When the redirect from /home/ occurs to /home-1/, google analytics on the /home-1/ page now thinks the referrer is yourself and converts the referrer to Direct Traffic since the Direct Traffic bucket is the unknown. I'm really surprised that GWO and GA do this when they both come from google. Now, How does one fix this to prevent the overwrite of the referrer using GWO?

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  • Last chance to vote in Optimizer Bumper Sticker Competition

    - by Maria Colgan
    There is still time to vote in our competition to find the best Optimizer bumper sticker, which we will give away at the Optimizer demo booth at this years Oracle Open World. Click here to vote for your favorite. Then stop by the Optimizer demo booth at Oracle Open World to claim your bumper sticker! Remember voting will close on June 30th and the winning slogan will be announced in early July. +Maria Colgan

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