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  • Optimizing Solr for Sorting

    - by devinfoley
    I'm using Solr for a realtime search index. My dataset is about 60M large documents. Instead of sorting by relevance, I need to sort by time. Currently I'm using the sort flag in the query to sort by time. This works fine for specific searches, but when searches return large numbers of results, Solr has to take all of the resulting documents and sort them by time before returning. This is slow, and there has to be a better way. What is the better way?

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  • Solr alphabetical sorting trouble. Sorting uppercase then lowercase for string type field

    - by Alauddin Ansari
    I've crated a title field with list below: Asking is good But answering is best join the group like this You are the best hey dudes. whass up When I'm sorting this ASC (&sort=title ASC) Asking is good But answering is best You are the best hey dudes. whass up join the group like this and (&sort=title DESC) join the group like this hey dudes. whass up You are the best But answering is best Asking is good But I'm expecting result like: (&sort=title ASC) Asking is good But answering is best hey dudes. whass up join the group like this You are the best schema.xml <field name="title" type="text_general" indexed="true" stored="true"/> <field name="title_sort" type="string" indexed="true" stored="false"/> <copyField source="title" dest="title_sort" /> I'm using title_sort field to sort (also tried title field) Please tell me where I'm going wrong

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  • Sorting by value with ORDER BY?

    - by Kevin
    For clarification, are you able to use MySQL this way to sort? ORDER BY CompanyID = XXX DESC What I am trying to do is use one sql query to sort everything where X = Y, in this case, where CompanyID = XXX. All values where CompanyID is not XXX should come after all the results where CompanyID = XXX. I don't want to limit my query but I do want to sort a particular company above other listings.

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  • Parallelism in .NET – Part 11, Divide and Conquer via Parallel.Invoke

    - by Reed
    Many algorithms are easily written to work via recursion.  For example, most data-oriented tasks where a tree of data must be processed are much more easily handled by starting at the root, and recursively “walking” the tree.  Some algorithms work this way on flat data structures, such as arrays, as well.  This is a form of divide and conquer: an algorithm design which is based around breaking up a set of work recursively, “dividing” the total work in each recursive step, and “conquering” the work when the remaining work is small enough to be solved easily. Recursive algorithms, especially ones based on a form of divide and conquer, are often a very good candidate for parallelization. This is apparent from a common sense standpoint.  Since we’re dividing up the total work in the algorithm, we have an obvious, built-in partitioning scheme.  Once partitioned, the data can be worked upon independently, so there is good, clean isolation of data. Implementing this type of algorithm is fairly simple.  The Parallel class in .NET 4 includes a method suited for this type of operation: Parallel.Invoke.  This method works by taking any number of delegates defined as an Action, and operating them all in parallel.  The method returns when every delegate has completed: Parallel.Invoke( () => { Console.WriteLine("Action 1 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); }, () => { Console.WriteLine("Action 2 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); }, () => { Console.WriteLine("Action 3 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); } ); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Running this simple example demonstrates the ease of using this method.  For example, on my system, I get three separate thread IDs when running the above code.  By allowing any number of delegates to be executed directly, concurrently, the Parallel.Invoke method provides us an easy way to parallelize any algorithm based on divide and conquer.  We can divide our work in each step, and execute each task in parallel, recursively. For example, suppose we wanted to implement our own quicksort routine.  The quicksort algorithm can be designed based on divide and conquer.  In each iteration, we pick a pivot point, and use that to partition the total array.  We swap the elements around the pivot, then recursively sort the lists on each side of the pivot.  For example, let’s look at this simple, sequential implementation of quicksort: public static void QuickSort<T>(T[] array) where T : IComparable<T> { QuickSortInternal(array, 0, array.Length - 1); } private static void QuickSortInternal<T>(T[] array, int left, int right) where T : IComparable<T> { if (left >= right) { return; } SwapElements(array, left, (left + right) / 2); int last = left; for (int current = left + 1; current <= right; ++current) { if (array[current].CompareTo(array[left]) < 0) { ++last; SwapElements(array, last, current); } } SwapElements(array, left, last); QuickSortInternal(array, left, last - 1); QuickSortInternal(array, last + 1, right); } static void SwapElements<T>(T[] array, int i, int j) { T temp = array[i]; array[i] = array[j]; array[j] = temp; } Here, we implement the quicksort algorithm in a very common, divide and conquer approach.  Running this against the built-in Array.Sort routine shows that we get the exact same answers (although the framework’s sort routine is slightly faster).  On my system, for example, I can use framework’s sort to sort ten million random doubles in about 7.3s, and this implementation takes about 9.3s on average. Looking at this routine, though, there is a clear opportunity to parallelize.  At the end of QuickSortInternal, we recursively call into QuickSortInternal with each partition of the array after the pivot is chosen.  This can be rewritten to use Parallel.Invoke by simply changing it to: // Code above is unchanged... SwapElements(array, left, last); Parallel.Invoke( () => QuickSortInternal(array, left, last - 1), () => QuickSortInternal(array, last + 1, right) ); } This routine will now run in parallel.  When executing, we now see the CPU usage across all cores spike while it executes.  However, there is a significant problem here – by parallelizing this routine, we took it from an execution time of 9.3s to an execution time of approximately 14 seconds!  We’re using more resources as seen in the CPU usage, but the overall result is a dramatic slowdown in overall processing time. This occurs because parallelization adds overhead.  Each time we split this array, we spawn two new tasks to parallelize this algorithm!  This is far, far too many tasks for our cores to operate upon at a single time.  In effect, we’re “over-parallelizing” this routine.  This is a common problem when working with divide and conquer algorithms, and leads to an important observation: When parallelizing a recursive routine, take special care not to add more tasks than necessary to fully utilize your system. This can be done with a few different approaches, in this case.  Typically, the way to handle this is to stop parallelizing the routine at a certain point, and revert back to the serial approach.  Since the first few recursions will all still be parallelized, our “deeper” recursive tasks will be running in parallel, and can take full advantage of the machine.  This also dramatically reduces the overhead added by parallelizing, since we’re only adding overhead for the first few recursive calls.  There are two basic approaches we can take here.  The first approach would be to look at the total work size, and if it’s smaller than a specific threshold, revert to our serial implementation.  In this case, we could just check right-left, and if it’s under a threshold, call the methods directly instead of using Parallel.Invoke. The second approach is to track how “deep” in the “tree” we are currently at, and if we are below some number of levels, stop parallelizing.  This approach is a more general-purpose approach, since it works on routines which parse trees as well as routines working off of a single array, but may not work as well if a poor partitioning strategy is chosen or the tree is not balanced evenly. This can be written very easily.  If we pass a maxDepth parameter into our internal routine, we can restrict the amount of times we parallelize by changing the recursive call to: // Code above is unchanged... SwapElements(array, left, last); if (maxDepth < 1) { QuickSortInternal(array, left, last - 1, maxDepth); QuickSortInternal(array, last + 1, right, maxDepth); } else { --maxDepth; Parallel.Invoke( () => QuickSortInternal(array, left, last - 1, maxDepth), () => QuickSortInternal(array, last + 1, right, maxDepth)); } We no longer allow this to parallelize indefinitely – only to a specific depth, at which time we revert to a serial implementation.  By starting the routine with a maxDepth equal to Environment.ProcessorCount, we can restrict the total amount of parallel operations significantly, but still provide adequate work for each processing core. With this final change, my timings are much better.  On average, I get the following timings: Framework via Array.Sort: 7.3 seconds Serial Quicksort Implementation: 9.3 seconds Naive Parallel Implementation: 14 seconds Parallel Implementation Restricting Depth: 4.7 seconds Finally, we are now faster than the framework’s Array.Sort implementation.

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  • CodePlex Daily Summary for Monday, March 15, 2010

    CodePlex Daily Summary for Monday, March 15, 2010New ProjectsAT Accounts: AT Accounts helps developers to intergrate accounting functionality in their applications. It has both the WPF userinterface and SilverlightChild page list(for dnn4/5): A free module which can display sub pages list for a selected tab. It is template based and support options like Recursive/Child tab prefix/link...dashCommerce: dashCommerce is the leading ASP.NET e-commerce platform.Fire Utilities: My Development Utiltites and base classes: New Zealand Bank Account ValidatorFlyCatch (Bugtracking System): A simple webbased Bugtracking System.fracback: Fractal feedback concepts, based on video feedbackftc3650: code for ftc 3650Google AJAX Search Services for jQuery: This plug-in encapsulates part of the Google AJAX Search API to streamline the process of Google Search integration.Little Black Book DB: This is the Database for the following Projects: SQL Azure PHP Connection SQL Azure Ruby Connection SQL Azure Python Connection SQL Azure .NE...MediaCommMVC: MediaCommMVC is a community platform focusing on photos, videos and discussions. It's based on ASP.NET MVC and uses (fluent) nhibernate, jquery an...Miracle OS: The Miracle OS is an OS from Fox. We work on it, but it isn't ready. Do you want help us? Please send a mail to victor@fox.fi.stMultiwfn: (1)Plotting various graph(filled color/contour/relief map...) (2)Generate Cube file (3)Manipulate & analyze wavefunction Supportting lots of proper...MySpace DataRelay: Data Relay is the foundation of MySpace's middle tier. At its heart, it is a messaging system for relaying information both between clients and ser...NinjaCMS: Ninja CMS is an asp.net based content management system which provides a designer friendly, developer friendly interface to work with. It's flexibl...open gaze and mouse analyzer: Ogama allows recording and analyzing eye- and mouse-tracking data from slideshow eyetracking experiments in parallel. It´s developed in C#.NET and ...Özkasoft.Net | E-Commerce: Özkasoft's E-Commerce ProjectProfiCV: Profi CVpyTarget: Implement a powerful iscsi target in python, and easily use under most popular systems. It also includes the following features: multi-target, mult...SharePoint Platform Extensions: SharePoint Platform Extensions by Espora. Sorting Algorithm Visualization: Sorting Algorithm Visualization Displays Bead Sort, Binary Tree Sort, Bubble Sort, Bucket Sort, Cocktail Sort, Counting Sort, Gnome Sort, In Place ...Specify: A framework for creating executable specifications in .NET. Spell Corrector: A spell corrector that uses Bayes algorithm and BK (Burkhard-Keller) tree.SQL Azure Ruby Connection: This is a demo to show how to connect to SQL Azure with Ruby on Rails.uManage - AD Self-Service Portal: uManage is an Active Directory Self-Service Portal as well as Help Desk web application designed for use on intranet systems. It allows users to u...Winforms Rounded Group Box Control: Rounded Group Box - A Grouping control with Rounded Corners, Gradients, and Drop ShadowWizard Engine: Host application agnostic wizard engine platform, that allows you to fluently define complex conditional flows and provides means for execution of ...WS-Transfer based File Upload: WS-Transer based upload of large files in multiple partsXAMLStylePad: XAMLStylePad - is a simple in use styles and templates XAML-editor. It designed for comfortable coding in XAML with real-time preview result on aut...Your Twitt Engine: Ovo je aplikacija za sve ljude koji su na svom radnom mjestu pod prismotrom poslodavca ili sefa, koji kontroliraju njihov monitor. Tako uz ovu apl...New ReleasesAmiBroker Plug-ins with C#. A non official AmiBroker Plug-in SDK: AniBroker Plug-in SDK v0.0.5: Removed dependency on .NET 4.0, now it works fine with .NET 2.0BeerMath.net: 0.1: Version 0.1Initial set of calculations supported: IBUs Color ABV/ABWChild page list(for dnn4/5): Child Page List 2.6: Source code is also include in module package.dashCommerce: dashCommerce Releases: You can download both Source and WebReady packages at http://www.dashcommerce.org. If you wish to submit patches, then use the Source Code tab her...ExcelDna: ExcelDna Version 0.23: ExcelDna Version 0.23 2010/03/14 - Packing and other features This release adds a number of features to ExcelDna: Add ExplicitExports attribute to ...Family Tree Analyzer: Version 1.0.7.1: Version 1.0.7.0 Update Census form to show family totals Fix England and Wales Lost Cousins reports to be England OR Wales Problems with Gedcom in...Foursquare BlogEngine Widget: foursquare widget for BlogEngine.NET Version 0.2: To see the changes which have been made, visit http://philippkueng.ch/post/Foursquare-BlogEngineNET-Widget-Version-02.aspx For installation instruc...GLB Virtual Player Builder: 0.4.0 Official Archetypes Release: Updated for new archetypes. The builder still includes the old player formats, and you can still import your old players' builds. Please PM me an...Home Access Plus+: v3.1.4.0: Version 3.1.3.1 Release Change Log: Added Breadcrumbs to My Computer File Changes: ~/bin/CHS Extranet.dll ~/bin/CHS Extranet.pdb ~/images/arro...Little Black Book DB: Little Black Book R1: This is the first release of the Little black book presentation I presented at Confoo. I decided to package the Database along with the Windows Az...mite.net - .NET API for mite: Version 1.2.1: Added Support for budget type Modified TimerMapper to return timers Fixed Encoding issue in xml conversionMultiwfn: multiwfn1.0: multiwfn1.0Multiwfn: multiwfn1.0_source: multiwfn1.0_sourceMultiwfn: multiwfn1.1: multiwfn1.1Multiwfn: multiwfn1.1_source: multiwfn1.1_sourceMultiwfn: multiwfn1.2: 1.2 2010-FEB-9 *加入了对10f型轨道的支持。 *新支持非限制性Post-HF波函数用以计算自旋密度。 *新增加直接读入高斯03/09的fch文件的支持,可以观看NBO轨道,详见readme实例4.10。 *绘制平面图时允许通过输入三个点坐标定义平面,允许自定义平面的原点与平移向...Multiwfn: multiwfn1.2_source: Include all the file that needed by compilation in CVF6.5PowerShell Community Extensions: 2.0 Beta 2: Release NotesThis is a pretty close to final release. We have eliminated all of the names that ran afound of the module loading mechanism which me...pyTarget: pyTarget.binary-for-windows-x86.rar: pyTarget.binary-for-windows-x86.rarpyTarget: pyTarget.src.tar.bz2: pyTarget.src.tar.bz2RedBulb for XNA Framework: RedBulbConsole (Console, Menu and TrackHUD Sample): http://bayimg.com/image/jalhmaacd.jpgScrum Sprint Monitor: 1.0.0.45262 (.NET 4.0 RC): Tested against TFS 2010 RC. For the .NET 3.5 SP1 platform, use the .NET 3.5 SP1 download. What is new in this release? Major performance increase ...sELedit: sELedit v1.1: Removed: Clone and Delete Button Added: Context Menu to Item List Added: Clone and Delete button to Context Menu Added: Export / Import Item ...Sorting Algorithm Visualization: Beta 1: Sorting Algorithm VisualizationSpecify: Version 1.0: Version 1.0Spell Corrector: Spell Corrector 0.1: A basic version that supports basic functionality.Spell Corrector: Spell Corrector 0.1 Source Code: Source code of version 0.1Spiral Architecture Driven Development (SADD): SADD v.0.9: Pre-final release with the NEW materials now all in English ! The Final release is coming soon. After guest column for SADD publication in MS Ar...Spiral Architecture Driven Development (SADD) for Russian: SADD v.0.9: Pre-final release with the NEW materials now all in English ! The Final release is coming soon. After guest column for SADD publication in MS Ar...SQL Azure Ruby Connection: Little Black Book Ruby R1: This is the Ruby Demo that I demostrated at Confoo. Special Thanks to Tony Thompson for putting this demo together. To check out Tony's Portfolio ...The Scrum Factory: The Scrum Factory Server - V1a: This is the newest version of the server. Some minor bugs from version v1 were fixed, and some slighted changed were made some database views.twNowplaying: twNowplaying 1.0.0.4: Please note that the user has to press the Twitter logo to log in the first time the application is started.uManage - AD Self-Service Portal: uManage - v1.0 (.NET 4.0 RC): Initial Release of uManage. NOTE: Designed for ASP.NET and .NET 4.0 RC ONLY! This is the initial release of uManage and covers the first phase of ...Virtu: Virtu 0.8: Source Requirements.NET Framework 3.5 with Service Pack 1 Visual Studio 2008 with Service Pack 1, or Visual C# 2008 Express Edition with Service Pa...Visual Studio DSite: Speech Synthesizer (Text to Speech) in Visual C++: A very simple text to speech program written in visual c 2008.White Tiger: 0.0.4.0: *now you can disable the file security checks *winforms aplications created to manage tablesWinforms Rounded Group Box Control: Release 1.0: To use this control simply add the class to your project and compile it. It will then show up in the projects components section in the toolbox. ...WS-Transfer based File Upload: 0.5: Implements the binary file transfer mechanism onlyXsltDb - DotNetNuke XSLT module: 01.00.89: Super modules configuration names. 16767 - Fixed more bug fixes...Yakiimo3D: DirectX11 Rheinhard Tonemapping Source and Binary: DirectX11 Rheinhard tonemapping source and binary.Your Twitt Engine: test: Slobodno probajte sa vasim twitter korisničkim računomMost Popular ProjectsMetaSharpWBFS ManagerRawrAJAX Control ToolkitMicrosoft SQL Server Product Samples: DatabaseSilverlight ToolkitASP.NET Ajax LibraryWindows Presentation Foundation (WPF)ASP.NETLiveUpload to FacebookMost Active ProjectsLINQ to TwitterRawrN2 CMSBlogEngine.NETpatterns & practices – Enterprise LibrarySharePoint Team-MailerjQuery Library for SharePoint Web ServicesCaliburn: An Application Framework for WPF and SilverlightFarseer Physics EngineCalcium: A modular application toolset leveraging Prism

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  • So…is it a Seek or a Scan?

    - by Paul White
    You’re probably most familiar with the terms ‘Seek’ and ‘Scan’ from the graphical plans produced by SQL Server Management Studio (SSMS).  The image to the left shows the most common ones, with the three types of scan at the top, followed by four types of seek.  You might look to the SSMS tool-tip descriptions to explain the differences between them: Not hugely helpful are they?  Both mention scans and ranges (nothing about seeks) and the Index Seek description implies that it will not scan the index entirely (which isn’t necessarily true). Recall also yesterday’s post where we saw two Clustered Index Seek operations doing very different things.  The first Seek performed 63 single-row seeking operations; and the second performed a ‘Range Scan’ (more on those later in this post).  I hope you agree that those were two very different operations, and perhaps you are wondering why there aren’t different graphical plan icons for Range Scans and Seeks?  I have often wondered about that, and the first person to mention it after yesterday’s post was Erin Stellato (twitter | blog): Before we go on to make sense of all this, let’s look at another example of how SQL Server confusingly mixes the terms ‘Scan’ and ‘Seek’ in different contexts.  The diagram below shows a very simple heap table with two columns, one of which is the non-clustered Primary Key, and the other has a non-unique non-clustered index defined on it.  The right hand side of the diagram shows a simple query, it’s associated query plan, and a couple of extracts from the SSMS tool-tip and Properties windows. Notice the ‘scan direction’ entry in the Properties window snippet.  Is this a seek or a scan?  The different references to Scans and Seeks are even more pronounced in the XML plan output that the graphical plan is based on.  This fragment is what lies behind the single Index Seek icon shown above: You’ll find the same confusing references to Seeks and Scans throughout the product and its documentation. Making Sense of Seeks Let’s forget all about scans for a moment, and think purely about seeks.  Loosely speaking, a seek is the process of navigating an index B-tree to find a particular index record, most often at the leaf level.  A seek starts at the root and navigates down through the levels of the index to find the point of interest: Singleton Lookups The simplest sort of seek predicate performs this traversal to find (at most) a single record.  This is the case when we search for a single value using a unique index and an equality predicate.  It should be readily apparent that this type of search will either find one record, or none at all.  This operation is known as a singleton lookup.  Given the example table from before, the following query is an example of a singleton lookup seek: Sadly, there’s nothing in the graphical plan or XML output to show that this is a singleton lookup – you have to infer it from the fact that this is a single-value equality seek on a unique index.  The other common examples of a singleton lookup are bookmark lookups – both the RID and Key Lookup forms are singleton lookups (an RID lookup finds a single record in a heap from the unique row locator, and a Key Lookup does much the same thing on a clustered table).  If you happen to run your query with STATISTICS IO ON, you will notice that ‘Scan Count’ is always zero for a singleton lookup. Range Scans The other type of seek predicate is a ‘seek plus range scan’, which I will refer to simply as a range scan.  The seek operation makes an initial descent into the index structure to find the first leaf row that qualifies, and then performs a range scan (either backwards or forwards in the index) until it reaches the end of the scan range. The ability of a range scan to proceed in either direction comes about because index pages at the same level are connected by a doubly-linked list – each page has a pointer to the previous page (in logical key order) as well as a pointer to the following page.  The doubly-linked list is represented by the green and red dotted arrows in the index diagram presented earlier.  One subtle (but important) point is that the notion of a ‘forward’ or ‘backward’ scan applies to the logical key order defined when the index was built.  In the present case, the non-clustered primary key index was created as follows: CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col ASC) ) ; Notice that the primary key index specifies an ascending sort order for the single key column.  This means that a forward scan of the index will retrieve keys in ascending order, while a backward scan would retrieve keys in descending key order.  If the index had been created instead on key_col DESC, a forward scan would retrieve keys in descending order, and a backward scan would return keys in ascending order. A range scan seek predicate may have a Start condition, an End condition, or both.  Where one is missing, the scan starts (or ends) at one extreme end of the index, depending on the scan direction.  Some examples might help clarify that: the following diagram shows four queries, each of which performs a single seek against a column holding every integer from 1 to 100 inclusive.  The results from each query are shown in the blue columns, and relevant attributes from the Properties window appear on the right: Query 1 specifies that all key_col values less than 5 should be returned in ascending order.  The query plan achieves this by seeking to the start of the index leaf (there is no explicit starting value) and scanning forward until the End condition (key_col < 5) is no longer satisfied (SQL Server knows it can stop looking as soon as it finds a key_col value that isn’t less than 5 because all later index entries are guaranteed to sort higher). Query 2 asks for key_col values greater than 95, in descending order.  SQL Server returns these results by seeking to the end of the index, and scanning backwards (in descending key order) until it comes across a row that isn’t greater than 95.  Sharp-eyed readers may notice that the end-of-scan condition is shown as a Start range value.  This is a bug in the XML show plan which bubbles up to the Properties window – when a backward scan is performed, the roles of the Start and End values are reversed, but the plan does not reflect that.  Oh well. Query 3 looks for key_col values that are greater than or equal to 10, and less than 15, in ascending order.  This time, SQL Server seeks to the first index record that matches the Start condition (key_col >= 10) and then scans forward through the leaf pages until the End condition (key_col < 15) is no longer met. Query 4 performs much the same sort of operation as Query 3, but requests the output in descending order.  Again, we have to mentally reverse the Start and End conditions because of the bug, but otherwise the process is the same as always: SQL Server finds the highest-sorting record that meets the condition ‘key_col < 25’ and scans backward until ‘key_col >= 20’ is no longer true. One final point to note: seek operations always have the Ordered: True attribute.  This means that the operator always produces rows in a sorted order, either ascending or descending depending on how the index was defined, and whether the scan part of the operation is forward or backward.  You cannot rely on this sort order in your queries of course (you must always specify an ORDER BY clause if order is important) but SQL Server can make use of the sort order internally.  In the four queries above, the query optimizer was able to avoid an explicit Sort operator to honour the ORDER BY clause, for example. Multiple Seek Predicates As we saw yesterday, a single index seek plan operator can contain one or more seek predicates.  These seek predicates can either be all singleton seeks or all range scans – SQL Server does not mix them.  For example, you might expect the following query to contain two seek predicates, a singleton seek to find the single record in the unique index where key_col = 10, and a range scan to find the key_col values between 15 and 20: SELECT key_col FROM dbo.Example WHERE key_col = 10 OR key_col BETWEEN 15 AND 20 ORDER BY key_col ASC ; In fact, SQL Server transforms the singleton seek (key_col = 10) to the equivalent range scan, Start:[key_col >= 10], End:[key_col <= 10].  This allows both range scans to be evaluated by a single seek operator.  To be clear, this query results in two range scans: one from 10 to 10, and one from 15 to 20. Final Thoughts That’s it for today – tomorrow we’ll look at monitoring singleton lookups and range scans, and I’ll show you a seek on a heap table. Yes, a seek.  On a heap.  Not an index! If you would like to run the queries in this post for yourself, there’s a script below.  Thanks for reading! IF OBJECT_ID(N'dbo.Example', N'U') IS NOT NULL BEGIN DROP TABLE dbo.Example; END ; -- Test table is a heap -- Non-clustered primary key on 'key_col' CREATE TABLE dbo.Example ( key_col INTEGER NOT NULL, data INTEGER NOT NULL, CONSTRAINT [PK dbo.Example key_col] PRIMARY KEY NONCLUSTERED (key_col) ) ; -- Non-unique non-clustered index on the 'data' column CREATE NONCLUSTERED INDEX [IX dbo.Example data] ON dbo.Example (data) ; -- Add 100 rows INSERT dbo.Example WITH (TABLOCKX) ( key_col, data ) SELECT key_col = V.number, data = V.number FROM master.dbo.spt_values AS V WHERE V.[type] = N'P' AND V.number BETWEEN 1 AND 100 ; -- ================ -- Singleton lookup -- ================ ; -- Single value equality seek in a unique index -- Scan count = 0 when STATISTIS IO is ON -- Check the XML SHOWPLAN SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col = 32 ; -- =========== -- Range Scans -- =========== ; -- Query 1 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col <= 5 ORDER BY E.key_col ASC ; -- Query 2 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col > 95 ORDER BY E.key_col DESC ; -- Query 3 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col >= 10 AND E.key_col < 15 ORDER BY E.key_col ASC ; -- Query 4 SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col >= 20 AND E.key_col < 25 ORDER BY E.key_col DESC ; -- Final query (singleton + range = 2 range scans) SELECT E.key_col FROM dbo.Example AS E WHERE E.key_col = 10 OR E.key_col BETWEEN 15 AND 20 ORDER BY E.key_col ASC ; -- === TIDY UP === DROP TABLE dbo.Example; © 2011 Paul White email: [email protected] twitter: @SQL_Kiwi

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  • Google lance la version 1.0 stable de mod_pagespeed, le module du serveur Apache pour « rendre le Web plus rapide »

    Google sort un module d'optimisation pour Apache HTTP Server Qui automatise 15 opérations et peut diminuer de moitié le temps de chargement des pages Après avoir mis à la disposition des développeurs Page Speed, un outil interne d'analyse et d'optimisation des performances des sites Web, Google récidive aujourd'hui et sort un module pour les serveurs Apache. Appelé à juste titre « mod_pagespeed », cet outil automatise bon nombre des conseils et bonne pratiques jusque-là seulement suggérés aux développeurs dans l'add-on du même nom qui se greffe à Firebug dans sa version pour Firefox. Le module « mod_pagespeed » pour Apache HTTP Server, automatise ainsi 15 opération...

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  • Meta package / quick reference for string manipulation commands?

    - by Dylan McCall
    The latest version of the Scribes text editor lets us select some text, hit Alt+X, and then run an arbitrary command. For example, I can run the sort command and the selected text is replaced appropriately. This is quite useful but I am also not very well-versed in awk and the like. Is there something I can grab that will provide more of these commands like sort? Maybe a package with a whole bunch of handy, task-specific string manipulation commands?

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  • Merge Join component sorted outputs [SSIS]

    - by jamiet
    One question that I have been asked a few times of late in regard to performance tuning SSIS data flows is this: Why isn’t the Merge Join output sorted (i.e.IsSorted=True)? This is a fair question. After all both of the Merge Join inputs are sorted, hence why wouldn’t the output be sorted as well? Well here’s a little secret, the Merge Join output IS sorted! There’s a caveat though – it is only under certain circumstances and SSIS itself doesn’t do a good job of informing you of it. Let’s take a look at an example. Here we have a dataflow that consumes data from the [AdventureWorks2008].[Sales].[SalesOrderHeader] & [AdventureWorks2008].[Sales].[SalesOrderDetail] tables then joins them using a Merge Join component: Let’s take a look inside the editor of the Merge Join: We are joining on the [SalesOrderId] field (which is what the two inputs just happen to be sorted upon). We are also putting [SalesOrderHeader].[SalesOrderId] into the output. Believe it or not the output from this Merge Join component is sorted (i.e. has IsSorted=True) but unfortunately the Merge Join component does not have an Advanced Editor hence it is hidden away from us. There are a couple of ways to prove to you that is the case; I could open up the package XML inside the .dtsx file and show you the metadata but there is an easier way than that – I can attach a Sort component to the output. Take a look: Notice that the Sort component is attempting to sort on the [SalesOrderId] column. This gives us the following warning: Validation warning. DFT Get raw data: {992B7C9A-35AD-47B9-A0B0-637F7DDF93EB}: The data is already sorted as specified so the transform can be removed. The warning proves that the output from the Merge Join is sorted! It must be noted that the Merge Join output will only have IsSorted=True if at least one of the join columns is included in the output. So there you go, the Merge Join component can indeed produce a sorted output and that’s very useful in order to avoid unnecessary expensive Sort operations downstream. Hope this is useful to someone out there! @Jamiet  P.S. Thank you to Bob Bojanic on the SSIS product team who pointed this out to me!

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  • How can I evaluate a candidate's knowledge of Html/CSS during an interview?

    - by webnoob
    I am trying to determine some good interview questions to assess the ability of people coming in for a Html/CSS job, however that topic is extremely broad, and I'm not sure what sort of questions I can ask to properly evaluate someone's HTML/CSS knowledge. What sort of questions can I ask to evaluate a candidate's Html/CSS abilities during an interview? Ideally I would like to ask few questions and then give them a real life scenario to combat.

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  • The Written Roles of Chief Technology Officer

    - by Jon Hopkins
    A follow up to this question: The Written Roles of Software Development Manager What is the role and what are the responsibilities of a CTO when it's done well, with particular reference to how it might pertain to a programmer with aspirations towards this sort of position? (Reason for asking - it's one potential career destination for programmers looking to move away from a purely hands-on role and for those with this sort of ambition it's worth knowing what it actually entails).

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  • Merge Join component sorted outputs [SSIS]

    - by jamiet
    One question that I have been asked a few times of late in regard to performance tuning SSIS data flows is this: Why isn’t the Merge Join output sorted (i.e.IsSorted=True)? This is a fair question. After all both of the Merge Join inputs are sorted, hence why wouldn’t the output be sorted as well? Well here’s a little secret, the Merge Join output IS sorted! There’s a caveat though – it is only under certain circumstances and SSIS itself doesn’t do a good job of informing you of it. Let’s take a look at an example. Here we have a dataflow that consumes data from the [AdventureWorks2008].[Sales].[SalesOrderHeader] & [AdventureWorks2008].[Sales].[SalesOrderDetail] tables then joins them using a Merge Join component: Let’s take a look inside the editor of the Merge Join: We are joining on the [SalesOrderId] field (which is what the two inputs just happen to be sorted upon). We are also putting [SalesOrderHeader].[SalesOrderId] into the output. Believe it or not the output from this Merge Join component is sorted (i.e. has IsSorted=True) but unfortunately the Merge Join component does not have an Advanced Editor hence it is hidden away from us. There are a couple of ways to prove to you that is the case; I could open up the package XML inside the .dtsx file and show you the metadata but there is an easier way than that – I can attach a Sort component to the output. Take a look: Notice that the Sort component is attempting to sort on the [SalesOrderId] column. This gives us the following warning: Validation warning. DFT Get raw data: {992B7C9A-35AD-47B9-A0B0-637F7DDF93EB}: The data is already sorted as specified so the transform can be removed. The warning proves that the output from the Merge Join is sorted! It must be noted that the Merge Join output will only have IsSorted=True if at least one of the join columns is included in the output. So there you go, the Merge Join component can indeed produce a sorted output and that’s very useful in order to avoid unnecessary expensive Sort operations downstream. Hope this is useful to someone out there! @Jamiet  P.S. Thank you to Bob Bojanic on the SSIS product team who pointed this out to me!

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  • Adjusting the Score on Oracle Text search results

    - by Kyle Hatlestad
    When you sort the results of a search by Score using OracleTextSearch as the search engine in WebCenter Content, the results coming back are based on the relevancy on the document.  In theory, the more relevant the search term is to the document, the higher ranked Score it should receive.  But in practice, the relevancy score can seem somewhat of a mystery.  It's not entirely clear how it ranks the importance of some documents over others based on the search term.  And often times, once a word appears a certain number of times within a document, the Score simply maxes out at 100 and the top results can be difficult to discern from one another.  Take for example the search for 'vacation' on this set of documents: Out of 7 results, 6 of them have a Score of '100' which means they are basically ranked the same.  This doesn't make the sort by Score very meaningful.   Besides sorting by relevance, you can also tell Oracle Text to sort by occurrence.  In that case, it is a much more predictable result in how they would be ranked. And for many cases provide a more meaningful sorting of results then relevance. To change this takes a small component change to the SearchOperatorMap resource.  By default, the query used for full-text searching looks like: <td>(ORACLETEXTSEARCH)fullText</td> <td>DEFINESCORE((%V), RELEVANCE * .1)</td> <td>text</td> Overriding this resource and changing it to: <td>(ORACLETEXTSEARCH)fullText</td> <td>DEFINESCORE((%V), OCCURRENCE * .01)</td>  <td>text</td> will force it to now use occurrence (note the change in scale to .01 as well).  So running the same search and sort options as the example above, the results come out quite a bit differently: In this case, there is a clear understanding of how the items rank.   And generally, if the search term appears 3 times more in one document then another, it's got a better chance of being a document I'm interested in.  You may or may not feel the relevance ranking is better then the search term occurrence, but this provides the opportunity to try an alternate method that might work better for your results.  A pre-built component is available for download here. There is one caveat in using this method.  The occurrence ranking also maxes out at 100, so if a search term is in the document more then that, the Score result will stay at 100.

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  • Powershell Exchange script returning inconsistent results - PS weirdness

    - by Ian
    Maybe someone can shed some light on a bit of Powershell weirdness I've come across and can't explain. This PS script returns a list of exchange databases, their sizes and the number of mailboxes in each one: Get-MailboxDatabase | Select Server, StorageGroupName, Name, @{Name="Size (GB)";Expression={$objitem = (Get-MailboxDatabase $_.Identity); $path = "`\`\" + $objitem.server + "`\" + $objItem.EdbFilePath.DriveName.Remove(1).ToString() + "$"+ $objItem.EdbFilePath.PathName.Remove(0,2); $size = ((Get-ChildItem $path).length)/1048576KB; [math]::round($size, 2)}}, @{Name="Size (MB)";Expression={$objitem = (Get-MailboxDatabase $_.Identity); $path = "`\`\" + $objitem.server + "`\" + $objItem.EdbFilePath.DriveName.Remove(1).ToString() + "$"+ $objItem.EdbFilePath.PathName.Remove(0,2); $size = ((Get-ChildItem $path).length)/1024KB; [math]::round($size, 2)}}, @{Name="No. Of Mbx";expression={(Get-Mailbox -Database $_.Identity | Measure-Object).Count}} | Format-table –AutoSize If I add a simple 'sort name' before the 'format-table' my resulting table contains blanks where the database sizes and number of mailboxes should appear (not zeros, blank empty space).... but only in some rows, not all rows. Some rows contain numbers! If I put the '|sort name| ' after the initial 'get-mailboxdatabase' it works fine. Whats even weirder is if I do the following: Execute the above command Add the sort before format-table Execute the new command Execute the initial command again What I see is different amounts in each of the three cases - all of which are incorrect. Yet 1 and 3 are the same command and the only difference with 2 is a sort. 1 and 3 should, at a minimum, return the same results. I get blanks where I should have MBs If I add the sort after the get-mailboxdatabase, it always returns identical results (as it should). Can anyone suggest an explanation as to what may be going on? If its of any help in reading the expression, I've reformatted it here to make it a bit more readable: Get-MailboxDatabase | Select Server, StorageGroupName, Name, @{Name="Size (GB)";Expression={ $objitem = (Get-MailboxDatabase $_.Identity); $path = "`\`\" + $objitem.server + "`\" + $objItem.EdbFilePath.DriveName.Remove(1).ToString() + "$" + $objItem.EdbFilePath.PathName.Remove(0,2); $size = ((Get-ChildItem $path).length)/1048576KB; [math]::round($size, 2) }}, @{Name="Size (MB)";Expression={ $objitem = (Get-MailboxDatabase $_.Identity); $path = "`\`\" + $objitem.server + "`\" + $objItem.EdbFilePath.DriveName.Remove(1).ToString() + "$" + $objItem.EdbFilePath.PathName.Remove(0,2); $size = ((Get-ChildItem $path).length)/1024KB; [math]::round($size, 2) }}, @{Name="No. Of Mbx";expression={ (Get-Mailbox -Database $_.Identity | Measure-Object).Count }} | Format-table –AutoSize

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  • How do I stop icons appearing on the desktop in a particular area?

    - by Seamus
    When I download something to my desktop, or insert a CD or flash drive, the icon appears on my desktop. When I have conky running, the icon sometimes appears in the top right corner, underneath conky; where I can't see it. How do I stop this happening? My .conkyrc is pasted below. I didn't write it all myself, so I'm not entirely sure what I need to change, or what parts are relevant for this particular question... # UBUNTU-CONKY # A comprehensive conky script, configured for use on # Ubuntu / Debian Gnome, without the need for any external scripts. # # Based on conky-jc and the default .conkyrc. # INCLUDES: # - tail of /var/log/messages # - netstat shows number of connections from your computer and application/PID making it. Kill spyware! # # -- Pengo # # Create own window instead of using desktop (required in nautilus) own_window yes own_window_type override own_window_transparent yes own_window_hints undecorated,below,sticky,skip_taskbar,skip_pager # Use double buffering (reduces flicker, may not work for everyone) double_buffer yes # fiddle with window use_spacer right # Use Xft? use_xft yes xftfont DejaVu Sans:size=8 xftalpha 0.8 text_buffer_size 2048 # Update interval in seconds update_interval 3.0 # Minimum size of text area # minimum_size 250 5 # Draw shades? draw_shades no # Text stuff draw_outline no # amplifies text if yes draw_borders no uppercase no # set to yes if you want all text to be in uppercase # Stippled borders? stippled_borders 3 # border margins border_margin 9 # border width border_width 10 # Default colors and also border colors, grey90 == #e5e5e5 default_color grey own_window_colour brown own_window_transparent yes # Text alignment, other possible values are commented #alignment top_left alignment top_right #alignment bottom_left #alignment bottom_right # Gap between borders of screen and text gap_x 10 gap_y 20 # stuff after 'TEXT' will be formatted on screen TEXT $color ${color orange}SYSTEM ${hr 2}$color $nodename $sysname $kernel on $machine ${color orange}CPU ${hr 2}$color ${freq}MHz Load: ${loadavg} Temp: ${acpitemp} $cpubar ${cpugraph 000000 ffffff} NAME ${goto 150}PID ${goto 200}CPU% ${goto 250}MEM% ${top name 1} ${goto 150}${top pid 1} ${goto 200}${top cpu 1} ${goto 250}${top mem 1} ${top name 2} ${goto 150}${top pid 2} ${goto 200}${top cpu 2} ${goto 250}${top mem 2} ${top name 3} ${goto 150}${top pid 3} ${goto 200}${top cpu 3} ${goto 250}${top mem 3} ${top name 4} ${goto 150}${top pid 4} ${goto 200}${top cpu 4} ${goto 250}${top mem 4} ${color orange}MEMORY / DISK ${hr 2}$color RAM: $memperc% ${membar 6}$color Swap: $swapperc% ${swapbar 6}$color Home: ${fs_free_perc /home}% ${fs_bar 6 /}$color Free Space: ${fs_free /home} ${color orange}NETWORK (${addr eth0}) ${hr 2}$color Down: $color${downspeed eth0} k/s ${alignr}Up: ${upspeed eth0} k/s ${downspeedgraph eth0 25,140 000000 ff0000} ${alignr}${upspeedgraph eth0 25,140 000000 00ff00}$color Total: ${totaldown eth0} ${alignr}Total: ${totalup eth0} ${execi 30 netstat -ept | grep ESTAB | awk '{print $9}' | cut -d: -f1 | sort | uniq -c | sort -nr} ${color orange}WIRELESS (${addr wlan0}) ${hr 2}$color Down: $color${downspeed wlan0} k/s ${alignr}Up: ${upspeed wlan0} k/s ${downspeedgraph wlan0 25,140 000000 ff0000} ${alignr}${upspeedgraph wlan0 25,140 000000 00ff00}$color Total: ${totaldown wlan0} ${alignr}Total: ${totalup wlan0} ${execi 30 netstat -ept | grep ESTAB | awk '{print $9}' | cut -d: -f1 | sort | uniq -c | sort -nr} Conky solutions have been offered, but perhaps these aren't the best way of approaching it. What I really want is to stop icons even appearing in that part of the desktop window: that is, I want to make part of the desktop real estate "off-limits" to new icons appearing on the desktop.

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  • How do I stop icons appearing on the desktop under conky?

    - by Seamus
    When I download something to my desktop, or insert a CD or flash drive, the icon appears on my desktop. When I have conky running, the icon sometimes appears in the top right corner, underneath conky; where I can't see it. How do I stop this happening? My .conkyrc is pasted below. I didn't write it all myself, so I'm not entirely sure what I need to change, or what parts are relevant for this particular question... # UBUNTU-CONKY # A comprehensive conky script, configured for use on # Ubuntu / Debian Gnome, without the need for any external scripts. # # Based on conky-jc and the default .conkyrc. # INCLUDES: # - tail of /var/log/messages # - netstat shows number of connections from your computer and application/PID making it. Kill spyware! # # -- Pengo # # Create own window instead of using desktop (required in nautilus) own_window yes own_window_type override own_window_transparent yes own_window_hints undecorated,below,sticky,skip_taskbar,skip_pager # Use double buffering (reduces flicker, may not work for everyone) double_buffer yes # fiddle with window use_spacer right # Use Xft? use_xft yes xftfont DejaVu Sans:size=8 xftalpha 0.8 text_buffer_size 2048 # Update interval in seconds update_interval 3.0 # Minimum size of text area # minimum_size 250 5 # Draw shades? draw_shades no # Text stuff draw_outline no # amplifies text if yes draw_borders no uppercase no # set to yes if you want all text to be in uppercase # Stippled borders? stippled_borders 3 # border margins border_margin 9 # border width border_width 10 # Default colors and also border colors, grey90 == #e5e5e5 default_color grey own_window_colour brown own_window_transparent yes # Text alignment, other possible values are commented #alignment top_left alignment top_right #alignment bottom_left #alignment bottom_right # Gap between borders of screen and text gap_x 10 gap_y 20 # stuff after 'TEXT' will be formatted on screen TEXT $color ${color orange}SYSTEM ${hr 2}$color $nodename $sysname $kernel on $machine ${color orange}CPU ${hr 2}$color ${freq}MHz Load: ${loadavg} Temp: ${acpitemp} $cpubar ${cpugraph 000000 ffffff} NAME ${goto 150}PID ${goto 200}CPU% ${goto 250}MEM% ${top name 1} ${goto 150}${top pid 1} ${goto 200}${top cpu 1} ${goto 250}${top mem 1} ${top name 2} ${goto 150}${top pid 2} ${goto 200}${top cpu 2} ${goto 250}${top mem 2} ${top name 3} ${goto 150}${top pid 3} ${goto 200}${top cpu 3} ${goto 250}${top mem 3} ${top name 4} ${goto 150}${top pid 4} ${goto 200}${top cpu 4} ${goto 250}${top mem 4} ${color orange}MEMORY / DISK ${hr 2}$color RAM: $memperc% ${membar 6}$color Swap: $swapperc% ${swapbar 6}$color Home: ${fs_free_perc /home}% ${fs_bar 6 /}$color Free Space: ${fs_free /home} ${color orange}NETWORK (${addr eth0}) ${hr 2}$color Down: $color${downspeed eth0} k/s ${alignr}Up: ${upspeed eth0} k/s ${downspeedgraph eth0 25,140 000000 ff0000} ${alignr}${upspeedgraph eth0 25,140 000000 00ff00}$color Total: ${totaldown eth0} ${alignr}Total: ${totalup eth0} ${execi 30 netstat -ept | grep ESTAB | awk '{print $9}' | cut -d: -f1 | sort | uniq -c | sort -nr} ${color orange}WIRELESS (${addr wlan0}) ${hr 2}$color Down: $color${downspeed wlan0} k/s ${alignr}Up: ${upspeed wlan0} k/s ${downspeedgraph wlan0 25,140 000000 ff0000} ${alignr}${upspeedgraph wlan0 25,140 000000 00ff00}$color Total: ${totaldown wlan0} ${alignr}Total: ${totalup wlan0} ${execi 30 netstat -ept | grep ESTAB | awk '{print $9}' | cut -d: -f1 | sort | uniq -c | sort -nr}

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  • Find directories that DON'T contain a file but YES another one

    - by muixca
    I have quite a large music collection and would like to find the directories in which I still have compressed files (*.rar) unprocessed. Hence looking for a command that lists directories in which i do NOT have *.flac or *.mp3 but YES *.rar present. Working off found examples in this post: Find directories that DON'T contain a file I tried: comm -3 \ <(find ~/Music/ -iname "*.rar" -not -iname "*.flac" -not -iname "*.mp3" -printf '%h\n' | sort -u) \ <(find ~/Music/ -maxdepth 5 -mindepth 2 -type d | sort) \ | sed 's/^.*Music\///' but don' work.

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  • What is a good Amazon S3 client?

    - by Eyal
    I've been using the Amazon S3 Management console to browse my S3 files. Unfortunately, it doesn't seem to be able to sort files (in a given bucket) by anything other than whatever its default is (which seems to be by name). I'd like a nice GUI client for seeing these files which will let me sort them by date, so the newest will appear on top. I did find a Firefox plug-in - S3Fox - but it doesn't work for the current version of Firefox.

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  • Meta package / quick reference for command line string manipulation tools?

    - by Dylan McCall
    The latest version of the Scribes text editor lets us select some text, hit Alt+X, and then run an arbitrary command. For example, I can run the sort command and the selected text is replaced appropriately. This is quite useful but I am also not very well-versed in awk and the like. Is there something I can grab that will provide more of these commands like sort? Maybe a package with a whole bunch of handy, task-specific string manipulation commands?

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  • First steps on setting up a query based server [closed]

    - by asghar ashgari
    I got a physical server at home and I want to do the following silly project to learn the concept behind server-backend development, and then do a real project later on: Idea: Turn the server to a calculator. I want any person publicly send a query to the server (i.e., 2+2) from the terminal and the server give me the result. So the question is basically where to start, what sort of software I need to install, and what sort of program I need to write?.

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  • Quit my job (for a new job). Old job wants me to be available for contracting. Steps to take?

    - by Zak
    The company I am leaving has asked that I make myself available to answer questions and/or debug programs occasionally should the need arise. I'm not opposed to this. After searching google for some king of standard contract for this sort of thing, I didn't see any. Is there a standard contract for this sort of thing that you use? Are there any other steps I should take to ensure this kind of arrangement works smoothly?

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  • How to join two command output

    - by UAdapter
    for example I have command that shows how much space folder takes du folder | sort -n it works great, however I would like to have human readable form du -h folder however if I do that than I cannot sort it as numeric. How to join "du folder" and "du -h folder" to see output sorted as "du folder", but with first column from "du -h folder" P.S. this is just an example. this technique might be very useful for me (if its possible)

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  • Plan Caching and Query Memory Part II (Hash Match) – When not to use stored procedure - Most common performance mistake SQL Server developers make.

    - by sqlworkshops
    SQL Server estimates Memory requirement at compile time, when stored procedure or other plan caching mechanisms like sp_executesql or prepared statement are used, the memory requirement is estimated based on first set of execution parameters. This is a common reason for spill over tempdb and hence poor performance. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union. This article covers Hash Match operations with examples. It is recommended to read Plan Caching and Query Memory Part I before this article which covers an introduction and Query memory for Sort. In most cases it is cheaper to pay for the compilation cost of dynamic queries than huge cost for spill over tempdb, unless memory requirement for a query does not change significantly based on predicates.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   To read additional articles I wrote click here.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script. Most of these concepts are also covered in our webcasts: www.sqlworkshops.com/webcasts  Let’s create a Customer’s State table that has 99% of customers in NY and the rest 1% in WA.Customers table used in Part I of this article is also used here.To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'. --Example provided by www.sqlworkshops.com drop table CustomersState go create table CustomersState (CustomerID int primary key, Address char(200), State char(2)) go insert into CustomersState (CustomerID, Address) select CustomerID, 'Address' from Customers update CustomersState set State = 'NY' where CustomerID % 100 != 1 update CustomersState set State = 'WA' where CustomerID % 100 = 1 go update statistics CustomersState with fullscan go   Let’s create a stored procedure that joins customers with CustomersState table with a predicate on State. --Example provided by www.sqlworkshops.com create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1) end go  Let’s execute the stored procedure first with parameter value ‘WA’ – which will select 1% of data. set statistics time on go --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' goThe stored procedure took 294 ms to complete.  The stored procedure was granted 6704 KB based on 8000 rows being estimated.  The estimated number of rows, 8000 is similar to actual number of rows 8000 and hence the memory estimation should be ok.  There was no Hash Warning in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Now let’s execute the stored procedure with parameter value ‘NY’ – which will select 99% of data. -Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  The stored procedure took 2922 ms to complete.   The stored procedure was granted 6704 KB based on 8000 rows being estimated.    The estimated number of rows, 8000 is way different from the actual number of rows 792000 because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘WA’ in our case. This underestimation will lead to spill over tempdb, resulting in poor performance.   There was Hash Warning (Recursion) in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Let’s recompile the stored procedure and then let’s first execute the stored procedure with parameter value ‘NY’.  In a production instance it is not advisable to use sp_recompile instead one should use DBCC FREEPROCCACHE (plan_handle). This is due to locking issues involved with sp_recompile, refer to our webcasts, www.sqlworkshops.com/webcasts for further details.   exec sp_recompile CustomersByState go --Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  Now the stored procedure took only 1046 ms instead of 2922 ms.   The stored procedure was granted 146752 KB of memory. The estimated number of rows, 792000 is similar to actual number of rows of 792000. Better performance of this stored procedure execution is due to better estimation of memory and avoiding spill over tempdb.   There was no Hash Warning in SQL Profiler.   Now let’s execute the stored procedure with parameter value ‘WA’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go  The stored procedure took 351 ms to complete, higher than the previous execution time of 294 ms.    This stored procedure was granted more memory (146752 KB) than necessary (6704 KB) based on parameter value ‘NY’ for estimation (792000 rows) instead of parameter value ‘WA’ for estimation (8000 rows). This is because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘NY’ in this case. This overestimation leads to poor performance of this Hash Match operation, it might also affect the performance of other concurrently executing queries requiring memory and hence overestimation is not recommended.     The estimated number of rows, 792000 is much more than the actual number of rows of 8000.  Intermediate Summary: This issue can be avoided by not caching the plan for memory allocating queries. Other possibility is to use recompile hint or optimize for hint to allocate memory for predefined data range.Let’s recreate the stored procedure with recompile hint. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, recompile) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 297 ms and 1102 ms in line with previous optimal execution times.   The stored procedure with parameter value ‘WA’ has good estimation like before.   Estimated number of rows of 8000 is similar to actual number of rows of 8000.   The stored procedure with parameter value ‘NY’ also has good estimation and memory grant like before because the stored procedure was recompiled with current set of parameter values.  Estimated number of rows of 792000 is similar to actual number of rows of 792000.    The compilation time and compilation CPU of 1 ms is not expensive in this case compared to the performance benefit.   There was no Hash Warning in SQL Profiler.   Let’s recreate the stored procedure with optimize for hint of ‘NY’. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, optimize for (@State = 'NY')) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 353 ms with parameter value ‘WA’, this is much slower than the optimal execution time of 294 ms we observed previously. This is because of overestimation of memory. The stored procedure with parameter value ‘NY’ has optimal execution time like before.   The stored procedure with parameter value ‘WA’ has overestimation of rows because of optimize for hint value of ‘NY’.   Unlike before, more memory was estimated to this stored procedure based on optimize for hint value ‘NY’.    The stored procedure with parameter value ‘NY’ has good estimation because of optimize for hint value of ‘NY’. Estimated number of rows of 792000 is similar to actual number of rows of 792000.   Optimal amount memory was estimated to this stored procedure based on optimize for hint value ‘NY’.   There was no Hash Warning in SQL Profiler.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   Summary: Cached plan might lead to underestimation or overestimation of memory because the memory is estimated based on first set of execution parameters. It is recommended not to cache the plan if the amount of memory required to execute the stored procedure has a wide range of possibilities. One can mitigate this by using recompile hint, but that will lead to compilation overhead. However, in most cases it might be ok to pay for compilation rather than spilling sort over tempdb which could be very expensive compared to compilation cost. The other possibility is to use optimize for hint, but in case one sorts more data than hinted by optimize for hint, this will still lead to spill. On the other side there is also the possibility of overestimation leading to unnecessary memory issues for other concurrently executing queries. In case of Hash Match operations, this overestimation of memory might lead to poor performance. When the values used in optimize for hint are archived from the database, the estimation will be wrong leading to worst performance, so one has to exercise caution before using optimize for hint, recompile hint is better in this case.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.  Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan

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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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  • Outlook conversation view and categories

    - by Greg Jackson
    At work, I tend to receive a couple of hundred emails a day. To keep from being overwhelmed, I have been using categories to sort and prioritize my mail messages. I auto-assign categories, then group by them: Code Reviews, To, CC, Distribution List/BCC. This means that, for example, a message that's explicitly to me will always show up higher in my inbox than one I get because I'm on a Distribution List. It's a huge time saver and it brings important emails to my attention much more quickly. Recently, the email threads I'm involved in have started to get quite long, and I'd like to be able to use conversation view, or at least sort by subject. Outlook, however, doesn't seem to support any (useful) combination of conversation view and categories. I've tried the following things without success: Grouping by category, then conversation view -- Outlook gives me an error (the grouping/sort combination is too complex). Using a custom view to group by conversation -- category doesn't show up as an option to sort by Grouping by category, then subject -- Getting closer, but the top subject is the first alphabetically, not the most recent Grouping by conversation, then category -- This works, but it doesn't do me much good, because the top conversation is the latest, without regard to what category it belongs to Is there a way for me to retain my category system or something similar while taking advantage of grouping related emails together? I've written Outlook plugins in the past, so even that's not too out there to serve as a proper solution.

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