Search Results

Search found 864 results on 35 pages for 'transformation'.

Page 9/35 | < Previous Page | 5 6 7 8 9 10 11 12 13 14 15 16  | Next Page >

  • Podcast Show Notes: William Ulrich and Neal McWhorter on Business Architecture

    - by Bob Rhubart
    The latest ArchBeat podcast program features a four-part conversation with William Ulrich and Neal McWhorter, the authors of Business Architecture: The Art and Practice of Business Transformation, available from Meghan-Kiffer Press. Listen to Part 1 Bill and Neal cover the basics and discuss the effects of the lack of business architecture on organizations. Listen to Part 2 (Jan 19) What really happens to the billions of dollars annually invested in IT. Listen to Part 3 (Jan 26) Why the IT and business sides of many organizations can’t play nice. Listen to Part 4 (Feb 2) How IT architects and business architects can work together to get the ship back on course and keep it there. Connect William Ulrich Website | LinkedIn | Business Architecture Guild Neal McWhorter Website | LinkedIn | Business Architecture Group on OMG Coming Soon Bob Hensle, Director, Oracle Enterprise Architecture Group, discusses the recently launched IT Solutions from Oracle (ITSO) library of documents. Excerpts from a recent OTN Architect Community Virtual Meet-up. Stay tuned: RSS del.icio.us Tags: business architecture,enterprise architecture,arch2arch,archbeat,podcast,business transformation,oracle,oracle technology network Technorati Tags: business architecture,enterprise architecture,arch2arch,archbeat,podcast,business transformation,oracle,oracle technology network

    Read the article

  • How to maintain encapsulation with composition in C++?

    - by iFreilicht
    I am designing a class Master that is composed from multiple other classes, A, Base, C and D. These four classes have absolutely no use outside of Master and are meant to split up its functionality into manageable and logically divided packages. They also provide extensible functionality as in the case of Base, which can be inherited from by clients. But, how do I maintain encapsulation of Master with this design? So far, I've got two approaches, which are both far from perfect: 1. Replicate all accessors: Just write accessor-methods for all accessor-methods of all classes that Master is composed of. This leads to perfect encapsulation, because no implementation detail of Master is visible, but is extremely tedious and makes the class definition monstrous, which is exactly what the composition should prevent. Also, adding functionality to one of the composees (is that even a word?) would require to re-write all those methods in Master. An additional problem is that inheritors of Base could only alter, but not add functionality. 2. Use non-assignable, non-copyable member-accessors: Having a class accessor<T> that can not be copied, moved or assigned to, but overrides the operator-> to access an underlying shared_ptr, so that calls like Master->A()->niceFunction(); are made possible. My problem with this is that it kind of breaks encapsulation as I would now be unable to change my implementation of Master to use a different class for the functionality of niceFunction(). Still, it is the closest I've gotten without using the ugly first approach. It also fixes the inheritance issue quite nicely. A small side question would be if such a class already existed in std or boost. EDIT: Wall of code I will now post the code of the header files of the classes discussed. It may be a bit hard to understand, but I'll give my best in explaining all of it. 1. GameTree.h The foundation of it all. This basically is a doubly-linked tree, holding GameObject-instances, which we'll later get to. It also has it's own custom iterator GTIterator, but I left that out for brevity. WResult is an enum with the values SUCCESS and FAILED, but it's not really important. class GameTree { public: //Static methods for the root. Only one root is allowed to exist at a time! static void ConstructRoot(seed_type seed, unsigned int depth); inline static bool rootExists(){ return static_cast<bool>(rootObject_); } inline static weak_ptr<GameTree> root(){ return rootObject_; } //delta is in ms, this is used for velocity, collision and such void tick(unsigned int delta); //Interaction with the tree inline weak_ptr<GameTree> parent() const { return parent_; } inline unsigned int numChildren() const{ return static_cast<unsigned int>(children_.size()); } weak_ptr<GameTree> getChild(unsigned int index) const; template<typename GOType> weak_ptr<GameTree> addChild(seed_type seed, unsigned int depth = 9001){ GOType object{ new GOType(seed) }; return addChildObject(unique_ptr<GameTree>(new GameTree(std::move(object), depth))); } WResult moveTo(weak_ptr<GameTree> newParent); WResult erase(); //Iterators for for( : ) loop GTIterator& begin(){ return *(beginIter_ = std::move(make_unique<GTIterator>(children_.begin()))); } GTIterator& end(){ return *(endIter_ = std::move(make_unique<GTIterator>(children_.end()))); } //unloading should be used when objects are far away WResult unloadChildren(unsigned int newDepth = 0); WResult loadChildren(unsigned int newDepth = 1); inline const RenderObject& renderObject() const{ return gameObject_->renderObject(); } //Getter for the underlying GameObject (I have not tested the template version) weak_ptr<GameObject> gameObject(){ return gameObject_; } template<typename GOType> weak_ptr<GOType> gameObject(){ return dynamic_cast<weak_ptr<GOType>>(gameObject_); } weak_ptr<PhysicsObject> physicsObject() { return gameObject_->physicsObject(); } private: GameTree(const GameTree&); //copying is only allowed internally GameTree(shared_ptr<GameObject> object, unsigned int depth = 9001); //pointer to root static shared_ptr<GameTree> rootObject_; //internal management of a child weak_ptr<GameTree> addChildObject(shared_ptr<GameTree>); WResult removeChild(unsigned int index); //private members shared_ptr<GameObject> gameObject_; shared_ptr<GTIterator> beginIter_; shared_ptr<GTIterator> endIter_; //tree stuff vector<shared_ptr<GameTree>> children_; weak_ptr<GameTree> parent_; unsigned int selfIndex_; //used for deletion, this isn't necessary void initChildren(unsigned int depth); //constructs children }; 2. GameObject.h This is a bit hard to grasp, but GameObject basically works like this: When constructing a GameObject, you construct its basic attributes and a CResult-instance, which contains a vector<unique_ptr<Construction>>. The Construction-struct contains all information that is needed to construct a GameObject, which is a seed and a function-object that is applied at construction by a factory. This enables dynamic loading and unloading of GameObjects as done by GameTree. It also means that you have to define that factory if you inherit GameObject. This inheritance is also the reason why GameTree has a template-function gameObject<GOType>. GameObject can contain a RenderObject and a PhysicsObject, which we'll later get to. Anyway, here's the code. class GameObject; typedef unsigned long seed_type; //this declaration magic means that all GameObjectFactorys inherit from GameObjectFactory<GameObject> template<typename GOType> struct GameObjectFactory; template<> struct GameObjectFactory<GameObject>{ virtual unique_ptr<GameObject> construct(seed_type seed) const = 0; }; template<typename GOType> struct GameObjectFactory : GameObjectFactory<GameObject>{ GameObjectFactory() : GameObjectFactory<GameObject>(){} unique_ptr<GameObject> construct(seed_type seed) const{ return unique_ptr<GOType>(new GOType(seed)); } }; //same as with the factories. this is important for storing them in vectors template<typename GOType> struct Construction; template<> struct Construction<GameObject>{ virtual unique_ptr<GameObject> construct() const = 0; }; template<typename GOType> struct Construction : Construction<GameObject>{ Construction(seed_type seed, function<void(GOType*)> func = [](GOType* null){}) : Construction<GameObject>(), seed_(seed), func_(func) {} unique_ptr<GameObject> construct() const{ unique_ptr<GameObject> gameObject{ GOType::factory.construct(seed_) }; func_(dynamic_cast<GOType*>(gameObject.get())); return std::move(gameObject); } seed_type seed_; function<void(GOType*)> func_; }; typedef struct CResult { CResult() : constructions{} {} CResult(CResult && o) : constructions(std::move(o.constructions)) {} CResult& operator= (CResult& other){ if (this != &other){ for (unique_ptr<Construction<GameObject>>& child : other.constructions){ constructions.push_back(std::move(child)); } } return *this; } template<typename GOType> void push_back(seed_type seed, function<void(GOType*)> func = [](GOType* null){}){ constructions.push_back(make_unique<Construction<GOType>>(seed, func)); } vector<unique_ptr<Construction<GameObject>>> constructions; } CResult; //finally, the GameObject class GameObject { public: GameObject(seed_type seed); GameObject(const GameObject&); virtual void tick(unsigned int delta); inline Matrix4f trafoMatrix(){ return physicsObject_->transformationMatrix(); } //getter inline seed_type seed() const{ return seed_; } inline CResult& properties(){ return properties_; } inline const RenderObject& renderObject() const{ return *renderObject_; } inline weak_ptr<PhysicsObject> physicsObject() { return physicsObject_; } protected: virtual CResult construct_(seed_type seed) = 0; CResult properties_; shared_ptr<RenderObject> renderObject_; shared_ptr<PhysicsObject> physicsObject_; seed_type seed_; }; 3. PhysicsObject That's a bit easier. It is responsible for position, velocity and acceleration. It will also handle collisions in the future. It contains three Transformation objects, two of which are optional. I'm not going to include the accessors on the PhysicsObject class because I tried my first approach on it and it's just pure madness (way over 30 functions). Also missing: the named constructors that construct PhysicsObjects with different behaviour. class Transformation{ Vector3f translation_; Vector3f rotation_; Vector3f scaling_; public: Transformation() : translation_{ 0, 0, 0 }, rotation_{ 0, 0, 0 }, scaling_{ 1, 1, 1 } {}; Transformation(Vector3f translation, Vector3f rotation, Vector3f scaling); inline Vector3f translation(){ return translation_; } inline void translation(float x, float y, float z){ translation(Vector3f(x, y, z)); } inline void translation(Vector3f newTranslation){ translation_ = newTranslation; } inline void translate(float x, float y, float z){ translate(Vector3f(x, y, z)); } inline void translate(Vector3f summand){ translation_ += summand; } inline Vector3f rotation(){ return rotation_; } inline void rotation(float pitch, float yaw, float roll){ rotation(Vector3f(pitch, yaw, roll)); } inline void rotation(Vector3f newRotation){ rotation_ = newRotation; } inline void rotate(float pitch, float yaw, float roll){ rotate(Vector3f(pitch, yaw, roll)); } inline void rotate(Vector3f summand){ rotation_ += summand; } inline Vector3f scaling(){ return scaling_; } inline void scaling(float x, float y, float z){ scaling(Vector3f(x, y, z)); } inline void scaling(Vector3f newScaling){ scaling_ = newScaling; } inline void scale(float x, float y, float z){ scale(Vector3f(x, y, z)); } void scale(Vector3f factor){ scaling_(0) *= factor(0); scaling_(1) *= factor(1); scaling_(2) *= factor(2); } Matrix4f matrix(){ return WMatrix::Translation(translation_) * WMatrix::Rotation(rotation_) * WMatrix::Scale(scaling_); } }; class PhysicsObject; typedef void tickFunction(PhysicsObject& self, unsigned int delta); class PhysicsObject{ PhysicsObject(const Transformation& trafo) : transformation_(trafo), transformationVelocity_(nullptr), transformationAcceleration_(nullptr), tick_(nullptr) {} PhysicsObject(PhysicsObject&& other) : transformation_(other.transformation_), transformationVelocity_(std::move(other.transformationVelocity_)), transformationAcceleration_(std::move(other.transformationAcceleration_)), tick_(other.tick_) {} Transformation transformation_; unique_ptr<Transformation> transformationVelocity_; unique_ptr<Transformation> transformationAcceleration_; tickFunction* tick_; public: void tick(unsigned int delta){ tick_ ? tick_(*this, delta) : 0; } inline Matrix4f transformationMatrix(){ return transformation_.matrix(); } } 4. RenderObject RenderObject is a base class for different types of things that could be rendered, i.e. Meshes, Light Sources or Sprites. DISCLAIMER: I did not write this code, I'm working on this project with someone else. class RenderObject { public: RenderObject(float renderDistance); virtual ~RenderObject(); float renderDistance() const { return renderDistance_; } void setRenderDistance(float rD) { renderDistance_ = rD; } protected: float renderDistance_; }; struct NullRenderObject : public RenderObject{ NullRenderObject() : RenderObject(0.f){}; }; class Light : public RenderObject{ public: Light() : RenderObject(30.f){}; }; class Mesh : public RenderObject{ public: Mesh(unsigned int seed) : RenderObject(20.f) { meshID_ = 0; textureID_ = 0; if (seed == 1) meshID_ = Model::getMeshID("EM-208_heavy"); else meshID_ = Model::getMeshID("cube"); }; unsigned int getMeshID() const { return meshID_; } unsigned int getTextureID() const { return textureID_; } private: unsigned int meshID_; unsigned int textureID_; }; I guess this shows my issue quite nicely: You see a few accessors in GameObject which return weak_ptrs to access members of members, but that is not really what I want. Also please keep in mind that this is NOT, by any means, finished or production code! It is merely a prototype and there may be inconsistencies, unnecessary public parts of classes and such.

    Read the article

  • Capturing and Transforming ASP.NET Output with Response.Filter

    - by Rick Strahl
    During one of my Handlers and Modules session at DevConnections this week one of the attendees asked a question that I didn’t have an immediate answer for. Basically he wanted to capture response output completely and then apply some filtering to the output – effectively injecting some additional content into the page AFTER the page had completely rendered. Specifically the output should be captured from anywhere – not just a page and have this code injected into the page. Some time ago I posted some code that allows you to capture ASP.NET Page output by overriding the Render() method, capturing the HtmlTextWriter() and reading its content, modifying the rendered data as text then writing it back out. I’ve actually used this approach on a few occasions and it works fine for ASP.NET pages. But this obviously won’t work outside of the Page class environment and it’s not really generic – you have to create a custom page class in order to handle the output capture. [updated 11/16/2009 – updated ResponseFilterStream implementation and a few additional notes based on comments] Enter Response.Filter However, ASP.NET includes a Response.Filter which can be used – well to filter output. Basically Response.Filter is a stream through which the OutputStream is piped back to the Web Server (indirectly). As content is written into the Response object, the filter stream receives the appropriate Stream commands like Write, Flush and Close as well as read operations although for a Response.Filter that’s uncommon to be hit. The Response.Filter can be programmatically replaced at runtime which allows you to effectively intercept all output generation that runs through ASP.NET. A common Example: Dynamic GZip Encoding A rather common use of Response.Filter hooking up code based, dynamic  GZip compression for requests which is dead simple by applying a GZipStream (or DeflateStream) to Response.Filter. The following generic routines can be used very easily to detect GZip capability of the client and compress response output with a single line of code and a couple of library helper routines: WebUtils.GZipEncodePage(); which is handled with a few lines of reusable code and a couple of static helper methods: /// <summary> ///Sets up the current page or handler to use GZip through a Response.Filter ///IMPORTANT:  ///You have to call this method before any output is generated! /// </summary> public static void GZipEncodePage() {     HttpResponse Response = HttpContext.Current.Response;     if(IsGZipSupported())     {         stringAcceptEncoding = HttpContext.Current.Request.Headers["Accept-Encoding"];         if(AcceptEncoding.Contains("deflate"))         {             Response.Filter = newSystem.IO.Compression.DeflateStream(Response.Filter,                                        System.IO.Compression.CompressionMode.Compress);             Response.AppendHeader("Content-Encoding", "deflate");         }         else        {             Response.Filter = newSystem.IO.Compression.GZipStream(Response.Filter,                                       System.IO.Compression.CompressionMode.Compress);             Response.AppendHeader("Content-Encoding", "gzip");                            }     }     // Allow proxy servers to cache encoded and unencoded versions separately    Response.AppendHeader("Vary", "Content-Encoding"); } /// <summary> /// Determines if GZip is supported /// </summary> /// <returns></returns> public static bool IsGZipSupported() { string AcceptEncoding = HttpContext.Current.Request.Headers["Accept-Encoding"]; if (!string.IsNullOrEmpty(AcceptEncoding) && (AcceptEncoding.Contains("gzip") || AcceptEncoding.Contains("deflate"))) return true; return false; } GZipStream and DeflateStream are streams that are assigned to Response.Filter and by doing so apply the appropriate compression on the active Response. Response.Filter content is chunked So to implement a Response.Filter effectively requires only that you implement a custom stream and handle the Write() method to capture Response output as it’s written. At first blush this seems very simple – you capture the output in Write, transform it and write out the transformed content in one pass. And that indeed works for small amounts of content. But you see, the problem is that output is written in small buffer chunks (a little less than 16k it appears) rather than just a single Write() statement into the stream, which makes perfect sense for ASP.NET to stream data back to IIS in smaller chunks to minimize memory usage en route. Unfortunately this also makes it a more difficult to implement any filtering routines since you don’t directly get access to all of the response content which is problematic especially if those filtering routines require you to look at the ENTIRE response in order to transform or capture the output as is needed for the solution the gentleman in my session asked for. So in order to address this a slightly different approach is required that basically captures all the Write() buffers passed into a cached stream and then making the stream available only when it’s complete and ready to be flushed. As I was thinking about the implementation I also started thinking about the few instances when I’ve used Response.Filter implementations. Each time I had to create a new Stream subclass and create my custom functionality but in the end each implementation did the same thing – capturing output and transforming it. I thought there should be an easier way to do this by creating a re-usable Stream class that can handle stream transformations that are common to Response.Filter implementations. Creating a semi-generic Response Filter Stream Class What I ended up with is a ResponseFilterStream class that provides a handful of Events that allow you to capture and/or transform Response content. The class implements a subclass of Stream and then overrides Write() and Flush() to handle capturing and transformation operations. By exposing events it’s easy to hook up capture or transformation operations via single focused methods. ResponseFilterStream exposes the following events: CaptureStream, CaptureString Captures the output only and provides either a MemoryStream or String with the final page output. Capture is hooked to the Flush() operation of the stream. TransformStream, TransformString Allows you to transform the complete response output with events that receive a MemoryStream or String respectively and can you modify the output then return it back as a return value. The transformed output is then written back out in a single chunk to the response output stream. These events capture all output internally first then write the entire buffer into the response. TransformWrite, TransformWriteString Allows you to transform the Response data as it is written in its original chunk size in the Stream’s Write() method. Unlike TransformStream/TransformString which operate on the complete output, these events only see the current chunk of data written. This is more efficient as there’s no caching involved, but can cause problems due to searched content splitting over multiple chunks. Using this implementation, creating a custom Response.Filter transformation becomes as simple as the following code. To hook up the Response.Filter using the MemoryStream version event: ResponseFilterStream filter = new ResponseFilterStream(Response.Filter); filter.TransformStream += filter_TransformStream; Response.Filter = filter; and the event handler to do the transformation: MemoryStream filter_TransformStream(MemoryStream ms) { Encoding encoding = HttpContext.Current.Response.ContentEncoding; string output = encoding.GetString(ms.ToArray()); output = FixPaths(output); ms = new MemoryStream(output.Length); byte[] buffer = encoding.GetBytes(output); ms.Write(buffer,0,buffer.Length); return ms; } private string FixPaths(string output) { string path = HttpContext.Current.Request.ApplicationPath; // override root path wonkiness if (path == "/") path = ""; output = output.Replace("\"~/", "\"" + path + "/").Replace("'~/", "'" + path + "/"); return output; } The idea of the event handler is that you can do whatever you want to the stream and return back a stream – either the same one that’s been modified or a brand new one – which is then sent back to as the final response. The above code can be simplified even more by using the string version events which handle the stream to string conversions for you: ResponseFilterStream filter = new ResponseFilterStream(Response.Filter); filter.TransformString += filter_TransformString; Response.Filter = filter; and the event handler to do the transformation calling the same FixPaths method shown above: string filter_TransformString(string output) { return FixPaths(output); } The events for capturing output and capturing and transforming chunks work in a very similar way. By using events to handle the transformations ResponseFilterStream becomes a reusable component and we don’t have to create a new stream class or subclass an existing Stream based classed. By the way, the example used here is kind of a cool trick which transforms “~/” expressions inside of the final generated HTML output – even in plain HTML controls not HTML controls – and transforms them into the appropriate application relative path in the same way that ResolveUrl would do. So you can write plain old HTML like this: <a href=”~/default.aspx”>Home</a>  and have it turned into: <a href=”/myVirtual/default.aspx”>Home</a>  without having to use an ASP.NET control like Hyperlink or Image or having to constantly use: <img src=”<%= ResolveUrl(“~/images/home.gif”) %>” /> in MVC applications (which frankly is one of the most annoying things about MVC especially given the path hell that extension-less and endpoint-less URLs impose). I can’t take credit for this idea. While discussing the Response.Filter issues on Twitter a hint from Dylan Beattie who pointed me at one of his examples which does something similar. I thought the idea was cool enough to use an example for future demos of Response.Filter functionality in ASP.NET next I time I do the Modules and Handlers talk (which was great fun BTW). How practical this is is debatable however since there’s definitely some overhead to using a Response.Filter in general and especially on one that caches the output and the re-writes it later. Make sure to test for performance anytime you use Response.Filter hookup and make sure it' doesn’t end up killing perf on you. You’ve been warned :-}. How does ResponseFilterStream work? The big win of this implementation IMHO is that it’s a reusable  component – so for implementation there’s no new class, no subclassing – you simply attach to an event to implement an event handler method with a straight forward signature to retrieve the stream or string you’re interested in. The implementation is based on a subclass of Stream as is required in order to handle the Response.Filter requirements. What’s different than other implementations I’ve seen in various places is that it supports capturing output as a whole to allow retrieving the full response output for capture or modification. The exception are the TransformWrite and TransformWrite events which operate only active chunk of data written by the Response. For captured output, the Write() method captures output into an internal MemoryStream that is cached until writing is complete. So Write() is called when ASP.NET writes to the Response stream, but the filter doesn’t pass on the Write immediately to the filter’s internal stream. The data is cached and only when the Flush() method is called to finalize the Stream’s output do we actually send the cached stream off for transformation (if the events are hooked up) and THEN finally write out the returned content in one big chunk. Here’s the implementation of ResponseFilterStream: /// <summary> /// A semi-generic Stream implementation for Response.Filter with /// an event interface for handling Content transformations via /// Stream or String. /// <remarks> /// Use with care for large output as this implementation copies /// the output into a memory stream and so increases memory usage. /// </remarks> /// </summary> public class ResponseFilterStream : Stream { /// <summary> /// The original stream /// </summary> Stream _stream; /// <summary> /// Current position in the original stream /// </summary> long _position; /// <summary> /// Stream that original content is read into /// and then passed to TransformStream function /// </summary> MemoryStream _cacheStream = new MemoryStream(5000); /// <summary> /// Internal pointer that that keeps track of the size /// of the cacheStream /// </summary> int _cachePointer = 0; /// <summary> /// /// </summary> /// <param name="responseStream"></param> public ResponseFilterStream(Stream responseStream) { _stream = responseStream; } /// <summary> /// Determines whether the stream is captured /// </summary> private bool IsCaptured { get { if (CaptureStream != null || CaptureString != null || TransformStream != null || TransformString != null) return true; return false; } } /// <summary> /// Determines whether the Write method is outputting data immediately /// or delaying output until Flush() is fired. /// </summary> private bool IsOutputDelayed { get { if (TransformStream != null || TransformString != null) return true; return false; } } /// <summary> /// Event that captures Response output and makes it available /// as a MemoryStream instance. Output is captured but won't /// affect Response output. /// </summary> public event Action<MemoryStream> CaptureStream; /// <summary> /// Event that captures Response output and makes it available /// as a string. Output is captured but won't affect Response output. /// </summary> public event Action<string> CaptureString; /// <summary> /// Event that allows you transform the stream as each chunk of /// the output is written in the Write() operation of the stream. /// This means that that it's possible/likely that the input /// buffer will not contain the full response output but only /// one of potentially many chunks. /// /// This event is called as part of the filter stream's Write() /// operation. /// </summary> public event Func<byte[], byte[]> TransformWrite; /// <summary> /// Event that allows you to transform the response stream as /// each chunk of bytep[] output is written during the stream's write /// operation. This means it's possibly/likely that the string /// passed to the handler only contains a portion of the full /// output. Typical buffer chunks are around 16k a piece. /// /// This event is called as part of the stream's Write operation. /// </summary> public event Func<string, string> TransformWriteString; /// <summary> /// This event allows capturing and transformation of the entire /// output stream by caching all write operations and delaying final /// response output until Flush() is called on the stream. /// </summary> public event Func<MemoryStream, MemoryStream> TransformStream; /// <summary> /// Event that can be hooked up to handle Response.Filter /// Transformation. Passed a string that you can modify and /// return back as a return value. The modified content /// will become the final output. /// </summary> public event Func<string, string> TransformString; protected virtual void OnCaptureStream(MemoryStream ms) { if (CaptureStream != null) CaptureStream(ms); } private void OnCaptureStringInternal(MemoryStream ms) { if (CaptureString != null) { string content = HttpContext.Current.Response.ContentEncoding.GetString(ms.ToArray()); OnCaptureString(content); } } protected virtual void OnCaptureString(string output) { if (CaptureString != null) CaptureString(output); } protected virtual byte[] OnTransformWrite(byte[] buffer) { if (TransformWrite != null) return TransformWrite(buffer); return buffer; } private byte[] OnTransformWriteStringInternal(byte[] buffer) { Encoding encoding = HttpContext.Current.Response.ContentEncoding; string output = OnTransformWriteString(encoding.GetString(buffer)); return encoding.GetBytes(output); } private string OnTransformWriteString(string value) { if (TransformWriteString != null) return TransformWriteString(value); return value; } protected virtual MemoryStream OnTransformCompleteStream(MemoryStream ms) { if (TransformStream != null) return TransformStream(ms); return ms; } /// <summary> /// Allows transforming of strings /// /// Note this handler is internal and not meant to be overridden /// as the TransformString Event has to be hooked up in order /// for this handler to even fire to avoid the overhead of string /// conversion on every pass through. /// </summary> /// <param name="responseText"></param> /// <returns></returns> private string OnTransformCompleteString(string responseText) { if (TransformString != null) TransformString(responseText); return responseText; } /// <summary> /// Wrapper method form OnTransformString that handles /// stream to string and vice versa conversions /// </summary> /// <param name="ms"></param> /// <returns></returns> internal MemoryStream OnTransformCompleteStringInternal(MemoryStream ms) { if (TransformString == null) return ms; //string content = ms.GetAsString(); string content = HttpContext.Current.Response.ContentEncoding.GetString(ms.ToArray()); content = TransformString(content); byte[] buffer = HttpContext.Current.Response.ContentEncoding.GetBytes(content); ms = new MemoryStream(); ms.Write(buffer, 0, buffer.Length); //ms.WriteString(content); return ms; } /// <summary> /// /// </summary> public override bool CanRead { get { return true; } } public override bool CanSeek { get { return true; } } /// <summary> /// /// </summary> public override bool CanWrite { get { return true; } } /// <summary> /// /// </summary> public override long Length { get { return 0; } } /// <summary> /// /// </summary> public override long Position { get { return _position; } set { _position = value; } } /// <summary> /// /// </summary> /// <param name="offset"></param> /// <param name="direction"></param> /// <returns></returns> public override long Seek(long offset, System.IO.SeekOrigin direction) { return _stream.Seek(offset, direction); } /// <summary> /// /// </summary> /// <param name="length"></param> public override void SetLength(long length) { _stream.SetLength(length); } /// <summary> /// /// </summary> public override void Close() { _stream.Close(); } /// <summary> /// Override flush by writing out the cached stream data /// </summary> public override void Flush() { if (IsCaptured && _cacheStream.Length > 0) { // Check for transform implementations _cacheStream = OnTransformCompleteStream(_cacheStream); _cacheStream = OnTransformCompleteStringInternal(_cacheStream); OnCaptureStream(_cacheStream); OnCaptureStringInternal(_cacheStream); // write the stream back out if output was delayed if (IsOutputDelayed) _stream.Write(_cacheStream.ToArray(), 0, (int)_cacheStream.Length); // Clear the cache once we've written it out _cacheStream.SetLength(0); } // default flush behavior _stream.Flush(); } /// <summary> /// /// </summary> /// <param name="buffer"></param> /// <param name="offset"></param> /// <param name="count"></param> /// <returns></returns> public override int Read(byte[] buffer, int offset, int count) { return _stream.Read(buffer, offset, count); } /// <summary> /// Overriden to capture output written by ASP.NET and captured /// into a cached stream that is written out later when Flush() /// is called. /// </summary> /// <param name="buffer"></param> /// <param name="offset"></param> /// <param name="count"></param> public override void Write(byte[] buffer, int offset, int count) { if ( IsCaptured ) { // copy to holding buffer only - we'll write out later _cacheStream.Write(buffer, 0, count); _cachePointer += count; } // just transform this buffer if (TransformWrite != null) buffer = OnTransformWrite(buffer); if (TransformWriteString != null) buffer = OnTransformWriteStringInternal(buffer); if (!IsOutputDelayed) _stream.Write(buffer, offset, buffer.Length); } } The key features are the events and corresponding OnXXX methods that handle the event hookups, and the Write() and Flush() methods of the stream implementation. All the rest of the members tend to be plain jane passthrough stream implementation code without much consequence. I do love the way Action<t> and Func<T> make it so easy to create the event signatures for the various events – sweet. A few Things to consider Performance Response.Filter is not great for performance in general as it adds another layer of indirection to the ASP.NET output pipeline, and this implementation in particular adds a memory hit as it basically duplicates the response output into the cached memory stream which is necessary since you may have to look at the entire response. If you have large pages in particular this can cause potentially serious memory pressure in your server application. So be careful of wholesale adoption of this (or other) Response.Filters. Make sure to do some performance testing to ensure it’s not killing your app’s performance. Response.Filter works everywhere A few questions came up in comments and discussion as to capturing ALL output hitting the site and – yes you can definitely do that by assigning a Response.Filter inside of a module. If you do this however you’ll want to be very careful and decide which content you actually want to capture especially in IIS 7 which passes ALL content – including static images/CSS etc. through the ASP.NET pipeline. So it is important to filter only on what you’re looking for – like the page extension or maybe more effectively the Response.ContentType. Response.Filter Chaining Originally I thought that filter chaining doesn’t work at all due to a bug in the stream implementation code. But it’s quite possible to assign multiple filters to the Response.Filter property. So the following actually works to both compress the output and apply the transformed content: WebUtils.GZipEncodePage(); ResponseFilterStream filter = new ResponseFilterStream(Response.Filter); filter.TransformString += filter_TransformString; Response.Filter = filter; However the following does not work resulting in invalid content encoding errors: ResponseFilterStream filter = new ResponseFilterStream(Response.Filter); filter.TransformString += filter_TransformString; Response.Filter = filter; WebUtils.GZipEncodePage(); In other words multiple Response filters can work together but it depends entirely on the implementation whether they can be chained or in which order they can be chained. In this case running the GZip/Deflate stream filters apparently relies on the original content length of the output and chokes when the content is modified. But if attaching the compression first it works fine as unintuitive as that may seem. Resources Download example code Capture Output from ASP.NET Pages © Rick Strahl, West Wind Technologies, 2005-2010Posted in ASP.NET  

    Read the article

  • Oracle Partners Delivering Business Transformations With Oracle WebCenter

    - by Brian Dirking
    This week we’ve been discussing a new online event, “Transform Your Business by Connecting People, Processes, and Content.” This event will include a number of Oracle partners presenting on their successes with transforming their customers by connecting people, processes, and content: Deloitte - Collaboration and Web 2.0 Technologies in Supporting Healthcare, delivered by Mike Matthews, the Canadian Healthcare partner and mandate partner on Canadian Partnership Against Cancer at Deloitte InfoSys - Leverage Enterprise 2.0 and SOA Paradigms in Building the Next Generation Business Platforms, delivered by Rizwan MK, who heads InfoSys' Oracle technology delivery business unit, defining and delivering strategic business and technology solutions to Infosys clients involving Oracle applications Capgemini - Simplifying the workflow process for work order management in the utility market, delivered by Léon Smiers, a Solution Architect for Capgemini. Wipro - Oracle BPM in Banking and Financial Services - Wipro's Technology and Implementation Expertise, delivered by Gopalakrishna Bylahalli, who is responsible for the Transformation Practice in Wipro which includes Business Process Transformation, Application Transformation and Information connect. In Mike Matthews’ session, one thing he will explore is how to CPAC has brought together an informational website and a community. CPAC has implemented Oracle WebCenter, and as part of that implementation, is providing a community where people can make connections and share their stories. This community is part of the CPAC website, which provides information of all types on cancer. This make CPAC a one-stop shop for the most up-to-date information in Canada.

    Read the article

  • Extending an ABCS

    - by jamie.phelps
    All AIA Application Business Connector Services (ABCS) are extension enabled out of the box. The number and location of extension points in each ABCS is dependent upon whether the ABCS is a request-response or fire-and-forget service. Below is an example of a request-reply ABCS with 4 extension call-out points: Pre-transformationPost-transformation, Pre-invokePost-invoke, Pre-transformationPost-transformation, Pre-reply You can also see in the diagram that each XSL Transformation has it's own extension call-out. However for now we are only discussing the ABCS extension call-outs. To extend an ABCS, you'll first need to identify the specific extension points that are available in your ABCS and choose the one or more that you want to implement. You can an get an idea of the extension points available in your ABCS by looking into the AIAConfigurationProperties.xml file found under the AIA_HOME/config directory. Find the for your ABCS and look for properties similar to the following: false false false false Each extension point in the ABCS will have a corresponding configuration property to control whether or not the extension call-out is active at runtime. So these properties can give you some idea of what extension points are available in your ABCS. However, you'll probably also want to look into the ABCS BPEL code itself to confirm the exact location of the call-out.

    Read the article

  • ASP.NET WebAPI Security 3: Extensible Authentication Framework

    - by Your DisplayName here!
    In my last post, I described the identity architecture of ASP.NET Web API. The short version was, that Web API (beta 1) does not really have an authentication system on its own, but inherits the client security context from its host. This is fine in many situations (e.g. AJAX style callbacks with an already established logon session). But there are many cases where you don’t use the containing web application for authentication, but need to do it yourself. Examples of that would be token based authentication and clients that don’t run in the context of the web application (e.g. desktop clients / mobile). Since Web API provides a nice extensibility model, it is easy to implement whatever security framework you want on top of it. My design goals were: Easy to use. Extensible. Claims-based. ..and of course, this should always behave the same, regardless of the hosting environment. In the rest of the post I am outlining some of the bits and pieces, So you know what you are dealing with, in case you want to try the code. At the very heart… is a so called message handler. This is a Web API extensibility point that gets to see (and modify if needed) all incoming and outgoing requests. Handlers run after the conversion from host to Web API, which means that handler code deals with HttpRequestMessage and HttpResponseMessage. See Pedro’s post for more information on the processing pipeline. This handler requires a configuration object for initialization. Currently this is very simple, it contains: Settings for the various authentication and credential types Settings for claims transformation Ability to block identity inheritance from host The most important part here is the credential type support, but I will come back to that later. The logic of the message handler is simple: Look at the incoming request. If the request contains an authorization header, try to authenticate the client. If this is successful, create a claims principal and populate the usual places. If not, return a 401 status code and set the Www-Authenticate header. Look at outgoing response, if the status code is 401, set the Www-Authenticate header. Credential type support Under the covers I use the WIF security token handler infrastructure to validate credentials and to turn security tokens into claims. The idea is simple: an authorization header consists of two pieces: the schema and the actual “token”. My configuration object allows to associate a security token handler with a scheme. This way you only need to implement support for a specific credential type, and map that to the incoming scheme value. The current version supports HTTP Basic Authentication as well as SAML and SWT tokens. (I needed to do some surgery on the standard security token handlers, since WIF does not directly support string-ified tokens. The next version of .NET will fix that, and the code should become simpler then). You can e.g. use this code to hook up a username/password handler to the Basic scheme (the default scheme name for Basic Authentication). config.Handler.AddBasicAuthenticationHandler( (username, password) => username == password); You simply have to provide a password validation function which could of course point back to your existing password library or e.g. membership. The following code maps a token handler for Simple Web Tokens (SWT) to the Bearer scheme (the currently favoured scheme name for OAuth2). You simply have to specify the issuer name, realm and shared signature key: config.Handler.AddSimpleWebTokenHandler(     "Bearer",     http://identity.thinktecture.com/trust,     Constants.Realm,     "Dc9Mpi3jaaaUpBQpa/4R7XtUsa3D/ALSjTVvK8IUZbg="); For certain integration scenarios it is very useful if your Web API can consume SAML tokens. This is also easily accomplishable. The following code uses the standard WIF API to configure the usual SAMLisms like issuer, audience, service certificate and certificate validation. Both SAML 1.1 and 2.0 are supported. var registry = new ConfigurationBasedIssuerNameRegistry(); registry.AddTrustedIssuer( "d1 c5 b1 25 97 d0 36 94 65 1c e2 64 fe 48 06 01 35 f7 bd db", "ADFS"); var adfsConfig = new SecurityTokenHandlerConfiguration(); adfsConfig.AudienceRestriction.AllowedAudienceUris.Add( new Uri(Constants.Realm)); adfsConfig.IssuerNameRegistry = registry; adfsConfig.CertificateValidator = X509CertificateValidator.None; // token decryption (read from configuration section) adfsConfig.ServiceTokenResolver = FederatedAuthentication.ServiceConfiguration.CreateAggregateTokenResolver(); config.Handler.AddSaml11SecurityTokenHandler("SAML", adfsConfig); Claims Transformation After successful authentication, if configured, the standard WIF ClaimsAuthenticationManager is called to run claims transformation and validation logic. This stage is used to transform the “technical” claims from the security token into application claims. You can either have a separate transformation logic, or share on e.g. with the containing web application. That’s just a matter of configuration. Adding the authentication handler to a Web API application In the spirit of Web API this is done in code, e.g. global.asax for web hosting: protected void Application_Start() {     AreaRegistration.RegisterAllAreas();     ConfigureApis(GlobalConfiguration.Configuration);     RegisterGlobalFilters(GlobalFilters.Filters);     RegisterRoutes(RouteTable.Routes);     BundleTable.Bundles.RegisterTemplateBundles(); } private void ConfigureApis(HttpConfiguration configuration) {     configuration.MessageHandlers.Add( new AuthenticationHandler(ConfigureAuthentication())); } private AuthenticationConfiguration ConfigureAuthentication() {     var config = new AuthenticationConfiguration     {         // sample claims transformation for consultants sample, comment out to see raw claims         ClaimsAuthenticationManager = new ApiClaimsTransformer(),         // value of the www-authenticate header, // if not set, the first scheme added to the handler collection is used         DefaultAuthenticationScheme = "Basic"     };     // add token handlers - see above     return config; } You can find the full source code and some samples here. In the next post I will describe some of the samples in the download, and then move on to authorization. HTH

    Read the article

  • Basics of Join Factorization

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

    Read the article

  • Translate report data export from RUEI into HTML for import into OpenOffice Calc Spreadsheets

    - by [email protected]
    A common question of users is, How to import the data from the automated data export of Real User Experience Insight (RUEI) into tools for archiving, dashboarding or combination with other sets of data.XML is well-suited for such a translation via the companion Extensible Stylesheet Language Transformations (XSLT). Basically XSLT utilizes XSL, a template on what to read from your input XML data file and where to place it into the target document. The target document can be anything you like, i.e. XHTML, CSV, or even a OpenOffice Spreadsheet, etc. as long as it is a plain text format.XML 2 OpenOffice.org SpreadsheetFor the XSLT to work as an OpenOffice.org Calc Import Filter:How to add an XML Import Filter to OpenOffice CalcStart OpenOffice.org Calc andselect Tools > XML Filter SettingsNew...Fill in the details as follows:Filter name: RUEI Import filterApplication: OpenOffice.org Calc (.ods)Name of file type: Oracle Real User Experience InsightFile extension: xmlSwitch to the transformation tab and enter/select the following leaving the rest untouchedXSLT for import: ruei_report_data_import_filter.xslPlease see at the end of this blog post for a download of the referenced file.Select RUEI Import filter from list and Test XSLTClick on Browse to selectTransform file: export.php.xmlOpenOffice.org Calc will transform and load the XML file you retrieved from RUEI in a human-readable format.You can now select File > Open... and change the filetype to open your RUEI exports directly in OpenOffice.org Calc, just like any other a native Spreadsheet format.Files of type: Oracle Real User Experience Insight (*.xml)File name: export.php.xml XML 2 XHTMLMost XML-powered browsers provides for inherent XSL Transformation capabilities, you only have to reference the XSLT Stylesheet in the head of your XML file. Then open the file in your favourite Web Browser, Firefox, Opera, Safari or Internet Explorer alike.<?xml version="1.0" encoding="ISO-8859-1"?><!-- inserted line below --> <?xml-stylesheet type="text/xsl" href="ruei_report_data_export_2_xhtml.xsl"?><!-- inserted line above --><report>You can find a patched example export from RUEI plus the above referenced XSL-Stylesheets here: export.php.xml - Example report data export from RUEI ruei_report_data_export_2_xhtml.xsl - RUEI to XHTML XSL Transformation Stylesheetruei_report_data_import_filter.xsl - OpenOffice.org XML import filter for RUEI report export data If you would like to do things like this on the command line you can use either Xalan or xsltproc.The basic command syntax for xsltproc is very simple:xsltproc -o output.file stylesheet.xslt inputfile.xmlYou can use this with the above two stylesheets to translate RUEI Data Exports into XHTML and/or OpenOffice.org Calc ODS-Format. Or you could write your own XSLT to transform into Comma separated Value lists.Please let me know what you think or do with this information in the comments below.Kind regards,Stefan ThiemeReferences used:OpenOffice XML Filter - Create XSLT filters for import and export - http://user.services.openoffice.org/en/forum/viewtopic.php?f=45&t=3490SUN OpenOffice.org XML File Format 1.0 - http://xml.openoffice.org/xml_specification.pdf

    Read the article

  • What's the standard location of a 3D clipping box?

    - by Kendall Frey
    The way I understand 3D rendering, polygons are transformed using several matrices, and they are then clipped if they are not inside a certain box, before projecting the box onto the screen. Before transformation, the visible area is typically a frustum, and after transformation, I am guessing it's a cube. This cube makes the clipping math easier than a frustum would. My question is, what's the 'standard' location/size for this clipping box? I can think of 3 possibilities: (0,0,0)-(1,1,1), (-0.5,-0.5,-0.5)-(0.5,0.5,0.5), (-1,-1,-1)-(1,1,1) Or is there no standard?

    Read the article

  • Three Global Telecoms Soar With Siebel

    - by michael.seback
    Deutsche Telekom Group Selects Oracle's Siebel CRM to Underpin Next-Generation CRM Strategy The Deutsche Telekom Group (DTAG), one of the world's leading telecommunications companies, and a customer of Oracle since 2001, has invested in Oracle's Siebel CRM as the standard platform for its Next Generation CRM strategy; a move to lower the cost of managing its 120 million customers across its European businesses. Oracle's Siebel CRM is planned to be deployed in Germany and all of the company's European business within five years. "...Our Next-Generation strategy is a significant move to lower our operating costs and enhance customer service for all our European customers. Not only is Oracle underpinning this strategy, but is also shaping the way our company operates and sells to customers. We look forward to working with Oracle over the coming years as the technology is extended across Europe," said Dr. Steffen Roehn, CIO Deutsche Telekom AG... "The telecommunications industry is currently undergoing some major changes. As a result, companies like Deutsche Telekom are needing to be more intelligent about the way they use technology, particularly when it comes to customer service. Deutsche Telekom is a great example of how organisations can use CRM to not just improve services, but also drive more commercial opportunities through the ability to offer highly tailored offers, while the customer is engaged online or on the phone," said Steve Fearon, vice president CRM, EMEA Read more. Telecom Argentina S.A. Accelerates Time-to-Market for New Communications Products and Services Telecom Argentina S.A. offers basic telephone, urban landline, and national and international long-distance services...."With Oracle's Siebel CRM and Oracle Communication Billing and Revenue Management, we started a technological transformation that allows us to satisfy our critical business needs, such as improving customer service and quickly launching new phone and internet products and services." - Saba Gooley, Chief Information Officer, Wire Line and Internet Services, Telecom Argentina S.A.Read more. Türk Telekom Develops Benefits-Driven CRM Roadmap Türk Telekom Group provides integrated telecommunication services from public switched telephone network (PSTN) and global systems for mobile communications technology (GSM). to broadband internet...."Oracle Insight provided us with a structured deployment approach that makes sense for our business. It quantified the benefits of the CRM solution allowing us to engage with the relevant business owners; essential for a successful transformation program." - Paul Taylor, VP Commercial Transformation, Türk Telekom Read more.

    Read the article

  • Extending SSIS with custom Data Flow components (Presentation)

    Download the slides and sample code from my Extending SSIS with custom Data Flow components presentation, first presented at the SQLBits II (The SQL) Community Conference. Abstract Get some real-world insights into developing data flow components for SSIS. This starts with an introduction to the data flow pipeline engine, and explains the real differences between adapters and the three sub-types of transformation. Understanding how the different types of component behave and manage data is key to writing components of your own, and probably should but be required knowledge for anyone building packages at all. Using sample code throughout, I will show you how to write components, as well as highlighting best practice and lessons learned. The sample code includes fully working example projects for source, destination and transformation components. Presentation & Samples (358KB) Extending SSIS with custom Data Flow components.zip

    Read the article

  • How to attach two XNA models together?

    - by jeangil
    I go back on unsolved question I asked about attaching two models together, could you give me some help on this ? For example, If I want to attach together Model1 (= Main model) & Model2 ? I have to get the transformation matrix of Model1 and after get the Bone index on Model1 where I want to attach Model2 and then apply some transformation to attach Model2 to Model1 I wrote some code below about this, but It does not work at all !! (6th line of my code seems to be wrong !?) Model1TransfoMatrix=New Matrix[Model1.Bones.Count]; Index=Model1.bone[x].Index; foreach (ModelMesh mesh in Model2.Meshes) { foreach(BasicEffect effect in mesh.effects) { matrix model2Transform = Matrix.CreateScale(0.1.0f)*Matrix.CreateFromYawPitchRoll(x,y,z); effect.World= model2Transform *Model1TransfoMatrix[Index]; effect.view = camera.View; effect.Projection= camera.Projection; } mesh.draw(); }

    Read the article

  • matrix to transform unit cube to space defined by 8 arbitrary points

    - by aadster
    I asked a question relating to similar to this already, but I think this is a clearer objective of what Im trying to achieve.. or whether its possible at all! Im trying to find a transformation (matrix ideally) which would transform the 8 points of a 3d unit cube to 8 arbitrary points in space. The 8 target points have no known structure. e.g: My gut feeling is that a matrix is unable to provide this xform since the cube faces vertices can be concave.. but are there any other methods of transformation? Thanks!

    Read the article

  • The Path to Best-In-Class Service Business Performance

    - by Charles Knapp
    What would it matter to offer your customers best-in-class service and support experiences? According to a new study, best-in-class companies enjoy margins that are nearly double the average, retain almost all of their customers each year, deliver annual revenue growth that is six greater than average, and realize cost decreases rather than increases! What does it take to become best in class? Some of the keys are: Engage customers effectively and consistently across all channels Focus on mobility to improve reactive service performance Continue to transition from primarily reactive to proactive and predictive service performance Build the support structure for new services and service contracts Construct an engaged service delivery team Join the Aberdeen Group, Oracle, Infosys, and Hyundai Capital as we highlight the key stages in the service transformation journey and reveal how Best-in-Class organizations are equipping themselves to thrive in this new era of service. Please join us for "Service Excellence and the Path to Business Transformation" -- this Thursday, October 25, 8:00 AM PDT | 11:00 AM EDT | 3:00 PM GMT | 4:00 PM BST.

    Read the article

  • Recursive calls in Pentaho Data Integration

    - by davek
    Is it possible for a step or transformation in Pentaho Data Integration to call itself, passing the results of the previous call as parameters/variables? My first thought was to create a loop in a transformation, but they don't seem to be allowed...

    Read the article

  • make a 3D spotlight cone matrix

    - by Soubok
    How to create the transformation matrix (4x4) that transforms a cylinder (of height 1 and diameter 1) into a cone that represents my spotlight (position, direction and cutoff angle) ? --edit-- In other words: how to draw the cone that represents my spotlight by drawing a cylinder through a suitable transformation matrix.

    Read the article

  • Linq Aggregate function

    - by Nyla Pareska
    I have a List like "test", "bla", "something", "else" But when I use the Aggrate on it and in the mean time call a function it seems to me that after 2 'iterations' the result of the first gets passed in? I am using it like : myList.Aggregate((current, next) => someMethod(current) + ", "+ someMethod(next)); and while I put a breakpoint in the someMethod function where some transformation on the information in the myList occurs, I notice that after the 3rd call I get a result from a former transformation as input paramter.

    Read the article

  • Transforming OLTP Relational Database to Data Warehousing Model

    - by Russ Cam
    What are the common design approaches taken in loading data from a typical Entity-Relationship OLTP database model into a Kimball star schema Data Warehouse/Marts model? Do you use a staging area to perform the transformation and then load into the warehouse? How do you link data between the warehouse and the OLTP database? Where/How do you manage the transformation process - in the database as sprocs, dts/ssis packages, or SQL from application code?

    Read the article

  • Enterprise Process Maps: A Process Picture worth a Million Words

    - by raul.goycoolea
    p { margin-bottom: 0.08in; }h1 { margin-top: 0.33in; margin-bottom: 0in; color: rgb(54, 95, 145); page-break-inside: avoid; }h1.western { font-family: "Cambria",serif; font-size: 14pt; }h1.cjk { font-family: "DejaVu Sans"; font-size: 14pt; }h1.ctl { font-size: 14pt; } Getting Started with Business Transformations A well-known proverb states that "A picture is worth a thousand words." In relation to Business Process Management (BPM), a credible analyst might have a few questions. What if the picture was taken from some particular angle, like directly overhead? What if it was taken from only an inch away or a mile away? What if the photographer did not focus the camera correctly? Does the value of the picture depend on who is looking at it? Enterprise Process Maps are analogous in this sense of relative value. Every BPM project (holistic BPM kick-off, enterprise system implementation, Service-oriented Architecture, business process transformation, corporate performance management, etc.) should be begin with a clear understanding of the business environment, from the biggest picture representations down to the lowest level required or desired for the particular project type, scope and objectives. The Enterprise Process Map serves as an entry point for the process architecture and is defined: the single highest level of process mapping for an organization. It is constructed and evaluated during the Strategy Phase of the Business Process Management Lifecycle. (see Figure 1) Fig. 1: Business Process Management Lifecycle Many organizations view such maps as visual abstractions, constructed for the single purpose of process categorization. This, in turn, results in a lesser focus on the inherent intricacies of the Enterprise Process view, which are explored in the course of this paper. With the main focus of a large scale process documentation effort usually underlying an ERP or other system implementation, it is common for the work to be driven by the desire to "get to the details," and to the type of modeling that will derive near-term tangible results. For instance, a project in American Pharmaceutical Company X is driven by the Director of IT. With 120+ systems in place, and a lack of standardized processes across the United States, he and the VP of IT have decided to embark on a long-term ERP implementation. At the forethought of both are questions, such as: How does my application architecture map to the business? What are each application's functionalities, and where do the business processes utilize them? Where can we retire legacy systems? Well-developed BPM methodologies prescribe numerous model types to capture such information and allow for thorough analysis in these areas. Process to application maps, Event Driven Process Chains, etc. provide this level of detail and facilitate the completion of such project-specific questions. These models and such analysis are appropriately carried out at a relatively low level of process detail. (see figure 2) Fig. 2: The Level Concept, Generic Process HierarchySome of the questions remaining are ones of documentation longevity, the continuation of BPM practice in the organization, process governance and ownership, process transparency and clarity in business process objectives and strategy. The Level Concept in Brief Figure 2 shows a generic, four-level process hierarchy depicting the breakdown of a "Process Area" into progressively more detailed process classifications. The number of levels and the names of these levels are flexible, and can be fit to the standards of the organization's chosen terminology or any other chosen reference model that makes logical sense for both short and long term process description. It is at Level 1 (in this case the Process Area level), that the Enterprise Process Map is created. This map and its contained objects become the foundation for a top-down approach to subsequent mapping, object relationship development, and analysis of the organization's processes and its supporting infrastructure. Additionally, this picture serves as a communication device, at an executive level, describing the design of the business in its service to a customer. It seems, then, imperative that the process development effort, and this map, start off on the right foot. Figuring out just what that right foot is, however, is critical and trend-setting in an evolving organization. Key Considerations Enterprise Process Maps are usually not as living and breathing as other process maps. Just as it would be an extremely difficult task to change the foundation of the Sears Tower or a city plan for the entire city of Chicago, the Enterprise Process view of an organization usually remains unchanged once developed (unless, of course, an organization is at a stage where it is capable of true, high-level process innovation). Regardless, the Enterprise Process map is a key first step, and one that must be taken in a precise way. What makes this groundwork solid depends on not only the materials used to construct it (process areas), but also the layout plan and knowledge base of what will be built (the entire process architecture). It seems reasonable that care and consideration are required to create this critical high level map... but what are the important factors? Does the process modeler need to worry about how many process areas there are? About who is looking at it? Should he only use the color pink because it's his boss' favorite color? Interestingly, and perhaps surprisingly, these are all valid considerations that may just require a bit of structure. Below are Three Key Factors to consider when building an Enterprise Process Map: Company Strategic Focus Process Categorization: Customer is Core End-to-end versus Functional Processes Company Strategic Focus As mentioned above, the Enterprise Process Map is created during the Strategy Phase of the Business Process Management Lifecycle. From Oracle Business Process Management methodology for business transformation, it is apparent that business processes exist for the purpose of achieving the strategic objectives of an organization. In a prescribed, top-down approach to process development, it must be ensured that each process fulfills its objectives, and in an aggregated manner, drives fulfillment of the strategic objectives of the company, whether for particular business segments or in a broader sense. This is a crucial point, as the strategic messages of the company must therefore resound in its process maps, in particular one that spans the processes of the complete business: the Enterprise Process Map. One simple example from Company X is shown below (see figure 3). Fig. 3: Company X Enterprise Process Map In reviewing Company X's Enterprise Process Map, one can immediately begin to understand the general strategic mindset of the organization. It shows that Company X is focused on its customers, defining 10 of its process areas belonging to customer-focused categories. Additionally, the organization views these end-customer-oriented process areas as part of customer-fulfilling value chains, while support process areas do not provide as much contiguous value. However, by including both support and strategic process categorizations, it becomes apparent that all processes are considered vital to the success of the customer-oriented focus processes. Below is an example from Company Y (see figure 4). Fig. 4: Company Y Enterprise Process Map Company Y, although also a customer-oriented company, sends a differently focused message with its depiction of the Enterprise Process Map. Along the top of the map is the company's product tree, overarching the process areas, which when executed deliver the products themselves. This indicates one strategic objective of excellence in product quality. Additionally, the view represents a less linear value chain, with strong overlaps of the various process areas. Marketing and quality management are seen as a key support processes, as they span the process lifecycle. Often, companies may incorporate graphics, logos and symbols representing customers and suppliers, and other objects to truly send the strategic message to the business. Other times, Enterprise Process Maps may show high level of responsibility to organizational units, or the application types that support the process areas. It is possible that hundreds of formats and focuses can be applied to an Enterprise Process Map. What is of vital importance, however, is which formats and focuses are chosen to truly represent the direction of the company, and serve as a driver for focusing the business on the strategic objectives set forth in that right. Process Categorization: Customer is Core In the previous two examples, processes were grouped using differing categories and techniques. Company X showed one support and three customer process categorizations using encompassing chevron objects; Customer Y achieved a less distinct categorization using a gradual color scheme. Either way, and in general, modeling of the process areas becomes even more valuable and easily understood within the context of business categorization, be it strategic or otherwise. But how one categorizes their processes is typically more complex than simply choosing object shapes and colors. Previously, it was stated that the ideal is a prescribed top-down approach to developing processes, to make certain linkages all the way back up to corporate strategy. But what about external influences? What forces push and pull corporate strategy? Industry maturity, product lifecycle, market profitability, competition, etc. can all drive the critical success factors of a particular business segment, or the company as a whole, in addition to previous corporate strategy. This may seem to be turning into a discussion of theory, but that is far from the case. In fact, in years of recent study and evolution of the way businesses operate, cross-industry and across the globe, one invariable has surfaced with such strength to make it undeniable in the game plan of any strategy fit for survival. That constant is the customer. Many of a company's critical success factors, in any business segment, relate to the customer: customer retention, satisfaction, loyalty, etc. Businesses serve customers, and so do a business's processes, mapped or unmapped. The most effective way to categorize processes is in a manner that visualizes convergence to what is core for a company. It is the value chain, beginning with the customer in mind, and ending with the fulfillment of that customer, that becomes the core or the centerpiece of the Enterprise Process Map. (See figure 5) Fig. 5: Company Z Enterprise Process Map Company Z has what may be viewed as several different perspectives or "cuts" baked into their Enterprise Process Map. It has divided its processes into three main categories (top, middle, and bottom) of Management Processes, the Core Value Chain and Supporting Processes. The Core category begins with Corporate Marketing (which contains the activities of beginning to engage customers) and ends with Customer Service Management. Within the value chain, this company has divided into the focus areas of their two primary business lines, Foods and Beverages. Does this mean that areas, such as Strategy, Information Management or Project Management are not as important as those in the Core category? No! In some cases, though, depending on the organization's understanding of high-level BPM concepts, use of category names, such as "Core," "Management" or "Support," can be a touchy subject. What is important to understand, is that no matter the nomenclature chosen, the Core processes are those that drive directly to customer value, Support processes are those which make the Core processes possible to execute, and Management Processes are those which steer and influence the Core. Some common terms for these three basic categorizations are Core, Customer Fulfillment, Customer Relationship Management, Governing, Controlling, Enabling, Support, etc. End-to-end versus Functional Processes Every high and low level of process: function, task, activity, process/work step (whatever an organization calls it), should add value to the flow of business in an organization. Suppose that within the process "Deliver package," there is a documented task titled "Stop for ice cream." It doesn't take a process expert to deduce the room for improvement. Though stopping for ice cream may create gain for the one person performing it, it likely benefits neither the organization nor, more importantly, the customer. In most cases, "Stop for ice cream" wouldn't make it past the first pass of To-Be process development. What would make the cut, however, would be a flow of tasks that, each having their own value add, build up to greater and greater levels of process objective. In this case, those tasks would combine to achieve a status of "package delivered." Figure 3 shows a simple example: Just as the package can only be delivered (outcome of the process) without first being retrieved, loaded, and the travel destination reached (outcomes of the process steps), some higher level of process "Play Practical Joke" (e.g., main process or process area) cannot be completed until a package is delivered. It seems that isolated or functionally separated processes, such as "Deliver Package" (shown in Figure 6), are necessary, but are always part of a bigger value chain. Each of these individual processes must be analyzed within the context of that value chain in order to ensure successful end-to-end process performance. For example, this company's "Create Joke Package" process could be operating flawlessly and efficiently, but if a joke is never developed, it cannot be created, so the end-to-end process breaks. Fig. 6: End to End Process Construction That being recognized, it is clear that processes must be viewed as end-to-end, customer-to-customer, and in the context of company strategy. But as can also be seen from the previous example, these vital end-to-end processes cannot be built without the functionally oriented building blocks. Without one, the other cannot be had, or at least not in a complete and organized fashion. As it turns out, but not discussed in depth here, the process modeling effort, BPM organizational development, and comprehensive coverage cannot be fully realized without a semi-functional, process-oriented approach. Then, an Enterprise Process Map should be concerned with both views, the building blocks, and access points to the business-critical end-to-end processes, which they construct. Without the functional building blocks, all streams of work needed for any business transformation would be lost mess of process disorganization. End-to-end views are essential for utilization in optimization in context, understanding customer impacts, base-lining all project phases and aligning objectives. Including both views on an Enterprise Process Map allows management to understand the functional orientation of the company's processes, while still providing access to end-to-end processes, which are most valuable to them. (See figures 7 and 8). Fig. 7: Simplified Enterprise Process Map with end-to-end Access Point The above examples show two unique ways to achieve a successful Enterprise Process Map. The first example is a simple map that shows a high level set of process areas and a separate section with the end-to-end processes of concern for the organization. This particular map is filtered to show just one vital end-to-end process for a project-specific focus. Fig. 8: Detailed Enterprise Process Map showing connected Functional Processes The second example shows a more complex arrangement and categorization of functional processes (the names of each process area has been removed). The end-to-end perspective is achieved at this level through the connections (interfaces at lower levels) between these functional process areas. An important point to note is that the organization of these two views of the Enterprise Process Map is dependent, in large part, on the orientation of its audience, and the complexity of the landscape at the highest level. If both are not apparent, the Enterprise Process Map is missing an opportunity to serve as a holistic, high-level view. Conclusion In the world of BPM, and specifically regarding Enterprise Process Maps, a picture can be worth as many words as the thought and effort that is put into it. Enterprise Process Maps alone cannot change an organization, but they serve more purposes than initially meet the eye, and therefore must be designed in a way that enables a BPM mindset, business process understanding and business transformation efforts. Every Enterprise Process Map will and should be different when looking across organizations. Its design will be driven by company strategy, a level of customer focus, and functional versus end-to-end orientations. This high-level description of the considerations of the Enterprise Process Maps is not a prescriptive "how to" guide. However, a company attempting to create one may not have the practical BPM experience to truly explore its options or impacts to the coming work of business process transformation. The biggest takeaway is that process modeling, at all levels, is a science and an art, and art is open to interpretation. It is critical that the modeler of the highest level of process mapping be a cognoscente of the message he is delivering and the factors at hand. Without sufficient focus on the design of the Enterprise Process Map, an entire BPM effort may suffer. For additional information please check: Oracle Business Process Management.

    Read the article

  • The blocking nature of aggregates

    - by Rob Farley
    I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

    Read the article

  • The blocking nature of aggregates

    - by Rob Farley
    I wrote a post recently about how query tuning isn’t just about how quickly the query runs – that if you have something (such as SSIS) that is consuming your data (and probably introducing a bottleneck), then it might be more important to have a query which focuses on getting the first bit of data out. You can read that post here.  In particular, we looked at two operators that could be used to ensure that a query returns only Distinct rows. and The Sort operator pulls in all the data, sorts it (discarding duplicates), and then pushes out the remaining rows. The Hash Match operator performs a Hashing function on each row as it comes in, and then looks to see if it’s created a Hash it’s seen before. If not, it pushes the row out. The Sort method is quicker, but has to wait until it’s gathered all the data before it can do the sort, and therefore blocks the data flow. But that was my last post. This one’s a bit different. This post is going to look at how Aggregate functions work, which ties nicely into this month’s T-SQL Tuesday. I’ve frequently explained about the fact that DISTINCT and GROUP BY are essentially the same function, although DISTINCT is the poorer cousin because you have less control over it, and you can’t apply aggregate functions. Just like the operators used for Distinct, there are different flavours of Aggregate operators – coming in blocking and non-blocking varieties. The example I like to use to explain this is a pile of playing cards. If I’m handed a pile of cards and asked to count how many cards there are in each suit, it’s going to help if the cards are already ordered. Suppose I’m playing a game of Bridge, I can easily glance at my hand and count how many there are in each suit, because I keep the pile of cards in order. Moving from left to right, I could tell you I have four Hearts in my hand, even before I’ve got to the end. By telling you that I have four Hearts as soon as I know, I demonstrate the principle of a non-blocking operation. This is known as a Stream Aggregate operation. It requires input which is sorted by whichever columns the grouping is on, and it will release a row as soon as the group changes – when I encounter a Spade, I know I don’t have any more Hearts in my hand. Alternatively, if the pile of cards are not sorted, I won’t know how many Hearts I have until I’ve looked through all the cards. In fact, to count them, I basically need to put them into little piles, and when I’ve finished making all those piles, I can count how many there are in each. Because I don’t know any of the final numbers until I’ve seen all the cards, this is blocking. This performs the aggregate function using a Hash Match. Observant readers will remember this from my Distinct example. You might remember that my earlier Hash Match operation – used for Distinct Flow – wasn’t blocking. But this one is. They’re essentially doing a similar operation, applying a Hash function to some data and seeing if the set of values have been seen before, but before, it needs more information than the mere existence of a new set of values, it needs to consider how many of them there are. A lot is dependent here on whether the data coming out of the source is sorted or not, and this is largely determined by the indexes that are being used. If you look in the Properties of an Index Scan, you’ll be able to see whether the order of the data is required by the plan. A property called Ordered will demonstrate this. In this particular example, the second plan is significantly faster, but is dependent on having ordered data. In fact, if I force a Stream Aggregate on unordered data (which I’m doing by telling it to use a different index), a Sort operation is needed, which makes my plan a lot slower. This is all very straight-forward stuff, and information that most people are fully aware of. I’m sure you’ve all read my good friend Paul White (@sql_kiwi)’s post on how the Query Optimizer chooses which type of aggregate function to apply. But let’s take a look at SQL Server Integration Services. SSIS gives us a Aggregate transformation for use in Data Flow Tasks, but it’s described as Blocking. The definitive article on Performance Tuning SSIS uses Sort and Aggregate as examples of Blocking Transformations. I’ve just shown you that Aggregate operations used by the Query Optimizer are not always blocking, but that the SSIS Aggregate component is an example of a blocking transformation. But is it always the case? After all, there are plenty of SSIS Performance Tuning talks out there that describe the value of sorted data in Data Flow Tasks, describing the IsSorted property that can be set through the Advanced Editor of your Source component. And so I set about testing the Aggregate transformation in SSIS, to prove for sure whether providing Sorted data would let the Aggregate transform behave like a Stream Aggregate. (Of course, I knew the answer already, but it helps to be able to demonstrate these things). A query that will produce a million rows in order was in order. Let me rephrase. I used a query which produced the numbers from 1 to 1000000, in a single field, ordered. The IsSorted flag was set on the source output, with the only column as SortKey 1. Performing an Aggregate function over this (counting the number of rows per distinct number) should produce an additional column with 1 in it. If this were being done in T-SQL, the ordered data would allow a Stream Aggregate to be used. In fact, if the Query Optimizer saw that the field had a Unique Index on it, it would be able to skip the Aggregate function completely, and just insert the value 1. This is a shortcut I wouldn’t be expecting from SSIS, but certainly the Stream behaviour would be nice. Unfortunately, it’s not the case. As you can see from the screenshots above, the data is pouring into the Aggregate function, and not being released until all million rows have been seen. It’s not doing a Stream Aggregate at all. This is expected behaviour. (I put that in bold, because I want you to realise this.) An SSIS transformation is a piece of code that runs. It’s a physical operation. When you write T-SQL and ask for an aggregation to be done, it’s a logical operation. The physical operation is either a Stream Aggregate or a Hash Match. In SSIS, you’re telling the system that you want a generic Aggregation, that will have to work with whatever data is passed in. I’m not saying that it wouldn’t be possible to make a sometimes-blocking aggregation component in SSIS. A Custom Component could be created which could detect whether the SortKeys columns of the input matched the Grouping columns of the Aggregation, and either call the blocking code or the non-blocking code as appropriate. One day I’ll make one of those, and publish it on my blog. I’ve done it before with a Script Component, but as Script components are single-use, I was able to handle the data knowing everything about my data flow already. As per my previous post – there are a lot of aspects in which tuning SSIS and tuning execution plans use similar concepts. In both situations, it really helps to have a feel for what’s going on behind the scenes. Considering whether an operation is blocking or not is extremely relevant to performance, and that it’s not always obvious from the surface. In a future post, I’ll show the impact of blocking v non-blocking and synchronous v asynchronous components in SSIS, using some of LobsterPot’s Script Components and Custom Components as examples. When I get that sorted, I’ll make a Stream Aggregate component available for download.

    Read the article

  • SQL SERVER – SSIS Look Up Component – Cache Mode – Notes from the Field #028

    - by Pinal Dave
    [Notes from Pinal]: Lots of people think that SSIS is all about arranging various operations together in one logical flow. Well, the understanding is absolutely correct, but the implementation of the same is not as easy as it seems. Similarly most of the people think lookup component is just component which does look up for additional information and does not pay much attention to it. Due to the same reason they do not pay attention to the same and eventually get very bad performance. Linchpin People are database coaches and wellness experts for a data driven world. In this 28th episode of the Notes from the Fields series database expert Tim Mitchell (partner at Linchpin People) shares very interesting conversation related to how to write a good lookup component with Cache Mode. In SQL Server Integration Services, the lookup component is one of the most frequently used tools for data validation and completion.  The lookup component is provided as a means to virtually join one set of data to another to validate and/or retrieve missing values.  Properly configured, it is reliable and reasonably fast. Among the many settings available on the lookup component, one of the most critical is the cache mode.  This selection will determine whether and how the distinct lookup values are cached during package execution.  It is critical to know how cache modes affect the result of the lookup and the performance of the package, as choosing the wrong setting can lead to poorly performing packages, and in some cases, incorrect results. Full Cache The full cache mode setting is the default cache mode selection in the SSIS lookup transformation.  Like the name implies, full cache mode will cause the lookup transformation to retrieve and store in SSIS cache the entire set of data from the specified lookup location.  As a result, the data flow in which the lookup transformation resides will not start processing any data buffers until all of the rows from the lookup query have been cached in SSIS. The most commonly used cache mode is the full cache setting, and for good reason.  The full cache setting has the most practical applications, and should be considered the go-to cache setting when dealing with an untested set of data. With a moderately sized set of reference data, a lookup transformation using full cache mode usually performs well.  Full cache mode does not require multiple round trips to the database, since the entire reference result set is cached prior to data flow execution. There are a few potential gotchas to be aware of when using full cache mode.  First, you can see some performance issues – memory pressure in particular – when using full cache mode against large sets of reference data.  If the table you use for the lookup is very large (either deep or wide, or perhaps both), there’s going to be a performance cost associated with retrieving and caching all of that data.  Also, keep in mind that when doing a lookup on character data, full cache mode will always do a case-sensitive (and in some cases, space-sensitive) string comparison even if your database is set to a case-insensitive collation.  This is because the in-memory lookup uses a .NET string comparison (which is case- and space-sensitive) as opposed to a database string comparison (which may be case sensitive, depending on collation).  There’s a relatively easy workaround in which you can use the UPPER() or LOWER() function in the pipeline data and the reference data to ensure that case differences do not impact the success of your lookup operation.  Again, neither of these present a reason to avoid full cache mode, but should be used to determine whether full cache mode should be used in a given situation. Full cache mode is ideally useful when one or all of the following conditions exist: The size of the reference data set is small to moderately sized The size of the pipeline data set (the data you are comparing to the lookup table) is large, is unknown at design time, or is unpredictable Each distinct key value(s) in the pipeline data set is expected to be found multiple times in that set of data Partial Cache When using the partial cache setting, lookup values will still be cached, but only as each distinct value is encountered in the data flow.  Initially, each distinct value will be retrieved individually from the specified source, and then cached.  To be clear, this is a row-by-row lookup for each distinct key value(s). This is a less frequently used cache setting because it addresses a narrower set of scenarios.  Because each distinct key value(s) combination requires a relational round trip to the lookup source, performance can be an issue, especially with a large pipeline data set to be compared to the lookup data set.  If you have, for example, a million records from your pipeline data source, you have the potential for doing a million lookup queries against your lookup data source (depending on the number of distinct values in the key column(s)).  Therefore, one has to be keenly aware of the expected row count and value distribution of the pipeline data to safely use partial cache mode. Using partial cache mode is ideally suited for the conditions below: The size of the data in the pipeline (more specifically, the number of distinct key column) is relatively small The size of the lookup data is too large to effectively store in cache The lookup source is well indexed to allow for fast retrieval of row-by-row values No Cache As you might guess, selecting no cache mode will not add any values to the lookup cache in SSIS.  As a result, every single row in the pipeline data set will require a query against the lookup source.  Since no data is cached, it is possible to save a small amount of overhead in SSIS memory in cases where key values are not reused.  In the real world, I don’t see a lot of use of the no cache setting, but I can imagine some edge cases where it might be useful. As such, it’s critical to know your data before choosing this option.  Obviously, performance will be an issue with anything other than small sets of data, as the no cache setting requires row-by-row processing of all of the data in the pipeline. I would recommend considering the no cache mode only when all of the below conditions are true: The reference data set is too large to reasonably be loaded into SSIS memory The pipeline data set is small and is not expected to grow There are expected to be very few or no duplicates of the key values(s) in the pipeline data set (i.e., there would be no benefit from caching these values) Conclusion The cache mode, an often-overlooked setting on the SSIS lookup component, represents an important design decision in your SSIS data flow.  Choosing the right lookup cache mode directly impacts the fidelity of your results and the performance of package execution.  Know how this selection impacts your ETL loads, and you’ll end up with more reliable, faster packages. If you want me to take a look at your server and its settings, or if your server is facing any issue we can Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: SSIS

    Read the article

< Previous Page | 5 6 7 8 9 10 11 12 13 14 15 16  | Next Page >