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  • VBoxManage modifyhd --resize doesn't exist?

    - by George Korac
    I'm trying to increase the size of a VirtualBox Win7 .vdi disk on Ubuntu 10.04 but when I try executing VBoxManage modifyhd /path/disk.vdi --resize 15360 it returns Syntax error: unknown option: --resize. I'm unsure as to why this is happening because I've used it before and it's still listed under valid options for VBoxManage modifyhd in the VirualBox User Manual . Cheers, George @maniat1k george@george-laptop:~$ VBoxManage modifyhd '/home/george/.VirtualBox/HardDisks/Windows 7 64bit.vdi' --resize 15360 Sun VirtualBox Command Line Management Interface Version 3.1.6_OSE (C) 2005-2010 Sun Microsystems, Inc. All rights reserved. Usage: VBoxManage modifyhd | [--type normal|writethrough|immutable] [--autoreset on|off] [--compact] Syntax error: unknown option: --resize

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  • Objective C style nil in java?

    - by Usman Ismail
    Objective C has a concept of a nil object which would accept any method call with any parameters without complaining and silently return another nil. I have used something similar in Java using easymock and mockito for testing. Is there something similar for main line code? Is it even a good idea to have something like this? One use-case where I am considering using it is with optional metrics. We have codahale metrics counters on which we call mark() every time an event is generated. This is surrounded by an If/then to check for metrics enabled flag. I could just use a nil object as counter and silently accept the mark call if metrics are not enabled.

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  • Oracle WebLogic Server 12c Launch Event - Dec 1, 2011, 10am PT

    - by arungupta
    Calling all IT managers, architects, and developers, to find out how the new release of Oracle WebLogic Server 12c is: Designed to help you seamlessly move into the public or private cloud with an open, standards-based platform Built to drive higher value for your current infrastructure and significantly reduce development time and cost Optimized to run your solutions for Java Platform, Enterprise Edition (Java EE); Oracle Fusion Middleware; and Oracle Fusion Enhanced with transformational platforms and technologies such as Java EE 6, Oracle’s Active GridLink for RAC, Oracle Traffic Director, and Oracle Virtual Assembly Builder When ? Dec 1, 2011, 10am - 12pm PT Where ? Register online! Here are some other links for you to follow: blogs.oracle.com/weblogicserver @OracleWebLogic youtube.com/OracleWebLogic facebook.com/OracleWebLogic Steve Button's Blog Jeff West's Blog WebLogic Forums WebLogic @ OTN Almost ready to unwrap the ribbons, pop open the cork, at the start line ... or whatever fits your analogy :-) And in case you are wondering ... here is a snapshot of WebLogic 12c administration console snapshot:

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  • Visual Studio 2012 - Express vs Professional

    - by Dan
    I'm having trouble finding a feature comparison between Visual Studio 2012 express edition and the professional edition. I'm using the trial Profession version at the moment, but it'll run out soon, so I need to make a decision whether to purchase the full version. Obviously I can just try both initially and see if the express edition is suitable, but the problem is that there are that many features in Visual Studio, there might be a really useful feature that was missing in the standard edition that I didn't even know existed! Or I didn't spot was missing until later down the line. I could really do with a feature comparison list like the one for all non-express editions here. It's a shame that page doesn't include the express edition. (as a side note, there doesn't seem to be a visual-studio-2012 tag, so I had to just use visual-studio. Could someone with enough rep to create tags add a visual-studio-2012 tag?)

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  • Oracle WebCenter: uma nova vis&atilde;o para os Portais

    - by Denisd
    O conceito de “Portal” existe há muito tempo, mas está sempre mudando. Afinal de contas, o que é um portal? Nos primórdios da internet, o termo “portal” era utilizado para sites que guardavam muitas páginas (ou seja, muita informação). “Portal de notícias” era um termo comum, embora estes “portais” não passassem de um conjunto de páginas estáticas, que basicamente serviam conteúdo aos usuários. Com a evolução da tecnologia, os web sites passaram a ficar mais dinâmicos, permitindo uma interação maior do usuário. Sites de comunidades sociais são o melhor exemplo disso. Neste momento, o “portal” passou a ser não apenas um grupo de páginas, mas um conjunto de serviços e recursos dinâmicos, como a possibilidade de publicar fotos e vídeos, e compartilhar este conteúdo com amigos on-line. Aqui temos o que podemos chamar de “Portais Sociais”. Ao mesmo tempo, dentro das empresas, outra mudança estava acontecendo: a criação de padrões de comunicação entre aplicativos, sendo o mais famoso destes padrões a tecnologia de Web Services. Com estes padrões, as aplicações podem trocar informações e facilitar a experiência dos usuários. Desta forma, é possível desenvolver mini-aplicativos (chamados “portlets”), que publicam informações dos sistemas corporativos nas páginas dos portais internos. Estes portlets permitem interações com os sistemas, para permitir que os usuários tenham acesso rápido e fácil às informações. Podemos chamar estes portais de “Portais Transacionais”. Aqui temos 2 pontos que eu gostaria de chamar a atenção: 1 – O desenvolvimento de portlets é necessário porque eu não consigo publicar uma aplicação inteira no portal, normalmente por uma questão de padrões de desenvolvimento. Explicando de uma forma simples, a aplicação não foi feita para rodar dentro de um portal. Portanto, é necessário desenvolvimento adicional para criar mini-aplicativos que replicam (ou melhor, duplicam) a lógica do aplicativo principal, dentro do portal. 2 – Os aplicativos corporativos normalmente não incluem os recursos colaborativos de um portal (por exemplo, fóruns de discussão, lista de contatos com sensores de presença on-line, wikis, tags, etc), simplesmente porque este tipo de recurso normalmente não está disponível de forma “empacotada” para ser utilizada em um aplicativo. Desta forma, se eu quiser que a minha aplicação tenha um fórum de discussão para que os meus clientes conversem com a minha equipe técnica, eu tenho que desenvolver todo o motor do fórum de discussão dentro do meu aplicativo, o que se torna inviável, devido ao custo, tempo e ao fato de que este tipo de recurso normalmente não está no escopo da minha aplicação. O que acaba acontecendo é que os usuários fazem a parte “transacional” dentro do aplicativo, mas acabam utilizando outras interfaces para atender suas demandas de colaboração (neste caso, utilizariam um fórum fora da aplicação para discutir problemas referentes ao aplicativo). O Oracle WebCenter 11g vem para resolver estes dois pontos citados acima. O WebCenter não é simplesmente um novo portal, com alguns recursos interessantes; ele é uma nova forma de se pensar em Portais Corporativos (portais que reúnem os cenários citados acima: conteúdo, social e transacional). O WebCenter 11g é extenso demais para ser descrito em um único post, e nem é a minha intenção entrar no detalhe deste produto agora. Mas podemos definir o WebCenter 11g como sendo 3 “coisas”: - Um framework de desenvolvimento, aonde os recursos que as minhas aplicações irão utilizar (por exemplo, validação de crédito, consulta à estoque, registro de um pedido, etc), são desenvolvidos de forma a serem reutilizados por qualquer outra aplicação ou portlet que seja executado neste framework. Este tipo de componente reutilizável é chamado de “Task Flow”. - Um conjunto de serviços voltados à colaboração, como fóruns, wikis, blogs, tags, links, people connections, busca, bibliotecas de documentos, etc. Todos estes recursos colaborativos também estão disponíveis como Task Flows, desta forma, qualquer aplicação que eu desenvolva pode se beneficiar destes recursos. - Um “Portal”, do ponto de vista tradicional, aonde os usuários podem criar páginas, inserir e compartilhar conteúdo com outros usuários. Este Portal consegue utilizar os recursos desenvolvidos no Framework, garantindo o reuso. A imagem abaixo traz uma visão deste Portal. Clique para ver em tamanho maior. A grande inovação que o WebCenter traz é que a divisão entre “portal” e “aplicação” desaparece: qualquer aplicação agora pode ser desenvolvida com recursos de portal. O meu sistema de CRM, por exemplo, pode ter um fórum de discussão para os clientes. O meu sistema de suporte pode utilizar Wikis para montar FAQs de forma rápida. O sistema financeiro pode incluir uma biblioteca de documentos para que o usuário possa consultar os manuais de procedimento. Portanto, não importa se eu estou desenvolvendo uma “aplicação” ou um “portal”; o que importa é que os meus usuários agora terão em uma única interface as funcionalidades dos aplicativos e os recursos de colaboração. Este conceito, dentro da Oracle, é chamado de “Composite Applications”, e é a base para a próxima geração dos aplicativos Oracle. Nos próximos posts iremos falar (é claro) sobre como o WebCenter e o UCM se relacionam, e que tipo de recursos podem ser aproveitados nas aplicações/portais. Até breve!

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  • The Evolution Of C#

    - by Paulo Morgado
    The first release of C# (C# 1.0) was all about building a new language for managed code that appealed, mostly, to C++ and Java programmers. The second release (C# 2.0) was mostly about adding what wasn’t time to built into the 1.0 release. The main feature for this release was Generics. The third release (C# 3.0) was all about reducing the impedance mismatch between general purpose programming languages and databases. To achieve this goal, several functional programming features were added to the language and LINQ was born. Going forward, new trends are showing up in the industry and modern programming languages need to be more: Declarative With imperative languages, although having the eye on the what, programs need to focus on the how. This leads to over specification of the solution to the problem in hand, making next to impossible to the execution engine to be smart about the execution of the program and optimize it to run it more efficiently (given the hardware available, for example). Declarative languages, on the other hand, focus only on the what and leave the how to the execution engine. LINQ made C# more declarative by using higher level constructs like orderby and group by that give the execution engine a much better chance of optimizing the execution (by parallelizing it, for example). Concurrent Concurrency is hard and needs to be thought about and it’s very hard to shoehorn it into a programming language. Parallel.For (from the parallel extensions) looks like a parallel for because enough expressiveness has been built into C# 3.0 to allow this without having to commit to specific language syntax. Dynamic There was been lots of debate on which ones are the better programming languages: static or dynamic. The fact is that both have good qualities and users of both types of languages want to have it all. All these trends require a paradigm switch. C# is, in many ways, already a multi-paradigm language. It’s still very object oriented (class oriented as some might say) but it can be argued that C# 3.0 has become a functional programming language because it has all the cornerstones of what a functional programming language needs. Moving forward, will have even more. Besides the influence of these trends, there was a decision of co-evolution of the C# and Visual Basic programming languages. Since its inception, there was been some effort to position C# and Visual Basic against each other and to try to explain what should be done with each language or what kind of programmers use one or the other. Each language should be chosen based on the past experience and familiarity of the developer/team/project/company and not by particular features. In the past, every time a feature was added to one language, the users of the other wanted that feature too. Going forward, when a feature is added to one language, the other will work hard to add the same feature. This doesn’t mean that XML literals will be added to C# (because almost the same can be achieved with LINQ To XML), but Visual Basic will have auto-implemented properties. Most of these features require or are built on top of features of the .NET Framework and, the focus for C# 4.0 was on dynamic programming. Not just dynamic types but being able to talk with anything that isn’t a .NET class. Also introduced in C# 4.0 is co-variance and contra-variance for generic interfaces and delegates. Stay tuned for more on the new C# 4.0 features.

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  • links for 2010-04-01

    - by Bob Rhubart
    Jason Williamson: Oracle Releases New Mainframe Re-Hosting in Oracle Tuxedo 11g Jason Williamson's update on new features in the latest release of Oracle Tuxedo 11g. (tags: otn oracle entarch) Jeanne Waldman: Using Oracle ADF Data Visualization Tools (DVT) Line Graphs to Display Weather Information Jeanne Waldman illustrates the nuts and bolts of modifications she made to a a simple JDeveloper Fusion application that retrieves weather data. I have a simple JDeveloper Fusion application that retrieves weather data. (tags: oracle otn virtualization jdeveloper ADF) Brian Harrison: Oracle WebCenter Interaction - New Release Overivew, Part 2 Brian Harrison continue his discussion of the next release of Oracle WebCenter Interaction with a look at at a few other new features. (tags: oracle otn enterprise2.0 webcenter)

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  • The Hunger Games for Aspiring IT Professionals

    - by Dain C. Hansen
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} It seems that no one can escape the buzz around Hunger Games. And who could? Stephen King said it best in his review when he referred to the Collins’ novel as “a violent, jarring speed-rap of a novel that generates nearly constant suspense and may also generate a fair amount of controversy”. So what’s the tie in for IT? Let’s leave the dystopia of District 12 and come back to today’s reality. This is the world of radical IT paradigm shifts that haven’t been seen since Java was introduced in 1995. Everything you learned in school is probably outdated as of Friday. And everything you learned on Friday will probably change when you get to work on Monday. Nevertheless, we’re eager, we’re aspiring, we’re hungry to learn. While the challenges upon us may not rival the venomous bees (or ‘tracker jackers’) seen in this blockbuster, there are certainly obstacles to be found. In preparation, I leave you two pieces of advice - aside from avoiding werewolves… Learn the Cloud If you had asked me what to learn in 1995, I would have said, “Go learn Java”. But now my advice is “Go learn Java and then learn Cloud”. Cloud computing and Java go hand in hand. This is especially true for Oracle’s own Public Cloud which uses Java (via WebLogic 12c) as well as Oracle Database at its core foundation. Understanding the connotations of elasticity, scale, virtualization, and multi-tenancy, (to name just a few) requires a strong foundation in computer science and especially Java to get it right. Without Java, the Cloud is nothing more than a brittle application meagerly deployed on the internet. Get Social and Actively Participate And at all levels. Socializing your ideas internally is dreadfully important. And this means socializing and communicating your good ideas to lines of business, to architects, business analysts, developers, DBAs and Operations. But don’t forget to go external. Stay current by being on the lookout for blogs, tweets, webcasts, papers, podcasts and videos for your technology area. Be not just a subscriber but a participant in these channels as well. Attend industry and vendor sponsored events to learn from the experts – and seek out opportunities to stay connected with those that are smarter than you. You’ll gain more understanding if you participate actively. At the same time you’ll make friends (and allies) and you’ll be glad you did. Tell help you get social and actively participate [while learning the Cloud] here are a couple of pointers for you: See our website on Cloud and Fusion Middleware Subscribe to our regular Fusion Middleware Newsletter Follow us on Twitter and Facebook Find us at one of our key events Meanwhile, happy IT hunger games!

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  • Powershell STA watin

    - by Mike Koerner
    Wow, two posts on the same day. I was working on a quick DLL project to do some web scripting using the awsome power of Watin.  In the past I use to create a vbscript as the test handler to call the DLL but lately I got a Powershell bug to call .NET DLLs. When I tried to debug the Watin call I received: The CurrentThread needs to have it's ApartmentState set to ApartmentState.STA to be able to automate Internet Explorer. I couldn't find a quick google answer to powershell apartmentstate .  Apparently you can set the powershell apartment state by the command line -STA.  http://technet.microsoft.com/en-us/library/dd315276.aspx I've found that the powershell documentation and examples is lacking compared to the Microsoft support I've come to expect.  Why is the Powershell v2.0 in C:\WINDOWS\SYSTEM32\windowspowershell\v1.0 ?

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  • Rotate Body From Corner

    - by Siddharth
    I want to ask that how to rotate body from corner? movableBeam.getBeamBody().setTransform(movableBeam.getBeamBody().getPosition(), angle); The above line of code rotate the beam from center that I want rotate from one of the conner. Any member please help me. EDIT : float beamCenterX = movableBeam.getX() + movableBeam.getWidth() / 2f; float beamCenterY = movableBeam.getY() + movableBeam.getHeight() / 2f; float cornerOffsetX = movableBeam.getX() - beamCenterX; float cornerOffsetY = movableBeam.getY() - beamCenterY; float bodyAngle = (float) Math.atan2(cornerOffsetY, cornerOffsetX); float newAngle = imageAngle + bodyAngle; float newCornerOffsetX = (float) Math.cos(Math .toDegrees(newAngle)); float newCornerOffsetY = (float) Math.sin(Math .toDegrees(newAngle)); cornerOffsetX = movableBeam.getX() - movableBeam.getWidth() / 2f; cornerOffsetY = movableBeam.getY() - movableBeam.getHeight() / 2f; Vector2 postion = new Vector2( (newCornerOffsetX - cornerOffsetX + movableBeam.getX()) / PhysicsConstants.PIXEL_TO_METER_RATIO_DEFAULT, (newCornerOffsetY - cornerOffsetY + movableBeam.getY()) / PhysicsConstants.PIXEL_TO_METER_RATIO_DEFAULT); movableBeam.getBeamBody().setTransform(postion, newAngle);

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  • Class Loading Deadlocks

    - by tomas.nilsson
    Mattis follows up on his previous post with one more expose on Class Loading Deadlocks As I wrote in a previous post, the class loading mechanism in Java is very powerful. There are many advanced techniques you can use, and when used wrongly you can get into all sorts of trouble. But one of the sneakiest deadlocks you can run into when it comes to class loading doesn't require any home made class loaders or anything. All you need is classes depending on each other, and some bad luck. First of all, here are some basic facts about class loading: 1) If a thread needs to use a class that is not yet loaded, it will try to load that class 2) If another thread is already loading the class, the first thread will wait for the other thread to finish the loading 3) During the loading of a class, one thing that happens is that the <clinit method of a class is being run 4) The <clinit method initializes all static fields, and runs any static blocks in the class. Take the following class for example: class Foo { static Bar bar = new Bar(); static { System.out.println("Loading Foo"); } } The first time a thread needs to use the Foo class, the class will be initialized. The <clinit method will run, creating a new Bar object and printing "Loading Foo" But what happens if the Bar object has never been used before either? Well, then we will need to load that class as well, calling the Bar <clinit method as we go. Can you start to see the potential problem here? A hint is in fact #2 above. What if another thread is currently loading class Bar? The thread loading class Foo will have to wait for that thread to finish loading. But what happens if the <clinit method of class Bar tries to initialize a Foo object? That thread will have to wait for the first thread, and there we have the deadlock. Thread one is waiting for thread two to initialize class Bar, thread two is waiting for thread one to initialize class Foo. All that is needed for a class loading deadlock is static cross dependencies between two classes (and a multi threaded environment): class Foo { static Bar b = new Bar(); } class Bar { static Foo f = new Foo(); } If two threads cause these classes to be loaded at exactly the same time, we will have a deadlock. So, how do you avoid this? Well, one way is of course to not have these circular (static) dependencies. On the other hand, it can be very hard to detect these, and sometimes your design may depend on it. What you can do in that case is to make sure that the classes are first loaded single threadedly, for example during an initialization phase of your application. The following program shows this kind of deadlock. To help bad luck on the way, I added a one second sleep in the static block of the classes to trigger the unlucky timing. Notice that if you uncomment the "//Foo f = new Foo();" line in the main method, the class will be loaded single threadedly, and the program will terminate as it should. public class ClassLoadingDeadlock { // Start two threads. The first will instansiate a Foo object, // the second one will instansiate a Bar object. public static void main(String[] arg) { // Uncomment next line to stop the deadlock // Foo f = new Foo(); new Thread(new FooUser()).start(); new Thread(new BarUser()).start(); } } class FooUser implements Runnable { public void run() { System.out.println("FooUser causing class Foo to be loaded"); Foo f = new Foo(); System.out.println("FooUser done"); } } class BarUser implements Runnable { public void run() { System.out.println("BarUser causing class Bar to be loaded"); Bar b = new Bar(); System.out.println("BarUser done"); } } class Foo { static { // We are deadlock prone even without this sleep... // The sleep just makes us more deterministic try { Thread.sleep(1000); } catch(InterruptedException e) {} } static Bar b = new Bar(); } class Bar { static { try { Thread.sleep(1000); } catch(InterruptedException e) {} } static Foo f = new Foo(); }

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  • Bitwise operators in DX9 ps_2_0 shader

    - by lapin
    I've got the following code in a shader: // v & y are both floats nPixel = v; nPixel << 8; nPixel |= y; and this gives me the following error in compilation: shader.fx(80,10): error X3535: Bitwise operations not supported on legacy targets. shader.fx(92,18): ID3DXEffectCompiler::CompileEffect: There was an error compiling expression ID3DXEffectCompiler: Compilation failed The error is on the following line: nPixel |= y; What am I doing wrong here?

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  • Transitioning from Oracle based CMS to MySQL based CMS

    - by KM01
    We're looking at a replacement for our CMS which runs on Oracle. The new CMSes that we've looked at can in theory run on Oracle, but most of the vendor's installs run off of MySQL vendor supports install of their CMS on MySQL, and a "theoretical" install on Oracle the vendor's dev shops use MySQL none of them develop/test against Oracle Our DBA team works exclusively with Oracle, and doesn't have the bandwidth to provide additional support for a highly available and performing MySQL setup. They could in theory go to training and get ramped up, but our time line is also short (surprise!). So ... I guess my question(s) are: If you've seen a situation like this, how have you dealt with it? What tipped the balance either way? What type of effort did it take? If you're to do it over, what would you do differently ... ? Thanks! KM

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  • Improve the Quality of ePub eBooks with Sigil

    - by Matthew Guay
    Would you like to correct errors in your ePub formatted eBooks, or even split them into chapters and create a Table of Contents?  Here’s how you can with the free program Sigil. eBooks are increasingly popular with the rise of eBook readers and reading apps on mobile devices.  We recently showed you how to convert a PDF eBook to ePub format, but as you may have noticed, sometimes the converted file had some glitches or odd formatting.  Additionally, many of the many free ePub books available online from sources like the Project Guttenberg do not include a table of contents.  Sigil is a free application for Windows, OS X, and Linux that lets you edit ePub files, so let’s look at how you can use it to improve your eBooks. Note: Sigil took several moments to open files in our tests, and froze momentarily when we maximized the window.  Sigil is currently pre-release software in active development, so we would expect the bugs to be worked out in future versions.  As usual, only install if you’re comfortable testing pre-release software. Getting Started Download Sigil (link below), making sure to select the correct version for your computer.  Run the installer, and select your preferred setup language when prompted. After a moment the installer will appear; setup as normal. Launch Sigil when it’s finished installing.  It opens with a default blank ePub file, so you could actually start writing an eBook from scratch right here. Edit Your ePub eBooks Now you’re ready to edit your ePub books.  Click Open and browse to the file you want to edit. Now you can double-click any of the HTML or XHTML files on the left sidebar and edit them just like you would in Word. Or you can choose to view it in Code View and edit the actual HTML directly. The sidebar also gives you access to the other parts of the ePub file, such as Images and CSS styles. If your ePub file has a Table of Contents, you can edit it with Sigil as well.  Click Tools in the menu bar, and then select TOC Editor.  Strangely there is no way to create a new table of contents, but you can remove entries from existing one.   Convert TXT Files to ePub Many free eBooks online, especially older, out of copyright titles, are available in plain text format.  One problem with these files is that they usually use hard returns at the end of lines, so they don’t reflow to fill your screen efficiently. Sigil can easily convert these files to the more useful ePub format.  Open the text file in Sigil, and it will automatically reflow the text and convert it ePub.  As you can see in the screenshot below, the text in the eBook does not have hard line-breaks at the end of each line, and will be much more readable on mobile devices. Note that Sigil may take several moments opening the book, and may even become unresponsive while analyzing it.   Now you can edit your eBook, split it into chapters, or just save it as is.  Either way, make sure to select Save as to save your book as ePub format. Conclusion As mentioned before, Sigil seems to run slow at times, especially when editing large eBooks.  But it’s still a nice solution to edit and extend your ePub eBooks, and even convert plain text eBooks to the nicer ePub format.  Now you can make your eBooks work just like you want, and read them on your favorite device! If you feel comfortable editing HTML files, check out our article on how to edit ePub eBooks with your favorite HTML editor. Link Download Sigil from Google Code Download free ePub eBooks from Project Guttenberg Similar Articles Productive Geek Tips Edit ePub eBooks with Your Favorite HTML EditorConvert a PDF eBook to ePub Format for Your iPad, iPhone, or eReaderRead Mobi eBooks on Kindle for PCFriday Fun: Watch HD Video Content with MeevidPreview and Purchase Ebooks with Kindle for PC TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips HippoRemote Pro 2.2 Xobni Plus for Outlook All My Movies 5.9 CloudBerry Online Backup 1.5 for Windows Home Server Get Your Team’s World Cup Schedule In Google Calendar Backup Drivers With Driver Magician TubeSort: YouTube Playlist Organizer XPS file format & XPS Viewer Explained Microsoft Office Web Apps Guide Know if Someone Accessed Your Facebook Account

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  • Functional programming constructs in non-functional programming languages

    - by Giorgio
    This question has been going through my mind quite a lot lately and since I haven't found a convincing answer to it I would like to know if other users of this site have thought about it as well. In the recent years, even though OOP is still the most popular programming paradigm, functional programming is getting a lot of attention. I have only used OOP languages for my work (C++ and Java) but I am trying to learn some FP in my free time because I find it very interesting. So, I started learning Haskell three years ago and Scala last summer. I plan to learn some SML and Caml as well, and to brush up my (little) knowledge of Scheme. Well, a lot of plans (too ambitious?) but I hope I will find the time to learn at least the basics of FP during the next few years. What is important for me is how functional programming works and how / whether I can use it for some real projects. I have already developed small tools in Haskell. In spite of my strong interest for FP, I find it difficult to understand why functional programming constructs are being added to languages like C#, Java, C++, and so on. As a developer interested in FP, I find it more natural to use, say, Scala or Haskell, instead of waiting for the next FP feature to be added to my favourite non-FP language. In other words, why would I want to have only some FP in my originally non-FP language instead of looking for a language that has a better support for FP? For example, why should I be interested to have lambdas in Java if I can switch to Scala where I have much more FP concepts and access all the Java libraries anyway? Similarly: why do some FP in C# instead of using F# (to my knowledge, C# and F# can work together)? Java was designed to be OO. Fine. I can do OOP in Java (and I would like to keep using Java in that way). Scala was designed to support OOP + FP. Fine: I can use a mix of OOP and FP in Scala. Haskell was designed for FP: I can do FP in Haskell. If I need to tune the performance of a particular module, I can interface Haskell with some external routines in C. But why would I want to do OOP with just some basic FP in Java? So, my main point is: why are non-functional programming languages being extended with some functional concept? Shouldn't it be more comfortable (interesting, exciting, productive) to program in a language that has been designed from the very beginning to be functional or multi-paradigm? Don't different programming paradigms integrate better in a language that was designed for it than in a language in which one paradigm was only added later? The first explanation I could think of is that, since FP is a new concept (it isn't new at all, but it is new for many developers), it needs to be introduced gradually. However, I remember my switch from imperative to OOP: when I started to program in C++ (coming from Pascal and C) I really had to rethink the way in which I was coding, and to do it pretty fast. It was not gradual. So, this does not seem to be a good explanation to me. Also, I asked myself if my impression is just plainly wrong due to lack of knowledge. E.g., do C# and C++11 support FP as extensively as, say, Scala or Caml do? In this case, my question would be simply non-existent. Or can it be that many non-FP programmers are not really interested in using functional programming, but they find it practically convenient to adopt certain FP-idioms in their non-FP language? IMPORTANT NOTE Just in case (because I have seen several language wars on this site): I mentioned the languages I know better, this question is in no way meant to start comparisons between different programming languages to decide which is better / worse. Also, I am not interested in a comparison of OOP versus FP (pros and cons). The point I am interested in is to understand why FP is being introduced one bit at a time into existing languages that were not designed for it even though there exist languages that were / are specifically designed to support FP.

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  • Configure EnableTransaction and IsolationLevel property in Business Rules for Dynamic Send Port

    - by Vishal
    Why do you want to add these properties to the BRE..??                 There is a lot of performance issue when using WCF adapters with Dynamic Send Port. Please check the below link for more info.   http://blogs.msdn.com/mdoctor/archive/2009/12/18/performance-tip-when-using-wcf-custom-with-dynamic-send-ports-and-custom-bindings-on-biztalk-server-2009.aspx?CommentPosted=true#commentmessage     So if you are using ESB Toolkit 2.0 in your solution and you do not want to move towards static adapte then you can add the below line in your SetEndpointConfig value for BRE.                 BindingType=xyzAdapterBinding&EnableTransaction=true&IsolationLevel=ReadCommited&BindingConfiguration=<bindingname=”xyzAdapterBinding" />   The IsolationLevel values can be: Serializable RepeatableRead ReadCommited ReadUncommited Snapshot Chaos   Below are few Business Rules Composer Screenshots.

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  • Intel Xeon 5600 (Westmere-EP) and AMD Magny-Cours Performance Update

    - by jchang
    HP has just released TPC-C and TPC-E results for the ProLiant DL380G7 with 2 Xeon 5680 3.33GHz 6-core processor, allowing a direct comparison with their DL385G& with 2 Opteron 6176 2.3GHz 12-core processors. Last month I complained about the lack of performance results for the Intel Xeon 5600 6-core 32nm processor line for 2-way systems. This might have been deliberate to not complicate the message for the Xeon 7500 8-core 45nm (for 4-way+ systems) launch two weeks later. http://sqlblog.com/blogs/joe_chang/archive/2010/04/07/intel-xeon-5600-westmere-ep-and-7500-nehalem-ex.aspx...(read more)

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  • wpa_supplicant ioctl[SIOCSIWENCODEEXT]: Invalid argument

    - by RobinJ
    I just installed Ubuntu Server on a spare computer with a broken graphic card, and I needed to setup my wifi. I thought No problem, I've done it before from the command line, in Arch Linux., only the steps I had to take in Arch Linux didn't work in Ubuntu Server (that's odd, wasn't Ubuntu supposed to be so much more user-friendly? :/). This is what I'd normally do: ip link set wlan0 up wpa_passphrase <ESSID> <WPA KEY> > /etc/wpa_supplicant.conf wpa_supplicant -B -Dwext -i wlan0 -c /etc/wpa_supplicant.conf dhcpcd wlan0 Only at the wpa_supplicant I get some strane message: ioctl[SIOCSIWENCODEEXT]: Invalid argument ioctl[SIOCSIWENCODEEXT]: Invalid argument And if I try to run dhcpcd then (which I manually installed, as it didn't come preinstalled with Ubuntu Server), it times out. Help on how to do it would be much appreciated. My wireless driver is iwl3945.

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  • MySQL is running VERY slow

    - by user1032531
    I have two servers: a VPS and a laptop. I recently re-built both of them, and MySQL is running about 20 times slower on the laptop. Both servers used to run CentOS 5.8 and I think MySQL 5.1, and the laptop used to do great so I do not think it is the hardware. For the VPS, my provider installed CentOS 6.4, and then I installed MySQL 5.1.69 using yum with the CentOS repo. For the laptop, I installed CentOS 6.4 basic server and then installed MySQL 5.1.69 using yum with the CentOS repo. my.cnf for both servers are identical, and I have shown below. For both servers, I've also included below the output from SHOW VARIABLES; as well as output from sysbench, file system information, and cpu information. I have tried adding skip-name-resolve, but it didn't help. The matrix below shows the SHOW VARIABLES output from both servers which is different. Again, MySQL was installed the same way, so I do not know why it is different, but it is and I think this might be why the laptop is executing MySQL so slowly. Why is the laptop running MySQL slowly, and how do I fix it? Differences between SHOW VARIABLES on both servers +---------------------------+-----------------------+-------------------------+ | Variable | Value-VPS | Value-Laptop | +---------------------------+-----------------------+-------------------------+ | hostname | vps.site1.com | laptop.site2.com | | max_binlog_cache_size | 4294963200 | 18446744073709500000 | | max_seeks_for_key | 4294967295 | 18446744073709500000 | | max_write_lock_count | 4294967295 | 18446744073709500000 | | myisam_max_sort_file_size | 2146435072 | 9223372036853720000 | | myisam_mmap_size | 4294967295 | 18446744073709500000 | | plugin_dir | /usr/lib/mysql/plugin | /usr/lib64/mysql/plugin | | pseudo_thread_id | 7568 | 2 | | system_time_zone | EST | PDT | | thread_stack | 196608 | 262144 | | timestamp | 1372252112 | 1372252046 | | version_compile_machine | i386 | x86_64 | +---------------------------+-----------------------+-------------------------+ my.cnf for both servers [root@server1 ~]# cat /etc/my.cnf [mysqld] datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql # Disabling symbolic-links is recommended to prevent assorted security risks symbolic-links=0 [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid innodb_strict_mode=on sql_mode=TRADITIONAL # sql_mode=STRICT_TRANS_TABLES,NO_ZERO_DATE,NO_ZERO_IN_DATE character-set-server=utf8 collation-server=utf8_general_ci log=/var/log/mysqld_all.log [root@server1 ~]# VPS SHOW VARIABLES Info Same as Laptop shown below but changes per above matrix (removed to allow me to be under the 30000 characters as required by ServerFault) Laptop SHOW VARIABLES Info auto_increment_increment 1 auto_increment_offset 1 autocommit ON automatic_sp_privileges ON back_log 50 basedir /usr/ big_tables OFF binlog_cache_size 32768 binlog_direct_non_transactional_updates OFF binlog_format STATEMENT bulk_insert_buffer_size 8388608 character_set_client utf8 character_set_connection utf8 character_set_database latin1 character_set_filesystem binary character_set_results utf8 character_set_server latin1 character_set_system utf8 character_sets_dir /usr/share/mysql/charsets/ collation_connection utf8_general_ci collation_database latin1_swedish_ci collation_server latin1_swedish_ci completion_type 0 concurrent_insert 1 connect_timeout 10 datadir /var/lib/mysql/ date_format %Y-%m-%d datetime_format %Y-%m-%d %H:%i:%s default_week_format 0 delay_key_write ON delayed_insert_limit 100 delayed_insert_timeout 300 delayed_queue_size 1000 div_precision_increment 4 engine_condition_pushdown ON error_count 0 event_scheduler OFF expire_logs_days 0 flush OFF flush_time 0 foreign_key_checks ON ft_boolean_syntax + -><()~*:""&| ft_max_word_len 84 ft_min_word_len 4 ft_query_expansion_limit 20 ft_stopword_file (built-in) general_log OFF general_log_file /var/run/mysqld/mysqld.log group_concat_max_len 1024 have_community_features YES have_compress YES have_crypt YES have_csv YES have_dynamic_loading YES have_geometry YES have_innodb YES have_ndbcluster NO have_openssl DISABLED have_partitioning YES have_query_cache YES have_rtree_keys YES have_ssl DISABLED have_symlink DISABLED hostname server1.site2.com identity 0 ignore_builtin_innodb OFF init_connect init_file init_slave innodb_adaptive_hash_index ON innodb_additional_mem_pool_size 1048576 innodb_autoextend_increment 8 innodb_autoinc_lock_mode 1 innodb_buffer_pool_size 8388608 innodb_checksums ON innodb_commit_concurrency 0 innodb_concurrency_tickets 500 innodb_data_file_path ibdata1:10M:autoextend innodb_data_home_dir innodb_doublewrite ON innodb_fast_shutdown 1 innodb_file_io_threads 4 innodb_file_per_table OFF innodb_flush_log_at_trx_commit 1 innodb_flush_method innodb_force_recovery 0 innodb_lock_wait_timeout 50 innodb_locks_unsafe_for_binlog OFF innodb_log_buffer_size 1048576 innodb_log_file_size 5242880 innodb_log_files_in_group 2 innodb_log_group_home_dir ./ innodb_max_dirty_pages_pct 90 innodb_max_purge_lag 0 innodb_mirrored_log_groups 1 innodb_open_files 300 innodb_rollback_on_timeout OFF innodb_stats_method nulls_equal innodb_stats_on_metadata ON innodb_support_xa ON innodb_sync_spin_loops 20 innodb_table_locks ON innodb_thread_concurrency 8 innodb_thread_sleep_delay 10000 innodb_use_legacy_cardinality_algorithm ON insert_id 0 interactive_timeout 28800 join_buffer_size 131072 keep_files_on_create OFF key_buffer_size 8384512 key_cache_age_threshold 300 key_cache_block_size 1024 key_cache_division_limit 100 language /usr/share/mysql/english/ large_files_support ON large_page_size 0 large_pages OFF last_insert_id 0 lc_time_names en_US license GPL local_infile ON locked_in_memory OFF log OFF log_bin OFF log_bin_trust_function_creators OFF log_bin_trust_routine_creators OFF log_error /var/log/mysqld.log log_output FILE log_queries_not_using_indexes OFF log_slave_updates OFF log_slow_queries OFF log_warnings 1 long_query_time 10.000000 low_priority_updates OFF lower_case_file_system OFF lower_case_table_names 0 max_allowed_packet 1048576 max_binlog_cache_size 18446744073709547520 max_binlog_size 1073741824 max_connect_errors 10 max_connections 151 max_delayed_threads 20 max_error_count 64 max_heap_table_size 16777216 max_insert_delayed_threads 20 max_join_size 18446744073709551615 max_length_for_sort_data 1024 max_long_data_size 1048576 max_prepared_stmt_count 16382 max_relay_log_size 0 max_seeks_for_key 18446744073709551615 max_sort_length 1024 max_sp_recursion_depth 0 max_tmp_tables 32 max_user_connections 0 max_write_lock_count 18446744073709551615 min_examined_row_limit 0 multi_range_count 256 myisam_data_pointer_size 6 myisam_max_sort_file_size 9223372036853727232 myisam_mmap_size 18446744073709551615 myisam_recover_options OFF myisam_repair_threads 1 myisam_sort_buffer_size 8388608 myisam_stats_method nulls_unequal myisam_use_mmap OFF net_buffer_length 16384 net_read_timeout 30 net_retry_count 10 net_write_timeout 60 new OFF old OFF old_alter_table OFF old_passwords OFF open_files_limit 1024 optimizer_prune_level 1 optimizer_search_depth 62 optimizer_switch index_merge=on,index_merge_union=on,index_merge_sort_union=on,index_merge_intersection=on pid_file /var/run/mysqld/mysqld.pid plugin_dir /usr/lib64/mysql/plugin port 3306 preload_buffer_size 32768 profiling OFF profiling_history_size 15 protocol_version 10 pseudo_thread_id 3 query_alloc_block_size 8192 query_cache_limit 1048576 query_cache_min_res_unit 4096 query_cache_size 0 query_cache_type ON query_cache_wlock_invalidate OFF query_prealloc_size 8192 rand_seed1 rand_seed2 range_alloc_block_size 4096 read_buffer_size 131072 read_only OFF read_rnd_buffer_size 262144 relay_log relay_log_index relay_log_info_file relay-log.info relay_log_purge ON relay_log_space_limit 0 report_host report_password report_port 3306 report_user rpl_recovery_rank 0 secure_auth OFF secure_file_priv server_id 0 skip_external_locking ON skip_name_resolve OFF skip_networking OFF skip_show_database OFF slave_compressed_protocol OFF slave_exec_mode STRICT slave_load_tmpdir /tmp slave_max_allowed_packet 1073741824 slave_net_timeout 3600 slave_skip_errors OFF slave_transaction_retries 10 slow_launch_time 2 slow_query_log OFF slow_query_log_file /var/run/mysqld/mysqld-slow.log socket /var/lib/mysql/mysql.sock sort_buffer_size 2097144 sql_auto_is_null ON sql_big_selects ON sql_big_tables OFF sql_buffer_result OFF sql_log_bin ON sql_log_off OFF sql_log_update ON sql_low_priority_updates OFF sql_max_join_size 18446744073709551615 sql_mode sql_notes ON sql_quote_show_create ON sql_safe_updates OFF sql_select_limit 18446744073709551615 sql_slave_skip_counter sql_warnings OFF ssl_ca ssl_capath ssl_cert ssl_cipher ssl_key storage_engine MyISAM sync_binlog 0 sync_frm ON system_time_zone PDT table_definition_cache 256 table_lock_wait_timeout 50 table_open_cache 64 table_type MyISAM thread_cache_size 0 thread_handling one-thread-per-connection thread_stack 262144 time_format %H:%i:%s time_zone SYSTEM timed_mutexes OFF timestamp 1372254399 tmp_table_size 16777216 tmpdir /tmp transaction_alloc_block_size 8192 transaction_prealloc_size 4096 tx_isolation REPEATABLE-READ unique_checks ON updatable_views_with_limit YES version 5.1.69 version_comment Source distribution version_compile_machine x86_64 version_compile_os redhat-linux-gnu wait_timeout 28800 warning_count 0 VPS Sysbench Info [root@vps ~]# cat sysbench.txt sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 8 Doing OLTP test. Running mixed OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 7 times) Done. OLTP test statistics: queries performed: read: 1449966 write: 0 other: 207138 total: 1657104 transactions: 103569 (1726.01 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 1449966 (24164.08 per sec.) other operations: 207138 (3452.01 per sec.) Test execution summary: total time: 60.0050s total number of events: 103569 total time taken by event execution: 479.1544 per-request statistics: min: 1.98ms avg: 4.63ms max: 330.73ms approx. 95 percentile: 8.26ms Threads fairness: events (avg/stddev): 12946.1250/381.09 execution time (avg/stddev): 59.8943/0.00 [root@vps ~]# Laptop Sysbench Info [root@server1 ~]# cat sysbench.txt sysbench 0.4.12: multi-threaded system evaluation benchmark Running the test with following options: Number of threads: 8 Doing OLTP test. Running mixed OLTP test Doing read-only test Using Special distribution (12 iterations, 1 pct of values are returned in 75 pct cases) Using "BEGIN" for starting transactions Using auto_inc on the id column Threads started! Time limit exceeded, exiting... (last message repeated 7 times) Done. OLTP test statistics: queries performed: read: 634718 write: 0 other: 90674 total: 725392 transactions: 45337 (755.56 per sec.) deadlocks: 0 (0.00 per sec.) read/write requests: 634718 (10577.78 per sec.) other operations: 90674 (1511.11 per sec.) Test execution summary: total time: 60.0048s total number of events: 45337 total time taken by event execution: 479.4912 per-request statistics: min: 2.04ms avg: 10.58ms max: 85.56ms approx. 95 percentile: 19.70ms Threads fairness: events (avg/stddev): 5667.1250/42.18 execution time (avg/stddev): 59.9364/0.00 [root@server1 ~]# VPS File Info [root@vps ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/simfs simfs 20971520 16187440 4784080 78% / none tmpfs 6224432 4 6224428 1% /dev none tmpfs 6224432 0 6224432 0% /dev/shm [root@vps ~]# Laptop File Info [root@server1 ~]# df -T Filesystem Type 1K-blocks Used Available Use% Mounted on /dev/mapper/vg_server1-lv_root ext4 72383800 4243964 64462860 7% / tmpfs tmpfs 956352 0 956352 0% /dev/shm /dev/sdb1 ext4 495844 60948 409296 13% /boot [root@server1 ~]# VPS CPU Info Removed to stay under the 30000 character limit required by ServerFault Laptop CPU Info [root@server1 ~]# cat /proc/cpuinfo processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 0 cpu cores : 2 apicid : 0 initial apicid : 0 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: processor : 1 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Core(TM)2 Duo CPU T7100 @ 1.80GHz stepping : 13 cpu MHz : 800.000 cache size : 2048 KB physical id : 0 siblings : 2 core id : 1 cpu cores : 2 apicid : 1 initial apicid : 1 fpu : yes fpu_exception : yes cpuid level : 10 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx lm constant_tsc arch_perfmon pebs bts rep_good aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm lahf_lm ida dts tpr_shadow vnmi flexpriority bogomips : 3591.39 clflush size : 64 cache_alignment : 64 address sizes : 36 bits physical, 48 bits virtual power management: [root@server1 ~]# EDIT New Info requested by shakalandy [root@localhost ~]# cat /proc/meminfo MemTotal: 2044804 kB MemFree: 761464 kB Buffers: 68868 kB Cached: 369708 kB SwapCached: 0 kB Active: 881080 kB Inactive: 246016 kB Active(anon): 688312 kB Inactive(anon): 4416 kB Active(file): 192768 kB Inactive(file): 241600 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 4095992 kB SwapFree: 4095992 kB Dirty: 0 kB Writeback: 0 kB AnonPages: 688428 kB Mapped: 65156 kB Shmem: 4216 kB Slab: 92428 kB SReclaimable: 31260 kB SUnreclaim: 61168 kB KernelStack: 2392 kB PageTables: 28356 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 5118392 kB Committed_AS: 1530212 kB VmallocTotal: 34359738367 kB VmallocUsed: 343604 kB VmallocChunk: 34359372920 kB HardwareCorrupted: 0 kB AnonHugePages: 520192 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 8556 kB DirectMap2M: 2078720 kB [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501360 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3036 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14449 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# ps aux | grep mysql root 2227 0.0 0.0 108332 1504 ? S 07:36 0:00 /bin/sh /usr/bin/mysqld_safe --datadir=/var/lib/mysql --pid-file=/var/lib/mysql/localhost.badobe.com.pid mysql 2319 0.1 24.5 1470068 501356 ? Sl 07:36 0:57 /usr/sbin/mysqld --basedir=/usr --datadir=/var/lib/mysql --plugin-dir=/usr/lib64/mysql/plugin --user=mysql --log-error=/var/lib/mysql/localhost.badobe.com.err --pid-file=/var/lib/mysql/localhost.badobe.com.pid root 3579 0.0 0.1 201840 3028 pts/0 S+ 07:40 0:00 mysql -u root -p root 13887 0.0 0.1 201840 3048 pts/3 S+ 18:08 0:00 mysql -uroot -px xxxxxxxxxx root 14470 0.0 0.0 103248 840 pts/2 S+ 18:16 0:00 grep mysql [root@localhost ~]# vmstat 1 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 0 0 742172 76376 371064 0 0 6 6 78 202 2 1 97 1 0 0 0 0 742164 76380 371060 0 0 0 16 191 467 2 1 93 5 0 0 0 0 742164 76380 371064 0 0 0 0 148 388 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 418 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 145 380 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 166 429 2 1 97 0 0 1 0 0 742164 76380 371064 0 0 0 0 148 373 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 149 382 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 168 408 2 0 97 0 0 0 0 0 742164 76380 371064 0 0 0 0 165 394 2 1 98 0 0 0 0 0 742164 76380 371064 0 0 0 0 159 354 2 1 98 0 0 0 0 0 742164 76388 371060 0 0 0 16 180 447 2 0 91 6 0 0 0 0 742164 76388 371064 0 0 0 0 143 344 2 1 98 0 0 0 1 0 742784 76416 370044 0 0 28 580 360 678 3 1 74 23 0 1 0 0 744768 76496 367772 0 0 40 1036 437 865 3 1 53 43 0 0 1 0 747248 76596 365412 0 0 48 1224 561 923 3 2 53 43 0 0 1 0 749232 76696 363092 0 0 32 1132 512 883 3 2 52 44 0 0 1 0 751340 76772 361020 0 0 32 1008 472 872 2 1 52 45 0 0 1 0 753448 76840 358540 0 0 36 1088 512 860 2 1 51 46 0 0 1 0 755060 76936 357636 0 0 28 1012 481 922 2 2 52 45 0 0 1 0 755060 77064 357988 0 0 12 896 444 902 2 1 53 45 0 0 1 0 754688 77148 358448 0 0 16 1096 506 1007 1 1 56 42 0 0 2 0 754192 77268 358932 0 0 12 1060 481 957 1 2 53 44 0 0 1 0 753696 77380 359392 0 0 12 1052 512 1025 2 1 55 42 0 0 1 0 751028 77480 359828 0 0 8 984 423 909 2 2 52 45 0 0 1 0 750524 77620 360200 0 0 8 788 367 869 1 2 54 44 0 0 1 0 749904 77700 360664 0 0 8 928 439 924 2 2 55 43 0 0 1 0 749408 77796 361084 0 0 12 976 468 967 1 1 56 43 0 0 1 0 748788 77896 361464 0 0 12 992 453 944 1 2 54 43 0 1 1 0 748416 77992 361996 0 0 12 784 392 868 2 1 52 46 0 0 1 0 747920 78092 362336 0 0 4 896 382 874 1 1 52 46 0 0 1 0 745252 78172 362780 0 0 12 1040 444 923 1 1 56 42 0 0 1 0 744764 78288 363220 0 0 8 1024 448 934 2 1 55 43 0 0 1 0 744144 78408 363668 0 0 8 1000 461 982 2 1 53 44 0 0 1 0 743648 78488 364148 0 0 8 872 443 888 2 1 54 43 0 0 1 0 743152 78548 364468 0 0 16 1020 511 995 2 1 55 43 0 0 1 0 742656 78632 365024 0 0 12 928 431 913 1 2 53 44 0 0 1 0 742160 78728 365468 0 0 12 996 470 955 2 2 54 44 0 1 1 0 739492 78840 365896 0 0 8 988 447 939 1 2 52 46 0 0 1 0 738872 78996 366352 0 0 12 972 442 928 1 1 55 44 0 1 1 0 738244 79148 366812 0 0 8 948 549 1126 2 2 54 43 0 0 1 0 737624 79312 367188 0 0 12 996 456 953 2 2 54 43 0 0 1 0 736880 79456 367660 0 0 12 960 444 918 1 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-----------memory---------- ---swap-- -----io---- --system-- -----cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 0 1 0 725600 81732 372296 0 0 4 328 439 1011 1 1 53 44 0 0 1 0 725476 81848 372308 0 0 0 316 441 1023 2 2 52 46 0 1 1 0 725352 81972 372300 0 0 4 344 451 1021 1 1 55 43 0 2 1 0 725228 82088 372320 0 0 0 328 427 1058 1 1 54 44 0 1 1 0 724980 82220 372300 0 0 4 336 419 999 2 1 54 44 0 1 1 0 724980 82328 372320 0 0 4 320 430 1019 1 1 54 44 0 1 1 0 724732 82436 372328 0 0 0 388 363 942 2 1 54 44 0 1 1 0 724608 82560 372312 0 0 4 308 419 993 1 2 54 44 0 1 0 0 724360 82684 372320 0 0 0 304 421 1028 2 1 55 42 0 1 0 0 724360 82684 372388 0 0 0 0 158 416 2 1 98 0 0 1 1 0 724236 82720 372360 0 0 0 6464 243 855 3 2 84 12 0 1 0 0 724112 82748 372360 0 0 0 5356 266 895 3 1 84 12 0 2 1 0 724112 82764 372380 0 0 0 3052 221 511 2 2 93 4 0 1 0 0 724112 82796 372372 0 0 0 4548 325 1067 2 2 81 16 0 1 0 0 724112 82816 372368 0 0 0 3240 259 829 3 1 90 6 0 1 0 0 724112 82836 372380 0 0 0 3260 309 822 3 2 88 8 0 1 1 0 724112 82876 372364 0 0 0 4680 326 978 3 1 77 19 0 1 0 0 724112 82884 372380 0 0 0 512 207 508 2 1 95 2 0 1 0 0 724112 82884 372388 0 0 0 0 138 361 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 158 397 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 146 395 2 1 98 0 0 2 0 0 724112 82884 372388 0 0 0 0 160 395 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 163 382 1 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 176 422 2 1 98 0 0 1 0 0 724112 82884 372388 0 0 0 0 134 351 2 1 98 0 0 0 0 0 724112 82884 372388 0 0 0 0 190 429 2 1 97 0 0 0 0 0 724104 82884 372392 0 0 0 0 139 358 2 1 98 0 0 0 0 0 724848 82884 372392 0 0 0 4 211 432 2 1 97 0 0 1 0 0 724980 82884 372392 0 0 0 0 166 370 2 1 98 0 0 0 0 0 724980 82884 372392 0 0 0 0 164 397 2 1 98 0 0 ^C [root@localhost ~]#

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  • Oracle-AmberPoint Webcast: Learn How Your Business Can Profit from the Combination

    - by jyothi.swaroop
    With the recent acquisition of AmberPoint, Oracle now offers an enhanced end-to-end SOA solution that features runtime governance, business transaction management, and cross-platform management capabilities. Put that solution to work and your business can achieve lower costs of implementation and higher profit. Join Ed Horst, Vice President, Oracle (former CMO of AmberPoint), and Ashish Mohindroo, Senior Director, Product Marketing, Oracle, as they discuss in this live Webcast the customer advantages of the Oracle and AmberPoint combination. Learn how our SOA solutions with AmberPoint capabilities can help you: Achieve more agility and visibility into your business processes Increase control and performance of critical applications Improve performance and reduce IT costs to benefit your bottom line Register for the Live Webcast Event Date: Thursday, May 20, 2010 Time: 10 a.m. PT/1 p.m. ET

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  • Integrating Code Metrics in TFS 2010 Build

    - by Jakob Ehn
    The build process template and custom activity described in this post is available here: http://cid-ee034c9f620cd58d.office.live.com/self.aspx/BlogSamples/CodeMetricsSample.zip Running code metrics has been available since VS 2008, but only from inside the IDE. Yesterday Microsoft finally releases a Visual Studio Code Metrics Power Tool 10.0, a command line tool that lets you run code metrics on your applications.  This means that it is now possible to perform code metrics analysis on the build server as part of your nightly/QA builds (for example). In this post I will show how you can run the metrics command line tool, and also a custom activity that reads the output and appends the results to the build log, and also fails he build if the metric values exceeds certain (configurable) treshold values. The code metrics tool analyzes all the methods in the assemblies, measuring cyclomatic complexity, class coupling, depth of inheritance and lines of code. Then it calculates a Maintainability Index from these values that is a measure f how maintanable this method is, between 0 (worst) and 100 (best). For information on hwo this value is calculated, see http://blogs.msdn.com/b/codeanalysis/archive/2007/11/20/maintainability-index-range-and-meaning.aspx. After this it aggregates the information and present it at the class, namespace and module level as well. Running Metrics.exe in a build definition Running the actual tool is easy, just use a InvokeProcess activity last in the Compile the Project sequence, reference the metrics.exe file and pass the correct arguments and you will end up with a result XML file in the drop directory. Here is how it is done in the attached build process template: In the above sequence I first assign the path to the code metrics result file ([BinariesDirectory]\result.xml) to a variable called MetricsResultFile, which is then sent to the InvokeProcess activity in the Arguments property. Here are the arguments for the InvokeProcess activity: Note that we tell metrics.exe to analyze all assemblies located in the Binaries folder. You might want to do some more intelligent filtering here, you probably don’t want to analyze all 3rd party assemblies for example. Note also the path to the metrics.exe, this is the default location when you install the Code Metrics power tool. You must of course install the power tool on all build servers. Using the standard output logging (in the Handle Standard Output/Handle Error Output sections), we get the following output when running the build: Integrating Code Metrics into the build Having the results available next to the build result is nice, but we want to have results integrated in the build result itself, and also to affect the outcome of the build. The point of having QA builds that measure, for example, code metrics is to make it very clear how the code being built measures up to the standards of the project/company. Just having a XML file available in the drop location will not cause the developers to improve their code, but a (partially) failing build will! To do this, we need to write a custom activity that parses the metrics result file, logs it to the build log and fails the build if the values frfom the metrics is below/above some predefined treshold values. The custom activity performs the following steps Parses the XML. I’m using Linq 2 XSD for this, since the XML schema for the result file is available, it is vey easy to generate code that lets you query the structure using standard Linq operators. Runs through the metric result hierarchy and logs the metrics for each level and also verifies maintainability index and the cyclomatic complexity with the treshold values. The treshold values are defined in the build process template are are sent in as arguments to the custom activity If the treshold values are exceeded, the activity either fails or partially fails the current build. For more information about the structure of the code metrics result file, read Cameron Skinner's post about it. It is very simpe and easy to understand. I won’t go through the code of the custom activity here, since there is nothing special about it and it is available for download so you can look at it and play with it yourself. The treshold values for Maintainability Index and Cyclomatic Complexity is defined in the build process template, and can be modified per build definition: I have taken the default value for these settings from my colleague Terje Sandström post on Code Metrics - suggestions for approriate limits. You’ll notice that this is quite an improvement compared to using code metrics inside the IDE, where Red/Yellow/Green limits are fixed (and the default values are somewaht strange, see Terjes post for a discussion on this) This is the first version of the code metrics integration with TFS 2010 Build, I will proabably enhance the functionality and the logging (the “tree view” structure in the log becomes quite hard to read) soon. I will also consider adding it to the Community TFS Build Extensions site when it becomes a bit more mature. Another obvious improvement is to extend the data warehouse of TFS and push the metric results back to the warehouse and make it visible in the reports.

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  • How John Got 15x Improvement Without Really Trying

    - by rchrd
    The following article was published on a Sun Microsystems website a number of years ago by John Feo. It is still useful and worth preserving. So I'm republishing it here.  How I Got 15x Improvement Without Really Trying John Feo, Sun Microsystems Taking ten "personal" program codes used in scientific and engineering research, the author was able to get from 2 to 15 times performance improvement easily by applying some simple general optimization techniques. Introduction Scientific research based on computer simulation depends on the simulation for advancement. The research can advance only as fast as the computational codes can execute. The codes' efficiency determines both the rate and quality of results. In the same amount of time, a faster program can generate more results and can carry out a more detailed simulation of physical phenomena than a slower program. Highly optimized programs help science advance quickly and insure that monies supporting scientific research are used as effectively as possible. Scientific computer codes divide into three broad categories: ISV, community, and personal. ISV codes are large, mature production codes developed and sold commercially. The codes improve slowly over time both in methods and capabilities, and they are well tuned for most vendor platforms. Since the codes are mature and complex, there are few opportunities to improve their performance solely through code optimization. Improvements of 10% to 15% are typical. Examples of ISV codes are DYNA3D, Gaussian, and Nastran. Community codes are non-commercial production codes used by a particular research field. Generally, they are developed and distributed by a single academic or research institution with assistance from the community. Most users just run the codes, but some develop new methods and extensions that feed back into the general release. The codes are available on most vendor platforms. Since these codes are younger than ISV codes, there are more opportunities to optimize the source code. Improvements of 50% are not unusual. Examples of community codes are AMBER, CHARM, BLAST, and FASTA. Personal codes are those written by single users or small research groups for their own use. These codes are not distributed, but may be passed from professor-to-student or student-to-student over several years. They form the primordial ocean of applications from which community and ISV codes emerge. Government research grants pay for the development of most personal codes. This paper reports on the nature and performance of this class of codes. Over the last year, I have looked at over two dozen personal codes from more than a dozen research institutions. The codes cover a variety of scientific fields, including astronomy, atmospheric sciences, bioinformatics, biology, chemistry, geology, and physics. The sources range from a few hundred lines to more than ten thousand lines, and are written in Fortran, Fortran 90, C, and C++. For the most part, the codes are modular, documented, and written in a clear, straightforward manner. They do not use complex language features, advanced data structures, programming tricks, or libraries. I had little trouble understanding what the codes did or how data structures were used. Most came with a makefile. Surprisingly, only one of the applications is parallel. All developers have access to parallel machines, so availability is not an issue. Several tried to parallelize their applications, but stopped after encountering difficulties. Lack of education and a perception that parallelism is difficult prevented most from trying. I parallelized several of the codes using OpenMP, and did not judge any of the codes as difficult to parallelize. Even more surprising than the lack of parallelism is the inefficiency of the codes. I was able to get large improvements in performance in a matter of a few days applying simple optimization techniques. Table 1 lists ten representative codes [names and affiliation are omitted to preserve anonymity]. Improvements on one processor range from 2x to 15.5x with a simple average of 4.75x. I did not use sophisticated performance tools or drill deep into the program's execution character as one would do when tuning ISV or community codes. Using only a profiler and source line timers, I identified inefficient sections of code and improved their performance by inspection. The changes were at a high level. I am sure there is another factor of 2 or 3 in each code, and more if the codes are parallelized. The study’s results show that personal scientific codes are running many times slower than they should and that the problem is pervasive. Computational scientists are not sloppy programmers; however, few are trained in the art of computer programming or code optimization. I found that most have a working knowledge of some programming language and standard software engineering practices; but they do not know, or think about, how to make their programs run faster. They simply do not know the standard techniques used to make codes run faster. In fact, they do not even perceive that such techniques exist. The case studies described in this paper show that applying simple, well known techniques can significantly increase the performance of personal codes. It is important that the scientific community and the Government agencies that support scientific research find ways to better educate academic scientific programmers. The inefficiency of their codes is so bad that it is retarding both the quality and progress of scientific research. # cacheperformance redundantoperations loopstructures performanceimprovement 1 x x 15.5 2 x 2.8 3 x x 2.5 4 x 2.1 5 x x 2.0 6 x 5.0 7 x 5.8 8 x 6.3 9 2.2 10 x x 3.3 Table 1 — Area of improvement and performance gains of 10 codes The remainder of the paper is organized as follows: sections 2, 3, and 4 discuss the three most common sources of inefficiencies in the codes studied. These are cache performance, redundant operations, and loop structures. Each section includes several examples. The last section summaries the work and suggests a possible solution to the issues raised. Optimizing cache performance Commodity microprocessor systems use caches to increase memory bandwidth and reduce memory latencies. Typical latencies from processor to L1, L2, local, and remote memory are 3, 10, 50, and 200 cycles, respectively. Moreover, bandwidth falls off dramatically as memory distances increase. Programs that do not use cache effectively run many times slower than programs that do. When optimizing for cache, the biggest performance gains are achieved by accessing data in cache order and reusing data to amortize the overhead of cache misses. Secondary considerations are prefetching, associativity, and replacement; however, the understanding and analysis required to optimize for the latter are probably beyond the capabilities of the non-expert. Much can be gained simply by accessing data in the correct order and maximizing data reuse. 6 out of the 10 codes studied here benefited from such high level optimizations. Array Accesses The most important cache optimization is the most basic: accessing Fortran array elements in column order and C array elements in row order. Four of the ten codes—1, 2, 4, and 10—got it wrong. Compilers will restructure nested loops to optimize cache performance, but may not do so if the loop structure is too complex, or the loop body includes conditionals, complex addressing, or function calls. In code 1, the compiler failed to invert a key loop because of complex addressing do I = 0, 1010, delta_x IM = I - delta_x IP = I + delta_x do J = 5, 995, delta_x JM = J - delta_x JP = J + delta_x T1 = CA1(IP, J) + CA1(I, JP) T2 = CA1(IM, J) + CA1(I, JM) S1 = T1 + T2 - 4 * CA1(I, J) CA(I, J) = CA1(I, J) + D * S1 end do end do In code 2, the culprit is conditionals do I = 1, N do J = 1, N If (IFLAG(I,J) .EQ. 0) then T1 = Value(I, J-1) T2 = Value(I-1, J) T3 = Value(I, J) T4 = Value(I+1, J) T5 = Value(I, J+1) Value(I,J) = 0.25 * (T1 + T2 + T5 + T4) Delta = ABS(T3 - Value(I,J)) If (Delta .GT. MaxDelta) MaxDelta = Delta endif enddo enddo I fixed both programs by inverting the loops by hand. Code 10 has three-dimensional arrays and triply nested loops. The structure of the most computationally intensive loops is too complex to invert automatically or by hand. The only practical solution is to transpose the arrays so that the dimension accessed by the innermost loop is in cache order. The arrays can be transposed at construction or prior to entering a computationally intensive section of code. The former requires all array references to be modified, while the latter is cost effective only if the cost of the transpose is amortized over many accesses. I used the second approach to optimize code 10. Code 5 has four-dimensional arrays and loops are nested four deep. For all of the reasons cited above the compiler is not able to restructure three key loops. Assume C arrays and let the four dimensions of the arrays be i, j, k, and l. In the original code, the index structure of the three loops is L1: for i L2: for i L3: for i for l for l for j for k for j for k for j for k for l So only L3 accesses array elements in cache order. L1 is a very complex loop—much too complex to invert. I brought the loop into cache alignment by transposing the second and fourth dimensions of the arrays. Since the code uses a macro to compute all array indexes, I effected the transpose at construction and changed the macro appropriately. The dimensions of the new arrays are now: i, l, k, and j. L3 is a simple loop and easily inverted. L2 has a loop-carried scalar dependence in k. By promoting the scalar name that carries the dependence to an array, I was able to invert the third and fourth subloops aligning the loop with cache. Code 5 is by far the most difficult of the four codes to optimize for array accesses; but the knowledge required to fix the problems is no more than that required for the other codes. I would judge this code at the limits of, but not beyond, the capabilities of appropriately trained computational scientists. Array Strides When a cache miss occurs, a line (64 bytes) rather than just one word is loaded into the cache. If data is accessed stride 1, than the cost of the miss is amortized over 8 words. Any stride other than one reduces the cost savings. Two of the ten codes studied suffered from non-unit strides. The codes represent two important classes of "strided" codes. Code 1 employs a multi-grid algorithm to reduce time to convergence. The grids are every tenth, fifth, second, and unit element. Since time to convergence is inversely proportional to the distance between elements, coarse grids converge quickly providing good starting values for finer grids. The better starting values further reduce the time to convergence. The downside is that grids of every nth element, n > 1, introduce non-unit strides into the computation. In the original code, much of the savings of the multi-grid algorithm were lost due to this problem. I eliminated the problem by compressing (copying) coarse grids into continuous memory, and rewriting the computation as a function of the compressed grid. On convergence, I copied the final values of the compressed grid back to the original grid. The savings gained from unit stride access of the compressed grid more than paid for the cost of copying. Using compressed grids, the loop from code 1 included in the previous section becomes do j = 1, GZ do i = 1, GZ T1 = CA(i+0, j-1) + CA(i-1, j+0) T4 = CA1(i+1, j+0) + CA1(i+0, j+1) S1 = T1 + T4 - 4 * CA1(i+0, j+0) CA(i+0, j+0) = CA1(i+0, j+0) + DD * S1 enddo enddo where CA and CA1 are compressed arrays of size GZ. Code 7 traverses a list of objects selecting objects for later processing. The labels of the selected objects are stored in an array. The selection step has unit stride, but the processing steps have irregular stride. A fix is to save the parameters of the selected objects in temporary arrays as they are selected, and pass the temporary arrays to the processing functions. The fix is practical if the same parameters are used in selection as in processing, or if processing comprises a series of distinct steps which use overlapping subsets of the parameters. Both conditions are true for code 7, so I achieved significant improvement by copying parameters to temporary arrays during selection. Data reuse In the previous sections, we optimized for spatial locality. It is also important to optimize for temporal locality. Once read, a datum should be used as much as possible before it is forced from cache. Loop fusion and loop unrolling are two techniques that increase temporal locality. Unfortunately, both techniques increase register pressure—as loop bodies become larger, the number of registers required to hold temporary values grows. Once register spilling occurs, any gains evaporate quickly. For multiprocessors with small register sets or small caches, the sweet spot can be very small. In the ten codes presented here, I found no opportunities for loop fusion and only two opportunities for loop unrolling (codes 1 and 3). In code 1, unrolling the outer and inner loop one iteration increases the number of result values computed by the loop body from 1 to 4, do J = 1, GZ-2, 2 do I = 1, GZ-2, 2 T1 = CA1(i+0, j-1) + CA1(i-1, j+0) T2 = CA1(i+1, j-1) + CA1(i+0, j+0) T3 = CA1(i+0, j+0) + CA1(i-1, j+1) T4 = CA1(i+1, j+0) + CA1(i+0, j+1) T5 = CA1(i+2, j+0) + CA1(i+1, j+1) T6 = CA1(i+1, j+1) + CA1(i+0, j+2) T7 = CA1(i+2, j+1) + CA1(i+1, j+2) S1 = T1 + T4 - 4 * CA1(i+0, j+0) S2 = T2 + T5 - 4 * CA1(i+1, j+0) S3 = T3 + T6 - 4 * CA1(i+0, j+1) S4 = T4 + T7 - 4 * CA1(i+1, j+1) CA(i+0, j+0) = CA1(i+0, j+0) + DD * S1 CA(i+1, j+0) = CA1(i+1, j+0) + DD * S2 CA(i+0, j+1) = CA1(i+0, j+1) + DD * S3 CA(i+1, j+1) = CA1(i+1, j+1) + DD * S4 enddo enddo The loop body executes 12 reads, whereas as the rolled loop shown in the previous section executes 20 reads to compute the same four values. In code 3, two loops are unrolled 8 times and one loop is unrolled 4 times. Here is the before for (k = 0; k < NK[u]; k++) { sum = 0.0; for (y = 0; y < NY; y++) { sum += W[y][u][k] * delta[y]; } backprop[i++]=sum; } and after code for (k = 0; k < KK - 8; k+=8) { sum0 = 0.0; sum1 = 0.0; sum2 = 0.0; sum3 = 0.0; sum4 = 0.0; sum5 = 0.0; sum6 = 0.0; sum7 = 0.0; for (y = 0; y < NY; y++) { sum0 += W[y][0][k+0] * delta[y]; sum1 += W[y][0][k+1] * delta[y]; sum2 += W[y][0][k+2] * delta[y]; sum3 += W[y][0][k+3] * delta[y]; sum4 += W[y][0][k+4] * delta[y]; sum5 += W[y][0][k+5] * delta[y]; sum6 += W[y][0][k+6] * delta[y]; sum7 += W[y][0][k+7] * delta[y]; } backprop[k+0] = sum0; backprop[k+1] = sum1; backprop[k+2] = sum2; backprop[k+3] = sum3; backprop[k+4] = sum4; backprop[k+5] = sum5; backprop[k+6] = sum6; backprop[k+7] = sum7; } for one of the loops unrolled 8 times. Optimizing for temporal locality is the most difficult optimization considered in this paper. The concepts are not difficult, but the sweet spot is small. Identifying where the program can benefit from loop unrolling or loop fusion is not trivial. Moreover, it takes some effort to get it right. Still, educating scientific programmers about temporal locality and teaching them how to optimize for it will pay dividends. Reducing instruction count Execution time is a function of instruction count. Reduce the count and you usually reduce the time. The best solution is to use a more efficient algorithm; that is, an algorithm whose order of complexity is smaller, that converges quicker, or is more accurate. Optimizing source code without changing the algorithm yields smaller, but still significant, gains. This paper considers only the latter because the intent is to study how much better codes can run if written by programmers schooled in basic code optimization techniques. The ten codes studied benefited from three types of "instruction reducing" optimizations. The two most prevalent were hoisting invariant memory and data operations out of inner loops. The third was eliminating unnecessary data copying. The nature of these inefficiencies is language dependent. Memory operations The semantics of C make it difficult for the compiler to determine all the invariant memory operations in a loop. The problem is particularly acute for loops in functions since the compiler may not know the values of the function's parameters at every call site when compiling the function. Most compilers support pragmas to help resolve ambiguities; however, these pragmas are not comprehensive and there is no standard syntax. To guarantee that invariant memory operations are not executed repetitively, the user has little choice but to hoist the operations by hand. The problem is not as severe in Fortran programs because in the absence of equivalence statements, it is a violation of the language's semantics for two names to share memory. Codes 3 and 5 are C programs. In both cases, the compiler did not hoist all invariant memory operations from inner loops. Consider the following loop from code 3 for (y = 0; y < NY; y++) { i = 0; for (u = 0; u < NU; u++) { for (k = 0; k < NK[u]; k++) { dW[y][u][k] += delta[y] * I1[i++]; } } } Since dW[y][u] can point to the same memory space as delta for one or more values of y and u, assignment to dW[y][u][k] may change the value of delta[y]. In reality, dW and delta do not overlap in memory, so I rewrote the loop as for (y = 0; y < NY; y++) { i = 0; Dy = delta[y]; for (u = 0; u < NU; u++) { for (k = 0; k < NK[u]; k++) { dW[y][u][k] += Dy * I1[i++]; } } } Failure to hoist invariant memory operations may be due to complex address calculations. If the compiler can not determine that the address calculation is invariant, then it can hoist neither the calculation nor the associated memory operations. As noted above, code 5 uses a macro to address four-dimensional arrays #define MAT4D(a,q,i,j,k) (double *)((a)->data + (q)*(a)->strides[0] + (i)*(a)->strides[3] + (j)*(a)->strides[2] + (k)*(a)->strides[1]) The macro is too complex for the compiler to understand and so, it does not identify any subexpressions as loop invariant. The simplest way to eliminate the address calculation from the innermost loop (over i) is to define a0 = MAT4D(a,q,0,j,k) before the loop and then replace all instances of *MAT4D(a,q,i,j,k) in the loop with a0[i] A similar problem appears in code 6, a Fortran program. The key loop in this program is do n1 = 1, nh nx1 = (n1 - 1) / nz + 1 nz1 = n1 - nz * (nx1 - 1) do n2 = 1, nh nx2 = (n2 - 1) / nz + 1 nz2 = n2 - nz * (nx2 - 1) ndx = nx2 - nx1 ndy = nz2 - nz1 gxx = grn(1,ndx,ndy) gyy = grn(2,ndx,ndy) gxy = grn(3,ndx,ndy) balance(n1,1) = balance(n1,1) + (force(n2,1) * gxx + force(n2,2) * gxy) * h1 balance(n1,2) = balance(n1,2) + (force(n2,1) * gxy + force(n2,2) * gyy)*h1 end do end do The programmer has written this loop well—there are no loop invariant operations with respect to n1 and n2. However, the loop resides within an iterative loop over time and the index calculations are independent with respect to time. Trading space for time, I precomputed the index values prior to the entering the time loop and stored the values in two arrays. I then replaced the index calculations with reads of the arrays. Data operations Ways to reduce data operations can appear in many forms. Implementing a more efficient algorithm produces the biggest gains. The closest I came to an algorithm change was in code 4. This code computes the inner product of K-vectors A(i) and B(j), 0 = i < N, 0 = j < M, for most values of i and j. Since the program computes most of the NM possible inner products, it is more efficient to compute all the inner products in one triply-nested loop rather than one at a time when needed. The savings accrue from reading A(i) once for all B(j) vectors and from loop unrolling. for (i = 0; i < N; i+=8) { for (j = 0; j < M; j++) { sum0 = 0.0; sum1 = 0.0; sum2 = 0.0; sum3 = 0.0; sum4 = 0.0; sum5 = 0.0; sum6 = 0.0; sum7 = 0.0; for (k = 0; k < K; k++) { sum0 += A[i+0][k] * B[j][k]; sum1 += A[i+1][k] * B[j][k]; sum2 += A[i+2][k] * B[j][k]; sum3 += A[i+3][k] * B[j][k]; sum4 += A[i+4][k] * B[j][k]; sum5 += A[i+5][k] * B[j][k]; sum6 += A[i+6][k] * B[j][k]; sum7 += A[i+7][k] * B[j][k]; } C[i+0][j] = sum0; C[i+1][j] = sum1; C[i+2][j] = sum2; C[i+3][j] = sum3; C[i+4][j] = sum4; C[i+5][j] = sum5; C[i+6][j] = sum6; C[i+7][j] = sum7; }} This change requires knowledge of a typical run; i.e., that most inner products are computed. The reasons for the change, however, derive from basic optimization concepts. It is the type of change easily made at development time by a knowledgeable programmer. In code 5, we have the data version of the index optimization in code 6. Here a very expensive computation is a function of the loop indices and so cannot be hoisted out of the loop; however, the computation is invariant with respect to an outer iterative loop over time. We can compute its value for each iteration of the computation loop prior to entering the time loop and save the values in an array. The increase in memory required to store the values is small in comparison to the large savings in time. The main loop in Code 8 is doubly nested. The inner loop includes a series of guarded computations; some are a function of the inner loop index but not the outer loop index while others are a function of the outer loop index but not the inner loop index for (j = 0; j < N; j++) { for (i = 0; i < M; i++) { r = i * hrmax; R = A[j]; temp = (PRM[3] == 0.0) ? 1.0 : pow(r, PRM[3]); high = temp * kcoeff * B[j] * PRM[2] * PRM[4]; low = high * PRM[6] * PRM[6] / (1.0 + pow(PRM[4] * PRM[6], 2.0)); kap = (R > PRM[6]) ? high * R * R / (1.0 + pow(PRM[4]*r, 2.0) : low * pow(R/PRM[6], PRM[5]); < rest of loop omitted > }} Note that the value of temp is invariant to j. Thus, we can hoist the computation for temp out of the loop and save its values in an array. for (i = 0; i < M; i++) { r = i * hrmax; TEMP[i] = pow(r, PRM[3]); } [N.B. – the case for PRM[3] = 0 is omitted and will be reintroduced later.] We now hoist out of the inner loop the computations invariant to i. Since the conditional guarding the value of kap is invariant to i, it behooves us to hoist the computation out of the inner loop, thereby executing the guard once rather than M times. The final version of the code is for (j = 0; j < N; j++) { R = rig[j] / 1000.; tmp1 = kcoeff * par[2] * beta[j] * par[4]; tmp2 = 1.0 + (par[4] * par[4] * par[6] * par[6]); tmp3 = 1.0 + (par[4] * par[4] * R * R); tmp4 = par[6] * par[6] / tmp2; tmp5 = R * R / tmp3; tmp6 = pow(R / par[6], par[5]); if ((par[3] == 0.0) && (R > par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * tmp5; } else if ((par[3] == 0.0) && (R <= par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * tmp4 * tmp6; } else if ((par[3] != 0.0) && (R > par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * TEMP[i] * tmp5; } else if ((par[3] != 0.0) && (R <= par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * TEMP[i] * tmp4 * tmp6; } for (i = 0; i < M; i++) { kap = KAP[i]; r = i * hrmax; < rest of loop omitted > } } Maybe not the prettiest piece of code, but certainly much more efficient than the original loop, Copy operations Several programs unnecessarily copy data from one data structure to another. This problem occurs in both Fortran and C programs, although it manifests itself differently in the two languages. Code 1 declares two arrays—one for old values and one for new values. At the end of each iteration, the array of new values is copied to the array of old values to reset the data structures for the next iteration. This problem occurs in Fortran programs not included in this study and in both Fortran 77 and Fortran 90 code. Introducing pointers to the arrays and swapping pointer values is an obvious way to eliminate the copying; but pointers is not a feature that many Fortran programmers know well or are comfortable using. An easy solution not involving pointers is to extend the dimension of the value array by 1 and use the last dimension to differentiate between arrays at different times. For example, if the data space is N x N, declare the array (N, N, 2). Then store the problem’s initial values in (_, _, 2) and define the scalar names new = 2 and old = 1. At the start of each iteration, swap old and new to reset the arrays. The old–new copy problem did not appear in any C program. In programs that had new and old values, the code swapped pointers to reset data structures. Where unnecessary coping did occur is in structure assignment and parameter passing. Structures in C are handled much like scalars. Assignment causes the data space of the right-hand name to be copied to the data space of the left-hand name. Similarly, when a structure is passed to a function, the data space of the actual parameter is copied to the data space of the formal parameter. If the structure is large and the assignment or function call is in an inner loop, then copying costs can grow quite large. While none of the ten programs considered here manifested this problem, it did occur in programs not included in the study. A simple fix is always to refer to structures via pointers. Optimizing loop structures Since scientific programs spend almost all their time in loops, efficient loops are the key to good performance. Conditionals, function calls, little instruction level parallelism, and large numbers of temporary values make it difficult for the compiler to generate tightly packed, highly efficient code. Conditionals and function calls introduce jumps that disrupt code flow. Users should eliminate or isolate conditionls to their own loops as much as possible. Often logical expressions can be substituted for if-then-else statements. For example, code 2 includes the following snippet MaxDelta = 0.0 do J = 1, N do I = 1, M < code omitted > Delta = abs(OldValue ? NewValue) if (Delta > MaxDelta) MaxDelta = Delta enddo enddo if (MaxDelta .gt. 0.001) goto 200 Since the only use of MaxDelta is to control the jump to 200 and all that matters is whether or not it is greater than 0.001, I made MaxDelta a boolean and rewrote the snippet as MaxDelta = .false. do J = 1, N do I = 1, M < code omitted > Delta = abs(OldValue ? NewValue) MaxDelta = MaxDelta .or. (Delta .gt. 0.001) enddo enddo if (MaxDelta) goto 200 thereby, eliminating the conditional expression from the inner loop. A microprocessor can execute many instructions per instruction cycle. Typically, it can execute one or more memory, floating point, integer, and jump operations. To be executed simultaneously, the operations must be independent. Thick loops tend to have more instruction level parallelism than thin loops. Moreover, they reduce memory traffice by maximizing data reuse. Loop unrolling and loop fusion are two techniques to increase the size of loop bodies. Several of the codes studied benefitted from loop unrolling, but none benefitted from loop fusion. This observation is not too surpising since it is the general tendency of programmers to write thick loops. As loops become thicker, the number of temporary values grows, increasing register pressure. If registers spill, then memory traffic increases and code flow is disrupted. A thick loop with many temporary values may execute slower than an equivalent series of thin loops. The biggest gain will be achieved if the thick loop can be split into a series of independent loops eliminating the need to write and read temporary arrays. I found such an occasion in code 10 where I split the loop do i = 1, n do j = 1, m A24(j,i)= S24(j,i) * T24(j,i) + S25(j,i) * U25(j,i) B24(j,i)= S24(j,i) * T25(j,i) + S25(j,i) * U24(j,i) A25(j,i)= S24(j,i) * C24(j,i) + S25(j,i) * V24(j,i) B25(j,i)= S24(j,i) * U25(j,i) + S25(j,i) * V25(j,i) C24(j,i)= S26(j,i) * T26(j,i) + S27(j,i) * U26(j,i) D24(j,i)= S26(j,i) * T27(j,i) + S27(j,i) * V26(j,i) C25(j,i)= S27(j,i) * S28(j,i) + S26(j,i) * U28(j,i) D25(j,i)= S27(j,i) * T28(j,i) + S26(j,i) * V28(j,i) end do end do into two disjoint loops do i = 1, n do j = 1, m A24(j,i)= S24(j,i) * T24(j,i) + S25(j,i) * U25(j,i) B24(j,i)= S24(j,i) * T25(j,i) + S25(j,i) * U24(j,i) A25(j,i)= S24(j,i) * C24(j,i) + S25(j,i) * V24(j,i) B25(j,i)= S24(j,i) * U25(j,i) + S25(j,i) * V25(j,i) end do end do do i = 1, n do j = 1, m C24(j,i)= S26(j,i) * T26(j,i) + S27(j,i) * U26(j,i) D24(j,i)= S26(j,i) * T27(j,i) + S27(j,i) * V26(j,i) C25(j,i)= S27(j,i) * S28(j,i) + S26(j,i) * U28(j,i) D25(j,i)= S27(j,i) * T28(j,i) + S26(j,i) * V28(j,i) end do end do Conclusions Over the course of the last year, I have had the opportunity to work with over two dozen academic scientific programmers at leading research universities. Their research interests span a broad range of scientific fields. Except for two programs that relied almost exclusively on library routines (matrix multiply and fast Fourier transform), I was able to improve significantly the single processor performance of all codes. Improvements range from 2x to 15.5x with a simple average of 4.75x. Changes to the source code were at a very high level. I did not use sophisticated techniques or programming tools to discover inefficiencies or effect the changes. Only one code was parallel despite the availability of parallel systems to all developers. Clearly, we have a problem—personal scientific research codes are highly inefficient and not running parallel. The developers are unaware of simple optimization techniques to make programs run faster. They lack education in the art of code optimization and parallel programming. I do not believe we can fix the problem by publishing additional books or training manuals. To date, the developers in questions have not studied the books or manual available, and are unlikely to do so in the future. Short courses are a possible solution, but I believe they are too concentrated to be much use. The general concepts can be taught in a three or four day course, but that is not enough time for students to practice what they learn and acquire the experience to apply and extend the concepts to their codes. Practice is the key to becoming proficient at optimization. I recommend that graduate students be required to take a semester length course in optimization and parallel programming. We would never give someone access to state-of-the-art scientific equipment costing hundreds of thousands of dollars without first requiring them to demonstrate that they know how to use the equipment. Yet the criterion for time on state-of-the-art supercomputers is at most an interesting project. Requestors are never asked to demonstrate that they know how to use the system, or can use the system effectively. A semester course would teach them the required skills. Government agencies that fund academic scientific research pay for most of the computer systems supporting scientific research as well as the development of most personal scientific codes. These agencies should require graduate schools to offer a course in optimization and parallel programming as a requirement for funding. About the Author John Feo received his Ph.D. in Computer Science from The University of Texas at Austin in 1986. After graduate school, Dr. Feo worked at Lawrence Livermore National Laboratory where he was the Group Leader of the Computer Research Group and principal investigator of the Sisal Language Project. In 1997, Dr. Feo joined Tera Computer Company where he was project manager for the MTA, and oversaw the programming and evaluation of the MTA at the San Diego Supercomputer Center. In 2000, Dr. Feo joined Sun Microsystems as an HPC application specialist. He works with university research groups to optimize and parallelize scientific codes. Dr. Feo has published over two dozen research articles in the areas of parallel parallel programming, parallel programming languages, and application performance.

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  • A temporary disagreement

    - by Tony Davis
    Last month, Phil Factor caused a furore amongst some MVPs with an article that attempted to offer simple advice to developers regarding the use of table variables, versus local and global temporary tables, in their code. Phil makes clear that the table variables do come with some fairly major limitations.no distribution statistics, no parallel query plans for queries that modify table variables.but goes on to suggest that for reasonably small-scale strategic uses, and with a bit of due care and testing, table variables are a "good thing". Not everyone shares his opinion; in fact, I imagine he was rather aghast to learn that there were those felt his article was akin to pulling the pin out of a grenade and tossing it into the database; table variables should be avoided in almost all cases, according to their advice, in favour of temp tables. In other words, a fairly major feature of SQL Server should be more-or-less 'off limits' to developers. The problem with temp tables is that, because they are scoped either in the procedure or the connection, it is easy to allow them to hang around for too long, eating up precious memory and bulking up the shared tempdb database. Unless they are explicitly dropped, global temporary tables, and local temporary tables created within a connection rather than within a stored procedure, will persist until the connection is closed or, with connection pooling, until the connection is reused. It's also quite common with ASP.NET applications to have connection leaks, as Bill Vaughn explains in his chapter in the "SQL Server Deep Dives" book, meaning that the web page exits without closing the connection object, maybe due to an error condition. This will then hang around in the heap for what might be hours before picked up by the garbage collector. Table variables are much safer in this regard, since they are batch-scoped and so are cleaned up automatically once the batch is complete, which also means that they are intuitive to use for the developer because they conform to scoping rules that are closer to those in procedural code. On the surface then, an ideal way to deal with issues related to tempdb memory hogging. So why did Phil qualify his recommendation to use Table Variables? This is another of those cases where, like scalar UDFs and table-valued multi-statement UDFs, developers can sometimes get into trouble with a relatively benign-looking feature, due to way it's been implemented in SQL Server. Once again the biggest problem is how they are handled internally, by the SQL Server query optimizer, which can make very poor choices for JOIN orders and so on, in the absence of statistics, especially when joining to tables with highly-skewed data. The resulting execution plans can be horrible, as will be the resulting performance. If the JOIN is to a large table, that will hurt. Ideally, Microsoft would simply fix this issue so that developers can't get burned in this way; they've been around since SQL Server 2000, so Microsoft has had a bit of time to get it right. As I commented in regard to UDFs, when developers discover issues like with such standard features, the database becomes an alien planet to them, where death lurks around each corner, and they continue to avoid these "killer" features years after the problems have been eventually resolved. In the meantime, what is the right approach? Is it to say "hammers can kill, don't ever use hammers", or is it to try to explain, as Phil's article and follow-up blog post have tried to do, what the feature was intended for, why care must be applied in its use, and so enable developers to make properly-informed decisions, without requiring them to delve deep into the inner workings of SQL Server? Cheers, Tony.

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  • How to tell the Browser the character encoding of a HTML website regardless of Server Content.-Type Headers?

    - by hakre
    I have a HTML page that correctly (the encoding of the physical on disk matches it) announces it's Content-Type: <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"> <html> <head> <meta http-equiv="Content-Type" content= "text/html; charset=utf-8"> <title> ... Opening the file from disk in browser (Google Chrome, Firefox) works fine. Requesting it via HTTP, the webserver sends a different Content-Type header: $ curl -I http:/example.com/file.html HTTP/1.1 200 OK Date: Fri, 19 Oct 2012 10:57:13 GMT ... Content-Type: text/html; charset=ISO-8859-1 (see last line). The browser then uses ISO-8859-1 to display which is an unwanted result. Is there a common way to override the server headers send to the browser from within the HTML document?

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  • OOW 2013 Summary for Fusion Middleware Architects & Administrators by Simon Haslam

    - by JuergenKress
    OOW 2013 Summary for Fusion Middleware Architects & Administrators by Simon Haslam This September during Oracle OpenWorld 2013 the weather in San Francisco, as you see can from the photo, was exceptionally sunny. The dramatic final few days of the Americas Cup sailing competition, being held every day in the bay, coincided with the conference and meant that there was almost a holiday feel to the whole event. Here's my annual round-up of what I think was most interesting at OpenWorld 2013 for Fusion Middleware architects and administrators; I hope you find it useful and if you think I've missed something please add a comment! WebLogic and Cloud Application Foundation (CAF) The big WebLogic release of the year has already happened a few months ago with 12.1.2 so I won't duplicate that here. Will Lyons discussed the WebLogic and Coherence roadmap which essentially is that 12.1.3 will probably be released to coincide with SOA 12c next year and that 12.1.4, the next feature-rich WebLogic release, is more likely to be in 2015. This latter release will probably include full Java EE 7 support, have enhancements for multi-tenancy and further auto-scaling features to support increased density (i.e. more WebLogic usage for the same amount of hardware). There's a new Oracle Virtual Assembly Builder (OVAB) out already and an Oracle Traffic Director (OTD) 12c release round the corner too. Also of relevance to administrators is that Oracle has increased the support lifetime for Fusion Middleware 11g (e.g. WebLogic 10.3.6) so that Premier Support will now run to the end of 2018 and Extended Support until 2021 - this should remove any Oracle-driven pressure to upgrade at least. Java Mission Control Java Mission Control (JMC) is the HotSpot Java 7 version of JRockit 6 Mission Control, a very nice performance monitoring tool from Oracle's BEA acquisition. Flight Recorder is a feature built into the JVM which records diagnostic events into, typically, a circular buffer which can then be used for historical analysis, particularly in the case of a JVM crash or hang. It's been available separately for WebLogic only for perhaps a year now but, more significantly, it now includes JVM events and was bundled in with JDK7 Update 40 a few weeks ago. I attended a couple of interesting Java One sessions on JMC/Flight Recorder and have to say it's looking really good - it has all the previous JRMC features except for memory leak detector, plus some enhancements around operative sets and ECID filtering I think. Marcus also showed how you could add your own events into flight recorder by building your own event class - they are then available for graphing alongside all the other events in JMC. This uses a currently an unsupported/undocumented API, but it's also the same one that WebLogic uses for WLDF events so I imagine it is stable. I'm not sure quite whether this would be useful to custom applications, as opposed to infrastructure services or ISV packaged applications, but it was a very nice demonstration. I've been testing JMC / FR enabling on several environments recently and my confidence is growing - it feels robust and I think could very soon be part of my standard builds. Read the full article here. WebLogic Partner Community For regular information become a member in the WebLogic Partner Community please visit: http://www.oracle.com/partners/goto/wls-emea ( OPN account required). If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Mix Forum Wiki Technorati Tags: OOW,Simon Haslam,Oracle OpenWorld,WebLogic,WebLogic Community,Oracle,OPN,Jürgen Kress

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