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• Why doesn't my IDE do background compiling/building?

  - by MKO

  Today I develop on a fairly complex computer, it has multiple cores, SSD drives and what not. Still, most of the time I'm programming the computer is leasurely doing nothing. When I need to compile and run/deploy a somewhat complex project at best it still takes a couple of seconds. Why? Now that we're living more and more in the "age of instant" why can't I press F5 in Visual studio and launch/deploy my application instantly? A couple of seconds might not sound so bad but it's still cognitive friction and time that adds up, and frankly it makes programming less fun. So how could compilation be instant? Well, People tend to edit files in different assemblies, what if Visual Studio/The IDE constantly did compilation/and building of everything that I modified anytime that it might be appropriate. Heck if they wanted to go really advanced they could do per-class compilation. The compilation might not work but then it could just silently do nothing (except adding error messages to the error window). Surely todays computer could dedicate a core or two to this task, and if someone found it annoying it could be disabled by option. I know there's probably a thousand technical issues and some fancy shadow copying that would need to be resolved for this to be seamless and practical but it sure would make programming more seamless. Is there any practical reason why this scenario isn't possible? Would the wear and tear of continually writing binaries be too much? Couldn't assemblies be held in memory until deployed/run?

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• VMPlayer 9, Xubuntu 12.10, Rails Development - Freezing frequently

  - by douglasisshiny

  I have a new Vizio Ultrabook that came with Windows 7. I develop Rails applications, and it's a pain to do that in windows, so I setup a Xubuntu VM with 1GB ram and 2 CPU cores. I basically keep the VM open all the time and have enough memory not to worry. Sometimes I pause the VM. For the first few days, everything was fine. The fourth day, Xubuntu froze up while running a test (with Guard and RSpec). I didn't think much of it and restarted the VM and went on my way. The freezes started becoming more frequent, though. I don't think they are only when I run a test, but often they are. It'll happen quickly, too. Startup VM, save file, test runs, it freezes, all within 5 minutes. Of note: the VM is using a shared folder from Windows (where the code is). This may be the problem. Any other people experience something like this?

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• Price Drop for Processor based License on Exalytics

  - by Mike.Hallett(at)Oracle-BI&EPM

  ·       33% reduction in the list `per processor` license pricing for the Oracle BI Foundation Suite ·       New capacity-based licensing which allows customers to think big & start small, significantly lowering the entry price point for an Exalytics. Oracle BI Software List Price changes In response to new powerful platforms like the in-memory Oracle Exalytics with 40 cpu cores (counted under Oracle pricing policy as 20 “processors”), the list price of “Oracle BI Foundation Suite” (BIFS) is reduced by 33% from $450K per processor to $300K per processor. Capacity-based licensing on Exalytics (Trusted Partitions) “Capacity-based pricing” for the BIFS, Endeca, Essbase and Times Ten for Exalytics software is now available for Exalytics systems. This is delivered using “Oracle VM” (OVM).  We still ship a full Exalytics machine to all customers, but they may choose to only use and license a subset of the processors installed in the machine.   Customers can license Exalytics software in units of 5 “processors”: 5, 10, 15 or the full capacity 20.   As the customer’s implementation and workload increases, it is a simple matter to license additional processors and, using OVM, make them available to the BI or EPM application. Endeca Information Discovery now available on Exalytics Oracle has also announced the certification of “Oracle Endeca Information Discovery” (EID) on the Exalytics machine.    EID can be licensed alone or in combination with the BIFS & Times Ten for an Exalytics stack, and also participates in the capacity based pricing outlined above.   The Exalytics hardware is the perfect platform for EID, and provides superb power and performance for this in-memory hybrid text-search-analytics.   For more information : Oracle Price lists Oracle Partitioning Policy Discussion by Mark Rittman (Rittman Mead Consulting ltd.) on Oracle Trusted Partitions for Oracle Engineered Systems, Oracle Exalytics and Updated BI Foundation Pricing.

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• Xna, after mouse click cpu usage goes 100%

  - by kosnkov

  Hi i have following code and it is enough just if i click on blue window then cpu goes to 100% for like at least one minute even with my i7 4 cores. I just check even with empty project and is the same !!! public class Game1 : Microsoft.Xna.Framework.Game { GraphicsDeviceManager graphics; SpriteBatch spriteBatch; private Texture2D cursorTex; private Vector2 cursorPos; GraphicsDevice device; float xPosition; float yPosition; public Game1() { graphics = new GraphicsDeviceManager(this); Content.RootDirectory = "Content"; } protected override void Initialize() { Viewport vp = GraphicsDevice.Viewport; xPosition = vp.X + (vp.Width / 2); yPosition = vp.Y + (vp.Height / 2); device = graphics.GraphicsDevice; base.Initialize(); } protected override void LoadContent() { spriteBatch = new SpriteBatch(GraphicsDevice); cursorTex = Content.Load<Texture2D>("strzalka"); } protected override void UnloadContent() { // TODO: Unload any non ContentManager content here } protected override void Update(GameTime gameTime) { // Allows the game to exit if (GamePad.GetState(PlayerIndex.One).Buttons.Back == ButtonState.Pressed) this.Exit(); base.Update(gameTime); } protected override void Draw(GameTime gameTime) { GraphicsDevice.Clear(Color.CornflowerBlue); spriteBatch.Begin(); spriteBatch.Draw(cursorTex, cursorPos, Color.White); spriteBatch.End(); base.Draw(gameTime); } }

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• Extension GLX missing...on a desktop PC

  - by Bart van Heukelom

  I just installed Ubuntu 12.10 on a new PC with an Nvidia GTX 560 graphics card, but after installing the Nvidia proprietary drivers (either -current or -current-updates), Unity won't start. When trying to start it manually I get the message "extension GLX missing". I've searched around and found results like this question which point out it's a problem with Nvidia Optimus laptops. However, I don't have this problem on a laptop, but on a desktop PC. lshw output for the graphics card: *-display description: VGA compatible controller product: GF114 [GeForce GTX 560 SE] vendor: NVIDIA Corporation physical id: 0 bus info: pci@0000:01:00.0 version: a1 width: 64 bits clock: 33MHz capabilities: pm msi pciexpress vga_controller bus_master cap_list rom configuration: driver=nouveau latency=0 resources: irq:16 memory:f4000000-f5ffffff memory:e0000000-e7ffffff memory:e8000000-ebffffff ioport:e000(size=128) memory:f6000000-f607ffff and CPU: *-cpu description: CPU product: Intel(R) Core(TM) i5-3570K CPU @ 3.40GHz vendor: Intel Corp. physical id: 40 bus info: cpu@0 version: Intel(R) Core(TM) i5-3570K CPU @ 3.40GHz slot: SOCKET 0 size: 1600MHz capacity: 3800MHz width: 64 bits clock: 100MHz capabilities: x86-64 fpu fpu_exception wp 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 rdtscp constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm pcid sse4_1 sse4_2 popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm ida arat epb xsaveopt pln pts dtherm tpr_shadow vnmi flexpriority ept vpid fsgsbase smep erms cpufreq configuration: cores=4 enabledcores=4 threads=4

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• How to REALLY start thinking in terms of objects?

  - by Mr Grieves

  I work with a team of developers who all have several years of experience with languages such as C# and Java. Most of them are young enough to have been shown OOP as a standard way to develop software in university and are very comfortable with concepts such as inheritance, abstraction, encapsulation and polymorphism. Yet, many of them, and I have to include myself, still tend to create classes which are meant to be used in a very functional fashion. The resulting software is often several smaller classes which correctly represent business objects which get passed through larger classes which only supply ways to modify and use those objects (functions). Large complex difficult-to-maintain classes named Manager are usually the result of such behaviour. I can see two theoretical reasons why people might write this type of code: It's easy to start thinking of everything in terms of the database Deep down, for me, a computer handling a web request feels more like a functional operation than an object oriented operation when you think about Request Handlers, Threads, Processes, CPU Cores and CPU operations... I want source code which is easy to read and easy to modify. I have seen excellent examples of OO code which meet these objectives. How can I start writing code like this? How I can I really start thinking in an object oriented fashion? How can I share such a mentality with my colleagues?

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• How do I debug an overheating problem?

  - by Tab

  Hello guys. I have a problem with my Laptop (Dell Inspiron 1564 Core i5 4GB Ram VGA ATI Mobility Radeon HD 4300 running Ubuntu 10.10 32bit). It shuts down abruptly without even a lag in the application I am working with before shutdown. I think it's overheating problem. Actually the laptop is hot all the time when I am running Ubuntu. When I switch back to windows, even with intense load it won't shutdown or show any problem as long as I keep proper ventilation (when the air openings are blocked it does the same). Actually on Ubuntu i don't usually do things that need much CPU power, usually surfing internet, coding web pages and sometimes playing with python and ruby. I am not enabling desktop effects so no GPU load except the normal GNOME gui. Now as I am writing the Processor load in the panel monitor applet is 0%, Memory 11% by programs, 22% by cache. And i have CPU Frequency monitor for each of the 4 cores set to 1.20 Ghz (the lowest possible value, i am not sure if this applet does really limit CPU usage). Running sensors in terminal gave me temp1: +26.8°C (crit = +100.0°C) temp2: +0.0°C (crit = +100.0°C) hddtemp /dev/sda at the terminal gave me /dev/sda: WDC WD3200BEVT-75ZCT2: 46°C All that fine but the laptop is Really hot i can feel it in the keyboard, mouse pad is painful to touch, and the fan is always spinning. I am also placing 2 small fans running on USB under the laptop right now and the laptop is lifted over the fans so it's well ventilated. When I am running windows it doesn't get that hot except when there is a really big load on the CPU and this is keeping me away from using Linux for everyday tasks. Actually I don't care much for speed as I can deal with low speed it's not going to shutdown abruptly. So please if you can help me and tell me what are the possible causes, where should I start ?

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• Using Clojure instead of Python for scalability (multi core) reasons, good idea?

  - by Vandell

  After reading http://clojure.org/rationale and other performance comparisons between Clojure and many languages, I started to think that apart from ease of use, I shouldn't be coding in Python anymore, but in Clojure instead. Actually, I began to fill irresponsisble for not learning clojure seeing it's benefits. Does it make sense? Can't I make really efficient use of all cores using a more imperative language like Python, than a lisp dialect or other functional language? It seems that all the benefits of it come from using immutable data, can't I do just that in Python and have all the benefits? I once started to learn some Common Lisp, read and done almost all exercices from a book I borrowod from my university library (I found it to be pretty good, despite it's low popularity on Amazon). But, after a while, I got myself struggling to much to do some simple things. I think there's somethings that are more imperative in their nature, that makes it difficult to model those thins in a functional way, I guess. The thing is, is Python as powerful as Clojure for building applications that takes advantages of this new multi core future? Note that I don't think that using semaphores, lock mechanisms or other similar concurrency mechanism are good alternatives to Clojure 'automatic' parallelization.

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• Processing Kinect v2 Color Streams in Parallel

  - by Chris Gardner

  Originally posted on: http://geekswithblogs.net/freestylecoding/archive/2014/08/20/processing-kinect-v2-color-streams-in-parallel.aspxProcessing Kinect v2 Color Streams in Parallel I've really been enjoying being a part of the Kinect for Windows Developer's Preview. The new hardware has some really impressive capabilities. However, with great power comes great system specs. Unfortunately, my little laptop that could is not 100% up to the task; I've had to get a little creative. The most disappointing thing I've run into is that I can't always cleanly display the color camera stream in managed code. I managed to strip the code down to what I believe is the bear minimum: using( ColorFrame _ColorFrame = e.FrameReference.AcquireFrame() ) { if( null == _ColorFrame ) return;   BitmapToDisplay.Lock(); _ColorFrame.CopyConvertedFrameDataToIntPtr( BitmapToDisplay.BackBuffer, Convert.ToUInt32( BitmapToDisplay.BackBufferStride * BitmapToDisplay.PixelHeight ), ColorImageFormat.Bgra ); BitmapToDisplay.AddDirtyRect( new Int32Rect( 0, 0, _ColorFrame.FrameDescription.Width, _ColorFrame.FrameDescription.Height ) ); BitmapToDisplay.Unlock(); } With this snippet, I'm placing the converted Bgra32 color stream directly on the BackBuffer of the WriteableBitmap. This gives me pretty smooth playback, but I still get the occasional freeze for half a second. After a bit of profiling, I discovered there were a few problems. The first problem is the size of the buffer along with the conversion on the buffer. At this time, the raw image format of the data from the Kinect is Yuy2. This is great for direct video processing. It would be ideal if I had a WriteableVideo object in WPF. However, this is not the case. Further digging led me to the real problem. It appears that the SDK is converting the input serially. Let's think about this for a second. The color camera is a 1080p camera. As we should all know, this give us a native resolution of 1920 x 1080. This produces 2,073,600 pixels. Yuy2 uses 4 bytes per 2 pixel, for a buffer size of 4,147,200 bytes. Bgra32 uses 4 bytes per pixel, for a buffer size of 8,294,400 bytes. The SDK appears to be doing this on one thread. I started wondering if I chould do this better myself. I mean, I have 8 cores in my system. Why can't I use them all? The first problem is converting a Yuy2 frame into a Bgra32 frame. It is NOT trivial. I spent a day of research of just how to do this. In the end, I didn't even produce the best algorithm possible, but it did work. After I managed to get that to work, I knew my next step was the get the conversion operation off the UI Thread. This was a simple process of throwing the work into a Task. Of course, this meant I had to marshal the final write to the WriteableBitmap back to the UI thread. Finally, I needed to vectorize the operation so I could run it safely in parallel. This was, mercifully, not quite as hard as I thought it would be. I had my loop return an index to a pair of pixels. From there, I had to tell the loop to do everything for this pair of pixels. If you're wondering why I did it for pairs of pixels, look back above at the specification for the Yuy2 format. I won't go into full detail on why each 4 bytes contains 2 pixels of information, but rest assured that there is a reason why the format is described in that way. The first working attempt at this algorithm successfully turned my poor laptop into a space heater. I very quickly brought and maintained all 8 cores up to about 97% usage. That's when I remembered that obscure option in the Task Parallel Library where you could limit the amount of parallelism used. After a little trial and error, I discovered 4 parallel tasks was enough for most cases. This yielded the follow code: private byte ClipToByte( int p_ValueToClip ) { return Convert.ToByte( ( p_ValueToClip < byte.MinValue ) ? byte.MinValue : ( ( p_ValueToClip > byte.MaxValue ) ? byte.MaxValue : p_ValueToClip ) ); }   private void ColorFrameArrived( object sender, ColorFrameArrivedEventArgs e ) { if( null == e.FrameReference ) return;   // If you do not dispose of the frame, you never get another one... using( ColorFrame _ColorFrame = e.FrameReference.AcquireFrame() ) { if( null == _ColorFrame ) return;   byte[] _InputImage = new byte[_ColorFrame.FrameDescription.LengthInPixels * _ColorFrame.FrameDescription.BytesPerPixel]; byte[] _OutputImage = new byte[BitmapToDisplay.BackBufferStride * BitmapToDisplay.PixelHeight]; _ColorFrame.CopyRawFrameDataToArray( _InputImage );   Task.Factory.StartNew( () => { ParallelOptions _ParallelOptions = new ParallelOptions(); _ParallelOptions.MaxDegreeOfParallelism = 4;   Parallel.For( 0, Sensor.ColorFrameSource.FrameDescription.LengthInPixels / 2, _ParallelOptions, ( _Index ) => { // See http://msdn.microsoft.com/en-us/library/windows/desktop/dd206750(v=vs.85).aspx int _Y0 = _InputImage[( _Index << 2 ) + 0] - 16; int _U = _InputImage[( _Index << 2 ) + 1] - 128; int _Y1 = _InputImage[( _Index << 2 ) + 2] - 16; int _V = _InputImage[( _Index << 2 ) + 3] - 128;   byte _R = ClipToByte( ( 298 * _Y0 + 409 * _V + 128 ) >> 8 ); byte _G = ClipToByte( ( 298 * _Y0 - 100 * _U - 208 * _V + 128 ) >> 8 ); byte _B = ClipToByte( ( 298 * _Y0 + 516 * _U + 128 ) >> 8 );   _OutputImage[( _Index << 3 ) + 0] = _B; _OutputImage[( _Index << 3 ) + 1] = _G; _OutputImage[( _Index << 3 ) + 2] = _R; _OutputImage[( _Index << 3 ) + 3] = 0xFF; // A   _R = ClipToByte( ( 298 * _Y1 + 409 * _V + 128 ) >> 8 ); _G = ClipToByte( ( 298 * _Y1 - 100 * _U - 208 * _V + 128 ) >> 8 ); _B = ClipToByte( ( 298 * _Y1 + 516 * _U + 128 ) >> 8 );   _OutputImage[( _Index << 3 ) + 4] = _B; _OutputImage[( _Index << 3 ) + 5] = _G; _OutputImage[( _Index << 3 ) + 6] = _R; _OutputImage[( _Index << 3 ) + 7] = 0xFF; } );   Application.Current.Dispatcher.Invoke( () => { BitmapToDisplay.WritePixels( new Int32Rect( 0, 0, Sensor.ColorFrameSource.FrameDescription.Width, Sensor.ColorFrameSource.FrameDescription.Height ), _OutputImage, BitmapToDisplay.BackBufferStride, 0 ); } ); } ); } } This seemed to yield a results I wanted, but there was still the occasional stutter. This lead to what I realized was the second problem. There is a race condition between the UI Thread and me locking the WriteableBitmap so I can write the next frame. Again, I'm writing approximately 8MB to the back buffer. Then, I started thinking I could cheat. The Kinect is running at 30 frames per second. The WPF UI Thread runs at 60 frames per second. This made me not feel bad about exploiting the Composition Thread. I moved the bulk of the code from the FrameArrived handler into CompositionTarget.Rendering. Once I was in there, I polled from a frame, and rendered it if it existed. Since, in theory, I'm only killing the Composition Thread every other hit, I decided I was ok with this for cases where silky smooth video performance REALLY mattered. This ode looked like this: private byte ClipToByte( int p_ValueToClip ) { return Convert.ToByte( ( p_ValueToClip < byte.MinValue ) ? byte.MinValue : ( ( p_ValueToClip > byte.MaxValue ) ? byte.MaxValue : p_ValueToClip ) ); }   void CompositionTarget_Rendering( object sender, EventArgs e ) { using( ColorFrame _ColorFrame = FrameReader.AcquireLatestFrame() ) { if( null == _ColorFrame ) return;   byte[] _InputImage = new byte[_ColorFrame.FrameDescription.LengthInPixels * _ColorFrame.FrameDescription.BytesPerPixel]; byte[] _OutputImage = new byte[BitmapToDisplay.BackBufferStride * BitmapToDisplay.PixelHeight]; _ColorFrame.CopyRawFrameDataToArray( _InputImage );   ParallelOptions _ParallelOptions = new ParallelOptions(); _ParallelOptions.MaxDegreeOfParallelism = 4;   Parallel.For( 0, Sensor.ColorFrameSource.FrameDescription.LengthInPixels / 2, _ParallelOptions, ( _Index ) => { // See http://msdn.microsoft.com/en-us/library/windows/desktop/dd206750(v=vs.85).aspx int _Y0 = _InputImage[( _Index << 2 ) + 0] - 16; int _U = _InputImage[( _Index << 2 ) + 1] - 128; int _Y1 = _InputImage[( _Index << 2 ) + 2] - 16; int _V = _InputImage[( _Index << 2 ) + 3] - 128;   byte _R = ClipToByte( ( 298 * _Y0 + 409 * _V + 128 ) >> 8 ); byte _G = ClipToByte( ( 298 * _Y0 - 100 * _U - 208 * _V + 128 ) >> 8 ); byte _B = ClipToByte( ( 298 * _Y0 + 516 * _U + 128 ) >> 8 );   _OutputImage[( _Index << 3 ) + 0] = _B; _OutputImage[( _Index << 3 ) + 1] = _G; _OutputImage[( _Index << 3 ) + 2] = _R; _OutputImage[( _Index << 3 ) + 3] = 0xFF; // A   _R = ClipToByte( ( 298 * _Y1 + 409 * _V + 128 ) >> 8 ); _G = ClipToByte( ( 298 * _Y1 - 100 * _U - 208 * _V + 128 ) >> 8 ); _B = ClipToByte( ( 298 * _Y1 + 516 * _U + 128 ) >> 8 );   _OutputImage[( _Index << 3 ) + 4] = _B; _OutputImage[( _Index << 3 ) + 5] = _G; _OutputImage[( _Index << 3 ) + 6] = _R; _OutputImage[( _Index << 3 ) + 7] = 0xFF; } );   BitmapToDisplay.WritePixels( new Int32Rect( 0, 0, Sensor.ColorFrameSource.FrameDescription.Width, Sensor.ColorFrameSource.FrameDescription.Height ), _OutputImage, BitmapToDisplay.BackBufferStride, 0 ); } }

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• OpenJDK In The News: AMD and Oracle to Collaborate in the OpenJDK Community [..]

  - by $utils.escapeXML($entry.author)

  During the JavaOne™ 2012 Strategy Keynote, AMD (NYSE: AMD) announced its participation in OpenJDK™ Project “Sumatra” in collaboration with Oracle and other members of the OpenJDK community to help bring heterogeneous computing capabilities to Java™ for server and cloud environments. The OpenJDK Project “Sumatra” will explore how the Java Virtual Machine (JVM), as well as the Java language and APIs, might be enhanced to allow applications to take advantage of graphics processing unit (GPU) acceleration, either in discrete graphics cards or in high-performance graphics processor cores such as those found in AMD accelerated processing units (APUs).“Affirming our plans to contribute to the OpenJDK Project represents the next step towards bringing heterogeneous computing to millions of Java developers and can potentially lead to future developments of new hardware models, as well as server and cloud programming paradigms,” said Manju Hegde, corporate vice president, Heterogeneous Applications and Developer Solutions at AMD. “AMD has an established track record of collaboration with open-software development communities from OpenCL™ to the Heterogeneous System Architecture (HSA) Foundation, and with this initiative we will help further the development of graphics acceleration within the Java community.”“We expect our work with AMD and other OpenJDK participants in Project “Sumatra” will eventually help provide Java developers with the ability to quickly leverage GPU acceleration for better performance,” said Georges Saab, vice president, Software Development, Java Platform Group at Oracle. "We hope individuals and other organizations interested in this exciting development will follow AMD's lead by joining us in Project “Sumatra."Quotes taken from the first press release from AMD mentioning OpenJDK, titled "AMD and Oracle to Collaborate in the OpenJDK Community to Explore Heterogeneous Computing for Java ".

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• Datenbank in a Box

  - by A&C Redaktion

  Die Oracle Database Appliance: ein zuverlässiges, einfach zu bedienendes und erschwingliches Datenbank-System. Endlich kommt ein Datenbanksystem auf den Markt, das auf die Bedürfnisse kleinerer Unternehmen zugeschnitten ist: Oracle Database Appliance (ODA). Nicht jeder, der große Datenmengen zu verwalten hat, kann schließlich gleich zu Exadata und Co. greifen. Die kompakte „Datenbank in a Box“ kombiniert Software, Server und Speicherkapazität und bietet diverse Vernetzungsmöglichkeiten. Sie beinhaltet zwei geclusterte SunFire-Server, die unter Oracle Linux laufen, vorinstalliert ist eine Oracle Database 11g Release 2. Einer der großen ODA-Vorteile: Die Datenbank wächst mit den Bedürfnissen des Unternehmens: Die Leistungsfähigkeit des Clusters lässt sich anpassen, indem per "Pay-as-you-grow" Software-Lizensierung sukzessive zwei bis 24 Cores freigeschaltet werden können. Sie bietet außerdem hohe Verfügbarkeit für Eigen- und Standard-OLTP sowie universelle Datenbanken, auch in großer Anzahl. Für den Schutz vor Server- und Speichersystemausfällen sorgen Oracle Real Application Clusters, beziehungsweise Oracle Automatic Storage Management. Proaktive Systemüberwachung, Software-Bereitstellung auf einen Klick, integrierte Patches über den gesamten Stack und ein automatischer Call-Home bei Hardware-Ausfällen sparen Kosten und Ressourcen bei der Instandhaltung. Über das Oracle PartnerNetzwerk steht Kunden eine große Anzahl an branchenübergreifenden und -spezifischen Anwendungen zur Verfügung, die von der besseren Verfügbarkeit der Oracle Database Appliance profitieren. Auch die Fachpresse setzt sich mit der neuen Oracle Database Appliance auseinander: Ausführlich berichten unter anderem die Computerwoche und heise online. Das Admin-Magazin bietet eine kurze aber treffende Übersicht. Eine ebenfalls anschauliche, etwas ausführlichere Darstellung bietet die Webseite von DOAG e.V. Im Webcast zur Oracle Database Appliance geht Judson Althoff unter anderem auf deren Bedeutung für das Partner-Business ein:

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• What is the best way to exploit multicores when making multithread games?

  - by Keeper

  Many people suggest to write a program, and then start optimizing it. But I think that when it's coming to multithreading with multicore, a little think ahead is required. I've read about using threads, and experienced it myself during some courses at the university (still a student). The big question is simple, but a bit abstract: What thread related steps in game design do I need to take, before implementation? Now trying to be more specific. Let's say, as an example, that I'm making a small board game (like Monopoly) that I want to be multithreaded. My goal Is that this multithreaded game will exploit the best of the multicore system, lets say 4-6 cores (like in i7 processors). My answer to this question at the moment is, one thread for each of these four basic components: GUI User Input / Output AI (computer rival) Other game related calculations (like shortest path from A to B, or level up status change) I'm not an expert (yet!), and I'm sure there are better answers out there. Any suggestion, answer, different approach will be helpful. Some thoughts: Maybe splitting the main database is a good way.. (or total disaster.. )

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• Is it worth moving from Microsoft tech to Linux, NodeJS & other open source frameworks to save money for a start-up?

  - by dormisher

  I am currently getting involved in a startup, I am the only developer involved at the moment, and the other guys are leaving all the tech decisions up to me at the moment. For my day job I work at a software house that uses Microsoft tech on a day to day basis, we utilise .NET, SqlServer, Windows Server etc. However, I realise that as a startup we need to keep costs down, and after having a brief look at the cost of hosting for Windows I was shocked to see some of the prices for a dedicated server. The cheapest I found was £100 a month. Also if the business needs to scale in the future and we end up needing multiple servers, we could end up shelling out £10's of £000's a year in SQL Server / Windows Server licenses etc. I then had a quick look at the price of Linux hosting for a dedicated server and saw the price was waaaaaay lower than windows hosting. One place was offering a machine with 2 cores for less than £20 a month. This got me thinking maybe the way to go is open source on Linux. As I write a lot of Javascript at work (I'm working on a single page backbone app at the moment), I thought maybe NodeJS and a web framework like Express would be cool to use. I then thought that instead of using SQL why not use an open source NoSQL database like MongoDB, which has great support on NodeJS? My only concern is that some of the work the application is going to do is going to be dynamically building images and various other image related stuff, i.e. stuff that is quite CPU heavy - so I'm thinking of maybe writing anything CPU heavy in C++ and consuming it as a module in Node. That's the background - but basically is Linux a good match for: Hosting a NodeJS/Express site? Compiling C++ node modules? Using a NoSQL DB like MongoDB? And is it a good idea to move to these unfamiliar technologies to save money?

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• Dim (NEARLY blank) laptop screen, secondary screen works - why?

  - by LIttle Ancient Forest Kami

  My laptop screen is (almost) black while my secondary screen is fine. I believe it to be backlight / brightness related. Problem description it starts when I start the laptop system loads and works fine, just screen has problems I can see the screen though very faintly / dimly - it's hard to see anything which ain't very white e.g. starting screen has big Thinkpad logo in white, large font - I can see it, though very dimly second screen works very well Official backligtht debugging: using acpi setting as prescribed there for Thinkpads didn't help I can see an entry in /sys/class/backlight/ and it changes when I press hotkeys for brightness (current backlight power for instance goes up or down) acpi-off didn't helpm neither did acpi_backlight=vendor Hardware data Laptop is Thinkpad Edge with glossy screen. 4 processors, 2 cores, exemplary CPU data from cat /proc/cpuinfo reports Genuine Intel i5 (M 480 @ 2.67GHz). OS is Ubuntu Lucid, 10.04 LTS, 64-bit, with Linux generic kernel (2.6.32-44) and GNOME 2.32.2 (though I doubt there lies the problem). $ lspci | grep VGA 01:00.0 VGA compatible controller: ATI Technologies Inc M92 [Mobility Radeon HD 4500 Series] $ lshw -C display *-display description: VGA compatible controller product: M92 [Mobility Radeon HD 4500 Series] vendor: ATI Technologies Inc physical id: 0 bus info: pci@0000:01:00.0 version: 00 width: 32 bits clock: 33MHz capabilities: pm pciexpress msi bus_master cap_list rom configuration: driver=radeon latency=0 resources: irq:33 memory:c0000000-dfffffff(prefetchable) ioport:2000(size=256) memory:f0300000-f030ffff memory:f0320000-f033ffff(prefetchable) Driver I was NOT running any proprietary drivers, just checked with "Hardware drivers". There is one for ATI that is suggested there, though I didn't need it so far. UPDATE: changing the driver to proprietary one (ATI/AMD FGLRX) didn't help. Tried and failed Resetting / running on power or battery / charging / getting rid of static electricity / warming up *doesn't help* This is NOT a blank-screen problem, at least it isn't following official Ubuntu black-screen diagnostics - I can see my screen, though barely. What I will try next: - check last updates I've made - IIRC I am running on nomodeset already, but will verify this Any ideas how to proceed best? What is most probable cause?

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• Impact of Server Failure on Coherence Request Processing

  - by jpurdy

  Requests against a given cache server may be temporarily blocked for several seconds following the failure of other cluster members. This may cause issues for applications that can not tolerate multi-second response times even during failover processing (ignoring for the moment that in practice there are a variety of issues that make such absolute guarantees challenging even when there are no server failures). In general, Coherence is designed around the principle that failures in one member should not affect the rest of the cluster if at all possible. However, it's obvious that if that failed member was managing a piece of state that another member depends on, the second member will need to wait until a new member assumes responsibility for managing that state. This transfer of responsibility is (as of Coherence 3.7) performed by the primary service thread for each cache service. The finest possible granularity for transferring responsibility is a single partition. So the question becomes how to minimize the time spent processing each partition. Here are some optimizations that may reduce this period: Reduce the size of each partition (by increasing the partition count) Increase the number of JVMs across the cluster (increasing the total number of primary service threads) Increase the number of CPUs across the cluster (making sure that each JVM has a CPU core when needed) Re-evaluate the set of configured indexes (as these will need to be rebuilt when a partition moves) Make sure that the backing map is as fast as possible (in most cases this means running on-heap) Make sure that the cluster is running on hardware with fast CPU cores (since the partition processing is single-threaded) As always, proper testing is required to make sure that configuration changes have the desired effect (and also to quantify that effect).

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• Less graphics power all the sudden (Intel HD 3000)

  - by queueoverflow

  I have a Intel Sandy Bridge i5 with the HD 3000 graphics card. I used to be able to play Urban Terror and Nexuiz comfortably with 85 and 60 frames per seconds until mid/end of October 2012, the former even on a full HD display with that many frames. Now I have around 30 to 45 on the smaller laptop screen and around 20 to 30 on the external monitor. Did something happen to Kubuntu 12.04 so that it has less graphics performance than previously? Update I looked into the system monitor and could not detect anything being at the maximum. The four CPU cores were pretty much bored, the 8 GB RAM were filled with maybe 2 GB. And I ran intel_cpu_top and did not notice anything at its limit. See the output. after Kernel bisecting I now did a kernel bisect and tried 3.2.0-23, 3.2.0-27, 3.2.0-29 and 3.2.0-30 and all had full graphics power. Interestingly, I then had full power when I just booted back into the regular 3.2.0-32 kernel. This does not make sense to me …

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• Hitching and Slowness Due to HDD Activity on Ubuntu, But Not Windows?

  - by Espionage724

  It's been bothering me for months now, but I've noticed in Ubuntu (or any distro of Linux I've tried), any major I/O activity will cause hitching and general slowness. For example, if I try doing a file transfer from my network computer to the computer I'm using and try moving the mouse after a while, it might not respond for a second or so. Similar incidents occur in other cases too (right-clicking to get a context menu takes a few seconds, hitting the drop-down application bar takes a while, etc). My HDD isn't top-notch (a WD Blue 500GB 7200RPM drive) but I don't recall it being nearly this bad in Windows 7, 8, or 8.1. CPU activity during file transfers is relatively low (less than 10-20% on all cores of a Phenom II X4 @ 3.3Ghz). I'm using Gnome System Monitor (on Xubuntu) and can't seem to see what kind of HDD activity is occurring though. I have 8GB of RAM too, which is moderately being used (2.5GB), but shouldn't be a problem either. Any ideas what's up? I've tried kernels between 3.8 and 3.11 (i'm using saucy currently with 3.11).

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• Oracle regains the #1 UNIX Shipments Marketshare

  - by EricReid-Oracle

  Oracle has regained the #1 UNIX Server Shipments spot! According to IDC, Oracle’s share was 33.6%, up from 32.7% in the year ago period, and 32.2% in C4Q13:  IDC: WW Unix Unit Shipments, Share, Growth 2013Q1 Share 2013Q4 Share 2014Q1 Share Sequential Growth Y/Y Growth Oracle 10,141 32.7% 10,294 32.2% 8,355 33.6% -18.8% -17.6% IBM 10,203 32.9% 11,533 36.0% 6,919 27.8% -40.0% -32.2% HP 7,046 22.7% 6,786 21.2% 6,549 26.4% -3.5% -7.1% Fujitsu 1,174 3.8% 1,141 3.6% 1,069 4.3% -6.3% -8.9% Dell 565 1.8% 499 1.6% 519 2.1% 4.0% -8.2% NEC 69 0.2% 81 0.3% 63 0.3% -22.5% -9.4% Others 1,804 5.8% 1,684 5.3% 1,380 5.6% -18.1% -23.5% Total Market 31,002 100.0% 32,018 100.0% 24,854 100.0% -22.4% -19.8% While the UNIX server space is currently undergoing some contraction (on a pure numbers basis), this can be traced in part to an overall consolidation trend, due to the greatly-increased price-performance of our systems. Consider this: one SPARC T5-4 system has 1/16th the number of sockets and 1/192nd the number of cores of the previous high-end M9000-64 system -- all at 5X the price-performance. SPARC. Solaris. Nuff' said.

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• Windows Azure: General Availability of Web Sites + Mobile Services, New AutoScale + Alerts Support, No Credit Card Needed for MSDN

  - by ScottGu

  This morning we released a major set of updates to Windows Azure.  These updates included: Web Sites: General Availability Release of Windows Azure Web Sites with SLA Mobile Services: General Availability Release of Windows Azure Mobile Services with SLA Auto-Scale: New automatic scaling support for Web Sites, Cloud Services and Virtual Machines Alerts/Notifications: New email alerting support for all Compute Services (Web Sites, Mobile Services, Cloud Services, and Virtual Machines) MSDN: No more credit card requirement for sign-up All of these improvements are now available to use immediately (note: some are still in preview).  Below are more details about them. Web Sites: General Availability Release of Windows Azure Web Sites I’m incredibly excited to announce the General Availability release of Windows Azure Web Sites. The Windows Azure Web Sites service is perfect for hosting a web presence, building customer engagement solutions, and delivering business web apps.  Today’s General Availability release means we are taking off the “preview” tag from the Free and Standard (formerly called reserved) tiers of Windows Azure Web Sites.  This means we are providing: A 99.9% monthly SLA (Service Level Agreement) for the Standard tier Microsoft Support available on a 24x7 basis (with plans that range from developer plans to enterprise Premier support) The Free tier runs in a shared compute environment and supports up to 10 web sites. While the Free tier does not come with an SLA, it works great for rapid development and testing and enables you to quickly spike out ideas at no cost. The Standard tier, which was called “Reserved” during the preview, runs using dedicated per-customer VM instances for great performance, isolation and scalability, and enables you to host up to 500 different Web sites within them.  You can easily scale your Standard instances on-demand using the Windows Azure Management Portal.  You can adjust VM instance sizes from a Small instance size (1 core, 1.75GB of RAM), up to a Medium instance size (2 core, 3.5GB of RAM), or Large instance (4 cores and 7 GB RAM).  You can choose to run between 1 and 10 Standard instances, enabling you to easily scale up your web backend to 40 cores of CPU and 70GB of RAM: Today’s release also includes general availability support for custom domain SSL certificate bindings for web sites running using the Standard tier. Customers will be able to utilize certificates they purchase for their custom domains and use either SNI or IP based SSL encryption. SNI encryption is available for all modern browsers and does not require an IP address.  SSL certificates can be used for individual sites or wild-card mapped across multiple sites (we charge extra for the use of a SSL cert – but the fee is per-cert and not per site which means you pay once for it regardless of how many sites you use it with).  Today’s release also includes the following new features: Auto-Scale support Today’s Windows Azure release adds preview support for Auto-Scaling web sites.  This enables you to setup automatic scale rules based on the activity of your instances – allowing you to automatically scale down (and save money) when they are below a CPU threshold you define, and automatically scale up quickly when traffic increases.  See below for more details. 64-bit and 32-bit mode support You can now choose to run your standard tier instances in either 32-bit or 64-bit mode (previously they only ran in 32-bit mode).  This enables you to address even more memory within individual web applications. Memory dumps Memory dumps can be very useful for diagnosing issues and debugging apps. Using a REST API, you can now get a memory dump of your sites, which you can then use for investigating issues in Visual Studio Debugger, WinDbg, and other tools. Scaling Sites Independently Prior to today’s release, all sites scaled up/down together whenever you scaled any site in a sub-region. So you may have had to keep your proof-of-concept or testing sites in a separate sub-region if you wanted to keep them in the Free tier. This will no longer be necessary.  Windows Azure Web Sites can now mix different tier levels in the same geographic sub-region. This allows you, for example, to selectively move some of your sites in the West US sub-region up to Standard tier when they require the features, scalability, and SLA of the Standard tier. Full pricing details on Windows Azure Web Sites can be found here.  Note that the “Shared Tier” of Windows Azure Web Sites remains in preview mode (and continues to have discounted preview pricing).  Mobile Services: General Availability Release of Windows Azure Mobile Services I’m incredibly excited to announce the General Availability release of Windows Azure Mobile Services.  Mobile Services is perfect for building scalable cloud back-ends for Windows 8.x, Windows Phone, Apple iOS, Android, and HTML/JavaScript applications.  Customers We’ve seen tremendous adoption of Windows Azure Mobile Services since we first previewed it last September, and more than 20,000 customers are now running mobile back-ends in production using it.  These customers range from startups like Yatterbox, to university students using Mobile Services to complete apps like Sly Fox in their spare time, to media giants like Verdens Gang finding new ways to deliver content, and telcos like TalkTalk Business delivering the up-to-the-minute information their customers require.  In today’s Build keynote, we demonstrated how TalkTalk Business is using Windows Azure Mobile Services to deliver service, outage and billing information to its customers, wherever they might be. Partners When we unveiled the source control and Custom API features I blogged about two weeks ago, we enabled a range of new scenarios, one of which is a more flexible way to work with third party services.  The following blogs, samples and tutorials from our partners cover great ways you can extend Mobile Services to help you build rich modern apps: New Relic allows developers to monitor and manage the end-to-end performance of iOS and Android applications connected to Mobile Services. SendGrid eliminates the complexity of sending email from Mobile Services, saving time and money, while providing reliable delivery to the inbox. Twilio provides a telephony infrastructure web service in the cloud that you can use with Mobile Services to integrate phone calls, text messages and IP voice communications into your mobile apps. Xamarin provides a Mobile Services add on to make it easy building cross-platform connected mobile aps. Pusher allows quickly and securely add scalable real-time messaging functionality to Mobile Services-based web and mobile apps. Visual Studio 2013 and Windows 8.1 This week during //build/ keynote, we demonstrated how Visual Studio 2013, Mobile Services and Windows 8.1 make building connected apps easier than ever. Developers building Windows 8 applications in Visual Studio can now connect them to Windows Azure Mobile Services by simply right clicking then choosing Add Connected Service. You can either create a new Mobile Service or choose existing Mobile Service in the Add Connected Service dialog. Once completed, Visual Studio adds a reference to Mobile Services SDK to your project and generates a Mobile Services client initialization snippet automatically. Add Push Notifications Push Notifications and Live Tiles are a key to building engaging experiences. Visual Studio 2013 and Mobile Services make it super easy to add push notifications to your Windows 8.1 app, by clicking Add a Push Notification item: The Add Push Notification wizard will then guide you through the registration with the Windows Store as well as connecting your app to a new or existing mobile service. Upon completion of the wizard, Visual Studio will configure your mobile service with the WNS credentials, as well as add sample logic to your client project and your mobile service that demonstrates how to send push notifications to your app. Server Explorer Integration In Visual Studio 2013 you can also now view your Mobile Services in the the Server Explorer. You can add tables, edit, and save server side scripts without ever leaving Visual Studio, as shown on the image below: Pricing With today’s general availability release we are announcing that we will be offering Mobile Services in three tiers – Free, Standard, and Premium.  Each tier is metered using a simple pricing model based on the # of API calls (bandwidth is included at no extra charge), and the Standard and Premium tiers are backed by 99.9% monthly SLAs.  You can elastically scale up or down the number of instances you have of each tier to increase the # of API requests your service can support – allowing you to efficiently scale as your business grows. The following table summarizes the new pricing model (full pricing details here):   You can find the full details of the new pricing model here. Build Conference Talks The //BUILD/ conference will be packed with sessions covering every aspect of developing connected applications with Mobile Services. The best part is that, even if you can’t be with us in San Francisco, every session is being streamed live. Be sure not to miss these talks: Mobile Services – Soup to Nuts — Josh Twist Building Cross-Platform Apps with Windows Azure Mobile Services — Chris Risner Connected Windows Phone Apps made Easy with Mobile Services — Yavor Georgiev Build Connected Windows 8.1 Apps with Mobile Services — Nick Harris Who’s that user? Identity in Mobile Apps — Dinesh Kulkarni Building REST Services with JavaScript — Nathan Totten Going Live and Beyond with Windows Azure Mobile Services — Kirill Gavrylyuk , Paul Batum Protips for Windows Azure Mobile Services — Chris Risner AutoScale: Dynamically scale up/down your app based on real-world usage One of the key benefits of Windows Azure is that you can dynamically scale your application in response to changing demand. In the past, though, you have had to either manually change the scale of your application, or use additional tooling (such as WASABi or MetricsHub) to automatically scale your application. Today, we’re announcing that AutoScale will be built-into Windows Azure directly.  With today’s release it is now enabled for Cloud Services, Virtual Machines and Web Sites (Mobile Services support will come soon). Auto-scale enables you to configure Windows Azure to automatically scale your application dynamically on your behalf (without any manual intervention) so you can achieve the ideal performance and cost balance. Once configured it will regularly adjust the number of instances running in response to the load in your application. Currently, we support two different load metrics: CPU percentage Storage queue depth (Cloud Services and Virtual Machines only) We’ll enable automatic scaling on even more scale metrics in future updates. When to use Auto-Scale The following are good criteria for services/apps that will benefit from the use of auto-scale: The service/app can scale horizontally (e.g. it can be duplicated to multiple instances) The service/app load changes over time If your app meets these criteria, then you should look to leverage auto-scale. How to Enable Auto-Scale To enable auto-scale, simply navigate to the Scale tab in the Windows Azure Management Portal for the app/service you wish to enable.  Within the scale tab turn the Auto-Scale setting on to either CPU or Queue (for Cloud Services and VMs) to enable Auto-Scale.  Then change the instance count and target CPU settings to configure the Auto-Scale ranges you want to maintain. The image below demonstrates how to enable Auto-Scale on a Windows Azure Web-Site.  I’ve configured the web-site so that it will run using between 1 and 5 VM instances.  The exact # used will depend on the aggregate CPU of the VMs using the 40-70% range I’ve configured below.  If the aggregate CPU goes above 70%, then Windows Azure will automatically add new VMs to the pool (up to the maximum of 5 instances I’ve configured it to use).  If the aggregate CPU drops below 40% then Windows Azure will automatically start shutting down VMs to save me money: Once you’ve turned auto-scale on, you can return to the Scale tab at any point and select Off to manually set the number of instances. Using the Auto-Scale Preview With today’s update you can now, in just a few minutes, have Windows Azure automatically adjust the number of instances you have running  in your apps to keep your service performant at an even better cost. Auto-scale is being released today as a preview feature, and will be free until General Availability. During preview, each subscription is limited to 10 separate auto-scale rules across all of the resources they have (Web sites, Cloud services or Virtual Machines). If you hit the 10 limit, you can disable auto-scale for any resource to enable it for another. Alerts and Notifications Starting today we are now providing the ability to configure threshold based alerts on monitoring metrics. This feature is available for compute services (cloud services, VM, websites and mobiles services). Alerts provide you the ability to get proactively notified of active or impending issues within your application.  You can define alert rules for: Virtual machine monitoring metrics that are collected from the host operating system (CPU percentage, network in/out, disk read bytes/sec and disk write bytes/sec) and on monitoring metrics from monitoring web endpoint urls (response time and uptime) that you have configured. Cloud service monitoring metrics that are collected from the host operating system (same as VM), monitoring metrics from the guest VM (from performance counters within the VM) and on monitoring metrics from monitoring web endpoint urls (response time and uptime) that you have configured. For Web Sites and Mobile Services, alerting rules can be configured on monitoring metrics from monitoring endpoint urls (response time and uptime) that you have configured. Creating Alert Rules You can add an alert rule for a monitoring metric by navigating to the Setting -> Alerts tab in the Windows Azure Management Portal. Click on the Add Rule button to create an alert rule. Give the alert rule a name and optionally add a description. Then pick the service which you want to define the alert rule on: The next step in the alert creation wizard will then filter the monitoring metrics based on the service you selected:   Once created the rule will show up in your alerts list within the settings tab: The rule above is defined as “not activated” since it hasn’t tripped over the CPU threshold we set.  If the CPU on the above machine goes over the limit, though, I’ll get an email notifying me from an Windows Azure Alerts email address ([email protected]). And when I log into the portal and revisit the alerts tab I’ll see it highlighted in red.  Clicking it will then enable me to see what is causing it to fail, as well as view the history of when it has happened in the past. Alert Notifications With today’s initial preview you can now easily create alerting rules based on monitoring metrics and get notified on active or impending issues within your application that require attention. During preview, each subscription is limited to 10 alert rules across all of the services that support alert rules. No More Credit Card Requirement for MSDN Subscribers Earlier this month (during TechEd 2013), Windows Azure announced that MSDN users will get Windows Azure Credits every month that they can use for any Windows Azure services they want. You can read details about this in my previous Dev/Test blog post. Today we are making further updates to enable an easier Windows Azure signup for MSDN users. MSDN users will now not be required to provide payment information (e.g. no credit card) during sign-up, so long as they use the service within the included monetary credit for the billing period. For usage beyond the monetary credit, they can enable overages by providing the payment information and remove the spending limit. This enables a super easy, one page sign-up experience for MSDN users.  Simply sign-up for your Windows Azure trial using the same Microsoft ID that you use to manage your MSDN account, then complete the one page sign-up form below and you will be able to spend your free monthly MSDN credits (up to $150 each month) on any Windows Azure resource for dev/test:   This makes it trivially easy for every MDSN customer to start using Windows Azure today.  If you haven’t signed up yet, I definitely recommend checking it out. Summary Today’s release includes a ton of great features that enable you to build even better cloud solutions.  If you don’t already have a Windows Azure account, you can sign-up for a free trial and start using all of the above features today.  Then visit the Windows Azure Developer Center to learn more about how to build apps with it. Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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• How to Load Oracle Tables From Hadoop Tutorial (Part 5 - Leveraging Parallelism in OSCH)

  - by Bob Hanckel

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Using OSCH: Beyond Hello World In the previous post we discussed a “Hello World” example for OSCH focusing on the mechanics of getting a toy end-to-end example working. In this post we are going to talk about how to make it work for big data loads. We will explain how to optimize an OSCH external table for load, paying particular attention to Oracle’s DOP (degree of parallelism), the number of external table location files we use, and the number of HDFS files that make up the payload. We will provide some rules that serve as best practices when using OSCH. The assumption is that you have read the previous post and have some end to end OSCH external tables working and now you want to ramp up the size of the loads. Using OSCH External Tables for Access and Loading OSCH external tables are no different from any other Oracle external tables.  They can be used to access HDFS content using Oracle SQL: SELECT * FROM my_hdfs_external_table; or use the same SQL access to load a table in Oracle. INSERT INTO my_oracle_table SELECT * FROM my_hdfs_external_table; To speed up the load time, you will want to control the degree of parallelism (i.e. DOP) and add two SQL hints. ALTER SESSION FORCE PARALLEL DML PARALLEL  8; ALTER SESSION FORCE PARALLEL QUERY PARALLEL 8; INSERT /*+ append pq_distribute(my_oracle_table, none) */ INTO my_oracle_table SELECT * FROM my_hdfs_external_table; There are various ways of either hinting at what level of DOP you want to use.  The ALTER SESSION statements above force the issue assuming you (the user of the session) are allowed to assert the DOP (more on that in the next section).  Alternatively you could embed additional parallel hints directly into the INSERT and SELECT clause respectively. /*+ parallel(my_oracle_table,8) *//*+ parallel(my_hdfs_external_table,8) */ Note that the "append" hint lets you load a target table by reserving space above a given "high watermark" in storage and uses Direct Path load.  In other doesn't try to fill blocks that are already allocated and partially filled. It uses unallocated blocks.  It is an optimized way of loading a table without incurring the typical resource overhead associated with run-of-the-mill inserts.  The "pq_distribute" hint in this context unifies the INSERT and SELECT operators to make data flow during a load more efficient. Finally your target Oracle table should be defined with "NOLOGGING" and "PARALLEL" attributes.   The combination of the "NOLOGGING" and use of the "append" hint disables REDO logging, and its overhead.  The "PARALLEL" clause tells Oracle to try to use parallel execution when operating on the target table. Determine Your DOP It might feel natural to build your datasets in Hadoop, then afterwards figure out how to tune the OSCH external table definition, but you should start backwards. You should focus on Oracle database, specifically the DOP you want to use when loading (or accessing) HDFS content using external tables. The DOP in Oracle controls how many PQ slaves are launched in parallel when executing an external table. Typically the DOP is something you want to Oracle to control transparently, but for loading content from Hadoop with OSCH, it's something that you will want to control. Oracle computes the maximum DOP that can be used by an Oracle user. The maximum value that can be assigned is an integer value typically equal to the number of CPUs on your Oracle instances, times the number of cores per CPU, times the number of Oracle instances. For example, suppose you have a RAC environment with 2 Oracle instances. And suppose that each system has 2 CPUs with 32 cores. The maximum DOP would be 128 (i.e. 2*2*32). In point of fact if you are running on a production system, the maximum DOP you are allowed to use will be restricted by the Oracle DBA. This is because using a system maximum DOP can subsume all system resources on Oracle and starve anything else that is executing. Obviously on a production system where resources need to be shared 24x7, this can’t be allowed to happen. The use cases for being able to run OSCH with a maximum DOP are when you have exclusive access to all the resources on an Oracle system. This can be in situations when your are first seeding tables in a new Oracle database, or there is a time where normal activity in the production database can be safely taken off-line for a few hours to free up resources for a big incremental load. Using OSCH on high end machines (specifically Oracle Exadata and Oracle BDA cabled with Infiniband), this mode of operation can load up to 15TB per hour. The bottom line is that you should first figure out what DOP you will be allowed to run with by talking to the DBAs who manage the production system. You then use that number to derive the number of location files, and (optionally) the number of HDFS data files that you want to generate, assuming that is flexible. Rule 1: Find out the maximum DOP you will be allowed to use with OSCH on the target Oracle system Determining the Number of Location Files Let’s assume that the DBA told you that your maximum DOP was 8. You want the number of location files in your external table to be big enough to utilize all 8 PQ slaves, and you want them to represent equally balanced workloads. Remember location files in OSCH are metadata lists of HDFS files and are created using OSCH’s External Table tool. They also represent the workload size given to an individual Oracle PQ slave (i.e. a PQ slave is given one location file to process at a time, and only it will process the contents of the location file.) Rule 2: The size of the workload of a single location file (and the PQ slave that processes it) is the sum of the content size of the HDFS files it lists For example, if a location file lists 5 HDFS files which are each 100GB in size, the workload size for that location file is 500GB. The number of location files that you generate is something you control by providing a number as input to OSCH’s External Table tool. Rule 3: The number of location files chosen should be a small multiple of the DOP Each location file represents one workload for one PQ slave. So the goal is to keep all slaves busy and try to give them equivalent workloads. Obviously if you run with a DOP of 8 but have 5 location files, only five PQ slaves will have something to do and the other three will have nothing to do and will quietly exit. If you run with 9 location files, then the PQ slaves will pick up the first 8 location files, and assuming they have equal work loads, will finish up about the same time. But the first PQ slave to finish its job will then be rescheduled to process the ninth location file, potentially doubling the end to end processing time. So for this DOP using 8, 16, or 32 location files would be a good idea. Determining the Number of HDFS Files Let’s start with the next rule and then explain it: Rule 4: The number of HDFS files should try to be a multiple of the number of location files and try to be relatively the same size In our running example, the DOP is 8. This means that the number of location files should be a small multiple of 8. Remember that each location file represents a list of unique HDFS files to load, and that the sum of the files listed in each location file is a workload for one Oracle PQ slave. The OSCH External Table tool will look in an HDFS directory for a set of HDFS files to load.  It will generate N number of location files (where N is the value you gave to the tool). It will then try to divvy up the HDFS files and do its best to make sure the workload across location files is as balanced as possible. (The tool uses a greedy algorithm that grabs the biggest HDFS file and delegates it to a particular location file. It then looks for the next biggest file and puts in some other location file, and so on). The tools ability to balance is reduced if HDFS file sizes are grossly out of balance or are too few. For example suppose my DOP is 8 and the number of location files is 8. Suppose I have only 8 HDFS files, where one file is 900GB and the others are 100GB. When the tool tries to balance the load it will be forced to put the singleton 900GB into one location file, and put each of the 100GB files in the 7 remaining location files. The load balance skew is 9 to 1. One PQ slave will be working overtime, while the slacker PQ slaves are off enjoying happy hour. If however the total payload (1600 GB) were broken up into smaller HDFS files, the OSCH External Table tool would have an easier time generating a list where each workload for each location file is relatively the same.  Applying Rule 4 above to our DOP of 8, we could divide the workload into160 files that were approximately 10 GB in size.  For this scenario the OSCH External Table tool would populate each location file with 20 HDFS file references, and all location files would have similar workloads (approximately 200GB per location file.) As a rule, when the OSCH External Table tool has to deal with more and smaller files it will be able to create more balanced loads. How small should HDFS files get? Not so small that the HDFS open and close file overhead starts having a substantial impact. For our performance test system (Exadata/BDA with Infiniband), I compared three OSCH loads of 1 TiB. One load had 128 HDFS files living in 64 location files where each HDFS file was about 8GB. I then did the same load with 12800 files where each HDFS file was about 80MB size. The end to end load time was virtually the same. However when I got ridiculously small (i.e. 128000 files at about 8MB per file), it started to make an impact and slow down the load time. What happens if you break rules 3 or 4 above? Nothing draconian, everything will still function. You just won’t be taking full advantage of the generous DOP that was allocated to you by your friendly DBA. The key point of the rules articulated above is this: if you know that HDFS content is ultimately going to be loaded into Oracle using OSCH, it makes sense to chop them up into the right number of files roughly the same size, derived from the DOP that you expect to use for loading. Next Steps So far we have talked about OLH and OSCH as alternative models for loading. That’s not quite the whole story. They can be used together in a way that provides for more efficient OSCH loads and allows one to be more flexible about scheduling on a Hadoop cluster and an Oracle Database to perform load operations. The next lesson will talk about Oracle Data Pump files generated by OLH, and loaded using OSCH. It will also outline the pros and cons of using various load methods.  This will be followed up with a final tutorial lesson focusing on how to optimize OLH and OSCH for use on Oracle's engineered systems: specifically Exadata and the BDA. /* 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-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}

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• More interruptions than cpu context switches

  - by Christopher Valles

  I have a machine running Debian GNU/Linux 5.0.8 (lenny) 8 cores and 12Gb of RAM. We have one core permanently around 40% ~ 60% wait time and trying to spot what is happening I realized that we have more interruptions than cpu context switches. I found that the normal ratio between context switch and interruptions is around 10x more context switching than interruptions but on my server the values are completely different. backend1:~# vmstat -s 12330788 K total memory 12221676 K used memory 3668624 K active memory 6121724 K inactive memory 109112 K free memory 3929400 K buffer memory 4095536 K swap cache 4194296 K total swap 7988 K used swap 4186308 K free swap 44547459 non-nice user cpu ticks 702408 nice user cpu ticks 13346333 system cpu ticks 1607583668 idle cpu ticks 374043393 IO-wait cpu ticks 4144149 IRQ cpu ticks 3994255 softirq cpu ticks 0 stolen cpu ticks 4445557114 pages paged in 2910596714 pages paged out 128642 pages swapped in 267400 pages swapped out 3519307319 interrupts 2464686911 CPU context switches 1306744317 boot time 11555115 forks Any ideas if that is an issue? And in that case, how can I spot the cause and fix it? Update Following the instructions of the comments and focusing on the core stuck in wait I checked the processes attached to that core and below you can find the list: PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ P COMMAND 24 root RT -5 0 0 0 S 0 0.0 0:03.42 7 migration/7 25 root 15 -5 0 0 0 S 0 0.0 0:04.78 7 ksoftirqd/7 26 root RT -5 0 0 0 S 0 0.0 0:00.00 7 watchdog/7 34 root 15 -5 0 0 0 S 0 0.0 1:18.90 7 events/7 83 root 15 -5 0 0 0 S 0 0.0 1:10.68 7 kblockd/7 291 root 15 -5 0 0 0 S 0 0.0 0:00.00 7 aio/7 569 root 15 -5 0 0 0 S 0 0.0 0:00.00 7 ata/7 1545 root 15 -5 0 0 0 S 0 0.0 0:00.00 7 ksnapd 1644 root 15 -5 0 0 0 S 0 0.0 0:36.73 7 kjournald 1725 root 16 -4 16940 1152 488 S 0 0.0 0:00.00 7 udevd 2342 root 20 0 8828 1140 956 S 0 0.0 0:00.00 7 sh 2375 root 20 0 8848 1220 1016 S 0 0.0 0:00.00 7 locate 2421 root 30 10 8896 1268 1016 S 0 0.0 0:00.00 7 updatedb.findut 2430 root 30 10 58272 49m 616 S 0 0.4 0:17.44 7 sort 2431 root 30 10 3792 448 360 S 0 0.0 0:00.00 7 frcode 2682 root 15 -5 0 0 0 S 0 0.0 3:25.98 7 kjournald 2683 root 15 -5 0 0 0 S 0 0.0 0:00.64 7 kjournald 2687 root 15 -5 0 0 0 S 0 0.0 1:31.30 7 kjournald 3261 root 15 -5 0 0 0 S 0 0.0 2:30.56 7 kondemand/7 3364 root 20 0 3796 596 476 S 0 0.0 0:00.00 7 acpid 3575 root 20 0 8828 1140 956 S 0 0.0 0:00.00 7 sh 3597 root 20 0 8848 1216 1016 S 0 0.0 0:00.00 7 locate 3603 root 30 10 8896 1268 1016 S 0 0.0 0:00.00 7 updatedb.findut 3612 root 30 10 58272 49m 616 S 0 0.4 0:27.04 7 sort 3655 root 20 0 11056 2852 516 S 0 0.0 5:36.46 7 redis-server 3706 root 20 0 19832 1056 816 S 0 0.0 0:01.64 7 cron 3746 root 20 0 3796 580 484 S 0 0.0 0:00.00 7 getty 3748 root 20 0 3796 580 484 S 0 0.0 0:00.00 7 getty 7674 root 20 0 28376 1000 736 S 0 0.0 0:00.00 7 cron 7675 root 20 0 8828 1140 956 S 0 0.0 0:00.00 7 sh 7708 root 30 10 58272 49m 616 S 0 0.4 0:03.36 7 sort 22049 root 20 0 8828 1136 956 S 0 0.0 0:00.00 7 sh 22095 root 20 0 8848 1220 1016 S 0 0.0 0:00.00 7 locate 22099 root 30 10 8896 1264 1016 S 0 0.0 0:00.00 7 updatedb.findut 22108 root 30 10 58272 49m 616 S 0 0.4 0:44.55 7 sort 22109 root 30 10 3792 452 360 S 0 0.0 0:00.00 7 frcode 26927 root 20 0 8828 1140 956 S 0 0.0 0:00.00 7 sh 26947 root 20 0 8848 1216 1016 S 0 0.0 0:00.00 7 locate 26951 root 30 10 8896 1268 1016 S 0 0.0 0:00.00 7 updatedb.findut 26960 root 30 10 58272 49m 616 S 0 0.4 0:10.24 7 sort 26961 root 30 10 3792 452 360 S 0 0.0 0:00.00 7 frcode 27952 root 20 0 65948 3028 2400 S 0 0.0 0:00.00 7 sshd 30731 root 20 0 0 0 0 S 0 0.0 0:01.34 7 pdflush 31204 root 20 0 0 0 0 S 0 0.0 0:00.24 7 pdflush 21857 deploy 20 0 1227m 2240 868 S 0 0.0 2:44.22 7 nginx 21858 deploy 20 0 1228m 2784 868 S 0 0.0 2:42.45 7 nginx 21862 deploy 20 0 1228m 2732 868 S 0 0.0 2:43.90 7 nginx 21869 deploy 20 0 1228m 2840 868 S 0 0.0 2:44.14 7 nginx 27994 deploy 20 0 19372 2216 1380 S 0 0.0 0:00.00 7 bash 28493 deploy 20 0 331m 32m 16m S 4 0.3 0:00.40 7 apache2 21856 deploy 20 0 1228m 2844 868 S 0 0.0 2:43.64 7 nginx 3622 nobody 30 10 21156 10m 916 D 0 0.1 4:42.31 7 find 7716 nobody 30 10 12268 1280 888 D 0 0.0 0:43.50 7 find 22116 nobody 30 10 12612 1696 916 D 0 0.0 6:32.26 7 find 26968 nobody 30 10 12268 1284 888 D 0 0.0 1:56.92 7 find Update As suggested I take a look at /proc/interrupts and below the info there: CPU0 CPU1 CPU2 CPU3 CPU4 CPU5 CPU6 CPU7 0: 35 0 0 1469085485 0 0 0 0 IO-APIC-edge timer 1: 0 0 0 8 0 0 0 0 IO-APIC-edge i8042 8: 0 0 0 1 0 0 0 0 IO-APIC-edge rtc0 9: 0 0 0 0 0 0 0 0 IO-APIC-fasteoi acpi 12: 0 0 0 105 0 0 0 0 IO-APIC-edge i8042 16: 0 0 0 0 0 0 0 580212114 IO-APIC-fasteoi 3w-9xxx, uhci_hcd:usb1 18: 0 0 142 0 0 0 0 0 IO-APIC-fasteoi uhci_hcd:usb6, ehci_hcd:usb7 19: 9 0 0 0 0 0 0 0 IO-APIC-fasteoi uhci_hcd:usb3, uhci_hcd:usb5 21: 0 0 0 0 0 0 0 0 IO-APIC-fasteoi uhci_hcd:usb2 23: 0 0 0 0 0 0 0 0 IO-APIC-fasteoi uhci_hcd:usb4, ehci_hcd:usb8 1273: 0 0 1600400502 0 0 0 0 0 PCI-MSI-edge eth0 1274: 0 0 0 0 0 0 0 0 PCI-MSI-edge ahci NMI: 0 0 0 0 0 0 0 0 Non-maskable interrupts LOC: 214252181 69439018 317298553 21943690 72562482 56448835 137923978 407514738 Local timer interrupts RES: 27516446 16935944 26430972 44957009 24935543 19881887 57746906 24298747 Rescheduling interrupts CAL: 10655 10705 10685 10567 10689 10669 10667 396 function call interrupts TLB: 529548 462587 801138 596193 922202 747313 2027966 946594 TLB shootdowns TRM: 0 0 0 0 0 0 0 0 Thermal event interrupts THR: 0 0 0 0 0 0 0 0 Threshold APIC interrupts SPU: 0 0 0 0 0 0 0 0 Spurious interrupts ERR: 0 All the values seems more or less the same for all the cores but this one IO-APIC-fasteoi 3w-9xxx, uhci_hcd:usb1 only affects to the core 7 (the same with the wait time of 40% ~ 60%) could be something attached to the usb port causing the issue? Thanks in advanced

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• Comparison of the multiprocessing module and pyro?

  - by fivebells

  I use pyro for basic management of parallel jobs on a compute cluster. I just moved to a cluster where I will be responsible for using all the cores on each compute node. (On previous clusters, each core has been a separate node.) The python multiprocessing module seems like a good fit for this. I notice it can also be used for remote-process communication. If anyone has used both frameworks for remote-process communication, I'd be grateful to hear how they stack up against each other. The obvious benefit of the multiprocessing module is that it's built-in from 2.6. Apart from that, it's hard for me to tell which is better.

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• Choosing between Berkeley DB Core and Berkeley DB JE

  - by zokier

  I'm designing a Java based web-app and I need a key-value store. Berkeley DB seems fitting enough for me, but there appears to be TWO Berkeley DBs to choose from: Berkeley DB Core which is implemented in C, and Berkeley DB Java Edition which is implemented in pure Java. The question is, how to choose which one to use? With web-apps scalability and performance is quite important (who knows, maybe my idea will become the next Youtube), and I couldn't find easily any meaningful benchmarks between the two. I have yet to familiarize with Cores Java API, but I find it hard to believe that it could be much worse than Java Editions, which seems to be quite nice. If some other key-value store would be much better, feel free to recommend that too. I'm storing smallish binary blobs, and keys probably will be hashes of the data, or some other unique id.

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• CPU consumption of my process

  - by Abruzzo Forte e Gentile

  Hi all I would like to use Performance Monitor to check the CPU consumption of my process. Right now I am working on a MultiCore machine. If I have a look at my process in TASK MANAGER I see that my process consumes 20% of CPU. If I start performance monitor, I select Process--% Processor Time I see values peaking up and over 100%. Do you know why and how to get the real measure? I also looked at the CPU consumption for all of my 4 cores, but I don't know exactly how to attribute consumption to my process. If you can suggest a link or url about how to read CPU usage I would really appreciate! Thanks a lot! AFG

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• iPhone Simulator locks up immediately upon Build / Run

  - by Steve

  I'm having a problem getting my MacBook set up to build iPhone *apps* in xCode. The iPhone Simulator locks up and shows the "spinning circle" busy icon. I've tried everything I can think of, including resetting the simulator tried all of the different hardware options tried the two debug build choices in xCode. uninstalling the SDK and completely reinstalling I downloaded the SDK today - "xcode_3.2.2_and_iphone_sdk_3.2_final" I'm just upgraded from Leopard to Snow Leopard (10.6.3). I've run all the software updates. xCode version says 3.2.2 (1650) If it matters, my MacBook is 3-4 years old, 13 inch, dual 2.16 ghz intel cores, 2 gig RAM. I've never had a single problem with it. I would be so grateful if anyone can help me thanks so much,

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