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  • want to restore windows 7 from linux ubuntu

    - by elisi
    Hi, I want to recovery Win7 from Linux and I dont have the Win7 CD or any previous back up files. Please tell me if there is a way to recovery Win7 from Linux because I do not want to boot it from the beginning cause I have important files and they are in one partition.

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  • I want to send Silent SMS

    - by user554445
    Hi, somebody help me..... It is sometimes necessary for me can send silent SMS to other subscriber, and for this purpose exist such program as Hushsms but It is intended for users Windows Mobile, and I prefer (and use) Nokia n97 with another operating system. Who knows the similar program for Symbian OS?(...or may be another way ?? decision of this problem) It is very important for me. Thankful in advance

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  • Windows8.1 create shortcuts with a custom group in My Computer

    - by user222010
    I have did many research about this. And what I could gather is something like this http://lifehacker.com/add-any-shortcut-to-my-computer-with-this-simple-tweak-479751317. The problem with that is it put the shortcuts under the Network Shortcuts, and this is not what I want. I want to create a shortcut in the My Computer explorer under a specific group such as Important Apps. So, how can I get that?

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  • what's the safest OS?

    - by Bob
    I have pretty important stuff on my PC (using Windows). All the programming files, passwords etc. And now I thought: Is that even safe to store all this information on a hard drive? What if some virus (or a pseudo-antivirus gets it) M.b. it is better to buy Mac for this purpose? I kinda don't like Linux, cause I hate making million small decisions manually (what drivers to install etc) Will like to hear some opinions.

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  • Where are stickies ( Sticky Notes) stored on mac 10.9.3?

    - by user332203
    i deleted an important note on stickies. And i retrieved an old version of it in time machine under preferences / widgets. but the setup appears to have changed in my upgrade to mavericks and I can't open the note. I'm trying to open a "post-mavericks" version in my time machine and I can't find where it is. i saw a post that said look under Library/Preferences/Container, i have no such folder or binary document. Please help.

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  • What's the best name for a non-mutating "add" method on an immutable collection?

    - by Jon Skeet
    Sorry for the waffly title - if I could come up with a concise title, I wouldn't have to ask the question. Suppose I have an immutable list type. It has an operation Foo(x) which returns a new immutable list with the specified argument as an extra element at the end. So to build up a list of strings with values "Hello", "immutable", "world" you could write: var empty = new ImmutableList<string>(); var list1 = empty.Foo("Hello"); var list2 = list1.Foo("immutable"); var list3 = list2.Foo("word"); (This is C# code, and I'm most interested in a C# suggestion if you feel the language is important. It's not fundamentally a language question, but the idioms of the language may be important.) The important thing is that the existing lists are not altered by Foo - so empty.Count would still return 0. Another (more idiomatic) way of getting to the end result would be: var list = new ImmutableList<string>().Foo("Hello"); .Foo("immutable"); .Foo("word"); My question is: what's the best name for Foo? EDIT 3: As I reveal later on, the name of the type might not actually be ImmutableList<T>, which makes the position clear. Imagine instead that it's TestSuite and that it's immutable because the whole of the framework it's a part of is immutable... (End of edit 3) Options I've come up with so far: Add: common in .NET, but implies mutation of the original list Cons: I believe this is the normal name in functional languages, but meaningless to those without experience in such languages Plus: my favourite so far, it doesn't imply mutation to me. Apparently this is also used in Haskell but with slightly different expectations (a Haskell programmer might expect it to add two lists together rather than adding a single value to the other list). With: consistent with some other immutable conventions, but doesn't have quite the same "additionness" to it IMO. And: not very descriptive. Operator overload for + : I really don't like this much; I generally think operators should only be applied to lower level types. I'm willing to be persuaded though! The criteria I'm using for choosing are: Gives the correct impression of the result of the method call (i.e. that it's the original list with an extra element) Makes it as clear as possible that it doesn't mutate the existing list Sounds reasonable when chained together as in the second example above Please ask for more details if I'm not making myself clear enough... EDIT 1: Here's my reasoning for preferring Plus to Add. Consider these two lines of code: list.Add(foo); list.Plus(foo); In my view (and this is a personal thing) the latter is clearly buggy - it's like writing "x + 5;" as a statement on its own. The first line looks like it's okay, until you remember that it's immutable. In fact, the way that the plus operator on its own doesn't mutate its operands is another reason why Plus is my favourite. Without the slight ickiness of operator overloading, it still gives the same connotations, which include (for me) not mutating the operands (or method target in this case). EDIT 2: Reasons for not liking Add. Various answers are effectively: "Go with Add. That's what DateTime does, and String has Replace methods etc which don't make the immutability obvious." I agree - there's precedence here. However, I've seen plenty of people call DateTime.Add or String.Replace and expect mutation. There are loads of newsgroup questions (and probably SO ones if I dig around) which are answered by "You're ignoring the return value of String.Replace; strings are immutable, a new string gets returned." Now, I should reveal a subtlety to the question - the type might not actually be an immutable list, but a different immutable type. In particular, I'm working on a benchmarking framework where you add tests to a suite, and that creates a new suite. It might be obvious that: var list = new ImmutableList<string>(); list.Add("foo"); isn't going to accomplish anything, but it becomes a lot murkier when you change it to: var suite = new TestSuite<string, int>(); suite.Add(x => x.Length); That looks like it should be okay. Whereas this, to me, makes the mistake clearer: var suite = new TestSuite<string, int>(); suite.Plus(x => x.Length); That's just begging to be: var suite = new TestSuite<string, int>().Plus(x => x.Length); Ideally, I would like my users not to have to be told that the test suite is immutable. I want them to fall into the pit of success. This may not be possible, but I'd like to try. I apologise for over-simplifying the original question by talking only about an immutable list type. Not all collections are quite as self-descriptive as ImmutableList<T> :)

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  • Fast block placement algorithm, advice needed?

    - by James Morris
    I need to emulate the window placement strategy of the Fluxbox window manager. As a rough guide, visualize randomly sized windows filling up the screen one at a time, where the rough size of each results in an average of 80 windows on screen without any window overlapping another. It is important to note that windows will close and the space that closed windows previously occupied becomes available once more for the placement of new windows. The window placement strategy has three binary options: Windows build horizontal rows or vertical columns (potentially) Windows are placed from left to right or right to left Windows are placed from top to bottom or bottom to top Why is the algorithm a problem? It needs to operate to the deadlines of a real time thread in an audio application. At this moment I am only concerned with getting a fast algorithm, don't concern yourself over the implications of real time threads and all the hurdles in programming that that brings. So far I have two choices which I have built loose prototypes for: 1) A port of the Fluxbox placement algorithm into my code. The problem with this is, the client (my program) gets kicked out of the audio server (JACK) when I try placing the worst case scenario of 256 blocks using the algorithm. This algorithm performs over 14000 full (linear) scans of the list of blocks already placed when placing the 256th window. 2) My alternative approach. Only partially implemented, this approach uses a data structure for each area of rectangular free unused space (the list of windows can be entirely separate, and is not required for testing of this algorithm). The data structure acts as a node in a doubly linked list (with sorted insertion), as well as containing the coordinates of the top-left corner, and the width and height. Furthermore, each block data structure also contains four links which connect to each immediately adjacent (touching) block on each of the four sides. IMPORTANT RULE: Each block may only touch with one block per side. The problem with this approach is, it's very complex. I have implemented the straightforward cases where 1) space is removed from one corner of a block, 2) splitting neighbouring blocks so that the IMPORTANT RULE is adhered to. The less straightforward case, where the space to be removed can only be found within a column or row of boxes, is only partially implemented - if one of the blocks to be removed is an exact fit for width (ie column) or height (ie row) then problems occur. And don't even mention the fact this only checks columns one box wide, and rows one box tall. I've implemented this algorithm in C - the language I am using for this project (I've not used C++ for a few years and am uncomfortable using it after having focused all my attention to C development, it's a hobby). The implementation is 700+ lines of code (including plenty of blank lines, brace lines, comments etc). The implementation only works for the horizontal-rows + left-right + top-bottom placement strategy. So I've either got to add some way of making this +700 lines of code work for the other 7 placement strategy options, or I'm going to have to duplicate those +700 lines of code for the other seven options. Neither of these is attractive, the first, because the existing code is complex enough, the second, because of bloat. The algorithm is not even at a stage where I can use it in the real time worst case scenario, because of missing functionality, so I still don't know if it actually performs better or worse than the first approach. What else is there? I've skimmed over and discounted: Bin Packing algorithms: their emphasis on optimal fit does not match the requirements of this algorithm. Recursive Bisection Placement algorithms: sounds promising, but these are for circuit design. Their emphasis is optimal wire length. Both of these, especially the latter, all elements to be placed/packs are known before the algorithm begins. I need an algorithm which works accumulatively with what it is given to do when it is told to do it. What are your thoughts on this? How would you approach it? What other algorithms should I look at? Or even what concepts should I research seeing as I've not studied computer science/software engineering? Please ask questions in comments if further information is needed. [edit] If it makes any difference, the units for the coordinates will not be pixels. The units are unimportant, but the grid where windows/blocks/whatever can be placed will be 127 x 127 units.

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  • android camera preview blank screen

    - by user1104836
    I want to capture a photo manually not by using existing camera apps. So i made this Activity: public class CameraActivity extends Activity { private Camera mCamera; private Preview mPreview; @Override protected void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.activity_camera); // Create an instance of Camera // mCamera = Camera.open(0); // Create our Preview view and set it as the content of our activity. mPreview = new Preview(this); mPreview.safeCameraOpen(0); FrameLayout preview = (FrameLayout) findViewById(R.id.camera_preview); preview.addView(mPreview); } @Override public boolean onCreateOptionsMenu(Menu menu) { // Inflate the menu; this adds items to the action bar if it is present. getMenuInflater().inflate(R.menu.activity_camera, menu); return true; } } This is the CameraPreview which i want to use: public class Preview extends ViewGroup implements SurfaceHolder.Callback { SurfaceView mSurfaceView; SurfaceHolder mHolder; //CAM INSTANCE ================================ private Camera mCamera; List<Size> mSupportedPreviewSizes; //============================================= /** * @param context */ public Preview(Context context) { super(context); mSurfaceView = new SurfaceView(context); addView(mSurfaceView); // Install a SurfaceHolder.Callback so we get notified when the // underlying surface is created and destroyed. mHolder = mSurfaceView.getHolder(); mHolder.addCallback(this); mHolder.setType(SurfaceHolder.SURFACE_TYPE_PUSH_BUFFERS); } /** * @param context * @param attrs */ public Preview(Context context, AttributeSet attrs) { super(context, attrs); // TODO Auto-generated constructor stub } /** * @param context * @param attrs * @param defStyle */ public Preview(Context context, AttributeSet attrs, int defStyle) { super(context, attrs, defStyle); // TODO Auto-generated constructor stub } /* (non-Javadoc) * @see android.view.ViewGroup#onLayout(boolean, int, int, int, int) */ @Override protected void onLayout(boolean arg0, int arg1, int arg2, int arg3, int arg4) { // TODO Auto-generated method stub } @Override public void surfaceChanged(SurfaceHolder holder, int format, int width, int height) { // Now that the size is known, set up the camera parameters and begin // the preview. Camera.Parameters parameters = mCamera.getParameters(); parameters.setPreviewSize(width, height); requestLayout(); mCamera.setParameters(parameters); /* Important: Call startPreview() to start updating the preview surface. Preview must be started before you can take a picture. */ mCamera.startPreview(); } @Override public void surfaceCreated(SurfaceHolder holder) { // TODO Auto-generated method stub } @Override public void surfaceDestroyed(SurfaceHolder holder) { // Surface will be destroyed when we return, so stop the preview. if (mCamera != null) { /* Call stopPreview() to stop updating the preview surface. */ mCamera.stopPreview(); } } /** * When this function returns, mCamera will be null. */ private void stopPreviewAndFreeCamera() { if (mCamera != null) { /* Call stopPreview() to stop updating the preview surface. */ mCamera.stopPreview(); /* Important: Call release() to release the camera for use by other applications. Applications should release the camera immediately in onPause() (and re-open() it in onResume()). */ mCamera.release(); mCamera = null; } } public void setCamera(Camera camera) { if (mCamera == camera) { return; } stopPreviewAndFreeCamera(); mCamera = camera; if (mCamera != null) { List<Size> localSizes = mCamera.getParameters().getSupportedPreviewSizes(); mSupportedPreviewSizes = localSizes; requestLayout(); try { mCamera.setPreviewDisplay(mHolder); } catch (IOException e) { e.printStackTrace(); } /* Important: Call startPreview() to start updating the preview surface. Preview must be started before you can take a picture. */ mCamera.startPreview(); } } public boolean safeCameraOpen(int id) { boolean qOpened = false; try { releaseCameraAndPreview(); mCamera = Camera.open(id); mCamera.startPreview(); qOpened = (mCamera != null); } catch (Exception e) { // Log.e(R.string.app_name, "failed to open Camera"); e.printStackTrace(); } return qOpened; } Camera.PictureCallback mPicCallback = new Camera.PictureCallback() { @Override public void onPictureTaken(byte[] data, Camera camera) { // TODO Auto-generated method stub Log.d("lala", "pic is taken"); } }; public void takePic() { mCamera.startPreview(); // mCamera.takePicture(null, mPicCallback, mPicCallback); } private void releaseCameraAndPreview() { this.setCamera(null); if (mCamera != null) { mCamera.release(); mCamera = null; } } } This is the Layout of CameraActivity: <LinearLayout xmlns:android="http://schemas.android.com/apk/res/android" xmlns:tools="http://schemas.android.com/tools" android:layout_width="match_parent" android:layout_height="match_parent" tools:context=".CameraActivity" > <FrameLayout android:id="@+id/camera_preview" android:layout_width="0dip" android:layout_height="fill_parent" android:layout_weight="1" /> <Button android:id="@+id/button_capture" android:text="Capture" android:layout_width="wrap_content" android:layout_height="wrap_content" android:layout_gravity="center" /> </LinearLayout> But when i start the CameraActivity, i just see a blank white background and the Capture-Button??? Why i dont see the Camera-Screen?

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  • How to add a 3rd level to my CSS drop down menu?

    - by Cynthia
    I have a 2-level drop down menu that looks great in all browsers. Now I want to add a 3rd level. How do I do that? Here is my HTML for the menu: <div class="nav"> <div class="navbar"> <ul class="menu"> <li><a href="#">Home</a></li> <li><a href="#">About JoyFactory</a> <ul class="sub-menu"> <li><a href="#">Who We Are</a></li> <li><a href="#">Our Education Concept</a></li> <li><a href="#">References</a></li> </ul> </li> <li><a href="#">JoyFactory Kinderkrippe</a> <ul class="sub-menu"> <li><a href="#">JoyFactory Kinderkrippe Oerlikon</a> <ul> <li><a href="#">item 1</a></li> <li><a href="#">item 2</a></li> <li><a href="#">item 3</a></li> <li><a href="#">item 4</a></li> </ul> </li> <li><a href="#">JoyFactory Kinderkrippe Seebach</a></li> </ul> </li> </ul> </div> </div> and here is my CSS: .nav { clear:both ; width:1020px ; height:55px ; background:url("images/nav-bg.png") no-repeat ; position:absolute ; top:125px ; left:-10px ; } .navbar { width:1000px ; height:50px ; margin:auto ; } ul.menu { margin-left:0 ; padding-left:0 ; list-style-type:none ; } .menu li { display:inline ; float:left ; height:50px ; margin:0 6px ; } .menu li a { font-family:'MyriadPro-SemiboldCond' ; font-size:24px ; color:#ffffff ; text-decoration:none ; height:50px ; line-height:50px ; padding:0px 10px ; } .menu li:hover, .menu li:hover a { background:#ffd322 ; color:#e32a0e ; } .sub-menu { position:absolute ; float:none ; padding:0 ; top:50px ; z-index:9999 ; background:#ffd322 ; margin-left:0 ; padding-left:0 ; } .sub-menu li { display:none ; min-width:175px !important ; margin: 0 !important; padding: 0 !important; } .sub-menu li a, .current-menu-parent .sub-menu li a { display:block ; background:#ffd322 ; font-family:arial,helvetica,sans-serif ; font-size:16px ; padding:0 10px ; border-top:1px solid #f37f10 ; border-left:none ; } .sub-menu li a:hover, .menu li.current-menu-parent .sub-menu li.current-menu-item a { background:#f37f10 } .menu li:hover li { float: none; display:block; clear: both; } Any help would be most appreciated! Many thanks :)

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  • How to Use Windows’ Advanced Search Features: Everything You Need to Know

    - by Chris Hoffman
    You should never have to hunt down a lost file on modern versions of Windows — just perform a quick search. You don’t even have to wait for a cartoon dog to find your files, like on Windows XP. The Windows search indexer is constantly running in the background to make quick local searches possible. This enables the kind of powerful search features you’d use on Google or Bing — but for your local files. Controlling the Indexer By default, the Windows search indexer watches everything under your user folder — that’s C:\Users\NAME. It reads all these files, creating an index of their names, contents, and other metadata. Whenever they change, it notices and updates its index. The index allows you to quickly find a file based on the data in the index. For example, if you want to find files that contain the word “beluga,” you can perform a search for “beluga” and you’ll get a very quick response as Windows looks up the word in its search index. If Windows didn’t use an index, you’d have to sit and wait as Windows opened every file on your hard drive, looked to see if the file contained the word “beluga,” and moved on. Most people shouldn’t have to modify this indexing behavior. However, if you store your important files in other folders — maybe you store your important data a separate partition or drive, such as at D:\Data — you may want to add these folders to your index. You can also choose which types of files you want to index, force Windows to rebuild the index entirely, pause the indexing process so it won’t use any system resources, or move the index to another location to save space on your system drive. To open the Indexing Options window, tap the Windows key on your keyboard, type “index”, and click the Indexing Options shortcut that appears. Use the Modify button to control the folders that Windows indexes or the Advanced button to control other options. To prevent Windows from indexing entirely, click the Modify button and uncheck all the included locations. You could also disable the search indexer entirely from the Programs and Features window. Searching for Files You can search for files right from your Start menu on Windows 7 or Start screen on Windows 8. Just tap the Windows key and perform a search. If you wanted to find files related to Windows, you could perform a search for “Windows.” Windows would show you files that are named Windows or contain the word Windows. From here, you can just click a file to open it. On Windows 7, files are mixed with other types of search results. On Windows 8 or 8.1, you can choose to search only for files. If you want to perform a search without leaving the desktop in Windows 8.1, press Windows Key + S to open a search sidebar. You can also initiate searches directly from Windows Explorer — that’s File Explorer on Windows 8. Just use the search box at the top-right of the window. Windows will search the location you’ve browsed to. For example, if you’re looking for a file related to Windows and know it’s somewhere in your Documents library, open the Documents library and search for Windows. Using Advanced Search Operators On Windows 7, you’ll notice that you can add “search filters” form the search box, allowing you to search by size, date modified, file type, authors, and other metadata. On Windows 8, these options are available from the Search Tools tab on the ribbon. These filters allow you to narrow your search results. If you’re a geek, you can use Windows’ Advanced Query Syntax to perform advanced searches from anywhere, including the Start menu or Start screen. Want to search for “windows,” but only bring up documents that don’t mention Microsoft? Search for “windows -microsoft”. Want to search for all pictures of penguins on your computer, whether they’re PNGs, JPEGs, or any other type of picture file? Search for “penguin kind:picture”. We’ve looked at Windows’ advanced search operators before, so check out our in-depth guide for more information. The Advanced Query Syntax gives you access to options that aren’t available in the graphical interface. Creating Saved Searches Windows allows you to take searches you’ve made and save them as a file. You can then quickly perform the search later by double-clicking the file. The file functions almost like a virtual folder that contains the files you specify. For example, let’s say you wanted to create a saved search that shows you all the new files created in your indexed folders within the last week. You could perform a search for “datecreated:this week”, then click the Save search button on the toolbar or ribbon. You’d have a new virtual folder you could quickly check to see your recent files. One of the best things about Windows search is that it’s available entirely from the keyboard. Just press the Windows key, start typing the name of the file or program you want to open, and press Enter to quickly open it. Windows 8 made this much more obnoxious with its non-unified search, but unified search is finally returning with Windows 8.1.     

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  • Tip/Trick: Fix Common SEO Problems Using the URL Rewrite Extension

    Search engine optimization (SEO) is important for any publically facing web-site.  A large % of traffic to sites now comes directly from search engines, and improving your sites search relevancy will lead to more users visiting your site from search engine queries.  This can directly or indirectly increase the money you make through your site. This blog post covers how you can use the free Microsoft URL Rewrite Extension to fix a bunch of common SEO problems that your site might...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • A Case for Women in Technology

    - by Denise McInerney
    Pragmatic Works and the PASS Women in Tech chapter are co-sponsoring a webinar series featuring women speakers. I presented a session on “A Case for Women in Technology” explaining why we are all affected by the lack of women studying and working in tech. The recording is available here. And here are the slides from that presentation: The presentation includes a link to a trailer for an upcoming documentary. This short video makes a good case for why we need more women creating technology. There are many organizations doing good and important work on this issue. Here are some of them: National Center for Women & Information Technology Catalyst Anita Borg Institute Girls Inc Girls Who Code Code.org Black Girls Code Teaching Kids Programming Digigirlz IGNITE She++ The Ada Initiative PASS WIT Here are the publications I referenced in my slides: Women in IT: The Facts Why Diversity Matters Women in IT: By the Numbers NCWIT Scorecard

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  • Adobe Photoshop Vs Lightroom Vs Aperture

    - by Aditi
    Adobe Photoshop is the standard choice for photographers, graphic artists and Web designers. Adobe Photoshop Lightroom  & Apple’s Aperture are also in the same league but the usage is vastly different. Although Photoshop is most popular & widely used by photographers, but in many ways it’s less relevant to photographers than ever before. As Lightroom & Aperture is aimed squarely at photographers for photo-processing. With this write up we are going to help you choose what is right for you and why. Adobe Photoshop Adobe Photoshop is the most liked tool for the detailed photo editing & designing work. Photoshop provides great features for rollover and Image slicing. Adobe Photoshop includes comprehensive optimization features for producing the highest quality Web graphics with the smallest possible file sizes. You can also create startling animations with it. Designers & Editors know how important precise masking is, PhotoShop lets you do that with various detailing tools. Art history brush, contact sheets, and history palette are some of the smart features, which add to its viability. Download Whether you’re producing printed pages or moving images, you can work more efficiently and produce better results because of its smooth integration across other adobe applications. Buy supporting layer effects, it allows you to quickly add drop shadows, inner and outer glows, bevels, and embossing to layers. It also provides Seamless Web Graphics Workflow. Photoshop is hands-down the BEST for editing. Photoshop Cons: • Slower, less precise editing features in Bridge • Processing lots of images requires actions and can be slower than exporting images from Lightroom • Much slower with editing and processing a large number of images Aperture Apple Aperture is aimed at the professional photographer who shoots predominantly raw files. It helps them to manage their workflow and perform their initial Raw conversion in a better way. Aperture provides adjustment tools such as Histogram to modify color and white balance, but most of the editing of photos is left for Photoshop. It gives users the option of seeing their photographs laid out like slides or negatives on a light table. It boasts of – stars, color-coding and easy techniques for filtering and picking images. Aperture has moved forward few steps than Photoshop, but most of the editing work has been left for Photoshop as it features seamless Photoshop integration. Aperture Pros: Aperture is a step up from the iPhoto software that comes with every Mac, and fairly easy to learn. Adjustments are made in a logical order from top to bottom of the menu. You can store the images in a library or any folder you choose. Aperture also works really well with direct Canon files. It is just $79 if you buy it through Apple’s App Store Moving forward, it will run on the iPad, and possibly the iPhone – Adobe products like Lightroom and Photoshop may never offer these options It is much nicer and simpler user interface. Lightroom Lightroom does a smashing job of basic fixing and editing. It is more advanced tool for photographers. They can use it to have a startling photography effect. Light room has many advanced features, which makes it one of the best tools for photographers and far ahead of the other two. They are Nondestructive editing. Nothing is actually changed in an image until the photo is exported. Better controls over organizing your photos. Lightroom helps to gather a group of photos to use in a slideshow. Lightroom has larger Compare and Survey views of images. Quickly customizable interface. Simple keystrokes allow you to perform different All Lightroom controls are kept available in panels right next to the photos. Always-available History palette, it doesn’t go when you close lightroom. You gain more colors to work with compared to Photoshop and with more precise control. Local control, or adjusting small parts of a photo without affecting anything else, has long been an important part of photography. In Lightroom 2, you can darken, lighten, and affect color and change sharpness and other aspects of specific areas in the photo simply by brushing your cursor across the areas. Photoshop has far more power in its Cloning and Healing Brush tools than Lightroom, but Lightroom offers simple cloning and healing that’s nondestructive. Lightroom supports the RAW formats of more cameras than Aperture. Lightroom provides the option of storing images outside the application in the file system. It costs less than photoshop. Download Why PhotoShop is advanced than Lightroom? There are countless image processing plug-ins on the market for doing specialized processing in Photoshop. For example, if your image needs sophisticated noise reduction, you can use the Noiseware plug-in with Photoshop to do a much better job or noise removal than Lightroom can do. Lightroom’s advantages over Aperture 3 Will always have better integration with Photoshop. Lightroom is backed by bigger and more active user community (So abundant availability for tutorials, etc.) Better noise reduction tool. Especially for photographers the Lens-distortion correction tool  is perfect Lightroom Cons: • Have to Import images to work on them • Slows down with over 10,000 images in the catalog • For processing just one or two images this is a slower workflow Photoshop Pros: • ACR has the same RAW processing controls as Lightroom • ACR Histogram is specialized to the chosen color space (Lightroom is locked into ProPhoto RGB color space with an sRGB tone curve) • Don’t have to Import images to open in Bridge or ACR • Ability to customize processing of RAW images with Photoshop Actions Pricing and Availability Get LightRoomGet PhotoShop Latest version Of Photoshop can be purchased from Adobe store and Adobe authorized reseller and it costs US$999. Latest version of Aperture can be bought for US$199 from Apple Online store or Mac App Store. You can buy latest version of LightRoom from Adobe Store or Adobe Authorized reseller for US$299. Related posts:Adobe Photoshop CS5 vs Photoshop CS5 extended Web based Alternatives to Photoshop 10 Free Alternatives for Adobe Photoshop Software

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  • mysql not starting

    - by Eiriks
    I have a server running on rackspace.com, it been running for about a year (collecting data for a project) and no problems. Now it seems mysql froze (could not connect either through ssh command line, remote app (sequel pro) or web (pages using the db just froze). I got a bit eager to fix this quick and rebooted the virtual server, running ubuntu 10.10. It is a small virtual LAMP server (10gig storage - I'm only using 1, 256mb ram -has not been a problem). Now after the reboot, I cannot get mysql to start again. service mysql status mysql stop/waiting I believe this just means mysql is not running. How do I get this running again? service mysql start start: Job failed to start No. Just typing 'mysql' gives: mysql ERROR 2002 (HY000): Can't connect to local MySQL server through socket '/var/run/mysqld/mysqld.sock' (111) There is a .sock file in this folder, 'ls -l' gives: srwxrwxrwx 1 mysql mysql 0 2012-12-01 17:20 mysqld.sock From googleing this for a while now, I see that many talk about the logfile and my.cnf. Logs Not sure witch ones I should look at. This log-file is empty: 'var/log/mysql/error.log', so is the 'var/log/mysql.err' and 'var/log/mysql.log'. my.cnf is located in '/etc/mysql' and looks like this. Can't see anything clearly wrong with it either. # # The MySQL database server configuration file. # # You can copy this to one of: # - "/etc/mysql/my.cnf" to set global options, # - "~/.my.cnf" to set user-specific options. # # One can use all long options that the program supports. # Run program with --help to get a list of available options and with # --print-defaults to see which it would actually understand and use. # # For explanations see # http://dev.mysql.com/doc/mysql/en/server-system-variables.html # This will be passed to all mysql clients # It has been reported that passwords should be enclosed with ticks/quotes # escpecially if they contain "#" chars... # Remember to edit /etc/mysql/debian.cnf when changing the socket location. [client] port = 3306 socket = /var/run/mysqld/mysqld.sock # Here is entries for some specific programs # The following values assume you have at least 32M ram # This was formally known as [safe_mysqld]. Both versions are currently parsed. [mysqld_safe] socket = /var/run/mysqld/mysqld.sock nice = 0 [mysqld] # # * Basic Settings # # # * IMPORTANT # If you make changes to these settings and your system uses apparmor, you may # also need to also adjust /etc/apparmor.d/usr.sbin.mysqld. # user = mysql socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp skip-external-locking # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. bind-address = 127.0.0.1 # # * Fine Tuning # key_buffer = 16M max_allowed_packet = 16M thread_stack = 192K thread_cache_size = 8 # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP #max_connections = 100 #table_cache = 64 #thread_concurrency = 10 # # * Query Cache Configuration # query_cache_limit = 1M query_cache_size = 16M # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. # As of 5.1 you can enable the log at runtime! #general_log_file = /var/log/mysql/mysql.log #general_log = 1 log_error = /var/log/mysql/error.log # Here you can see queries with especially long duration #log_slow_queries = /var/log/mysql/mysql-slow.log #long_query_time = 2 #log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. #server-id = 1 #log_bin = /var/log/mysql/mysql-bin.log expire_logs_days = 10 max_binlog_size = 100M #binlog_do_db = include_database_name #binlog_ignore_db = include_database_name # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 16M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 16M # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/ I need the data in the database (so i'd like to avoid reinstalling), and I need it back up running again. All hint, tips and solutions are welcomed and appreciated.

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  • Improving Partitioned Table Join Performance

    - by Paul White
    The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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  • The ASP.NET Daily Community Spotlight - How posts get there, and how to make it your Visual Studio Start Page

    - by Jon Galloway
    One really cool part of my job is selecting the articles for the Daily Community Spotlight, on the home page of the ASP.NET website. The spotlight highlights a new post about ASP.NET development every day from a member of the ASP.NET community. You can find it on the home page of the ASP.NET site, at http://asp.net These posts aren't automatically drawn from a pool of RSS feeds or anything - I pick a new post for each day of the year. How I pick the posts I have a few important selection criteria: Interesting to well rounded ASP.NET developers The ASP.NET website has a lot of material for all skill and experience levels, from download / get started to advanced. I try to select community spotlight posts to round that out with fresh and timely information that working ASP.NET developers can really use. Posts highlight solutions to common problems, clever projects and code that helps you leverage ASP.NET, and important announcements about things you can use today. As part of that, I try to mix between ASP.NET MVC, Web Forms, and Web Pages (a.k.a. WebMatrix). As a professional developer, I want to keep on top of all of my options for ASP.NET development, and the common platform base they all share generally means that good ASP.NET code is good ASP.NET code. Exposing new and non-Microsoft community members as much as possible The exercise of selecting good ASP.NET community posts every day of the year has made me think about what the community is. Given the choice, I'll always favor non-Microsoft employees, but since Microsoft often hires ASP.NET community members and MVP's (myself included), I really think that the ASP.NET community includes developers who are using and writing about ASP.NET, both inside and outside of Microsoft. I'm especially excited about the opportunity to highlight new and lesser known bloggers. Usually being featured on the ASP.NET Community Spotlight gives a pretty good traffic bump, and I love being able to both provide great content to the community and encourage lesser known community members by giving them some (much deserved) attention. Announcements only when they're useful to working developers - not marketing Some of the posts are announcements about new releases, such as Scott Hanselman's post on ASP.NET Universal Providers for Session, Memebership, and Roles. I include those when I think they're interesting and of immediate use to you on projects. I occasionally get asked to link to new content from a team at Microsoft; if it's useful and timely content I'll ask them to point me to a blog post by an actual person rather than a faceless team. How the posts are managed This feed used to be managed by an internal spreadsheet on a Sharepoint site, which was painful for a lot of reasons. I took a cue from Jon Udell, who uses of a public Delicious feed feed for his Elm City project, and we moved the management of these posts over to a Delicious feed as well. You can hear more about Jon's use of Delicious in Elm City in our Herding Code interview - still one of my favorite interviews. We ended up with a simpler scenario, but Note: I watched the Yahoo/Delicious news over the past year and was happy to see that Delicious was recently acquired by the founders of YouTube. I investigated several other Delicious competitors, but am happy with Delicious for now. My Delicious feed here: http://www.delicious.com/jon_galloway You can also browse through this past year's ASP.NET Community Spotlight posts using the (pretty cool) Delicious Browse Bar Submitting articles I'm always on the lookout for new articles to feature. The best way to get them to me is to share them via Delicious. It's pretty easy - sign up for an account, then you can add a post and share it to me. Alternatively, you can send them to me via Twitter (@jongalloway) or e-mail (). If you do e-mail me, it helps to include a short description and your full name so I can credit you. Way too many developer blogs don't include names and pictures; if I can't find them I can't feature the post. Subscribing to the Community Spotlight feed The Community Spotlight is available as an RSS feed, so you might want to subscribe to it: http://www.asp.net/rss/spotlight Setting the ASP.NET Community Spotlight feed as your Visual Studio start page If you're an ASP.NET developer, you might consider setting the ASP.NET Community Spotlight as the content for your Visual Studio Start Page. It's really easy - here's how to do it in Visual Studio 2010: Display the Visual Studio Start Page if it's not already showing (View / Start Page) Click on the Latest News tab and enter the following RSS URL: http://www.asp.net/rss/spotlight If you didn't previously have RSS feeds enabled for your start page, click the Enable RSS Feed button Now, every time you start up Visual Studio you'll see great content from members of the ASP.NET community: You can also configure - and disable, if you'd like - the Visual Studio start page in the Tools / Options / Environment / Startup dialog. Credits I'll do a follow-up highlighting some places I commonly find great content for the feed, but I'd like to specifically point out two of them: Elijah Manor posts a lot of great content, which is available in his Twitter feed at @elijahmanor, on his Delicious feed, and on a dedicated website - Web Dev Tweets Chris Alcock's The Morning Brew is a must-read blog which highlights each day's best blog posts across the .NET community. He's an absolute machine, and no matter how obscure the post I find, I can guarantee he'll find it as well if he hasn't already. Did I say must read?

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  • 8 Backup Tools Explained for Windows 7 and 8

    - by Chris Hoffman
    Backups on Windows can be confusing. Whether you’re using Windows 7 or 8, you have quite a few integrated backup tools to think about. Windows 8 made quite a few changes, too. You can also use third-party backup software, whether you want to back up to an external drive or back up your files to online storage. We won’t cover third-party tools here — just the ones built into Windows. Backup and Restore on Windows 7 Windows 7 has its own Backup and Restore feature that lets you create backups manually or on a schedule. You’ll find it under Backup and Restore in the Control Panel. The original version of Windows 8 still contained this tool, and named it Windows 7 File Recovery. This allowed former Windows 7 users to restore files from those old Windows 7 backups or keep using the familiar backup tool for a little while. Windows 7 File Recovery was removed in Windows 8.1. System Restore System Restore on both Windows 7 and 8 functions as a sort of automatic system backup feature. It creates backup copies of important system and program files on a schedule or when you perform certain tasks, such as installing a hardware driver. If system files become corrupted or your computer’s software becomes unstable, you can use System Restore to restore your system and program files from a System Restore point. This isn’t a way to back up your personal files. It’s more of a troubleshooting feature that uses backups to restore your system to its previous working state. Previous Versions on Windows 7 Windows 7′s Previous Versions feature allows you to restore older versions of files — or deleted files. These files can come from backups created with Windows 7′s Backup and Restore feature, but they can also come from System Restore points. When Windows 7 creates a System Restore point, it will sometimes contain your personal files. Previous Versions allows you to extract these personal files from restore points. This only applies to Windows 7. On Windows 8, System Restore won’t create backup copies of your personal files. The Previous Versions feature was removed on Windows 8. File History Windows 8 replaced Windows 7′s backup tools with File History, although this feature isn’t enabled by default. File History is designed to be a simple, easy way to create backups of your data files on an external drive or network location. File History replaces both Windows 7′s Backup and Previous Versions features. Windows System Restore won’t create copies of personal files on Windows 8. This means you can’t actually recover older versions of files until you enable File History yourself — it isn’t enabled by default. System Image Backups Windows also allows you to create system image backups. These are backup images of your entire operating system, including your system files, installed programs, and personal files. This feature was included in both Windows 7 and Windows 8, but it was hidden in the preview versions of Windows 8.1. After many user complaints, it was restored and is still available in the final version of Windows 8.1 — click System Image Backup on the File History Control Panel. Storage Space Mirroring Windows 8′s Storage Spaces feature allows you to set up RAID-like features in software. For example, you can use Storage Space to set up two hard disks of the same size in a mirroring configuration. They’ll appear as a single drive in Windows. When you write to this virtual drive, the files will be saved to both physical drives. If one drive fails, your files will still be available on the other drive. This isn’t a good long-term backup solution, but it is a way of ensuring you won’t lose important files if a single drive fails. Microsoft Account Settings Backup Windows 8 and 8.1 allow you to back up a variety of system settings — including personalization, desktop, and input settings. If you’re signing in with a Microsoft account, OneDrive settings backup is enabled automatically. This feature can be controlled under OneDrive > Sync settings in the PC settings app. This feature only backs up a few settings. It’s really more of a way to sync settings between devices. OneDrive Cloud Storage Microsoft hasn’t been talking much about File History since Windows 8 was released. That’s because they want people to use OneDrive instead. OneDrive — formerly known as SkyDrive — was added to the Windows desktop in Windows 8.1. Save your files here and they’ll be stored online tied to your Microsoft account. You can then sign in on any other computer, smartphone, tablet, or even via the web and access your files. Microsoft wants typical PC users “backing up” their files with OneDrive so they’ll be available on any device. You don’t have to worry about all these features. Just choose a backup strategy to ensure your files are safe if your computer’s hard disk fails you. Whether it’s an integrated backup tool or a third-party backup application, be sure to back up your files.

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  • “Being Agile” Means No Documentation, Right?

    - by jesschadwick
    Ask most software professionals what Agile is and they’ll probably start talking about flexibility and delivering what the customer wants.  Some may even mention the word “iterations”.  But inevitably, they’ll say at some point that it means less or even no documentation.  After all, doesn’t creating, updating, and circulating painstakingly comprehensive documentation that everyone and their mother have officially signed off on go against the very core of Agile?  Of course it does!  But really, they’re missing the point! Read The Agile Manifesto. (No, seriously - read it now. It’s short. I’ll wait.)  It’s essentially a list of values.  More specifically, it’s a right-side/left-side weighted list of values:  “Value this over that”. Many people seem to get the impression that this is really a “good vs. bad” list and that those values on the right side are evil and should essentially be tossed on the floor.  This leads to the conclusion that in order to be Agile we must throw away our fancy expensive tools, document as little as possible, and scoff at the idea of a project plan.  This conclusion is quite convenient because it essentially means “less work, more productivity!” (particularly in regards to the documentation and project planning).  I couldn’t disagree with this conclusion more. My interpretation of the Manifesto targets “over” as the operative word.  It’s not just a list of right vs. wrong or good vs. bad.  It’s a list of priorities.  In other words, none of the concepts on the list should be removed from your development lifecycle – they are all important… just not equally important.  This is not a unique interpretation, in fact it says so right at the end of the manifesto! So, the next time your team sits down to tackle that big new project, don’t make the first order of business to outlaw all meetings, documentation, and project plans.  Instead, collaborate with both your team and the business members involved (you do have business members sitting in the room, directly involved in the project planning, right?) and determine the bare minimum that will allow all of you to work and communicate in the best way possible.  This often means that you can pick and choose which parts of the Agile methodologies and process work for your particular project and end up with an amalgamation of Waterfall, Agile, XP, SCRUM and whatever other methodologies the members of your team have been exposed to (my favorite is “SCRUMerfall”). The biggest implication of this is that there is no one way to implement Agile.  There is no checklist with which you can tick off boxes and confidently conclude that, “Yep, we’re Agile™!”  In fact, depending on your business and the members of your team, moving to Agile full-bore may actually be ill-advised.  Such a drastic change just ends up taking everyone out of their comfort zone which they inevitably fall back into by the end of the project.  This often results in frustration to the point that Agile is abandoned altogether because “we just need to ship something!”  Needless to say, this is far more devastating to a project. Instead, I offer this approach: keep it simple and take it slow.  If your business members or customers are only involved at the beginning phases and nowhere to be seen until the project is delivered, invite them to your daily meetings; encourage them to keep up to speed on what’s going on on a daily basis and provide feedback.  If your current process is heavy on the documentation, try to reduce it as opposed to eliminating it outright.  If you need a “TPS Change Request” signed in triplicate with a 5-day “cooling off period” before a change is implemented, try a simple bug tracking system!  Tighten the feedback loop! Finally, at the end of every “iteration” (whatever that means to you, as long as it’s relatively frequent), take as much time as you can spare (even if it’s an hour or so) and perform some kind of retrospective.  Learn from your mistakes.  Figure out what’s working for you and what’s not, then fix it.  Before you know it you’ve got a handful of iterations and/or projects under your belt and you sit down with your team to realize that, “Hey, this is working - we’re pretty Agile!”  After all, Agile is a Zen journey.  It’s a destination that you aim for, not force, and even if you never reach true “enlightenment” that doesn’t mean your team can’t be exponentially better off from merely taking the journey.

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  • Cleaner HTML Markup with ASP.NET 4 Web Forms - Client IDs (VS 2010 and .NET 4.0 Series)

    This is the sixteenth in a series of blog posts Im doing on the upcoming VS 2010 and .NET 4 release. Todays post is the first of a few blog posts Ill be doing that talk about some of the important changes weve made to make Web Forms in ASP.NET 4 generate clean, standards-compliant, CSS-friendly markup.  Today Ill cover the work we are doing to provide better control over the ID attributes rendered by server controls to the client. [In addition to blogging, I am also now using Twitter...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • ATG Live Webcast Feb. 24th: Using the EBS 12 SOA Adapter

    - by Bill Sawyer
    Our next ATG Live Webcast is now open for registration. The event is titled:E-Business Suite R12.x SOA Using the E-Business Suite AdapterThis live one-hour webcast will offer a review of the Service Oriented Architecture (SOA) capabilities within E-Business Suite R12 focusing on the E-Business Suite Adapter. While primarily focused on integrators and developers, understanding SOA capabilities is important for all E-Business Suite technologists and superusers.ATG Live Webcast Logistics The one-hour event will be webcast live with a dial-in access for Q&A with the Applications Technology Group (ATG) Development experts presenting the event. The basic information for the event is as follows:E-Business Suite R12.x SOA Using the E-Business Suite AdapterDate: Thursday, February 24, 2011Time: 8:00 AM - 9:00 AM Pacific Standard TimePresenters:  Neeraj Chauhan, Product Manager, ATG DevelopmentNOTE: When you register for the event, the confirmation will show the event starting at 7:30 AM Pacific Standard Time. This is to allow you time to connect to the conference call and web conference. The presentation will start at 8:00 AM Pacfic Standard Time.

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  • Default vs Impl when implementing interfaces in Java

    - by Gary Rowe
    After reading Should package names be singular or plural? it occurred to me that I've never seen a proper debate covering one of my pet peeves: naming implementations of interfaces. Let's assume that you have a interface Order that is intended to be implemented in a variety of ways but there is only the initial implementation when the project is first created. Do you go for DefaultOrder or OrderImpl or some other variant to avoid the false dichotomy? And what do you do when more implementations come along? And most important... why?

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  • Best criteria for choosing a DNS provider : Redundancy, Locations, Cost, IPV6, Reliability

    - by antoinet
    What criteria should I use to choose a good DNS provider? Redundancy - Your DNS service should use at least 4 nameservers. You should also check for the use of anycast servers such as Amazon Route 53 and dyn.com services. Worldwide server location - Servers shall be located worldwide, not just in one country! Ipv6 support - It shall be possible to declare an AAAA entry to your server if it supports IPV6 Cost is of course an issue. Some service are free, Amazon Route 53 seems quite cheap. Reliability : SLA is also important, it demonstrate that reliability is measured. Your dns provider shall then state for a refund in case a failure is encountered. Anything else? For reference, a couple of links for more information: http://serverfault.com/questions/216330/why-should-i-use-amazon-route-53-over-my-registrars-dns-servers http://aws.amazon.com/route53/ http://dyn.com/dns/

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