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  • Multiple Rails app, single MySQL database

    - by Gaius Parx
    I intend to have multiple Rails apps each for site.com, api.site.com, admin.site.com. All apps will access the same tables from one single MySQL database. Apps and database runs in the same server. Is there any settings in Rails, ActiveRecord or MySQL that I need to be concerned about for above access scenerio? Thanks Running: Rails 2.3.5, MySQL 5.0, Nginx, Passenger, RubyEE

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  • What are the implications of multi-tasking in iOS 4.0 for developers?

    - by MrDatabase
    I just watched this video from Apple that shows multi-tasking on the new iPhone (running iOS 4.0). What are the implications of multi-tasking to developers? Include both positives and negatives. For example what happens if the user decides to launch two resource-intensives apps at the same time, one of the apps crashes and progress in a game (for example) is lost. Should developers be considering this when writing apps for the new OS and phone?

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  • How to avoid my this facebook app api login page?

    - by user1035140
    I got a problem regrading with my apps which is once I go to my apps, it sure will show me a login page instead of allow page? it always display the login page 1st then only display allow page, I had tried other apps, if I am 1st time user, It sure will appear the allow page only, it did not show me the login page. my question is how to I avoid my login page direct go to allow page? here is my login page picture here is my apps link https://apps.facebook.com/christmas_testing/ here is my facebook php jdk api coding <?php $fbconfig['appid' ] = "XXXXXXXXXXXXX"; $fbconfig['secret'] = "XXXXXXXXXXXXX"; $fbconfig['baseUrl'] = "myserverlink"; $fbconfig['appBaseUrl'] = "http://apps.facebook.com/christmas_testing/"; if (isset($_GET['code'])){ header("Location: " . $fbconfig['appBaseUrl']); exit; } if (isset($_GET['request_ids'])){ //user comes from invitation //track them if you need header("Location: " . $fbconfig['appBaseUrl']); } $user = null; //facebook user uid try{ include_once "facebook.php"; } catch(Exception $o){ echo '<pre>'; print_r($o); echo '</pre>'; } // Create our Application instance. $facebook = new Facebook(array( 'appId' => $fbconfig['appid'], 'secret' => $fbconfig['secret'], 'cookie' => true, )); //Facebook Authentication part $user = $facebook->getUser(); $loginUrl = $facebook->getLoginUrl( array( 'scope' => 'email,publish_stream,user_birthday,user_location,user_work_history,user_about_me,user_hometown' ) ); if ($user) { try { // Proceed knowing you have a logged in user who's authenticated. $user_profile = $facebook->api('/me'); } catch (FacebookApiException $e) { //you should use error_log($e); instead of printing the info on browser d($e); // d is a debug function defined at the end of this file $user = null; } } if (!$user) { echo "<script type='text/javascript'>top.location.href = '$loginUrl';</script>"; exit; } //get user basic description $userInfo = $facebook->api("/$user"); function d($d){ echo '<pre>'; print_r($d); echo '</pre>'; } ?

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  • Is There a Standard Help Document/Manual in Android?

    - by Yenchi
    Hi All, I am writing and publishing my apps on android and would like to provide help document (manual) to users of my apps. I've seen apps open up external web pages as their help, or use html view to open local html documents. Are these the ways we are supposed to deliver manual to our users?

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  • Which Android hardware devices should I test on? [closed]

    - by Tchami
    Possible Duplicate: What hardware devices do you test your Android apps on? I'm trying to compile a list of Android hardware devices that it would make sense to buy and test against if you want to target an as broad audience as possible, while still not buying every single Android device out there. I know there's a lot of information regarding screen sizes and Android versions available elsewhere, but: when developing for Android it's not terribly useful to know if the screen size of a device is 480x800 or 320x240, unless you feel like doing the math to convert that into Android "units" (i.e. small, normal, large or xlarge screens, and ldpi, mdpi, hdpi or xhdpi densities). Even knowing the dimensions of a device, you cannot be sure of the actual Android units as there's some overlap, see Range of screens supported in the Android documentation Taking into account the distribution of Platform versions and Screen Sizes and Densities, below is my current list based on information from the Wikipedia article on Comparison of Android devices. I'm fairly sure the information in this list is correct, but I'd welcome any suggestions/changes. Phones | Model | Android Version | Screen Size | Density | | HTC Wildfire | 2.1/2.2 | Normal | mdpi | | HTC Tattoo | 1.6 | Normal | mdpi | | HTC Hero | 2.1 | Normal | mdpi | | HTC Legend | 2.1 | Normal | mdpi | | Sony Ericsson Xperia X8 | 1.6/2.1 | Normal | mdpi | | Motorola Droid | 2.0-2.2 | Normal | hdpi | | Samsung Galaxy S II | 2.3 | Normal | hdpi | | Samsung Galaxy Nexus | 4.0 | Normal | xhdpi | | Samsung Galaxy S III | 4.0 | Normal | xhdpi | **Tablets** | Model | Android Version | Screen Size | Density | | Samsung Galaxy Tab 7" | 2.2 | Large | hdpi | | Samsung Galaxy Tab 10" | 3.0 | X-Large | mdpi | | Asus Transformer Prime | 4.0 | X-Large | mdpi | | Motorola Xoom | 3.1/4.0 | X-Large | mdpi | N.B.: I have seen (and read) other posts on SO on this subject, e.g. Which Android devices should I test against? and What hardware devices do you test your Android apps on? but they don't seem very canonical. Maybe this should be marked community wiki?

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  • svn: trying to commit after remove a folder and create it again (with the same name)

    - by user248959
    Hi, imagine i have made a co. Then if I remove a folder and create another one with the same name. Then if i try to ci I get: svn: Commit failed (details follow): svn: Directory '/opt/lampp/htdocs/prueba4/apps/frontend/modules/moto/.svn' containing working copy admin area is missing laptop@laptop:/opt/lampp/htdocs/prueba4$ sudo svn st ~ apps/frontend/modules/moto If i tried to add that folder i get: svn: warning: 'apps/frontend/modules/moto' is already under version control What should i do? Regards Javi

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  • I'm maintaining a java class that's 40K lines long.. problem?

    - by Billworth Vandory
    This may be a subjective question leading to deletion but I would really like some feedback. Recently, I moved to another very large enterprise project where I work as a C++ developer. I was aghast to find most classes in the project are anywhere from 8K to 50K lines long with methods that are 1K to 8K lines long. It's mostly business logic dealing with DB tables and data management, full of conditional statements to handle the use cases. Are classes this large common in large enterprise systems? I realize without looking at the code it's hard to make a determination, but have you ever worked on a system with classes this large?

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  • SQL Server and Hyper-V Dynamic Memory Part 2

    - by SQLOS Team
    Part 1 of this series was an introduction and overview of Hyper-V Dynamic Memory. This part looks at SQL Server memory management and how the SQL engine responds to changing OS memory conditions.   Part 2: SQL Server Memory Management As with any Windows process, sqlserver.exe has a virtual address space (VAS) of 4GB on 32-bit and 8TB in 64-bit editions. Pages in its VAS are mapped to pages in physical memory when the memory is committed and referenced for the first time. The collection of VAS pages that have been recently referenced is known as the Working Set. How and when SQL Server allocates virtual memory and grows its working set depends on the memory model it uses. SQL Server supports three basic memory models:   1. Conventional Memory Model   The Conventional model is the default SQL Server memory model and has the following properties: - Dynamic - can grow or shrink its working set in response to load and external (operating system) memory conditions. - OS uses 4K pages – (not to be confused with SQL Server “pages” which are 8K regions of committed memory).- Pageable - Can be paged out to disk by the operating system.   2. Locked Page Model The locked page memory model is set when SQL Server is started with "Lock Pages in Memory" privilege*. It has the following characteristics: - Dynamic - can grow or shrink its working set in the same way as the Conventional model.- OS uses 4K pages - Non-Pageable – When memory is committed it is locked in memory, meaning that it will remain backed by physical memory and will not be paged out by the operating system. A common misconception is to interpret "locked" as non-dynamic. A SQL Server instance using the locked page memory model will grow and shrink (allocate memory and release memory) in response to changing workload and OS memory conditions in the same way as it does with the conventional model.   This is an important consideration when we look at Hyper-V Dynamic Memory – “locked” memory works perfectly well with “dynamic” memory.   * Note in “Denali” (Standard Edition and above), and in SQL 2008 R2 64-bit (Enterprise and above editions) the Lock Pages in Memory privilege is all that is required to set this model. In 2008 R2 64-Bit standard edition it also requires trace flag 845 to be set, in 2008 R2 32-bit editions it requires sp_configure 'awe enabled' 1.   3. Large Page Model The Large page model is set using trace flag 834 and potentially offers a small performance boost for systems that are configured with large pages. It is characterized by: - Static - memory is allocated at startup and does not change. - OS uses large (>2MB) pages - Non-Pageable The large page model is supported with Hyper-V Dynamic Memory (and Hyper-V also supports large pages), but you get no benefit from using Dynamic Memory with this model since SQL Server memory does not grow or shrink. The rest of this article will focus on the locked and conventional SQL Server memory models.   When does SQL Server grow? For “dynamic” configurations (Conventional and Locked memory models), the sqlservr.exe process grows – allocates and commits memory from the OS – in response to a workload. As much memory is allocated as is required to optimally run the query and buffer data for future queries, subject to limitations imposed by:   - SQL Server max server memory setting. If this configuration option is set, the buffer pool is not allowed to grow to more than this value. In SQL Server 2008 this value represents single page allocations, and in “Denali” it represents any size page allocations and also managed CLR procedure allocations.   - Memory signals from OS. The operating system sets a signal on memory resource notification objects to indicate whether it has memory available or whether it is low on available memory. If there is only 32MB free for every 4GB of memory a low memory signal is set, which continues until 64MB/4GB is free. If there is 96MB/4GB free the operating system sets a high memory signal. SQL Server only allocates memory when the high memory signal is set.   To summarize, for SQL Server to grow you need three conditions: a workload, max server memory setting higher than the current allocation, high memory signals from the OS.    When does SQL Server shrink caches? SQL Server as a rule does not like to return memory to the OS, but it will shrink its caches in response to memory pressure. Memory pressure can be divided into “internal” and “external”.   - External memory pressure occurs when the operating system is running low on memory and low memory signals are set. The SQL Server Resource Monitor checks for low memory signals approximately every 5 seconds and it will attempt to free memory until the signals stop.   To free memory SQL Server does the following: ·         Frees unused memory. ·         Notifies Memory Manager Clients to release memory o   Caches – Free unreferenced cache objects. o   Buffer pool - Based on oldest access times.   The freed memory is released back to the operating system. This process continues until the low memory resource notifications stop.    - Internal memory pressure occurs when the size of different caches and allocations increase but the SQL Server process needs to keep its total memory within a target value. For example if max server memory is set and certain caches are growing large, it will cause SQL to free memory for re-use internally, but not to release memory back to the OS. If you lower the value of max server memory you will generate internal memory pressure that will cause SQL to release memory back to the OS.    Memory pressure handling has not changed much since SQL 2005 and it was described in detail in a blog post by Slava Oks.   Note that SQL Server Express is an exception to the above behavior. Unlike other editions it does not assume it is the most important process running on the system but tries to be more “desktop” friendly. It will empty its working set after a period of inactivity.   How does SQL Server respond to changing OS memory?    In SQL Server 2005 support for Hot-Add memory was introduced. This feature, available in Enterprise and above editions, allows the server to make use of any extra physical memory that was added after SQL Server started. Being able to add physical memory when the system is running is limited to specialized hardware, but with the Hyper-V Dynamic Memory feature, when new memory is allocated to a guest virtual machine, it looks like hot-add physical memory to the guest. What this means is that thanks to the hot-add memory feature, SQL Server 2005 and higher can dynamically grow if more “physical” memory is granted to a guest VM by Hyper-V dynamic memory.   SQL Server checks OS memory every second and dynamically adjusts its “target” (based on available OS memory and max server memory) accordingly.   In “Denali” Standard Edition will also have sqlserver.exe support for hot-add memory when running virtualized (i.e. detecting and acting on Hyper-V Dynamic Memory allocations).   How does a SQL Server workload in a guest VM impact Hyper-V dynamic memory scheduling?   When a SQL workload causes the sqlserver.exe process to grow its working set, the Hyper-V memory scheduler will detect memory pressure in the guest VM and add memory to it. SQL Server will then detect the extra memory and grow according to workload demand. In our tests we have seen this feedback process cause a guest VM to grow quickly in response to SQL workload - we are still working on characterizing this ramp-up.    How does SQL Server respond when Hyper-V removes memory from a guest VM through ballooning?   If pressure from other VM's cause Hyper-V Dynamic Memory to take memory away from a VM through ballooning (allocating memory with a virtual device driver and returning it to the host OS), Windows Memory Manager will page out unlocked portions of memory and signal low resource notification events. When SQL Server detects these events it will shrink memory until the low memory notifications stop (see cache shrinking description above).    This raises another question. Can we make SQL Server release memory more readily and hence behave more "dynamically" without compromising performance? In certain circumstances where the application workload is predictable it may be possible to have a job which varies "max server memory" according to need, lowering it when the engine is inactive and raising it before a period of activity. This would have limited applicaability but it is something we're looking into.   What Memory Management changes are there in SQL Server “Denali”?   In SQL Server “Denali” (aka SQL11) the Memory Manager has been re-written to be more efficient. The main changes are summarized in this post. An important change with respect to Hyper-V Dynamic Memory support is that now the max server memory setting includes any size page allocations and managed CLR procedure allocations it now represents a closer approximation to total sqlserver.exe memory usage. This makes it easier to calculate a value for max server memory, which becomes important when configuring virtual machines to work well with Hyper-V Dynamic Memory Startup and Maximum RAM settings.   Another important change is no more AWE or hot-add support for 32-bit edition. This means if you're running a 32-bit edition of Denali you're limited to a 4GB address space and will not be able to take advantage of dynamically added OS memory that wasn't present when SQL Server started (though Hyper-V Dynamic Memory is still a supported configuration).   In part 3 we’ll develop some best practices for configuring and using SQL Server with Dynamic Memory. Originally posted at http://blogs.msdn.com/b/sqlosteam/

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  • OAF Page to Upload Files into Server from local Machine

    - by PRajkumar
    1. Create a New Workspace and Project File > New > General > Workspace Configured for Oracle Applications File Name – PrajkumarFileUploadDemo   Automatically a new OA Project will also be created   Project Name -- FileUploadDemo Default Package -- prajkumar.oracle.apps.fnd.fileuploaddemo   2. Create a New Application Module (AM) Right Click on FileUploadDemo > New > ADF Business Components > Application Module Name -- FileUploadAM Package -- prajkumar.oracle.apps.fnd.fileuploaddemo.server Check Application Module Class: FileUploadAMImpl Generate JavaFile(s)   3. Create a New Page Right click on FileUploadDemo > New > Web Tier > OA Components > Page Name -- FileUploadPG Package -- prajkumar.oracle.apps.fnd.fileuploaddemo.webui   4. Select the FileUploadPG and go to the strcuture pane where a default region has been created   5. Select region1 and set the following properties --     Attribute Property ID PageLayoutRN AM Definition prajkumar.oracle.apps.fnd.fileuploaddemo.server.FileUploadAM Window Title Uploading File into Server from Local Machine Demo Window Title Uploading File into Server from Local Machine Demo     6. Create Stack Layout Region Under Page Layout Region Right click PageLayoutRN > New > Region   Attribute Property ID MainRN AM Definition messageComponentLayout   7. Create a New Item messageFileUpload Bean under MainRN Right click on MainRN > New > messageFileUpload Set Following Properties for New Item --   Attribute Property ID MessageFileUpload Item Style messageFileUpload   8. Create a New Item Submit Button Bean under MainRN Right click on MainRN > New > messageLayout Set Following Properties for messageLayout --   Attribute Property ID ButtonLayout   Right Click on ButtonLayout > New > Item   Attribute Property ID Submit Item Style submitButton Attribute Set /oracle/apps/fnd/attributesets/Buttons/Go   9. Create Controller for page FileUploadPG Right Click on PageLayoutRN > Set New Controller Package Name: prajkumar.oracle.apps.fnd.fileuploaddemo.webui Class Name: FileUploadCO   Write Following Code in FileUploadCO processFormRequest   import oracle.cabo.ui.data.DataObject; import java.io.FileOutputStream; import java.io.InputStream; import oracle.jbo.domain.BlobDomain; import java.io.File; import oracle.apps.fnd.framework.OAException; public void processFormRequest(OAPageContext pageContext, OAWebBean webBean) { super.processFormRequest(pageContext, webBean);    if(pageContext.getParameter("Submit")!=null)  {   upLoadFile(pageContext,webBean);      } }   -- Use Following Code if want to Upload Files in Local Machine -- ----------------------------------------------------------------------------------- public void upLoadFile(OAPageContext pageContext,OAWebBean webBean) { String filePath = "D:\\PRajkumar";  System.out.println("Default File Path---->"+filePath);  String fileUrl = null;  try  {   DataObject fileUploadData =  pageContext.getNamedDataObject("MessageFileUpload"); //FileUploading is my MessageFileUpload Bean Id   if(fileUploadData!=null)   {    String uFileName = (String)fileUploadData.selectValue(null, "UPLOAD_FILE_NAME");  // include this line    String contentType = (String) fileUploadData.selectValue(null, "UPLOAD_FILE_MIME_TYPE");  // For Mime Type    System.out.println("User File Name---->"+uFileName);    FileOutputStream output = null;    InputStream input = null;    BlobDomain uploadedByteStream = (BlobDomain)fileUploadData.selectValue(null, uFileName);    System.out.println("uploadedByteStream---->"+uploadedByteStream);                               File file = new File("D:\\PRajkumar", uFileName);    System.out.println("File output---->"+file);    output = new FileOutputStream(file);    System.out.println("output----->"+output);    input = uploadedByteStream.getInputStream();    System.out.println("input---->"+input);    byte abyte0[] = new byte[0x19000];    int i;         while((i = input.read(abyte0)) > 0)    output.write(abyte0, 0, i);    output.close();    input.close();   }  }  catch(Exception ex)  {   throw new OAException(ex.getMessage(), OAException.ERROR);  }     }   -- Use Following Code if want to Upload File into Server -- ------------------------------------------------------------------------- public void upLoadFile(OAPageContext pageContext,OAWebBean webBean) { String filePath = "/u01/app/apnac03r12/PRajkumar/";  System.out.println("Default File Path---->"+filePath);  String fileUrl = null;  try  {   DataObject fileUploadData =  pageContext.getNamedDataObject("MessageFileUpload");  //FileUploading is my MessageFileUpload Bean Id     if(fileUploadData!=null)   {    String uFileName = (String)fileUploadData.selectValue(null, "UPLOAD_FILE_NAME");   // include this line    String contentType = (String) fileUploadData.selectValue(null, "UPLOAD_FILE_MIME_TYPE");   // For Mime Type    System.out.println("User File Name---->"+uFileName);    FileOutputStream output = null;    InputStream input = null;    BlobDomain uploadedByteStream = (BlobDomain)fileUploadData.selectValue(null, uFileName);    System.out.println("uploadedByteStream---->"+uploadedByteStream);                               File file = new File("/u01/app/apnac03r12/PRajkumar", uFileName);    System.out.println("File output---->"+file);    output = new FileOutputStream(file);    System.out.println("output----->"+output);    input = uploadedByteStream.getInputStream();    System.out.println("input---->"+input);    byte abyte0[] = new byte[0x19000];    int i;         while((i = input.read(abyte0)) > 0)    output.write(abyte0, 0, i);    output.close();    input.close();   }  }  catch(Exception ex)  {   throw new OAException(ex.getMessage(), OAException.ERROR);  }     }   10. Congratulation you have successfully finished. Run Your page and Test Your Work           -- Used Code to Upload files into Server   -- Before Upload files into Server     -- After Upload files into Server       -- Used Code to Upload files into Local Machine   -- Before Upload files into Local Machine       -- After Upload files into Local Machine

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  • Oracle on Oracle: Is that all?

    - by Darin Pendergraft
    On October 17th, I posted a short blog and a podcast interview with Chirag Andani, talking about how Oracle IT uses its own IDM products. Blog link here. In response, I received a comment from reader Jaime Cardoso ([email protected]) who posted: “- You could have talked about how by deploying Oracle's Open standards base technology you were able to integrate any new system in your infrastructure in days. - You could have talked about how by deploying federation you were enabling the business side to keep all their options open in terms of companies to buy and sell while maintaining perfect employee and customer's single view. - You could have talked about how you are now able to cut response times to your audit and security teams into 1/10th of your former times Instead you spent 6 minutes talking about single sign on and self provisioning? If I didn't knew your IDM offer so well I would now be wondering what its differences from Microsoft's offer was. Sorry for not giving a positive comment here but, please your IDM suite is very good and, you simply aren't promoting it well enough” So I decided to send Jaime a note asking him about his experience, and to get his perspective on what makes the Oracle products great. What I found out is that Jaime is a very experienced IDM Architect with several major projects under his belt. Darin Pendergraft: Can you tell me a bit about your experience? How long have you worked in IT, and what is your IDM experience? Jaime Cardoso: I started working in "serious" IT in 1998 when I became Netscape's technical specialist in Portugal. Netscape Portugal didn't exist so, I was working for their VAR here. Most of my work at the time was with Netscape's mail server and LDAP server. Since that time I've been bouncing between the system's side like Sun resellers, Solaris stuff and even worked with Sun's Engineering in the making of an Hierarchical Storage Product (Sun CIS if you know it) and the application's side, mostly in LDAP and IDM. Over the years I've been doing support, service delivery and pre-sales / architecture design of IDM solutions in most big customers in Portugal, to name a few projects: - The first European deployment of Sun Access Manager (SAPO – Portugal Telecom) - The identity repository of 5/5 of the Biggest Portuguese banks - The Portuguese government federation of services project DP: OK, in your blog response, you mentioned 3 topics: 1. Using Oracle's standards based architecture; (you) were able to integrate any new system in days: can you give an example? What systems, how long did it take, number of apps/users/accounts/roles etc. JC: It's relatively easy to design a user management strategy for a static environment, or if you simply assume that you're an <insert vendor here> shop and all your systems will bow to that vendor's will. We've all seen that path, the use of proprietary technologies in interoperability solutions but, then reality kicks in. As an ISP I recall that I made the technical decision to use Active Directory as a central authentication system for the entire IT infrastructure. Clients, systems, apps, everything was there. As a good part of the systems and apps were running on UNIX, then a connector became needed in order to have UNIX boxes to authenticate against AD. And, that strategy worked but, each new machine required the component to be installed, monitoring had to be made for that component and each new app had to be independently certified. A self care user portal was an ongoing project, AD access assumes the client is inside the domain, something the ISP's customers (and UNIX boxes) weren't nor had any intention of ever being. When the Windows 2008 rollout was done, Microsoft changed the Active Directory interface. The Windows administrators didn't have enough know-how about directories and the way systems outside the MS world behaved so, on the go live, things weren't properly tested and a general outage followed. Several hours and 1 roll back later, everything was back working. But, the ISP still had to change all of its applications to work with the new access methods and reset the effort spent on the self service user portal. To keep with the same strategy, they would also have to trust Microsoft not to change interfaces again. Simply by putting up an Oracle LDAP server in the middle and replicating the user info from the AD into LDAP, most of the problems went away. Even systems for which no AD connector existed had PAM in them so, integration was made at the OS level, fully supported by the OS supplier. Sun Identity Manager already had a self care portal, combined with a user workflow so, all the clearances had to be given before the account was created or updated. Adding a new system as a client for these authentication services was simply a new checkbox in the OS installer and, even True64 systems were, for the first time integrated also with a 5 minute work of a junior system admin. True, all the windows clients and MS apps still went to the AD for their authentication needs so, from the start everybody knew that they weren't 100% free of migration pains but, now they had a single point of problems to look at. If you're looking for numbers: - 500K directory entries (users) - 2-300 systems After the initial setup, I personally integrated about 20 systems / apps against LDAP in 1 day while being watched by the different IT teams. The internal IT staff did the rest. DP: 2. Using Federation allows the business to keep options open for buying and selling companies, and yet maintain a single view for both employee and customer. What do you mean by this? Can you give an example? JC: The market is dynamic. The company that's being bought today tomorrow will be sold again. Companies that spread on different markets may see the regulator forcing a sale of part of a company due to monopoly reasons and companies that are in multiple countries have to comply with different legislations. Our job, as IT architects, while addressing the customers and employees authentication services, is quite hard and, quite contrary. On one hand, we need to give access to all of our employees to the relevant systems, apps and resources and, we already have marketing talking with us trying to find out who's a customer of the bough company but not from ours to address. On the other hand, we have to do that and keep in mind we may have to break up all that effort and that different countries legislation may became a problem with a full integration plan. That's a job for user Federation. you don't want to be the one who's telling your President that he will sell that business unit without it's customer's database (making the deal worth a lot less) or that the buyer will take with him a copy of your entire customer's database. Federation enables you to start controlling permissions to users outside of your traditional authentication realm. So what if the people of that company you just bought are keeping their old logins? Do you want, because of that, to have a dedicated system for their expenses reports? And do you want to keep their sales (and pre-sales) people out of the loop in terms of your group's path? Control the information flow, establish a Federation trust circle and give access to your apps to users that haven't (yet?) been brought into your internal login systems. You can still see your users in a unified view, you obviously control if a user has access to any particular application, either that user is in your local database or stored in a directory on the other side of the world. DP: 3. Cut response times of audit and security teams to 1/10. Is this a real number? Can you give an example? JC: No, I don't have any backing for this number. One of the companies I did system Administration for has a SOX compliance policy in place (I remind you that I live in Portugal so, this definition of SOX may be somewhat different from what you're used to) and, every time the audit team says they'll do another audit, we have to negotiate with them the size of the sample and we spend about 15 man/days gathering all the required info they ask. I did some work with Sun's Identity auditor and, from what I've been seeing, Oracle's product is even better and, I've seen that most of the information they ask would have been provided in a few hours with the help of this tool. I do stand by what I said here but, to be honest, someone from Identity Auditor team would do a much better job than me explaining this time savings. Jaime is right: the Oracle IDM products have a lot of business value, and Oracle IT is using them for a lot more than I was able to cover in the short podcast that I posted. I want to thank Jaime for his comments and perspective. We want these blog posts to be informative and honest – so if you have feedback for the Oracle IDM team on any topic discussed here, please post your comments below.

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  • Upload File to Windows Azure Blob in Chunks through ASP.NET MVC, JavaScript and HTML5

    - by Shaun
    Originally posted on: http://geekswithblogs.net/shaunxu/archive/2013/07/01/upload-file-to-windows-azure-blob-in-chunks-through-asp.net.aspxMany people are using Windows Azure Blob Storage to store their data in the cloud. Blob storage provides 99.9% availability with easy-to-use API through .NET SDK and HTTP REST. For example, we can store JavaScript files, images, documents in blob storage when we are building an ASP.NET web application on a Web Role in Windows Azure. Or we can store our VHD files in blob and mount it as a hard drive in our cloud service. If you are familiar with Windows Azure, you should know that there are two kinds of blob: page blob and block blob. The page blob is optimized for random read and write, which is very useful when you need to store VHD files. The block blob is optimized for sequential/chunk read and write, which has more common usage. Since we can upload block blob in blocks through BlockBlob.PutBlock, and them commit them as a whole blob with invoking the BlockBlob.PutBlockList, it is very powerful to upload large files, as we can upload blocks in parallel, and provide pause-resume feature. There are many documents, articles and blog posts described on how to upload a block blob. Most of them are focus on the server side, which means when you had received a big file, stream or binaries, how to upload them into blob storage in blocks through .NET SDK.  But the problem is, how can we upload these large files from client side, for example, a browser. This questioned to me when I was working with a Chinese customer to help them build a network disk production on top of azure. The end users upload their files from the web portal, and then the files will be stored in blob storage from the Web Role. My goal is to find the best way to transform the file from client (end user’s machine) to the server (Web Role) through browser. In this post I will demonstrate and describe what I had done, to upload large file in chunks with high speed, and save them as blocks into Windows Azure Blob Storage.   Traditional Upload, Works with Limitation The simplest way to implement this requirement is to create a web page with a form that contains a file input element and a submit button. 1: @using (Html.BeginForm("About", "Index", FormMethod.Post, new { enctype = "multipart/form-data" })) 2: { 3: <input type="file" name="file" /> 4: <input type="submit" value="upload" /> 5: } And then in the backend controller, we retrieve the whole content of this file and upload it in to the blob storage through .NET SDK. We can split the file in blocks and upload them in parallel and commit. The code had been well blogged in the community. 1: [HttpPost] 2: public ActionResult About(HttpPostedFileBase file) 3: { 4: var container = _client.GetContainerReference("test"); 5: container.CreateIfNotExists(); 6: var blob = container.GetBlockBlobReference(file.FileName); 7: var blockDataList = new Dictionary<string, byte[]>(); 8: using (var stream = file.InputStream) 9: { 10: var blockSizeInKB = 1024; 11: var offset = 0; 12: var index = 0; 13: while (offset < stream.Length) 14: { 15: var readLength = Math.Min(1024 * blockSizeInKB, (int)stream.Length - offset); 16: var blockData = new byte[readLength]; 17: offset += stream.Read(blockData, 0, readLength); 18: blockDataList.Add(Convert.ToBase64String(BitConverter.GetBytes(index)), blockData); 19:  20: index++; 21: } 22: } 23:  24: Parallel.ForEach(blockDataList, (bi) => 25: { 26: blob.PutBlock(bi.Key, new MemoryStream(bi.Value), null); 27: }); 28: blob.PutBlockList(blockDataList.Select(b => b.Key).ToArray()); 29:  30: return RedirectToAction("About"); 31: } This works perfect if we selected an image, a music or a small video to upload. But if I selected a large file, let’s say a 6GB HD-movie, after upload for about few minutes the page will be shown as below and the upload will be terminated. In ASP.NET there is a limitation of request length and the maximized request length is defined in the web.config file. It’s a number which less than about 4GB. So if we want to upload a really big file, we cannot simply implement in this way. Also, in Windows Azure, a cloud service network load balancer will terminate the connection if exceed the timeout period. From my test the timeout looks like 2 - 3 minutes. Hence, when we need to upload a large file we cannot just use the basic HTML elements. Besides the limitation mentioned above, the simple HTML file upload cannot provide rich upload experience such as chunk upload, pause and pause-resume. So we need to find a better way to upload large file from the client to the server.   Upload in Chunks through HTML5 and JavaScript In order to break those limitation mentioned above we will try to upload the large file in chunks. This takes some benefit to us such as - No request size limitation: Since we upload in chunks, we can define the request size for each chunks regardless how big the entire file is. - No timeout problem: The size of chunks are controlled by us, which means we should be able to make sure request for each chunk upload will not exceed the timeout period of both ASP.NET and Windows Azure load balancer. It was a big challenge to upload big file in chunks until we have HTML5. There are some new features and improvements introduced in HTML5 and we will use them to implement our solution.   In HTML5, the File interface had been improved with a new method called “slice”. It can be used to read part of the file by specifying the start byte index and the end byte index. For example if the entire file was 1024 bytes, file.slice(512, 768) will read the part of this file from the 512nd byte to 768th byte, and return a new object of interface called "Blob”, which you can treat as an array of bytes. In fact,  a Blob object represents a file-like object of immutable, raw data. The File interface is based on Blob, inheriting blob functionality and expanding it to support files on the user's system. For more information about the Blob please refer here. File and Blob is very useful to implement the chunk upload. We will use File interface to represent the file the user selected from the browser and then use File.slice to read the file in chunks in the size we wanted. For example, if we wanted to upload a 10MB file with 512KB chunks, then we can read it in 512KB blobs by using File.slice in a loop.   Assuming we have a web page as below. User can select a file, an input box to specify the block size in KB and a button to start upload. 1: <div> 2: <input type="file" id="upload_files" name="files[]" /><br /> 3: Block Size: <input type="number" id="block_size" value="512" name="block_size" />KB<br /> 4: <input type="button" id="upload_button_blob" name="upload" value="upload (blob)" /> 5: </div> Then we can have the JavaScript function to upload the file in chunks when user clicked the button. 1: <script type="text/javascript"> 1: 2: $(function () { 3: $("#upload_button_blob").click(function () { 4: }); 5: });</script> Firstly we need to ensure the client browser supports the interfaces we are going to use. Just try to invoke the File, Blob and FormData from the “window” object. If any of them is “undefined” the condition result will be “false” which means your browser doesn’t support these premium feature and it’s time for you to get your browser updated. FormData is another new feature we are going to use in the future. It could generate a temporary form for us. We will use this interface to create a form with chunk and associated metadata when invoked the service through ajax. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: if (window.File && window.Blob && window.FormData) { 4: alert("Your brwoser is awesome, let's rock!"); 5: } 6: else { 7: alert("Oh man plz update to a modern browser before try is cool stuff out."); 8: return; 9: } 10: }); Each browser supports these interfaces by their own implementation and currently the Blob, File and File.slice are supported by Chrome 21, FireFox 13, IE 10, Opera 12 and Safari 5.1 or higher. After that we worked on the files the user selected one by one since in HTML5, user can select multiple files in one file input box. 1: var files = $("#upload_files")[0].files; 2: for (var i = 0; i < files.length; i++) { 3: var file = files[i]; 4: var fileSize = file.size; 5: var fileName = file.name; 6: } Next, we calculated the start index and end index for each chunks based on the size the user specified from the browser. We put them into an array with the file name and the index, which will be used when we upload chunks into Windows Azure Blob Storage as blocks since we need to specify the target blob name and the block index. At the same time we will store the list of all indexes into another variant which will be used to commit blocks into blob in Azure Storage once all chunks had been uploaded successfully. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10:  11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: var blockSizeInKB = $("#block_size").val(); 14: var blockSize = blockSizeInKB * 1024; 15: var blocks = []; 16: var offset = 0; 17: var index = 0; 18: var list = ""; 19: while (offset < fileSize) { 20: var start = offset; 21: var end = Math.min(offset + blockSize, fileSize); 22:  23: blocks.push({ 24: name: fileName, 25: index: index, 26: start: start, 27: end: end 28: }); 29: list += index + ","; 30:  31: offset = end; 32: index++; 33: } 34: } 35: }); Now we have all chunks’ information ready. The next step should be upload them one by one to the server side, and at the server side when received a chunk it will upload as a block into Blob Storage, and finally commit them with the index list through BlockBlobClient.PutBlockList. But since all these invokes are ajax calling, which means not synchronized call. So we need to introduce a new JavaScript library to help us coordinate the asynchronize operation, which named “async.js”. You can download this JavaScript library here, and you can find the document here. I will not explain this library too much in this post. We will put all procedures we want to execute as a function array, and pass into the proper function defined in async.js to let it help us to control the execution sequence, in series or in parallel. Hence we will define an array and put the function for chunk upload into this array. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4:  5: // start to upload each files in chunks 6: var files = $("#upload_files")[0].files; 7: for (var i = 0; i < files.length; i++) { 8: var file = files[i]; 9: var fileSize = file.size; 10: var fileName = file.name; 11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: ... ... 14:  15: // define the function array and push all chunk upload operation into this array 16: blocks.forEach(function (block) { 17: putBlocks.push(function (callback) { 18: }); 19: }); 20: } 21: }); 22: }); As you can see, I used File.slice method to read each chunks based on the start and end byte index we calculated previously, and constructed a temporary HTML form with the file name, chunk index and chunk data through another new feature in HTML5 named FormData. Then post this form to the backend server through jQuery.ajax. This is the key part of our solution. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: blocks.forEach(function (block) { 15: putBlocks.push(function (callback) { 16: // load blob based on the start and end index for each chunks 17: var blob = file.slice(block.start, block.end); 18: // put the file name, index and blob into a temporary from 19: var fd = new FormData(); 20: fd.append("name", block.name); 21: fd.append("index", block.index); 22: fd.append("file", blob); 23: // post the form to backend service (asp.net mvc controller action) 24: $.ajax({ 25: url: "/Home/UploadInFormData", 26: data: fd, 27: processData: false, 28: contentType: "multipart/form-data", 29: type: "POST", 30: success: function (result) { 31: if (!result.success) { 32: alert(result.error); 33: } 34: callback(null, block.index); 35: } 36: }); 37: }); 38: }); 39: } 40: }); Then we will invoke these functions one by one by using the async.js. And once all functions had been executed successfully I invoked another ajax call to the backend service to commit all these chunks (blocks) as the blob in Windows Azure Storage. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.series(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); That’s all in the client side. The outline of our logic would be - Calculate the start and end byte index for each chunks based on the block size. - Defined the functions of reading the chunk form file and upload the content to the backend service through ajax. - Execute the functions defined in previous step with “async.js”. - Commit the chunks by invoking the backend service in Windows Azure Storage finally.   Save Chunks as Blocks into Blob Storage In above we finished the client size JavaScript code. It uploaded the file in chunks to the backend service which we are going to implement in this step. We will use ASP.NET MVC as our backend service, and it will receive the chunks, upload into Windows Azure Bob Storage in blocks, then finally commit as one blob. As in the client side we uploaded chunks by invoking the ajax call to the URL "/Home/UploadInFormData", I created a new action under the Index controller and it only accepts HTTP POST request. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: } 8: catch (Exception e) 9: { 10: error = e.ToString(); 11: } 12:  13: return new JsonResult() 14: { 15: Data = new 16: { 17: success = string.IsNullOrWhiteSpace(error), 18: error = error 19: } 20: }; 21: } Then I retrieved the file name, index and the chunk content from the Request.Form object, which was passed from our client side. And then, used the Windows Azure SDK to create a blob container (in this case we will use the container named “test”.) and create a blob reference with the blob name (same as the file name). Then uploaded the chunk as a block of this blob with the index, since in Blob Storage each block must have an index (ID) associated with so that finally we can put all blocks as one blob by specifying their block ID list. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var index = int.Parse(Request.Form["index"]); 9: var file = Request.Files[0]; 10: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 11:  12: var container = _client.GetContainerReference("test"); 13: container.CreateIfNotExists(); 14: var blob = container.GetBlockBlobReference(name); 15: blob.PutBlock(id, file.InputStream, null); 16: } 17: catch (Exception e) 18: { 19: error = e.ToString(); 20: } 21:  22: return new JsonResult() 23: { 24: Data = new 25: { 26: success = string.IsNullOrWhiteSpace(error), 27: error = error 28: } 29: }; 30: } Next, I created another action to commit the blocks into blob once all chunks had been uploaded. Similarly, I retrieved the blob name from the Request.Form. I also retrieved the chunks ID list, which is the block ID list from the Request.Form in a string format, split them as a list, then invoked the BlockBlob.PutBlockList method. After that our blob will be shown in the container and ready to be download. 1: [HttpPost] 2: public JsonResult Commit() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var list = Request.Form["list"]; 9: var ids = list 10: .Split(',') 11: .Where(id => !string.IsNullOrWhiteSpace(id)) 12: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 13: .ToArray(); 14:  15: var container = _client.GetContainerReference("test"); 16: container.CreateIfNotExists(); 17: var blob = container.GetBlockBlobReference(name); 18: blob.PutBlockList(ids); 19: } 20: catch (Exception e) 21: { 22: error = e.ToString(); 23: } 24:  25: return new JsonResult() 26: { 27: Data = new 28: { 29: success = string.IsNullOrWhiteSpace(error), 30: error = error 31: } 32: }; 33: } Now we finished all code we need. The whole process of uploading would be like this below. Below is the full client side JavaScript code. 1: <script type="text/javascript" src="~/Scripts/async.js"></script> 2: <script type="text/javascript"> 3: $(function () { 4: $("#upload_button_blob").click(function () { 5: // assert the browser support html5 6: if (window.File && window.Blob && window.FormData) { 7: alert("Your brwoser is awesome, let's rock!"); 8: } 9: else { 10: alert("Oh man plz update to a modern browser before try is cool stuff out."); 11: return; 12: } 13:  14: // start to upload each files in chunks 15: var files = $("#upload_files")[0].files; 16: for (var i = 0; i < files.length; i++) { 17: var file = files[i]; 18: var fileSize = file.size; 19: var fileName = file.name; 20:  21: // calculate the start and end byte index for each blocks(chunks) 22: // with the index, file name and index list for future using 23: var blockSizeInKB = $("#block_size").val(); 24: var blockSize = blockSizeInKB * 1024; 25: var blocks = []; 26: var offset = 0; 27: var index = 0; 28: var list = ""; 29: while (offset < fileSize) { 30: var start = offset; 31: var end = Math.min(offset + blockSize, fileSize); 32:  33: blocks.push({ 34: name: fileName, 35: index: index, 36: start: start, 37: end: end 38: }); 39: list += index + ","; 40:  41: offset = end; 42: index++; 43: } 44:  45: // define the function array and push all chunk upload operation into this array 46: var putBlocks = []; 47: blocks.forEach(function (block) { 48: putBlocks.push(function (callback) { 49: // load blob based on the start and end index for each chunks 50: var blob = file.slice(block.start, block.end); 51: // put the file name, index and blob into a temporary from 52: var fd = new FormData(); 53: fd.append("name", block.name); 54: fd.append("index", block.index); 55: fd.append("file", blob); 56: // post the form to backend service (asp.net mvc controller action) 57: $.ajax({ 58: url: "/Home/UploadInFormData", 59: data: fd, 60: processData: false, 61: contentType: "multipart/form-data", 62: type: "POST", 63: success: function (result) { 64: if (!result.success) { 65: alert(result.error); 66: } 67: callback(null, block.index); 68: } 69: }); 70: }); 71: }); 72:  73: // invoke the functions one by one 74: // then invoke the commit ajax call to put blocks into blob in azure storage 75: async.series(putBlocks, function (error, result) { 76: var data = { 77: name: fileName, 78: list: list 79: }; 80: $.post("/Home/Commit", data, function (result) { 81: if (!result.success) { 82: alert(result.error); 83: } 84: else { 85: alert("done!"); 86: } 87: }); 88: }); 89: } 90: }); 91: }); 92: </script> And below is the full ASP.NET MVC controller code. 1: public class HomeController : Controller 2: { 3: private CloudStorageAccount _account; 4: private CloudBlobClient _client; 5:  6: public HomeController() 7: : base() 8: { 9: _account = CloudStorageAccount.Parse(CloudConfigurationManager.GetSetting("DataConnectionString")); 10: _client = _account.CreateCloudBlobClient(); 11: } 12:  13: public ActionResult Index() 14: { 15: ViewBag.Message = "Modify this template to jump-start your ASP.NET MVC application."; 16:  17: return View(); 18: } 19:  20: [HttpPost] 21: public JsonResult UploadInFormData() 22: { 23: var error = string.Empty; 24: try 25: { 26: var name = Request.Form["name"]; 27: var index = int.Parse(Request.Form["index"]); 28: var file = Request.Files[0]; 29: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 30:  31: var container = _client.GetContainerReference("test"); 32: container.CreateIfNotExists(); 33: var blob = container.GetBlockBlobReference(name); 34: blob.PutBlock(id, file.InputStream, null); 35: } 36: catch (Exception e) 37: { 38: error = e.ToString(); 39: } 40:  41: return new JsonResult() 42: { 43: Data = new 44: { 45: success = string.IsNullOrWhiteSpace(error), 46: error = error 47: } 48: }; 49: } 50:  51: [HttpPost] 52: public JsonResult Commit() 53: { 54: var error = string.Empty; 55: try 56: { 57: var name = Request.Form["name"]; 58: var list = Request.Form["list"]; 59: var ids = list 60: .Split(',') 61: .Where(id => !string.IsNullOrWhiteSpace(id)) 62: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 63: .ToArray(); 64:  65: var container = _client.GetContainerReference("test"); 66: container.CreateIfNotExists(); 67: var blob = container.GetBlockBlobReference(name); 68: blob.PutBlockList(ids); 69: } 70: catch (Exception e) 71: { 72: error = e.ToString(); 73: } 74:  75: return new JsonResult() 76: { 77: Data = new 78: { 79: success = string.IsNullOrWhiteSpace(error), 80: error = error 81: } 82: }; 83: } 84: } And if we selected a file from the browser we will see our application will upload chunks in the size we specified to the server through ajax call in background, and then commit all chunks in one blob. Then we can find the blob in our Windows Azure Blob Storage.   Optimized by Parallel Upload In previous example we just uploaded our file in chunks. This solved the problem that ASP.NET MVC request content size limitation as well as the Windows Azure load balancer timeout. But it might introduce the performance problem since we uploaded chunks in sequence. In order to improve the upload performance we could modify our client side code a bit to make the upload operation invoked in parallel. The good news is that, “async.js” library provides the parallel execution function. If you remembered the code we invoke the service to upload chunks, it utilized “async.series” which means all functions will be executed in sequence. Now we will change this code to “async.parallel”. This will invoke all functions in parallel. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallel(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); In this way all chunks will be uploaded to the server side at the same time to maximize the bandwidth usage. This should work if the file was not very large and the chunk size was not very small. But for large file this might introduce another problem that too many ajax calls are sent to the server at the same time. So the best solution should be, upload the chunks in parallel with maximum concurrency limitation. The code below specified the concurrency limitation to 4, which means at the most only 4 ajax calls could be invoked at the same time. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallelLimit(putBlocks, 4, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: });   Summary In this post we discussed how to upload files in chunks to the backend service and then upload them into Windows Azure Blob Storage in blocks. We focused on the frontend side and leverage three new feature introduced in HTML 5 which are - File.slice: Read part of the file by specifying the start and end byte index. - Blob: File-like interface which contains the part of the file content. - FormData: Temporary form element that we can pass the chunk alone with some metadata to the backend service. Then we discussed the performance consideration of chunk uploading. Sequence upload cannot provide maximized upload speed, but the unlimited parallel upload might crash the browser and server if too many chunks. So we finally came up with the solution to upload chunks in parallel with the concurrency limitation. We also demonstrated how to utilize “async.js” JavaScript library to help us control the asynchronize call and the parallel limitation.   Regarding the chunk size and the parallel limitation value there is no “best” value. You need to test vary composition and find out the best one for your particular scenario. It depends on the local bandwidth, client machine cores and the server side (Windows Azure Cloud Service Virtual Machine) cores, memory and bandwidth. Below is one of my performance test result. The client machine was Windows 8 IE 10 with 4 cores. I was using Microsoft Cooperation Network. The web site was hosted on Windows Azure China North data center (in Beijing) with one small web role (1.7GB 1 core CPU, 1.75GB memory with 100Mbps bandwidth). The test cases were - Chunk size: 512KB, 1MB, 2MB, 4MB. - Upload Mode: Sequence, parallel (unlimited), parallel with limit (4 threads, 8 threads). - Chunk Format: base64 string, binaries. - Target file: 100MB. - Each case was tested 3 times. Below is the test result chart. Some thoughts, but not guidance or best practice: - Parallel gets better performance than series. - No significant performance improvement between parallel 4 threads and 8 threads. - Transform with binaries provides better performance than base64. - In all cases, chunk size in 1MB - 2MB gets better performance.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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    - by Mysticgeek
    Boxee is a very cool multimedia app that lets you access and stream your digital media in many different ways. There’s also a lot of extra apps included with it, and today we take a look at the Pandora application in Boxee. Pandora has been a favorite free music streaming service that’s been around for some time now. Though there are new services like Grooveshark and Spotify that are competing, Pandora is still a reliable choice. It’s now included in Boxee, and here we take a look at using it. Create a Pandora Account If you don’t already have a Pandora account, you can easily create one at their website (link below). Pandora in Boxee To start using Pandora from Boxee, launch Boxee and from the main menu select Apps. Now from the My Apps section select Pandora. When the Pandora app menu comes up, select Start. Now you need to log into your Pandora account. After signing in you can starting listening to your stations, viewing artist info, and cover art. All while enjoying some cool visuals in the background. From the controls at the top you can control playback, skip songs, control volume, get information on why a song was picked, and give a song a thumbs up or down. Of course you can also pull up your stations and switch between them and add more. The same features you’ve come to expect from Pandora are available. One thing we noticed missing is not being able to click on the band or artist to get additional information about them –which you can do on the Pandora site and desktop app. But that isn’t a deal breaker by any means, and we’re hoping the feature will be added in the future. Then while you’re checking out other apps, shows, and setting within Boxee, the cool visuals continue and the songs from you stations keep playing. Conclusion Pandora is a great streaming music service and a welcome edition to Boxee. If you’re a fan of Pandora now you can listen to it on your home theater system. If you’re new to Boxee, make sure to check out our article on getting started with Boxee. Create a Pandora Account Download Boxee Similar Articles Productive Geek Tips Integrate Boxee with Media Center in Windows 7Getting Started with BoxeePandora One is a Worthwhile Upgrade for Your Current Pandora AccountCreate Music Video Playlists with TubeRadio.fmSpotify is an Awesome Music Streaming Service TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional Draw Online using Harmony How to Browse Privately in Firefox Kill Processes Quickly with Process Assassin Need to Come Up with a Good Name? Try Wordoid StockFox puts a Lightweight Stock Ticker in your Statusbar Explore Google Public Data Visually

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  • IDC Analyst Mike Fauscette Writes About Oracle And The Cloud

    - by Roxana Babiciu
    "It's becoming clear that cloud is now a core part of Oracle's strategy," says analyst Michael Fauscette in his post-OpenWorld article in Seeking Alpha. He believes we have a well-rounded portfolio "with a cloud platform/infrastructure, a broad selection of apps, and a partner marketplace." From his numerous conversations with customers, he highlights their continual interest in hybrid deployments and also in shifting apps to the cloud. Read more.

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  • IDC Analyst Mike Fauscette Writes About Oracle and The Cloud

    - by Cinzia Mascanzoni
    "It's becoming clear that cloud is now a core part of Oracle's strategy," says analyst Michael Fauscette in his post-OpenWorld article in Seeking Alpha. He believes we have a well-rounded portfolio "with a cloud platform/infrastructure, a broad selection of apps, and a partner marketplace." From his numerous conversations with customers, he highlights their continual interest in hybrid deployments and also in shifting apps to the cloud. Read more.

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  • Presentaciones del Customers Day sobre J.D. Edwards

    - by [email protected]
    Durante el Customers Day sobre J.D. Edwards celebrado el pasado 9 de marzo de 2010, se presentaron los siguientes servicios: E1 Gestión de Mantenimiento Impacto del cambio en los tipos de IVA BI Apps para J.D. Edwards A continuación puede encontrar las presentaciones incrustadas. Presentacion JDE Customers Day 1 E1 Gestion de MantenimientoView more presentations from oracledirect. Presentacion JDE Customers Day 2 Impacto Cambio Tipos IVAView more presentations from oracledirect. Presentacion JDE Customers Day 3 BI Apps para JDEView more presentations from oracledirect.

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  • Advanced TSQL Tuning: Why Internals Knowledge Matters

    - by Paul White
    There is much more to query tuning than reducing logical reads and adding covering nonclustered indexes.  Query tuning is not complete as soon as the query returns results quickly in the development or test environments.  In production, your query will compete for memory, CPU, locks, I/O and other resources on the server.  Today’s entry looks at some tuning considerations that are often overlooked, and shows how deep internals knowledge can help you write better TSQL. As always, we’ll need some example data.  In fact, we are going to use three tables today, each of which is structured like this: Each table has 50,000 rows made up of an INTEGER id column and a padding column containing 3,999 characters in every row.  The only difference between the three tables is in the type of the padding column: the first table uses CHAR(3999), the second uses VARCHAR(MAX), and the third uses the deprecated TEXT type.  A script to create a database with the three tables and load the sample data follows: USE master; GO IF DB_ID('SortTest') IS NOT NULL DROP DATABASE SortTest; GO CREATE DATABASE SortTest COLLATE LATIN1_GENERAL_BIN; GO ALTER DATABASE SortTest MODIFY FILE ( NAME = 'SortTest', SIZE = 3GB, MAXSIZE = 3GB ); GO ALTER DATABASE SortTest MODIFY FILE ( NAME = 'SortTest_log', SIZE = 256MB, MAXSIZE = 1GB, FILEGROWTH = 128MB ); GO ALTER DATABASE SortTest SET ALLOW_SNAPSHOT_ISOLATION OFF ; ALTER DATABASE SortTest SET AUTO_CLOSE OFF ; ALTER DATABASE SortTest SET AUTO_CREATE_STATISTICS ON ; ALTER DATABASE SortTest SET AUTO_SHRINK OFF ; ALTER DATABASE SortTest SET AUTO_UPDATE_STATISTICS ON ; ALTER DATABASE SortTest SET AUTO_UPDATE_STATISTICS_ASYNC ON ; ALTER DATABASE SortTest SET PARAMETERIZATION SIMPLE ; ALTER DATABASE SortTest SET READ_COMMITTED_SNAPSHOT OFF ; ALTER DATABASE SortTest SET MULTI_USER ; ALTER DATABASE SortTest SET RECOVERY SIMPLE ; USE SortTest; GO CREATE TABLE dbo.TestCHAR ( id INTEGER IDENTITY (1,1) NOT NULL, padding CHAR(3999) NOT NULL,   CONSTRAINT [PK dbo.TestCHAR (id)] PRIMARY KEY CLUSTERED (id), ) ; CREATE TABLE dbo.TestMAX ( id INTEGER IDENTITY (1,1) NOT NULL, padding VARCHAR(MAX) NOT NULL,   CONSTRAINT [PK dbo.TestMAX (id)] PRIMARY KEY CLUSTERED (id), ) ; CREATE TABLE dbo.TestTEXT ( id INTEGER IDENTITY (1,1) NOT NULL, padding TEXT NOT NULL,   CONSTRAINT [PK dbo.TestTEXT (id)] PRIMARY KEY CLUSTERED (id), ) ; -- ============= -- Load TestCHAR (about 3s) -- ============= INSERT INTO dbo.TestCHAR WITH (TABLOCKX) ( padding ) SELECT padding = REPLICATE(CHAR(65 + (Data.n % 26)), 3999) FROM ( SELECT TOP (50000) n = ROW_NUMBER() OVER (ORDER BY (SELECT 0)) - 1 FROM master.sys.columns C1, master.sys.columns C2, master.sys.columns C3 ORDER BY n ASC ) AS Data ORDER BY Data.n ASC ; -- ============ -- Load TestMAX (about 3s) -- ============ INSERT INTO dbo.TestMAX WITH (TABLOCKX) ( padding ) SELECT CONVERT(VARCHAR(MAX), padding) FROM dbo.TestCHAR ORDER BY id ; -- ============= -- Load TestTEXT (about 5s) -- ============= INSERT INTO dbo.TestTEXT WITH (TABLOCKX) ( padding ) SELECT CONVERT(TEXT, padding) FROM dbo.TestCHAR ORDER BY id ; -- ========== -- Space used -- ========== -- EXECUTE sys.sp_spaceused @objname = 'dbo.TestCHAR'; EXECUTE sys.sp_spaceused @objname = 'dbo.TestMAX'; EXECUTE sys.sp_spaceused @objname = 'dbo.TestTEXT'; ; CHECKPOINT ; That takes around 15 seconds to run, and shows the space allocated to each table in its output: To illustrate the points I want to make today, the example task we are going to set ourselves is to return a random set of 150 rows from each table.  The basic shape of the test query is the same for each of the three test tables: SELECT TOP (150) T.id, T.padding FROM dbo.Test AS T ORDER BY NEWID() OPTION (MAXDOP 1) ; Test 1 – CHAR(3999) Running the template query shown above using the TestCHAR table as the target, we find that the query takes around 5 seconds to return its results.  This seems slow, considering that the table only has 50,000 rows.  Working on the assumption that generating a GUID for each row is a CPU-intensive operation, we might try enabling parallelism to see if that speeds up the response time.  Running the query again (but without the MAXDOP 1 hint) on a machine with eight logical processors, the query now takes 10 seconds to execute – twice as long as when run serially. Rather than attempting further guesses at the cause of the slowness, let’s go back to serial execution and add some monitoring.  The script below monitors STATISTICS IO output and the amount of tempdb used by the test query.  We will also run a Profiler trace to capture any warnings generated during query execution. DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TC.id, TC.padding FROM dbo.TestCHAR AS TC ORDER BY NEWID() OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; Let’s take a closer look at the statistics and query plan generated from this: Following the flow of the data from right to left, we see the expected 50,000 rows emerging from the Clustered Index Scan, with a total estimated size of around 191MB.  The Compute Scalar adds a column containing a random GUID (generated from the NEWID() function call) for each row.  With this extra column in place, the size of the data arriving at the Sort operator is estimated to be 192MB. Sort is a blocking operator – it has to examine all of the rows on its input before it can produce its first row of output (the last row received might sort first).  This characteristic means that Sort requires a memory grant – memory allocated for the query’s use by SQL Server just before execution starts.  In this case, the Sort is the only memory-consuming operator in the plan, so it has access to the full 243MB (248,696KB) of memory reserved by SQL Server for this query execution. Notice that the memory grant is significantly larger than the expected size of the data to be sorted.  SQL Server uses a number of techniques to speed up sorting, some of which sacrifice size for comparison speed.  Sorts typically require a very large number of comparisons, so this is usually a very effective optimization.  One of the drawbacks is that it is not possible to exactly predict the sort space needed, as it depends on the data itself.  SQL Server takes an educated guess based on data types, sizes, and the number of rows expected, but the algorithm is not perfect. In spite of the large memory grant, the Profiler trace shows a Sort Warning event (indicating that the sort ran out of memory), and the tempdb usage monitor shows that 195MB of tempdb space was used – all of that for system use.  The 195MB represents physical write activity on tempdb, because SQL Server strictly enforces memory grants – a query cannot ‘cheat’ and effectively gain extra memory by spilling to tempdb pages that reside in memory.  Anyway, the key point here is that it takes a while to write 195MB to disk, and this is the main reason that the query takes 5 seconds overall. If you are wondering why using parallelism made the problem worse, consider that eight threads of execution result in eight concurrent partial sorts, each receiving one eighth of the memory grant.  The eight sorts all spilled to tempdb, resulting in inefficiencies as the spilled sorts competed for disk resources.  More importantly, there are specific problems at the point where the eight partial results are combined, but I’ll cover that in a future post. CHAR(3999) Performance Summary: 5 seconds elapsed time 243MB memory grant 195MB tempdb usage 192MB estimated sort set 25,043 logical reads Sort Warning Test 2 – VARCHAR(MAX) We’ll now run exactly the same test (with the additional monitoring) on the table using a VARCHAR(MAX) padding column: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TM.id, TM.padding FROM dbo.TestMAX AS TM ORDER BY NEWID() OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; This time the query takes around 8 seconds to complete (3 seconds longer than Test 1).  Notice that the estimated row and data sizes are very slightly larger, and the overall memory grant has also increased very slightly to 245MB.  The most marked difference is in the amount of tempdb space used – this query wrote almost 391MB of sort run data to the physical tempdb file.  Don’t draw any general conclusions about VARCHAR(MAX) versus CHAR from this – I chose the length of the data specifically to expose this edge case.  In most cases, VARCHAR(MAX) performs very similarly to CHAR – I just wanted to make test 2 a bit more exciting. MAX Performance Summary: 8 seconds elapsed time 245MB memory grant 391MB tempdb usage 193MB estimated sort set 25,043 logical reads Sort warning Test 3 – TEXT The same test again, but using the deprecated TEXT data type for the padding column: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TT.id, TT.padding FROM dbo.TestTEXT AS TT ORDER BY NEWID() OPTION (MAXDOP 1, RECOMPILE) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; This time the query runs in 500ms.  If you look at the metrics we have been checking so far, it’s not hard to understand why: TEXT Performance Summary: 0.5 seconds elapsed time 9MB memory grant 5MB tempdb usage 5MB estimated sort set 207 logical reads 596 LOB logical reads Sort warning SQL Server’s memory grant algorithm still underestimates the memory needed to perform the sorting operation, but the size of the data to sort is so much smaller (5MB versus 193MB previously) that the spilled sort doesn’t matter very much.  Why is the data size so much smaller?  The query still produces the correct results – including the large amount of data held in the padding column – so what magic is being performed here? TEXT versus MAX Storage The answer lies in how columns of the TEXT data type are stored.  By default, TEXT data is stored off-row in separate LOB pages – which explains why this is the first query we have seen that records LOB logical reads in its STATISTICS IO output.  You may recall from my last post that LOB data leaves an in-row pointer to the separate storage structure holding the LOB data. SQL Server can see that the full LOB value is not required by the query plan until results are returned, so instead of passing the full LOB value down the plan from the Clustered Index Scan, it passes the small in-row structure instead.  SQL Server estimates that each row coming from the scan will be 79 bytes long – 11 bytes for row overhead, 4 bytes for the integer id column, and 64 bytes for the LOB pointer (in fact the pointer is rather smaller – usually 16 bytes – but the details of that don’t really matter right now). OK, so this query is much more efficient because it is sorting a very much smaller data set – SQL Server delays retrieving the LOB data itself until after the Sort starts producing its 150 rows.  The question that normally arises at this point is: Why doesn’t SQL Server use the same trick when the padding column is defined as VARCHAR(MAX)? The answer is connected with the fact that if the actual size of the VARCHAR(MAX) data is 8000 bytes or less, it is usually stored in-row in exactly the same way as for a VARCHAR(8000) column – MAX data only moves off-row into LOB storage when it exceeds 8000 bytes.  The default behaviour of the TEXT type is to be stored off-row by default, unless the ‘text in row’ table option is set suitably and there is room on the page.  There is an analogous (but opposite) setting to control the storage of MAX data – the ‘large value types out of row’ table option.  By enabling this option for a table, MAX data will be stored off-row (in a LOB structure) instead of in-row.  SQL Server Books Online has good coverage of both options in the topic In Row Data. The MAXOOR Table The essential difference, then, is that MAX defaults to in-row storage, and TEXT defaults to off-row (LOB) storage.  You might be thinking that we could get the same benefits seen for the TEXT data type by storing the VARCHAR(MAX) values off row – so let’s look at that option now.  This script creates a fourth table, with the VARCHAR(MAX) data stored off-row in LOB pages: CREATE TABLE dbo.TestMAXOOR ( id INTEGER IDENTITY (1,1) NOT NULL, padding VARCHAR(MAX) NOT NULL,   CONSTRAINT [PK dbo.TestMAXOOR (id)] PRIMARY KEY CLUSTERED (id), ) ; EXECUTE sys.sp_tableoption @TableNamePattern = N'dbo.TestMAXOOR', @OptionName = 'large value types out of row', @OptionValue = 'true' ; SELECT large_value_types_out_of_row FROM sys.tables WHERE [schema_id] = SCHEMA_ID(N'dbo') AND name = N'TestMAXOOR' ; INSERT INTO dbo.TestMAXOOR WITH (TABLOCKX) ( padding ) SELECT SPACE(0) FROM dbo.TestCHAR ORDER BY id ; UPDATE TM WITH (TABLOCK) SET padding.WRITE (TC.padding, NULL, NULL) FROM dbo.TestMAXOOR AS TM JOIN dbo.TestCHAR AS TC ON TC.id = TM.id ; EXECUTE sys.sp_spaceused @objname = 'dbo.TestMAXOOR' ; CHECKPOINT ; Test 4 – MAXOOR We can now re-run our test on the MAXOOR (MAX out of row) table: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) MO.id, MO.padding FROM dbo.TestMAXOOR AS MO ORDER BY NEWID() OPTION (MAXDOP 1, RECOMPILE) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; TEXT Performance Summary: 0.3 seconds elapsed time 245MB memory grant 0MB tempdb usage 193MB estimated sort set 207 logical reads 446 LOB logical reads No sort warning The query runs very quickly – slightly faster than Test 3, and without spilling the sort to tempdb (there is no sort warning in the trace, and the monitoring query shows zero tempdb usage by this query).  SQL Server is passing the in-row pointer structure down the plan and only looking up the LOB value on the output side of the sort. The Hidden Problem There is still a huge problem with this query though – it requires a 245MB memory grant.  No wonder the sort doesn’t spill to tempdb now – 245MB is about 20 times more memory than this query actually requires to sort 50,000 records containing LOB data pointers.  Notice that the estimated row and data sizes in the plan are the same as in test 2 (where the MAX data was stored in-row). The optimizer assumes that MAX data is stored in-row, regardless of the sp_tableoption setting ‘large value types out of row’.  Why?  Because this option is dynamic – changing it does not immediately force all MAX data in the table in-row or off-row, only when data is added or actually changed.  SQL Server does not keep statistics to show how much MAX or TEXT data is currently in-row, and how much is stored in LOB pages.  This is an annoying limitation, and one which I hope will be addressed in a future version of the product. So why should we worry about this?  Excessive memory grants reduce concurrency and may result in queries waiting on the RESOURCE_SEMAPHORE wait type while they wait for memory they do not need.  245MB is an awful lot of memory, especially on 32-bit versions where memory grants cannot use AWE-mapped memory.  Even on a 64-bit server with plenty of memory, do you really want a single query to consume 0.25GB of memory unnecessarily?  That’s 32,000 8KB pages that might be put to much better use. The Solution The answer is not to use the TEXT data type for the padding column.  That solution happens to have better performance characteristics for this specific query, but it still results in a spilled sort, and it is hard to recommend the use of a data type which is scheduled for removal.  I hope it is clear to you that the fundamental problem here is that SQL Server sorts the whole set arriving at a Sort operator.  Clearly, it is not efficient to sort the whole table in memory just to return 150 rows in a random order. The TEXT example was more efficient because it dramatically reduced the size of the set that needed to be sorted.  We can do the same thing by selecting 150 unique keys from the table at random (sorting by NEWID() for example) and only then retrieving the large padding column values for just the 150 rows we need.  The following script implements that idea for all four tables: SET STATISTICS IO ON ; WITH TestTable AS ( SELECT * FROM dbo.TestCHAR ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id = ANY (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestMAX ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestTEXT ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestMAXOOR ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; All four queries now return results in much less than a second, with memory grants between 6 and 12MB, and without spilling to tempdb.  The small remaining inefficiency is in reading the id column values from the clustered primary key index.  As a clustered index, it contains all the in-row data at its leaf.  The CHAR and VARCHAR(MAX) tables store the padding column in-row, so id values are separated by a 3999-character column, plus row overhead.  The TEXT and MAXOOR tables store the padding values off-row, so id values in the clustered index leaf are separated by the much-smaller off-row pointer structure.  This difference is reflected in the number of logical page reads performed by the four queries: Table 'TestCHAR' logical reads 25511 lob logical reads 000 Table 'TestMAX'. logical reads 25511 lob logical reads 000 Table 'TestTEXT' logical reads 00412 lob logical reads 597 Table 'TestMAXOOR' logical reads 00413 lob logical reads 446 We can increase the density of the id values by creating a separate nonclustered index on the id column only.  This is the same key as the clustered index, of course, but the nonclustered index will not include the rest of the in-row column data. CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestCHAR (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestMAX (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestTEXT (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestMAXOOR (id); The four queries can now use the very dense nonclustered index to quickly scan the id values, sort them by NEWID(), select the 150 ids we want, and then look up the padding data.  The logical reads with the new indexes in place are: Table 'TestCHAR' logical reads 835 lob logical reads 0 Table 'TestMAX' logical reads 835 lob logical reads 0 Table 'TestTEXT' logical reads 686 lob logical reads 597 Table 'TestMAXOOR' logical reads 686 lob logical reads 448 With the new index, all four queries use the same query plan (click to enlarge): Performance Summary: 0.3 seconds elapsed time 6MB memory grant 0MB tempdb usage 1MB sort set 835 logical reads (CHAR, MAX) 686 logical reads (TEXT, MAXOOR) 597 LOB logical reads (TEXT) 448 LOB logical reads (MAXOOR) No sort warning I’ll leave it as an exercise for the reader to work out why trying to eliminate the Key Lookup by adding the padding column to the new nonclustered indexes would be a daft idea Conclusion This post is not about tuning queries that access columns containing big strings.  It isn’t about the internal differences between TEXT and MAX data types either.  It isn’t even about the cool use of UPDATE .WRITE used in the MAXOOR table load.  No, this post is about something else: Many developers might not have tuned our starting example query at all – 5 seconds isn’t that bad, and the original query plan looks reasonable at first glance.  Perhaps the NEWID() function would have been blamed for ‘just being slow’ – who knows.  5 seconds isn’t awful – unless your users expect sub-second responses – but using 250MB of memory and writing 200MB to tempdb certainly is!  If ten sessions ran that query at the same time in production that’s 2.5GB of memory usage and 2GB hitting tempdb.  Of course, not all queries can be rewritten to avoid large memory grants and sort spills using the key-lookup technique in this post, but that’s not the point either. The point of this post is that a basic understanding of execution plans is not enough.  Tuning for logical reads and adding covering indexes is not enough.  If you want to produce high-quality, scalable TSQL that won’t get you paged as soon as it hits production, you need a deep understanding of execution plans, and as much accurate, deep knowledge about SQL Server as you can lay your hands on.  The advanced database developer has a wide range of tools to use in writing queries that perform well in a range of circumstances. By the way, the examples in this post were written for SQL Server 2008.  They will run on 2005 and demonstrate the same principles, but you won’t get the same figures I did because 2005 had a rather nasty bug in the Top N Sort operator.  Fair warning: if you do decide to run the scripts on a 2005 instance (particularly the parallel query) do it before you head out for lunch… This post is dedicated to the people of Christchurch, New Zealand. © 2011 Paul White email: @[email protected] twitter: @SQL_Kiwi

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  • Google I/O 2011: Smart App Design

    Google I/O 2011: Smart App Design Travis Green, Max Lin, Robert Kaplow, Jóhannes Kristinsson, Ryan McGee Learn how to recommend the unexpected, automate the repetitive, and distill the essential using machine learning. This session will show you how you can easily add smarts to your apps with the Prediction API, and how to create apps that rapidly adapt to new data. From: GoogleDevelopers Views: 10078 47 ratings Time: 01:01:04 More in Science & Technology

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  • how to reset gnome panel?

    - by Matt
    I think my gnome-panel is messed up because I alt+right click it and nothing pops up. I'm on 12.04, classic gnome desktop. so I used locate and found gnome-panel in .gconf somewhere, how do I clear just gnome-panel's settings so that I can add things to my panel again? edit: matt: ~/.gconf $ find|grep -iw panel ./desktop/ibus/panel ./desktop/ibus/panel/%gconf.xml ./apps/gnome-settings/gnome-panel ./apps/gnome-settings/gnome-panel/%gconf.xml

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  • Dartisans ep. 10: Dart Plugin for IntelliJ

    Dartisans ep. 10: Dart Plugin for IntelliJ Ask and vote for questions at: goo.gl Edit and debug your Dart apps with IntelliJ and WebStorm! In this episode of Dartisans, we'll talk to the engineers working on this exciting project. Join hosts Seth Ladd and JJ Behrens to learn more about writing Dart apps with JetBrain's powerful editors. From: GoogleDevelopers Views: 1279 35 ratings Time: 35:25 More in Science & Technology

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  • Is INT_MIN-1 an underflow or overflow?

    - by Johannes Schaub - litb
    I seem to remember that I was reading that underflow means you have a too small magnitude that cannot be presented anymore in a type overflow means you have a too large magnitude that cannot be presented anymore in a type However, in practice I perceive that the terms are used such that underflow means you have a too small value that cannot be presented anymore in a type overflow means you have a too large value that cannot be presented anymore in a type What is the correct meaning to use here? Are the terms defined differently for integer and floating point types?

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  • Apple Mac App Store?

    - by Riddler
    The Mac App store seems like an ideal distribution channel for apps made specifically for OSX. However, due to the high quantity of apps, I wasn't sure if there was an actual chance of my app making money. What would be a reasonable amount of sales from the Mac App Store for an app made by a small developer? I am wondering if the profit would be worth the effort and money required to get the app in the store.

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  • How you can extend Tasklists in Fusion Applications

    - by Elie Wazen
    In this post we describe the process of modifying and extending a Tasklist available in the Regional Area of a Fusion Applications UI Shell. This is particularly useful to Customers who would like to expose Setup Tasks (generally available in the Fusion Setup Manager application) in the various functional pillars workareas. Oracle Composer, the tool used to implement such extensions allows changes to be made at runtime. The example provided in this document is for an Oracle Fusion Financials page. Let us examine the case of a customer role who requires access to both, a workarea and its associated functional tasks, and to an FSM (setup) task.  Both of these tasks represent ADF Taskflows but each is accessible from a different page.  We will show how an FSM task is added to a Functional tasklist and made accessible to a user from within a single workarea, eliminating the need to navigate between the FSM application and the Functional workarea where transactions are conducted. In general, tasks in Fusion Applications are grouped in two ways: Setup tasks are grouped in tasklists available to implementers in the Functional Setup Manager (FSM). These Tasks are accessed by implementation users and in general do not represent daily operational tasks that fit into a functional business process and were consequently included in the FSM application. For these tasks, the primary organizing principle is precedence between tasks. If task "Manage Suppliers" has prerequisites, those tasks must precede it in a tasklist. Task Lists are organized to efficiently implement an offering. Tasks frequently performed as part of business process flows are made available as links in the tasklist of their corresponding menu workarea. The primary organizing principle in the menu and task pane entries is to group tasks that are generally accessed together. Customizing a tasklist thus becomes required for business scenarios where a task packaged under FSM as a setup task, is for a particular customer a regular maintenance task that is accessed for record updates or creation as part of normal operational activities and where the frequency of this access merits the inclusion of that task in the related operational tasklist A user with the role of maintaining Journals in General Ledger is also responsible for maintaining Chart of Accounts Mappings.  In the Fusion Financials Product Family, Manage Journals is a task available from within the Journals Menu whereas Chart of Accounts Mapping is available via FSM under the Define Chart of Accounts tasklist Figure 1. The Manage Chart of Accounts Mapping Task in FSM Figure 2. The Manage Journals Task in the Task Pane of the Journals Workarea Our goal is to simplify cross task navigation and allow the user to access both tasks from a single tasklist on a single page without having to navigate to FSM for the Mapping task and to the Journals workarea for the Manage task. To accomplish that, we use Oracle Composer to customize  the Journals tasklist by adding to it the Mapping task. Identify the Taskflow name and path of the FSM Task The first step in our process is to identify the underlying taskflow for the Manage Chart of Accounts Mappings task. We select to Setup and Maintenance from the Navigator to launch the FSM Application, and we query the task from Manage Tasklists and Tasks Figure 3. Task Details including Taskflow path The Manage Chart of Accounts Mapping Task Taskflow is: /WEB-INF/oracle/apps/financials/generalLedger/sharedSetup/coaMappings/ui/flow /CoaMappingsMainAreaFlow.xml#CoaMappingsMainAreaFlow We copy that value and use it later as a parameter to our new task in the customized Journals Tasklist. Customize the Journals Page A user with Administration privileges can start the run time customization directly from the Administration Menu of the Global Area.  This customization is done at the Site level and once implemented becomes available to all users with access to the Journals Workarea. Figure 4.  Customization Menu The Oracle Composer Window is displayed in the same browser and the Hierarchy of the page component is displayed and available for modification. Figure 5.  Oracle Composer In the composer Window select the PanelFormLayout node and click on the Edit Button.  Note that the selected component is simultaneously highlighted in the lower pane in the browser. In the Properties popup window, select the Tasks List and Task Properties Tab, where the user finds the hierarchy of the Tasklist and is able to Edit nodes or create new ones. src="https://blogs.oracle.com/FunctionalArchitecture/resource/TL5.jpg" Figure 6.  The Tasklist in edit mode Add a Child Task to the Tasklist In the Edit Window the user will now create a child node at the desired level in the hierarchy by selecting the immediate parent node and clicking on the insert node button.  This process requires four values to be set as described in Table 1 below. Parameter Value How to Determine the Value Focus View Id /JournalEntryPage This is the Focus View ID of the UI Shell where the Tasklist we want to customize is.  A simple way to determine this value is to copy it from any of the Standard tasks on the Tasklist Label COA Mapping This is the Display name of the Task as it will appear in the Tasklist Task Type dynamicMain If the value is dynamicMain, the page contains a new link in the Regional Area. When you click the link, a new tab with the loaded task opens Taskflowid /WEB-INF/oracle/apps/financials/generalLedger/sharedSetup/ coaMappings/ui/flow/ CoaMappingsMainAreaFlow.xml#CoaMappingsMainAreaFlow This is the Taskflow path we retrieved from the Task Definition in FSM earlier in the process Table 1.  Parameters and Values for the Task to be added to the customized Tasklist Figure 7.   The parameters window of the newly added Task   Access the FSM Task from the Journals Workarea Once the FSM task is added and its parameters defined, the user saves the record, closes the Composer making the new task immediately available to users with access to the Journals workarea (Refer to Figure 8 below). Figure 8.   The COA Mapping Task is now visible and can be invoked from the Journals Workarea   Additional Considerations If a Task Flow is part of a product that is deployed on the same app server as the Tasklist workarea then that task flow can be added to a customized tasklist in that workarea. Otherwise that task flow can be invoked from its parent product’s workarea tasklist by selecting that workarea from the Navigator menu. For Example The following Taskflows  belong respectively to the Subledger Accounting, and to the General Ledger Products.  /WEB-INF/oracle/apps/financials/subledgerAccounting/accountingMethodSetup/mappingSets/ui/flow/MappingSetFlow.xml#MappingSetFlow /WEB-INF/oracle/apps/financials/generalLedger/sharedSetup/coaMappings/ui/flow/CoaMappingsMainAreaFlow.xml#CoaMappingsMainAreaFlow Since both the Subledger Accounting and General Ledger products are part of the LedgerApp J2EE Applicaton and are both deployed on the General Ledger Cluster Server (Figure 8 below), the user can add both of the above taskflows to the  tasklist in the  /JournalEntryPage FocusVIewID Workarea. Note:  both FSM Taskflows and Functional Taskflows can be added to the Tasklists as described in this document Figure 8.   The Topology of the Fusion Financials Product Family. Note that SubLedger Accounting and General Ledger are both deployed on the Ledger App Conclusion In this document we have shown how an administrative user can edit the Tasklist in the Regional Area of a Fusion Apps page using Oracle Composer. This is useful for cases where tasks packaged in different workareas are frequently accessed by the same user. By making these tasks available from the same page, we minimize the number of steps in the navigation the user has to do to perform their transactions and queries in Fusion Apps.  The example explained above showed that tasks classified as Setup tasks, meaning made accessible to implementation users from the FSM module can be added to the workarea of their respective Fusion application. This eliminates the need to navigate to FSM to access tasks that are both setup and regular maintenance tasks. References Oracle Fusion Applications Extensibility Guide 11g Release 1 (11.1.1.5) Part Number E16691-02 (Section 3.2) Oracle Fusion Applications Developer's Guide 11g Release 1 (11.1.4) Part Number E15524-05

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  • Silverlight Cream for November 26, 2011 -- #1175

    - by Dave Campbell
    In this Issue: Michael Washington, Manas Patnaik, Jeff Blankenburg, Doug Mair, Jon Galloway, Richard Bartholomew, Peter Bromberg, Joel Reyes, Zeben Chen, Navneet Gupta, and Cathy Sullivan. Above the Fold: Silverlight: "Using ASP.NET PageMethods With Silverlight" Peter Bromberg WP7: "Leveraging Background Services and Agents in Windows Phone 7 (Mango)" Jon Galloway Metro/WinRT/Windows8: "Debugging Contracts using Windows Simulator" Cathy Sullivan LightSwitch: "LightSwitch: It Is About The Money (It Is Always About The Money)" Michael Washington Shoutouts: Michael Palermo's latest Desert Mountain Developers is up Michael Washington's latest Visual Studio #LightSwitch Daily is up From SilverlightCream.com:LightSwitch: It Is About The Money (It Is Always About The Money)Michael Washington has a very nice post up about LightSwitch apps in general and his opinion about the future use... based on what he and I have been up to, I tend to agree on all counts!Accessing Controls from DataGrid ColumnHeader – SilverlightManas Patnaik's latest post is about using the VisualTreeHelper class to iterate through the visual tree to find the controls you need ... including sample code31 Days of Mango | Day #18: Using Sample DataJeff Blankenburg's Day 18 in his 31-Day Mango quest is on Sample Data using Expression Blend, and he begins with great links to his other Blend posts followed by a nice sample data tutorial and source31 Days of Mango | Day #19: Tilt EffectsDoug Mair returns to the reigns of Jeff's 31-Days series with number 19 which is all about Tilt Effects ... as seen in the Phone application when you select a user... Doug shows how to add this effect to your appLeveraging Background Services and Agents in Windows Phone 7 (Mango)Jon Galloway has a WP7 post up discussing Background Services and how they all fit together... he's got a great diagram of that as an overview then really nice discussion of each followed up by his slides from DevConnections, and codeNetflix on Windows 8This one isn't C#/XAML, but Richard Bartholomew has a Netflix on Windows 8 app running that bears noticeUsing ASP.NET PageMethods With SilverlightPeter Bromberg has a post up demonstrating calling PageMethods from a Silverlight app using the ScriptManager controlAWESOME Windows Phone Power ToolJoel Reyes announced the release of a full-featured tool for side-loading apps to your WP7 device... available at codeplexMicrosoft Windows Simulator Rotation and Resolution EmulationZeben Chen discusses the Windows 8 Simulator a bit deeper with this code-laden post showing how to look at roation and orientation-aware apps and resolution.First look at Windows SimulatorNavneet Gupta has a great into post to using the simulator in VS2011 for Windows 8 apps. Four things you really need this for: Touch Emulation, Rotation, Different target resolutions, and ContractsDebugging Contracts using Windows SimulatorCathy Sullivan shows how to debug W8 Contracts in VS2011... why you ask? because when you hit one in the debugger, the target app disappears.. but enter the simulator... check it outStay in the 'Light!Twitter SilverlightNews | Twitter WynApse | WynApse.com | Tagged Posts | SilverlightCreamJoin me @ SilverlightCream | Phoenix Silverlight User GroupTechnorati Tags:Silverlight    Silverlight 3    Silverlight 4    Windows PhoneMIX10

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  • Can I blacklist an appindicator?

    - by d3vid
    I've whitelisted some indicators for apps that don't yet have Unity-compliant appindicators. Is there any way to blacklist appindicators for apps that are Unity-compliant (not old-style indicators) but don't provide a "Don't show in the system tray" option? Any solutions to ban an appindicator from being displayed, GUI- or CLI-based, are welcome. (I'm not looking for a way to just hide them like you can hide system tray icons in Windows.) (New-style appindicators can't be removed from the systray-whitelist.)

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