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  • how to learn a library/framework structure?

    - by fayer
    a lot of people are contributing to open source libraries/frameworks. i wonder how these people learn the structure so that they can contribute? lets take doctrine and symfony as an example. is there a blueprint over these frameworks to give the developers an insight of the structure? or do they just download it and study the code? how does it work? please you contributors, share your learning strategies! thanks

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  • Is there a concurrent container library for C++

    - by Lirik
    I'm looking for implementations of lock-free containers: Blocking Queue Blocking Stack Hash Map etc... Are there any good libraries out there? I would like to refrain from writing these data structures... I would much rather use something that has been tested by the community.

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  • Calendar control GUI C++ library

    - by Dmitriy
    Who knows a good component for a "calendar control" (NOT date/time picker)? "Calendar control" means something like Mozilla Sunbird: Requirements to the control: - C++; - Day/Week/Month view; - Support of several calendars; - Without MFC dependences; Nice to have: - Open source; - Cross plathform; - Free; - Minimum external dependences (boost etc are fine);

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  • Load a model in a Codeigniter library

    - by ci
    Hello, people! I have this piece of code: class MY_Language extends CI_Language { function MY_Language() { parent::CI_Language(); $CI =& get_instance(); $CI->load->model('language_model'); $languages = $this->language_model->get_languages(); print_r($languages); } } But I keep getting "Fatal error: Call to undefined function get_instance() in C:\xampp\htdocs\application\libraries\MY_Language.php on line 44". Any ideas? Thanks in advance!

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  • 3D framework/library os x

    - by Deano
    Does anyone have any advice as to a good framework for simplifying the generation of 3D models? I am trying to construct a parametric program for tasks such as ship design. Actions such as surface modelling, intersections etc are a must. I have investigated openCASCADE and it shows promise but getting it to integrate into a native cocoa interface is not currently achievable (By me at any rate). All ideas and suggestions welcome. Should I just forget it and integrate an X11 window, if so any tutorials for doing this?

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  • C++ RPC library suggestions

    - by Oxsnarder
    I'm looking for suggestions regarding RPC libraries implemented in C++, for C++ developers. Some requirements constraints: Should work on both linux/unix and win32 systems Be able to execute free function and class methods Hopefully written in modern C++ not 90's/java-esque C++ Be able to function over networks and hetrogenous architectures Not too slow or inefficient Hopefully provide interfaces for TR1 style std::function's et al. My example usage is to invoke the free function foo on a remote machine. ---snip--- // foo translation unit int foo(int i, int j) { return i + j; } ---snip--- ---snip--- // client side main int main() { //register foo on client and server //setup necassary connections and states int result; if (RPCmechanism.invoke("foo",4,9,result)) std::cout << "foo(4,9) = " result << std::endl; else std::cout << "failed to invoke foo(4,9)!" << std::endl; return 0; } ---snip--- Something that can achieve the above or similar would be great.

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  • Task Parallel Library exception handling

    - by user1680766
    When handling exceptions in TPL tasks I have come across two ways to handle exceptions. The first catches the exception within the task and returns it within the result like so: var task = Task<Exception>.Factory.StartNew( () => { try { // Do Something return null; } catch (System.Exception e) { return e; } }); task.ContinueWith( r => { if (r.Result != null) { // Handle Exception } }); The second is the one shown within the documentation and I guess the proper way to do things: var task = Task.Factory.StartNew( () => { // Do Something }); task.ContinueWith( r => { if (r.Exception != null) { // Handle Aggregate Exception r.Exception.Handle(y => true); } }); I am wondering if there is anything wrong with the first approach? I have received 'unhandled aggregate exception' exceptions every now and again using this technique and was wondering how this can happen?

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  • Help with PHPExcel Library and mySQL data from a table

    - by user547363
    Hello! Everyone.. I have this script $query = "SELECT id,last_name,first_name FROM users WHERE tmima_id='6'"; $result = @mysql_query($query); while($row = mysql_fetch_array($result)) { $i = 3; $emp_id = $row['id']; $cell = 'A'.$i; $objPHPExcel->setActiveSheetIndex(0) ->setCellValue($cell, $row['last_name']. $row['first_name']); $i++; } But in the .xls file it prints only one user. Why id doesnt print all of the users ? W Thanks in advance.

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  • Class library modification / migration

    - by Clint
    I have 3 class libraries. A BBL, a DAL, and a DATA (about 15 datasets). Currently 4 [major] applications utilize the functionality in these DLL's. I'm rewriting one of those applications and I need to (1) Use some of the existing functionality in the libraries (2) Change some of it (3) Add new functionality (4) Add new datasets. I'm back and forth about the best way to do this, while keeping my risks at a minimum. Some thoughts.. 1) Use the existing projects and don't make any modifications, only additions 2) Make new libraries, bring over the code I can use, and make additions as needed 3) Implement partial classes in the existing projects Eventually all 4 applications will use the newest functionality, but it will be a slow migration; so the old code can't be depricated yet. Any thoughts?

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  • Creating a relative path to a Database in Asp.net for a library

    - by Greener
    In school I am part of a team of four working to create a GUI to translate the paper records of a made-up company and their functionality to a digital format. We're using an ASP.NET website for this purpose. Basically we use stored procedures and C# classes to represent the database. The folder we're using for the project contains the site and the libraries in separate folders. If I try to open the site from the folder containing both these elements the site will not run. I want to know if there is some way I can set up a relative path to the database in the Settings.Settings.cs file (or by some other means) of my libraries so I don't have to constantly change the database location for the connection string value every time we move the project. I suppose I should also mention that the database is in an App_Data folder.

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  • New .NET Library for Accessing the Survey Monkey API

    - by Ben Emmett
    I’ve used Survey Monkey’s API for a while, and though it’s pretty powerful, there’s a lot of boilerplate each time it’s used in a new project, and the json it returns needs a bunch of processing to be able to use the raw information. So I’ve finally got around to releasing a .NET library you can use to consume the API more easily. The main advantages are: Only ever deal with strongly-typed .NET objects, making everything much more robust and a lot faster to get going Automatically handles things like rate-limiting and paging through results Uses combinations of endpoints to get all relevant data for you, and processes raw response data to map responses to questions To start, either install it using NuGet with PM> Install-Package SurveyMonkeyApi (easier option), or grab the source from https://github.com/bcemmett/SurveyMonkeyApi if you prefer to build it yourself. You’ll also need to have signed up for a developer account with Survey Monkey, and have both your API key and an OAuth token. A simple usage would be something like: string apiKey = "KEY"; string token = "TOKEN"; var sm = new SurveyMonkeyApi(apiKey, token); List<Survey> surveys = sm.GetSurveyList(); The surveys object is now a list of surveys with all the information available from the /surveys/get_survey_list API endpoint, including the title, id, date it was created and last modified, language, number of questions / responses, and relevant urls. If there are more than 1000 surveys in your account, the library pages through the results for you, making multiple requests to get a complete list of surveys. All the filtering available in the API can be controlled using .NET objects. For example you might only want surveys created in the last year and containing “pineapple” in the title: var settings = new GetSurveyListSettings { Title = "pineapple", StartDate = DateTime.Now.AddYears(-1) }; List<Survey> surveys = sm.GetSurveyList(settings); By default, whenever optional fields can be requested with a response, they will all be fetched for you. You can change this behaviour if for some reason you explicitly don’t want the information, using var settings = new GetSurveyListSettings { OptionalData = new GetSurveyListSettingsOptionalData { DateCreated = false, AnalysisUrl = false } }; Survey Monkey’s 7 read-only endpoints are supported, and the other 4 which make modifications to data might be supported in the future. The endpoints are: Endpoint Method Object returned /surveys/get_survey_list GetSurveyList() List<Survey> /surveys/get_survey_details GetSurveyDetails() Survey /surveys/get_collector_list GetCollectorList() List<Collector> /surveys/get_respondent_list GetRespondentList() List<Respondent> /surveys/get_responses GetResponses() List<Response> /surveys/get_response_counts GetResponseCounts() Collector /user/get_user_details GetUserDetails() UserDetails /batch/create_flow Not supported Not supported /batch/send_flow Not supported Not supported /templates/get_template_list Not supported Not supported /collectors/create_collector Not supported Not supported The hierarchy of objects the library can return is Survey List<Page> List<Question> QuestionType List<Answer> List<Item> List<Collector> List<Response> Respondent List<ResponseQuestion> List<ResponseAnswer> Each of these classes has properties which map directly to the names of properties returned by the API itself (though using PascalCasing which is more natural for .NET, rather than the snake_casing used by SurveyMonkey). For most users, Survey Monkey imposes a rate limit of 2 requests per second, so by default the library leaves at least 500ms between requests. You can request higher limits from them, so if you want to change the delay between requests just use a different constructor: var sm = new SurveyMonkeyApi(apiKey, token, 200); //200ms delay = 5 reqs per sec There’s a separate cap of 1000 requests per day for each API key, which the library doesn’t currently enforce, so if you think you’ll be in danger of exceeding that you’ll need to handle it yourself for now.  To help, you can see how many requests the current instance of the SurveyMonkeyApi object has made by reading its RequestsMade property. If the library encounters any errors, including communicating with the API, it will throw a SurveyMonkeyException, so be sure to handle that sensibly any time you use it to make calls. Finally, if you have a survey (or list of surveys) obtained using GetSurveyList(), the library can automatically fill in all available information using sm.FillMissingSurveyInformation(surveys); For each survey in the list, it uses the other endpoints to fill in the missing information about the survey’s question structure, respondents, and responses. This results in at least 5 API calls being made per survey, so be careful before passing it a large list. It also joins up the raw response information to the survey’s question structure, so that for each question in a respondent’s set of replies, you can access a ProcessedAnswer object. For example, a response to a dropdown question (from the /surveys/get_responses endpoint) might be represented in json as { "answers": [ { "row": "9384627365", } ], "question_id": "615487516" } Separately, the question’s structure (from the /surveys/get_survey_details endpoint) might have several possible answers, one of which might look like { "text": "Fourth item in dropdown list", "visible": true, "position": 4, "type": "row", "answer_id": "9384627365" } The library understands how this mapping works, and uses that to give you the following ProcessedAnswer object, which first describes the family and type of question, and secondly gives you the respondent’s answers as they relate to the question. Survey Monkey has many different question types, with 11 distinct data structures, each of which are supported by the library. If you have suggestions or spot any bugs, let me know in the comments, or even better submit a pull request .

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  • Oracle Big Data Learning Library - Click on LEARN BY PRODUCT to Open Page

    - by chberger
    Oracle Big Data Learning Library... Learn about Oracle Big Data, Data Science, Learning Analytics, Oracle NoSQL Database, and more! Oracle Big Data Essentials Attend this Oracle University Course! Using Oracle NoSQL Database Attend this Oracle University class! Oracle and Big Data on OTN See the latest resource on OTN. Search Welcome Get Started Learn by Role Learn by Product Latest Additions Additional Resources Oracle Big Data Appliance Oracle Big Data and Data Science Basics Meeting the Challenge of Big Data Oracle Big Data Tutorial Video Series Oracle MoviePlex - a Big Data End-to-End Series of Demonstrations Oracle Big Data Overview Oracle Big Data Essentials Data Mining Oracle NoSQL Database Tutorial Videos Oracle NoSQL Database Tutorial Series Oracle NoSQL Database Release 2 New Features Using Oracle NoSQL Database Exalytics Enterprise Manager 12c R3: Manage Exalytics Setting Up and Running Summary Advisor on an E s Oracle R Enterprise Oracle R Enterprise Tutorial Series Oracle Big Data Connectors Integrate All Your Data with Oracle Big Data Connectors Using Oracle Direct Connector for HDFS to Read the Data from HDSF Using Oracle R Connector for Hadoop to Analyze Data Oracle NoSQL Database Oracle NoSQL Database Tutorial Videos Oracle NoSQL Database Tutorial Series Oracle NoSQL Database Release 2 New Features  Using Oracle NoSQL Database eries Oracle Business Intelligence Enterprise Edition Oracle Business Intelligence Oracle BI 11g R1: Create Analyses and Dashboards - 4 day class Oracle BI Publisher 11g R1: Fundamentals - 3 day class Oracle BI 11g R1: Build Repositories - 5 day class

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  • Windows Azure: Backup Services Release, Hyper-V Recovery Manager, VM Enhancements, Enhanced Enterprise Management Support

    - by ScottGu
    This morning we released a huge set of updates to Windows Azure.  These new capabilities include: Backup Services: General Availability of Windows Azure Backup Services Hyper-V Recovery Manager: Public preview of Windows Azure Hyper-V Recovery Manager Virtual Machines: Delete Attached Disks, Availability Set Warnings, SQL AlwaysOn Configuration Active Directory: Securely manage hundreds of SaaS applications Enterprise Management: Use Active Directory to Better Manage Windows Azure Windows Azure SDK 2.2: A massive update of our SDK + Visual Studio tooling support All of these improvements are now available to use immediately.  Below are more details about them. Backup Service: General Availability Release of Windows Azure Backup Today we are releasing Windows Azure Backup Service as a general availability service.  This release is now live in production, backed by an enterprise SLA, supported by Microsoft Support, and is ready to use for production scenarios. Windows Azure Backup is a cloud based backup solution for Windows Server which allows files and folders to be backed up and recovered from the cloud, and provides off-site protection against data loss. The service provides IT administrators and developers with the option to back up and protect critical data in an easily recoverable way from any location with no upfront hardware cost. Windows Azure Backup is built on the Windows Azure platform and uses Windows Azure blob storage for storing customer data. Windows Server uses the downloadable Windows Azure Backup Agent to transfer file and folder data securely and efficiently to the Windows Azure Backup Service. Along with providing cloud backup for Windows Server, Windows Azure Backup Service also provides capability to backup data from System Center Data Protection Manager and Windows Server Essentials, to the cloud. All data is encrypted onsite before it is sent to the cloud, and customers retain and manage the encryption key (meaning the data is stored entirely secured and can’t be decrypted by anyone but yourself). Getting Started To get started with the Windows Azure Backup Service, create a new Backup Vault within the Windows Azure Management Portal.  Click New->Data Services->Recovery Services->Backup Vault to do this: Once the backup vault is created you’ll be presented with a simple tutorial that will help guide you on how to register your Windows Servers with it: Once the servers you want to backup are registered, you can use the appropriate local management interface (such as the Microsoft Management Console snap-in, System Center Data Protection Manager Console, or Windows Server Essentials Dashboard) to configure the scheduled backups and to optionally initiate recoveries. You can follow these tutorials to learn more about how to do this: Tutorial: Schedule Backups Using the Windows Azure Backup Agent This tutorial helps you with setting up a backup schedule for your registered Windows Servers. Additionally, it also explains how to use Windows PowerShell cmdlets to set up a custom backup schedule. Tutorial: Recover Files and Folders Using the Windows Azure Backup Agent This tutorial helps you with recovering data from a backup. Additionally, it also explains how to use Windows PowerShell cmdlets to do the same tasks. Below are some of the key benefits the Windows Azure Backup Service provides: Simple configuration and management. Windows Azure Backup Service integrates with the familiar Windows Server Backup utility in Windows Server, the Data Protection Manager component in System Center and Windows Server Essentials, in order to provide a seamless backup and recovery experience to a local disk, or to the cloud. Block level incremental backups. The Windows Azure Backup Agent performs incremental backups by tracking file and block level changes and only transferring the changed blocks, hence reducing the storage and bandwidth utilization. Different point-in-time versions of the backups use storage efficiently by only storing the changes blocks between these versions. Data compression, encryption and throttling. The Windows Azure Backup Agent ensures that data is compressed and encrypted on the server before being sent to the Windows Azure Backup Service over the network. As a result, the Windows Azure Backup Service only stores encrypted data in the cloud storage. The encryption key is not available to the Windows Azure Backup Service, and as a result the data is never decrypted in the service. Also, users can setup throttling and configure how the Windows Azure Backup service utilizes the network bandwidth when backing up or restoring information. Data integrity is verified in the cloud. In addition to the secure backups, the backed up data is also automatically checked for integrity once the backup is done. As a result, any corruptions which may arise due to data transfer can be easily identified and are fixed automatically. Configurable retention policies for storing data in the cloud. The Windows Azure Backup Service accepts and implements retention policies to recycle backups that exceed the desired retention range, thereby meeting business policies and managing backup costs. Hyper-V Recovery Manager: Now Available in Public Preview I’m excited to also announce the public preview of a new Windows Azure Service – the Windows Azure Hyper-V Recovery Manager (HRM). Windows Azure Hyper-V Recovery Manager helps protect your business critical services by coordinating the replication and recovery of System Center Virtual Machine Manager 2012 SP1 and System Center Virtual Machine Manager 2012 R2 private clouds at a secondary location. With automated protection, asynchronous ongoing replication, and orderly recovery, the Hyper-V Recovery Manager service can help you implement Disaster Recovery and restore important services accurately, consistently, and with minimal downtime. Application data in an Hyper-V Recovery Manager scenarios always travels on your on-premise replication channel. Only metadata (such as names of logical clouds, virtual machines, networks etc.) that is needed for orchestration is sent to Azure. All traffic sent to/from Azure is encrypted. You can begin using Windows Azure Hyper-V Recovery today by clicking New->Data Services->Recovery Services->Hyper-V Recovery Manager within the Windows Azure Management Portal.  You can read more about Windows Azure Hyper-V Recovery Manager in Brad Anderson’s 9-part series, Transform the datacenter. To learn more about setting up Hyper-V Recovery Manager follow our detailed step-by-step guide. Virtual Machines: Delete Attached Disks, Availability Set Warnings, SQL AlwaysOn Today’s Windows Azure release includes a number of nice updates to Windows Azure Virtual Machines.  These improvements include: Ability to Delete both VM Instances + Attached Disks in One Operation Prior to today’s release, when you deleted VMs within Windows Azure we would delete the VM instance – but not delete the drives attached to the VM.  You had to manually delete these yourself from the storage account.  With today’s update we’ve added a convenience option that now allows you to either retain or delete the attached disks when you delete the VM:   We’ve also added the ability to delete a cloud service, its deployments, and its role instances with a single action. This can either be a cloud service that has production and staging deployments with web and worker roles, or a cloud service that contains virtual machines.  To do this, simply select the Cloud Service within the Windows Azure Management Portal and click the “Delete” button: Warnings on Availability Sets with Only One Virtual Machine In Them One of the nice features that Windows Azure Virtual Machines supports is the concept of “Availability Sets”.  An “availability set” allows you to define a tier/role (e.g. webfrontends, databaseservers, etc) that you can map Virtual Machines into – and when you do this Windows Azure separates them across fault domains and ensures that at least one of them is always available during servicing operations.  This enables you to deploy applications in a high availability way. One issue we’ve seen some customers run into is where they define an availability set, but then forget to map more than one VM into it (which defeats the purpose of having an availability set).  With today’s release we now display a warning in the Windows Azure Management Portal if you have only one virtual machine deployed in an availability set to help highlight this: You can learn more about configuring the availability of your virtual machines here. Configuring SQL Server Always On SQL Server Always On is a great feature that you can use with Windows Azure to enable high availability and DR scenarios with SQL Server. Today’s Windows Azure release makes it even easier to configure SQL Server Always On by enabling “Direct Server Return” endpoints to be configured and managed within the Windows Azure Management Portal.  Previously, setting this up required using PowerShell to complete the endpoint configuration.  Starting today you can enable this simply by checking the “Direct Server Return” checkbox: You can learn more about how to use direct server return for SQL Server AlwaysOn availability groups here. Active Directory: Application Access Enhancements This summer we released our initial preview of our Application Access Enhancements for Windows Azure Active Directory.  This service enables you to securely implement single-sign-on (SSO) support against SaaS applications (including Office 365, SalesForce, Workday, Box, Google Apps, GitHub, etc) as well as LOB based applications (including ones built with the new Windows Azure AD support we shipped last week with ASP.NET and VS 2013). Since the initial preview we’ve enhanced our SAML federation capabilities, integrated our new password vaulting system, and shipped multi-factor authentication support. We've also turned on our outbound identity provisioning system and have it working with hundreds of additional SaaS Applications: Earlier this month we published an update on dates and pricing for when the service will be released in general availability form.  In this blog post we announced our intention to release the service in general availability form by the end of the year.  We also announced that the below features would be available in a free tier with it: SSO to every SaaS app we integrate with – Users can Single Sign On to any app we are integrated with at no charge. This includes all the top SAAS Apps and every app in our application gallery whether they use federation or password vaulting. Application access assignment and removal – IT Admins can assign access privileges to web applications to the users in their active directory assuring that every employee has access to the SAAS Apps they need. And when a user leaves the company or changes jobs, the admin can just as easily remove their access privileges assuring data security and minimizing IP loss User provisioning (and de-provisioning) – IT admins will be able to automatically provision users in 3rd party SaaS applications like Box, Salesforce.com, GoToMeeting, DropBox and others. We are working with key partners in the ecosystem to establish these connections, meaning you no longer have to continually update user records in multiple systems. Security and auditing reports – Security is a key priority for us. With the free version of these enhancements you'll get access to our standard set of access reports giving you visibility into which users are using which applications, when they were using them and where they are using them from. In addition, we'll alert you to un-usual usage patterns for instance when a user logs in from multiple locations at the same time. Our Application Access Panel – Users are logging in from every type of devices including Windows, iOS, & Android. Not all of these devices handle authentication in the same manner but the user doesn't care. They need to access their apps from the devices they love. Our Application Access Panel will support the ability for users to access access and launch their apps from any device and anywhere. You can learn more about our plans for application management with Windows Azure Active Directory here.  Try out the preview and start using it today. Enterprise Management: Use Active Directory to Better Manage Windows Azure Windows Azure Active Directory provides the ability to manage your organization in a directory which is hosted entirely in the cloud, or alternatively kept in sync with an on-premises Windows Server Active Directory solution (allowing you to seamlessly integrate with the directory you already have).  With today’s Windows Azure release we are integrating Windows Azure Active Directory even more within the core Windows Azure management experience, and enabling an even richer enterprise security offering.  Specifically: 1) All Windows Azure accounts now have a default Windows Azure Active Directory created for them.  You can create and map any users you want into this directory, and grant administrative rights to manage resources in Windows Azure to these users. 2) You can keep this directory entirely hosted in the cloud – or optionally sync it with your on-premises Windows Server Active Directory.  Both options are free.  The later approach is ideal for companies that wish to use their corporate user identities to sign-in and manage Windows Azure resources.  It also ensures that if an employee leaves an organization, his or her access control rights to the company’s Windows Azure resources are immediately revoked. 3) The Windows Azure Service Management APIs have been updated to support using Windows Azure Active Directory credentials to sign-in and perform management operations.  Prior to today’s release customers had to download and use management certificates (which were not scoped to individual users) to perform management operations.  We still support this management certificate approach (don’t worry – nothing will stop working).  But we think the new Windows Azure Active Directory authentication support enables an even easier and more secure way for customers to manage resources going forward.  4) The Windows Azure SDK 2.2 release (which is also shipping today) includes built-in support for the new Service Management APIs that authenticate with Windows Azure Active Directory, and now allow you to create and manage Windows Azure applications and resources directly within Visual Studio using your Active Directory credentials.  This, combined with updated PowerShell scripts that also support Active Directory, enables an end-to-end enterprise authentication story with Windows Azure. Below are some details on how all of this works: Subscriptions within a Directory As part of today’s update, we have associated all existing Window Azure accounts with a Windows Azure Active Directory (and created one for you if you don’t already have one). When you login to the Windows Azure Management Portal you’ll now see the directory name in the URI of the browser.  For example, in the screen-shot below you can see that I have a “scottgu” directory that my subscriptions are hosted within: Note that you can continue to use Microsoft Accounts (formerly known as Microsoft Live IDs) to sign-into Windows Azure.  These map just fine to a Windows Azure Active Directory – so there is no need to create new usernames that are specific to a directory if you don’t want to.  In the scenario above I’m actually logged in using my @hotmail.com based Microsoft ID which is now mapped to a “scottgu” active directory that was created for me.  By default everything will continue to work just like you used to before. Manage your Directory You can manage an Active Directory (including the one we now create for you by default) by clicking the “Active Directory” tab in the left-hand side of the portal.  This will list all of the directories in your account.  Clicking one the first time will display a getting started page that provides documentation and links to perform common tasks with it: You can use the built-in directory management support within the Windows Azure Management Portal to add/remove/manage users within the directory, enable multi-factor authentication, associate a custom domain (e.g. mycompanyname.com) with the directory, and/or rename the directory to whatever friendly name you want (just click the configure tab to do this).  You can also setup the directory to automatically sync with an on-premises Active Directory using the “Directory Integration” tab. Note that users within a directory by default do not have admin rights to login or manage Windows Azure based resources.  You still need to explicitly grant them co-admin permissions on a subscription for them to login or manage resources in Windows Azure.  You can do this by clicking the Settings tab on the left-hand side of the portal and then by clicking the administrators tab within it. Sign-In Integration within Visual Studio If you install the new Windows Azure SDK 2.2 release, you can now connect to Windows Azure from directly inside Visual Studio without having to download any management certificates.  You can now just right-click on the “Windows Azure” icon within the Server Explorer and choose the “Connect to Windows Azure” context menu option to do so: Doing this will prompt you to enter the email address of the username you wish to sign-in with (make sure this account is a user in your directory with co-admin rights on a subscription): You can use either a Microsoft Account (e.g. Windows Live ID) or an Active Directory based Organizational account as the email.  The dialog will update with an appropriate login prompt depending on which type of email address you enter: Once you sign-in you’ll see the Windows Azure resources that you have permissions to manage show up automatically within the Visual Studio server explorer and be available to start using: No downloading of management certificates required.  All of the authentication was handled using your Windows Azure Active Directory! Manage Subscriptions across Multiple Directories If you have already have multiple directories and multiple subscriptions within your Windows Azure account, we have done our best to create a good default mapping of your subscriptions->directories as part of today’s update.  If you don’t like the default subscription-to-directory mapping we have done you can click the Settings tab in the left-hand navigation of the Windows Azure Management Portal and browse to the Subscriptions tab within it: If you want to map a subscription under a different directory in your account, simply select the subscription from the list, and then click the “Edit Directory” button to choose which directory to map it to.  Mapping a subscription to a different directory takes only seconds and will not cause any of the resources within the subscription to recycle or stop working.  We’ve made the directory->subscription mapping process self-service so that you always have complete control and can map things however you want. Filtering By Directory and Subscription Within the Windows Azure Management Portal you can filter resources in the portal by subscription (allowing you to show/hide different subscriptions).  If you have subscriptions mapped to multiple directory tenants, we also now have a filter drop-down that allows you to filter the subscription list by directory tenant.  This filter is only available if you have multiple subscriptions mapped to multiple directories within your Windows Azure Account:   Windows Azure SDK 2.2 Today we are also releasing a major update of our Windows Azure SDK.  The Windows Azure SDK 2.2 release adds some great new features including: Visual Studio 2013 Support Integrated Windows Azure Sign-In support within Visual Studio Remote Debugging Cloud Services with Visual Studio Firewall Management support within Visual Studio for SQL Databases Visual Studio 2013 RTM VM Images for MSDN Subscribers Windows Azure Management Libraries for .NET Updated Windows Azure PowerShell Cmdlets and ScriptCenter I’ll post a follow-up blog shortly with more details about all of the above. Additional Updates In addition to the above enhancements, today’s release also includes a number of additional improvements: AutoScale: Richer time and date based scheduling support (set different rules on different dates) AutoScale: Ability to Scale to Zero Virtual Machines (very useful for Dev/Test scenarios) AutoScale: Support for time-based scheduling of Mobile Service AutoScale rules Operation Logs: Auditing support for Service Bus management operations Today we also shipped a major update to the Windows Azure SDK – Windows Azure SDK 2.2.  It has so much goodness in it that I have a whole second blog post coming shortly on it! :-) Summary Today’s Windows Azure release enables a bunch of great new scenarios, and enables a much richer enterprise authentication offering. If you don’t already have a Windows Azure account, you can sign-up for a free trial and start using all of the above features today.  Then visit the Windows Azure Developer Center to learn more about how to build apps with it. Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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  • OBIEE 11.1.1 - (Updated) Best Practices Guide for Tuning Oracle® Business Intelligence Enterprise Edition (Whitepaper)

    - by Ahmed Awan
    Applies To: This whitepaper applies to OBIEE release 11.1.1.3, 11.1.1.5 and 11.1.1.6 Introduction: One of the most challenging aspects of performance tuning is knowing where to begin. To maximize Oracle® Business Intelligence Enterprise Edition performance, you need to monitor, analyze, and tune all the Fusion Middleware / BI components. This guide describes the tools that you can use to monitor performance and the techniques for optimizing the performance of Oracle® Business Intelligence Enterprise Edition components. Click to Download the OBIEE Infrastructure Tuning Whitepaper (Right click or option-click the link and choose "Save As..." to download this file) Disclaimer: All tuning information stated in this guide is only for orientation, every modification has to be tested and its impact should be monitored and analyzed. Before implementing any of the tuning settings, it is recommended to carry out end to end performance testing that will also include to obtain baseline performance data for the default configurations, make incremental changes to the tuning settings and then collect performance data. Otherwise it may worse the system performance.

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  • Oracle Enterprise Data Quality: Ever Integration-ready

    - by Mala Narasimharajan
    It is closing in on a year now since Oracle’s acquisition of Datanomic, and the addition of Oracle Enterprise Data Quality (EDQ) to the Oracle software family. The big move has caused some big shifts in emphasis and some very encouraging excitement from the field.  To give an illustration, combined with a shameless promotion of how EDQ can help to give quick insights into your data, I did a quick Phrase Profile of the subject field of emails to the Global EDQ mailing list since it was set up last September. The results revealed a very clear theme:   Integration, Integration, Integration! As well as the important Siebel and Oracle Data Integrator (ODI) integrations, we have been asked about integration with a huge variety of Oracle applications, including EBS, Peoplesoft, CRM on Demand, Fusion, DRM, Endeca, RightNow, and more - and we have not stood still! While it would not have been possible to develop specific pre-integrations with all of the above within a year, we have developed a package of feature-rich out-of-the-box web services and batch processes that can be plugged into any application or middleware technology with ease. And with Siebel, they work out of the box. Oracle Enterprise Data Quality version 9.0.4 includes the Customer Data Services (CDS) pack – a ready set of standard processes with standard interfaces, to provide integrated: Address verification and cleansing  Individual matching Organization matching The services can are suitable for either Batch or Real-Time processing, and are enabled for international data, with simple configuration options driving the set of locale-specific dictionaries that are used. For example, large dictionaries are provided to support international name transcription and variant matching, including highly specialized handling for Arabic, Japanese, Chinese and Korean data. In total across all locales, CDS includes well over a million dictionary entries.   Excerpt from EDQ’s CDS Individual Name Standardization Dictionary CDS has been developed to replace the OEM of Informatica Identity Resolution (IIR) for attached Data Quality on the Oracle price list, but does this in a way that creates a ‘best of both worlds’ situation for customers, who can harness not only the out-of-the-box functionality of pre-packaged matching and standardization services, but also the flexibility of OEDQ if they want to customize the interfaces or the process logic, without having to learn more than one product. From a competitive point of view, we believe this stands us in good stead against our key competitors, including Informatica, who have separate ‘Identity Resolution’ and general DQ products, and IBM, who provide limited out-of-the-box capabilities (with a steep learning curve) in both their QualityStage data quality and Initiate matching products. Here is a brief guide to the main services provided in the pack: Address Verification and Standardization EDQ’s CDS Address Cleaning Process The Address Verification and Standardization service uses EDQ Address Verification (an OEM of Loqate software) to verify and clean addresses in either real-time or batch. The Address Verification processor is wrapped in an EDQ process – this adds significant capabilities over calling the underlying Address Verification API directly, specifically: Country-specific thresholds to determine when to accept the verification result (and therefore to change the input address) based on the confidence level of the API Optimization of address verification by pre-standardizing data where required Formatting of output addresses into the input address fields normally used by applications Adding descriptions of the address verification and geocoding return codes The process can then be used to provide real-time and batch address cleansing in any application; such as a simple web page calling address cleaning and geocoding as part of a check on individual data.     Duplicate Prevention Unlike Informatica Identity Resolution (IIR), EDQ uses stateless services for duplicate prevention to avoid issues caused by complex replication and synchronization of large volume customer data. When a record is added or updated in an application, the EDQ Cluster Key Generation service is called, and returns a number of key values. These are used to select other records (‘candidates’) that may match in the application data (which has been pre-seeded with keys using the same service). The ‘driving record’ (the new or updated record) is then presented along with all selected candidates to the EDQ Matching Service, which decides which of the candidates are a good match with the driving record, and scores them according to the strength of match. In this model, complex multi-locale EDQ techniques can be used to generate the keys and ensure that the right balance between performance and matching effectiveness is maintained, while ensuring that the application retains control of data integrity and transactional commits. The process is explained below: EDQ Duplicate Prevention Architecture Note that where the integration is with a hub, there may be an additional call to the Cluster Key Generation service if the master record has changed due to merges with other records (and therefore needs to have new key values generated before commit). Batch Matching In order to allow customers to use different match rules in batch to real-time, separate matching templates are provided for batch matching. For example, some customers want to minimize intervention in key user flows (such as adding new customers) in front end applications, but to conduct a more exhaustive match on a regular basis in the back office. The batch matching jobs are also used when migrating data between systems, and in this case normally a more precise (and automated) type of matching is required, in order to minimize the review work performed by Data Stewards.  In batch matching, data is captured into EDQ using its standard interfaces, and records are standardized, clustered and matched in an EDQ job before matches are written out. As with all EDQ jobs, batch matching may be called from Oracle Data Integrator (ODI) if required. When working with Siebel CRM (or master data in Siebel UCM), Siebel’s Data Quality Manager is used to instigate batch jobs, and a shared staging database is used to write records for matching and to consume match results. The CDS batch matching processes automatically adjust to Siebel’s ‘Full Match’ (match all records against each other) and ‘Incremental Match’ (match a subset of records against all of their selected candidates) modes. The Future The Customer Data Services Pack is an important part of the Oracle strategy for EDQ, offering a clear path to making Data Quality Assurance an integral part of enterprise applications, and providing a strong value proposition for adopting EDQ. We are planning various additions and improvements, including: An out-of-the-box Data Quality Dashboard Even more comprehensive international data handling Address search (suggesting multiple results) Integrated address matching The EDQ Customer Data Services Pack is part of the Enterprise Data Quality Media Pack, available for download at http://www.oracle.com/technetwork/middleware/oedq/downloads/index.html.

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  • How to install Revolution R Enterprise?

    - by Abe
    Revolution R Enterprise is available as a red-hat rpm file. Normally I would use alien to install an rpm file, but the instructions for installing this package have an install.py file that I am supposed to execute. When I ./install.py, I get the following instructions: rpm: please use alien to install rpm packages on Debian, if you are really sure use --force-debian switch. See README.Debian for more details. There is no README.Debian file in the directory, and although I am not proficient in python, I can tell that there are at least four different directories with *rpm files in them. Has anyone had success with this? If possible, I'd prefer to install the Enterprise version instead of community version in the Ubuntu repository so that I can test it out.

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  • Announcing MySQL Enterprise Backup 3.7.1

    - by Hema Sridharan
    The MySQL Enterprise Backup (MEB) Team is pleased to announce the release of MEB 3.7.1, a maintenance release version that includes bug fixes and enhancements to some of the existing features. The most important feature introduced in this release is Automatic Incremental Backup. The new  argument syntax for the --incremental-base option is introduced which makes it simpler to perform automatic incremental backups. When the options --incremental & --incremental-base=history:last_backup are combined, the mysqlbackup command  uses the metadata in the mysql.backup_history table to determine the LSN to use as the lower limit of the incremental backup. You no longer need to keep track of the actual LSN (as in the option --start-lsn=LSN) or even the location of the previous backup (as in the option --incremental-base=dir:directory_path)This release also incudes various bug fixes related to some options used in MEB. The most important are few of them as listed below,1. The option --force now allows overwriting InnoDB data and log files in  combination with the apply-log and apply-incremental-backup options, and replacing the image file in combination with the backup-to-image and backup-dir-to-image options. 2. Resolved a bug that prevented MEB to interface with third-party storage managers to execute backup and restore jobs in combination with the SBT interface and associated --sbt* options for mysqlbackup. 3. When MEB is run with the copy-back option,  it now displays warnings as existing files are overwritten.For more information about other bug fixes, please refer to the change-log in http://dev.mysql.com/doc/mysql-enterprise-backup/3.7/en/meb-news.html The complete MEB documentation is located at http://dev.mysql.com/doc/mysql-enterprise-backup/3.7/en/index.html. You will find the binaries for the new release in My Oracle Support,  https://support.oracle.comChoose the "Patches & Updates" tab, and then use the "Product or Family (Advanced Search)" feature. If you haven't looked at MEB 3.7.1 recently, please do so now and let us know how MEB works for you. Send your feedback to [email protected].

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  • Convert ddply {plyr} to Oracle R Enterprise, or use with Embedded R Execution

    - by Mark Hornick
    The plyr package contains a set of tools for partitioning a problem into smaller sub-problems that can be more easily processed. One function within {plyr} is ddply, which allows you to specify subsets of a data.frame and then apply a function to each subset. The result is gathered into a single data.frame. Such a capability is very convenient. The function ddply also has a parallel option that if TRUE, will apply the function in parallel, using the backend provided by foreach. This type of functionality is available through Oracle R Enterprise using the ore.groupApply function. In this blog post, we show a few examples from Sean Anderson's "A quick introduction to plyr" to illustrate the correpsonding functionality using ore.groupApply. To get started, we'll create a demo data set and load the plyr package. set.seed(1) d <- data.frame(year = rep(2000:2014, each = 3),         count = round(runif(45, 0, 20))) dim(d) library(plyr) This first example takes the data frame, partitions it by year, and calculates the coefficient of variation of the count, returning a data frame. # Example 1 res <- ddply(d, "year", function(x) {   mean.count <- mean(x$count)   sd.count <- sd(x$count)   cv <- sd.count/mean.count   data.frame(cv.count = cv)   }) To illustrate the equivalent functionality in Oracle R Enterprise, using embedded R execution, we use the ore.groupApply function on the same data, but pushed to the database, creating an ore.frame. The function ore.push creates a temporary table in the database, returning a proxy object, the ore.frame. D <- ore.push(d) res <- ore.groupApply (D, D$year, function(x) {   mean.count <- mean(x$count)   sd.count <- sd(x$count)   cv <- sd.count/mean.count   data.frame(year=x$year[1], cv.count = cv)   }, FUN.VALUE=data.frame(year=1, cv.count=1)) You'll notice the similarities in the first three arguments. With ore.groupApply, we augment the function to return the specific data.frame we want. We also specify the argument FUN.VALUE, which describes the resulting data.frame. From our previous blog posts, you may recall that by default, ore.groupApply returns an ore.list containing the results of each function invocation. To get a data.frame, we specify the structure of the result. The results in both cases are the same, however the ore.groupApply result is an ore.frame. In this case the data stays in the database until it's actually required. This can result in significant memory and time savings whe data is large. R> class(res) [1] "ore.frame" attr(,"package") [1] "OREbase" R> head(res)    year cv.count 1 2000 0.3984848 2 2001 0.6062178 3 2002 0.2309401 4 2003 0.5773503 5 2004 0.3069680 6 2005 0.3431743 To make the ore.groupApply execute in parallel, you can specify the argument parallel with either TRUE, to use default database parallelism, or to a specific number, which serves as a hint to the database as to how many parallel R engines should be used. The next ddply example uses the summarise function, which creates a new data.frame. In ore.groupApply, the year column is passed in with the data. Since no automatic creation of columns takes place, we explicitly set the year column in the data.frame result to the value of the first row, since all rows received by the function have the same year. # Example 2 ddply(d, "year", summarise, mean.count = mean(count)) res <- ore.groupApply (D, D$year, function(x) {   mean.count <- mean(x$count)   data.frame(year=x$year[1], mean.count = mean.count)   }, FUN.VALUE=data.frame(year=1, mean.count=1)) R> head(res)    year mean.count 1 2000 7.666667 2 2001 13.333333 3 2002 15.000000 4 2003 3.000000 5 2004 12.333333 6 2005 14.666667 Example 3 uses the transform function with ddply, which modifies the existing data.frame. With ore.groupApply, we again construct the data.frame explicilty, which is returned as an ore.frame. # Example 3 ddply(d, "year", transform, total.count = sum(count)) res <- ore.groupApply (D, D$year, function(x) {   total.count <- sum(x$count)   data.frame(year=x$year[1], count=x$count, total.count = total.count)   }, FUN.VALUE=data.frame(year=1, count=1, total.count=1)) > head(res)    year count total.count 1 2000 5 23 2 2000 7 23 3 2000 11 23 4 2001 18 40 5 2001 4 40 6 2001 18 40 In Example 4, the mutate function with ddply enables you to define new columns that build on columns just defined. Since the construction of the data.frame using ore.groupApply is explicit, you always have complete control over when and how to use columns. # Example 4 ddply(d, "year", mutate, mu = mean(count), sigma = sd(count),       cv = sigma/mu) res <- ore.groupApply (D, D$year, function(x) {   mu <- mean(x$count)   sigma <- sd(x$count)   cv <- sigma/mu   data.frame(year=x$year[1], count=x$count, mu=mu, sigma=sigma, cv=cv)   }, FUN.VALUE=data.frame(year=1, count=1, mu=1,sigma=1,cv=1)) R> head(res)    year count mu sigma cv 1 2000 5 7.666667 3.055050 0.3984848 2 2000 7 7.666667 3.055050 0.3984848 3 2000 11 7.666667 3.055050 0.3984848 4 2001 18 13.333333 8.082904 0.6062178 5 2001 4 13.333333 8.082904 0.6062178 6 2001 18 13.333333 8.082904 0.6062178 In Example 5, ddply is used to partition data on multiple columns before constructing the result. Realizing this with ore.groupApply involves creating an index column out of the concatenation of the columns used for partitioning. This example also allows us to illustrate using the ORE transparency layer to subset the data. # Example 5 baseball.dat <- subset(baseball, year > 2000) # data from the plyr package x <- ddply(baseball.dat, c("year", "team"), summarize,            homeruns = sum(hr)) We first push the data set to the database to get an ore.frame. We then add the composite column and perform the subset, using the transparency layer. Since the results from database execution are unordered, we will explicitly sort these results and view the first 6 rows. BB.DAT <- ore.push(baseball) BB.DAT$index <- with(BB.DAT, paste(year, team, sep="+")) BB.DAT2 <- subset(BB.DAT, year > 2000) X <- ore.groupApply (BB.DAT2, BB.DAT2$index, function(x) {   data.frame(year=x$year[1], team=x$team[1], homeruns=sum(x$hr))   }, FUN.VALUE=data.frame(year=1, team="A", homeruns=1), parallel=FALSE) res <- ore.sort(X, by=c("year","team")) R> head(res)    year team homeruns 1 2001 ANA 4 2 2001 ARI 155 3 2001 ATL 63 4 2001 BAL 58 5 2001 BOS 77 6 2001 CHA 63 Our next example is derived from the ggplot function documentation. This illustrates the use of ddply within using the ggplot2 package. We first create a data.frame with demo data and use ddply to create some statistics for each group (gp). We then use ggplot to produce the graph. We can take this same code, push the data.frame df to the database and invoke this on the database server. The graph will be returned to the client window, as depicted below. # Example 6 with ggplot2 library(ggplot2) df <- data.frame(gp = factor(rep(letters[1:3], each = 10)),                  y = rnorm(30)) # Compute sample mean and standard deviation in each group library(plyr) ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y)) # Set up a skeleton ggplot object and add layers: ggplot() +   geom_point(data = df, aes(x = gp, y = y)) +   geom_point(data = ds, aes(x = gp, y = mean),              colour = 'red', size = 3) +   geom_errorbar(data = ds, aes(x = gp, y = mean,                                ymin = mean - sd, ymax = mean + sd),              colour = 'red', width = 0.4) DF <- ore.push(df) ore.tableApply(DF, function(df) {   library(ggplot2)   library(plyr)   ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))   ggplot() +     geom_point(data = df, aes(x = gp, y = y)) +     geom_point(data = ds, aes(x = gp, y = mean),                colour = 'red', size = 3) +     geom_errorbar(data = ds, aes(x = gp, y = mean,                                  ymin = mean - sd, ymax = mean + sd),                   colour = 'red', width = 0.4) }) But let's take this one step further. Suppose we wanted to produce multiple graphs, partitioned on some index column. We replicate the data three times and add some noise to the y values, just to make the graphs a little different. We also create an index column to form our three partitions. Note that we've also specified that this should be executed in parallel, allowing Oracle Database to control and manage the server-side R engines. The result of ore.groupApply is an ore.list that contains the three graphs. Each graph can be viewed by printing the list element. df2 <- rbind(df,df,df) df2$y <- df2$y + rnorm(nrow(df2)) df2$index <- c(rep(1,300), rep(2,300), rep(3,300)) DF2 <- ore.push(df2) res <- ore.groupApply(DF2, DF2$index, function(df) {   df <- df[,1:2]   library(ggplot2)   library(plyr)   ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))   ggplot() +     geom_point(data = df, aes(x = gp, y = y)) +     geom_point(data = ds, aes(x = gp, y = mean),                colour = 'red', size = 3) +     geom_errorbar(data = ds, aes(x = gp, y = mean,                                  ymin = mean - sd, ymax = mean + sd),                   colour = 'red', width = 0.4)   }, parallel=TRUE) res[[1]] res[[2]] res[[3]] To recap, we've illustrated how various uses of ddply from the plyr package can be realized in ore.groupApply, which affords the user explicit control over the contents of the data.frame result in a straightforward manner. We've also highlighted how ddply can be used within an ore.groupApply call.

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