Search Results

Search found 2261 results on 91 pages for 'numerical computing'.

Page 91/91 | < Previous Page | 87 88 89 90 91 

  • CodePlex Daily Summary for Thursday, November 01, 2012

    CodePlex Daily Summary for Thursday, November 01, 2012Popular ReleasesAccess 2010 Application Platform - Build Your Own Database: Application Platform - 0.0.1: Initial Release This is the first version of the database. At the moment is all contained in one file to make development easier, but the obvious idea would be to split it into Front and Back End for a production version of the tool. The features it contains at the moment are the "Core" features.Python Tools for Visual Studio: Python Tools for Visual Studio 1.5: We’re pleased to announce the release of Python Tools for Visual Studio 1.5 RTM. Python Tools for Visual Studio (PTVS) is an open-source plug-in for Visual Studio which supports programming with the Python language. PTVS supports a broad range of features including CPython/IronPython, Edit/Intellisense/Debug/Profile, Cloud, HPC, IPython, etc. support. For a quick overview of the general IDE experience, please watch this video There are a number of exciting improvement in this release comp...Devpad: 4.25: Whats new for Devpad 4.25: New Theme support New Export Wordpress Minor Bug Fix's, improvements and speed upsAssaultCube Reloaded: 2.5.5: Linux has Ubuntu 11.10 32-bit precompiled binaries and Ubuntu 10.10 64-bit precompiled binaries, but you can compile your own as it also contains the source. If you are using Mac or other operating systems, please wait while we try to package for those OSes. Try to compile it. If it fails, download a virtual machine. The server pack is ready for both Windows and Linux, but you might need to compile your own for Linux (source included) Changelog: Fixed potential bot bugs: Map change, OpenAL...Edi: Edi 1.0 with DarkExpression: Added DarkExpression theme (dialogs and message boxes are not completely themed, yet)MCEBuddy 2.x: MCEBuddy 2.3.6: Changelog for 2.3.6 (32bit and 64bit) 1. Fixed a bug in multichannel audio conversion failure. AAC does not support 6 channel audio, MCEBuddy now checks for it and force the output to 2 channel if AAC codec is specified 2. Fixed a bug in Original Broadcast Date and Time. Original Broadcast Date and Time is reported in UTC timezone in WTV metadata. TVDB and MovieDB dates are reported in network timezone. It is assumed the video is recorded and converted on the same machine, i.e. local timezone...MVVM Light Toolkit: MVVM Light Toolkit V4.1 for Visual Studio 2012: This version only supports Visual Studio 2012 (and all Express editions too). If you use Visual Studio 2010, please stay tuned, we will publish an update in a few days with support for VS10. V4.1 supports: Windows Phone 8 Windows 8 (Windows RT) Silverlight 5 Silverlight 4 WPF 4.5 WPF 4 WPF 3.5 And the following development environments: Visual Studio 2012 (Pro, Premium, Ultimate) Visual Studio 2012 Express for Windows 8 Visual Studio 2012 Express for Windows Phone 8 Visual...Microsoft Ajax Minifier: Microsoft Ajax Minifier 4.73: Fix issue in Discussion #401101 (unreferenced var in a for-in statement was getting removed). add the grouping operator to the parsed output so that unminified parsed code is closer to the original. Will still strip unneeded parens later, if minifying. more cleaning of references as they are minified out of the code.Liberty: v3.4.0.1 Release 28th October 2012: Change Log -Fixed -H4 Fixed the save verification screen showing incorrect mission and difficulty information for some saves -H4 Hopefully fixed the issue where progress did not save between missions and saves would not revert correctly -H3 Fixed crashes that occurred when trying to load player information -Proper exception dialogs will now show in place of crashesPlayer Framework by Microsoft: Player Framework for Windows 8 (Preview 7): This release is compatible with the version of the Smooth Streaming SDK released today (10/26). Release 1 of the player framework is expected to be available next week. IMPROVEMENTS & FIXESIMPORTANT: List of breaking changes from preview 6 Support for the latest smooth streaming SDK. Xaml only: Support for moving any of the UI elements outside the MediaPlayer (e.g. into the appbar). Note: Equivelent changes to the JS version due in coming week. Support for localizing all text used in t...Send multiple SMS via Way2SMS C#: SMS 1.1: Added support for 160by2Quick Launch: Quick Launch 1.0: A Lightweight and Fast Way to Manage and Launch Thousands of Tools and ApplicationsPress Win+Q and start to search and run. http://www.codeplex.com/Download?ProjectName=quicklaunch&DownloadId=523536Orchard Project: Orchard 1.6: Please read our release notes for Orchard 1.6: http://docs.orchardproject.net/Documentation/Orchard-1-6-Release-Notes Please do not post questions as reviews. Questions should be posted in the Discussions tab, where they will usually get promptly responded to. If you post a question as a review, you will pollute the rating, and you won't get an answer.Media Companion: Media Companion 3.507b: Once again, it has been some time since our release, and there have been a number changes since then. It is hoped that these changes will address some of the issues users have been experiencing, and of course, work continues! New Features: Added support for adding Home Movies. Option to sort Movies by votes. Added 'selectedBrowser' preference used when opening links in an external browser. Added option to fallback to getting runtime from the movie file if not available on IMDB. Added new Big...MSBuild Extension Pack: October 2012: Release Blog Post The MSBuild Extension Pack October 2012 release provides a collection of over 475 MSBuild tasks. A high level summary of what the tasks currently cover includes the following: System Items: Active Directory, Certificates, COM+, Console, Date and Time, Drives, Environment Variables, Event Logs, Files and Folders, FTP, GAC, Network, Performance Counters, Registry, Services, Sound Code: Assemblies, AsyncExec, CAB Files, Code Signing, DynamicExecute, File Detokenisation, GUI...NAudio: NAudio 1.6: Release notes at http://mark-dot-net.blogspot.co.uk/2012/10/naudio-16-release-notes-10th.htmlPowerShell Community Extensions: 2.1 Production: PowerShell Community Extensions 2.1 Release NotesOct 25, 2012 This version of PSCX supports both Windows PowerShell 2.0 and 3.0. See the ReleaseNotes.txt download above for more information.Umbraco CMS: Umbraco 4.9.1: Umbraco 4.9.1 is a bugfix release to fix major issues in 4.9.0 BugfixesThe full list of fixes can be found in the issue tracker's filtered results. A summary: Split buttons work again, you can now also scroll easier when the list is too long for the screen Media and Content pickers have information of the full path of the picked item Fixed: Publish status may not be accurate on nodes with large doctypes Fixed: 2 media folders and recycle bins after upgrade to 4.9 The template/code ...AcDown????? - AcDown Downloader Framework: AcDown????? v4.2.2: ??●AcDown??????????、??、??、???????。????,????,?????????????????????????。???????????Acfun、????(Bilibili)、??、??、YouTube、??、???、??????、SF????、????????????。 ●??????AcPlay?????,??????、????????????????。 ● AcDown??????????????????,????????????????????????????。 ● AcDown???????C#??,????.NET Framework 2.0??。?????"Acfun?????"。 ????32??64? Windows XP/Vista/7/8 ???? 32??64? ???Linux ????(1)????????Windows XP???,????????.NET Framework 2.0???(x86),?????"?????????"??? (2)???????????Linux???,????????Mono?? ??2...Rawr: Rawr 5.0.2: This is the Downloadable WPF version of Rawr!For web-based version see http://elitistjerks.com/rawr.php You can find the version notes at: http://rawr.codeplex.com/wikipage?title=VersionNotes Rawr Addon (NOT UPDATED YET FOR MOP)We now have a Rawr Official Addon for in-game exporting and importing of character data hosted on Curse. The Addon does not perform calculations like Rawr, it simply shows your exported Rawr data in wow tooltips and lets you export your character to Rawr (including ba...New ProjectsAsbesto: Proyecto grupo: "2ravas" para Laboratorio de Computación IV de la carrera TSP de la UTN-FRGP Realizado en C# y ASP.NET en Visual Studio 2012 y SQL Server 2012C++ Diamond printer on console without if statement: prints just a diamond with stars(*). only one important and funny feature is that it's not using 'if' statement. C++ used.CloudTest: Test cloud computing projectEnumeration of objects Class Library C#: At core level in Java I like extension of traditional enum type permiting use as the elements instances of a class. The project implements the same idea by C# with some more advanced features like a set type with boolean operators extending idea of FlagsAttributeEquation Inversion: Visual Studion 2008 Add-in for equation inversions.ESENT Serialization Class Library: ESENT Serialization class library is built above Managed ESENT. It allows you to store your objects in the underlying extensible storage engine database.ForceHttps: Very simple httpModule to ensure that all http requests are https. 1. Drop the dll into your website's bin directory 2. Update httpModules section of your web.config to reference the dll 3. Make sure your Web Server can handle SSL requests for the URL ALL http requests will be redirected as https.forrajeriaPAV2: tp pav2 asd as asd as fasfjaijiasjifoa as asf asf as afs fas asf afs fsaGoogle Analytics for WinRT: A Windows Store (WinRT) class library for tracking Google Analytics page views, events, and custom variables for your Metro style desktop and tablet apps.huanglitest10312: mvc projectiMan: iMan will be your own port manager, which help to provide the information about all the ports open in your PC It's completely developed in .NET C#InjectionCop: Facilitates secure coding through static code analysis and contract annotations in the Common Language Infrastructure.Master of Olympus: Remake of Master of Olympus : Zeus, a game developed by Impressions Games in 2000.MediaScribe: MediaScribe is a note app for your media.MouseNestDotNet: A small personal website application.Project Estimator ???????? ?? ?????????????? ?? ???????: Project Estimator ? ???????? ??????????? ? ??????????? ?? ????? ? ???????? ????.Projekt grupowy 1: Project created only for school purpose.SecondHandApp: Warenwirtschaftsprogramm für denn SecondHand LädenSimple .NET XML Serialization: .NET's XML serialization using Linq XObject classes EG: XElement in an IXmlSerializable base classStrip Converter: A Very Handy Converter for 2D Games Developers Developer Website: http://www.bluebulk.infoSwitch JS Control (Client Side): Switch JS control is a very light client side library to create switch(es) on web applications or mobile applications.VisaSys: Visa System????????: TODO::????

    Read the article

  • E-Business Suite Technology Sessions at OpenWorld 2012

    - by Max Arderius
    Oracle OpenWorld 2012 is almost here! We're looking forward to updating you on our products, strategy, and roadmaps. This year, the E-Business Suite Applications Technology Group (ATG) will participate in 25 speaker sessions, two Meet the Experts round-table discussions, five demoground booths and seven Special Interest Group meetings as guest speakers. We hope to see you at our sessions.  Please join us to hear the latest news and connect with senior ATG development staff. Here's a downloadable listing of all Applications Technology Group-related sessions with times and locations: FOCUS ON Oracle E-Business Suite - Applications Tools and Technology (PDF) General Sessions GEN8474 - Oracle E-Business Suite - Strategy, Update, and RoadmapCliff Godwin, SVP, Oracle Monday, Oct 1, 12:15 PM - 1:15 PM - Moscone West 2002/2004 In this session, hear Oracle E-Business Suite General Manager Cliff Godwin deliver an update on the Oracle E-Business Suite product line. This session covers the value delivered by the current release of Oracle E-Business Suite, the momentum, and how Oracle E-Business Suite applications integrate into Oracle’s overall applications strategy. You’ll come away with an understanding of the value Oracle E-Business Suite applications deliver now and will deliver in the future. GEN9173 - Optimize and Extend Oracle Applications - The Path to Oracle Fusion ApplicationsNadia Bendjedou, Oracle; Corre Curtice, Bhavish Madurai (CSC) Tuesday, Oct 2, 10:15 AM - 11:15 AM - Moscone West 3002/3004 One of the main objectives of this session is to help organizations build their IT roadmap for the next five years and be aligned with the Oracle Applications strategy in general and the Oracle Fusion Applications strategy in particular. Come hear about some of the common sense, practical steps you can take to optimize the performance of your Oracle Applications today and prepare your path to Oracle Fusion Applications for when your organization is ready to embrace them. Each step you take in adopting Oracle Fusion technology gets you partway to Oracle Fusion Applications. Conference Sessions CON9024 - Oracle E-Business Suite Technology: Latest Features and Roadmap Lisa Parekh, Oracle Monday, Oct 1, 10:45 AM - 11:45 AM - Moscone West 2016 This Oracle development session provides a comprehensive overview of Oracle’s product strategy for Oracle E-Business Suite technology, the capabilities and associated business benefits of recent releases, and a review of capabilities on the product roadmap. This is the cornerstone session for the Oracle E-Business Suite technology stack. Come hear about the latest new usability enhancements of the user interface; systems administration and configuration management tools; security-related updates; and tools and options for extending, customizing, and integrating Oracle E-Business Suite with other applications. CON9021 - Oracle E-Business Suite Future Directions: Deployment and System AdministrationMax Arderius, Oracle Monday, Oct 1, 3:15 PM - 4:15 PM - Moscone West 2016  What’s coming in the next major version of Oracle E-Business Suite 12? This Oracle Development session covers the latest technology stack, including the use of Oracle WebLogic Server (Oracle Fusion Middleware 11g) and Oracle Database 11g Release 2 (11.2). Topics include an architectural overview of the latest updates, installation and upgrade options, new configuration options, and new tools for hot cloning and automated “lights-out” cloning. Come learn how online patching (based on the Oracle Database 11g Release 2 Edition-Based Redefinition feature) will reduce your database patching downtimes to however long it takes to bounce your database server. CON9017 - Desktop Integration in Oracle E-Business Suite 12.1 Padmaprabodh Ambale, Gustavo Jimenez, Oracle Monday, Oct 1, 4:45 PM - 5:45 PM - Moscone West 2016 This presentation covers the latest functional enhancements in Oracle Web Applications Desktop Integrator and Oracle Report Manager, enhanced Microsoft Office support, and greater support for building custom desktop integration solutions. The session also presents tips and tricks for upgrading from Oracle Applications Desktop Integrator to Oracle Web Applications Desktop Integrator and Oracle Report Manager. CON9023 - Oracle E-Business Suite Technology Certification Primer and Roadmap Steven Chan, Oracle Tuesday, Oct 2, 10:15 AM - 11:15 AM - Moscone West 2016  Is your Oracle E-Business Suite technology stack up to date? Are you taking advantage of all the latest options and capabilities? This Oracle development session summarizes the latest certifications and roadmap for the Oracle E-Business Suite technology stack, including elements such as database releases and options, Java, Oracle Forms, Oracle Containers for J2EE, desktop operating systems, browsers, JRE releases, development and Web authoring tools, user authentication and management, business intelligence, Oracle Application Management Packs, security options, clouds, Oracle VM, and virtualization. The session also covers the most commonly asked questions about tech stack component support dates and upgrade implications. CON9028 - Minimizing Oracle E-Business Suite Maintenance DowntimesSantiago Bastidas, Elke Phelps, Oracle Tuesday, Oct 2, 11:45 AM - 12:45 PM - Moscone West 2016 This Oracle development session features a survey of the best techniques sysadmins can use to minimize patching downtimes. It starts with an architectural-level review of Oracle E-Business Suite fundamentals and then moves to a practical view of the various tools and approaches for downtimes. Topics include patching shortcuts, merging patches, distributing worker processes across multiple servers, running ADPatch in noninteractive mode, staged APPL_TOPs, shared file systems, deferring systemwide database tasks, avoiding resource bottlenecks, and more. An added bonus: hear about the upcoming Oracle E-Business Suite 12 online patching capabilities based on the groundbreaking Oracle Database 11g Release 2 Edition-Based Redefinition feature. CON9116 - Extending the Use of Oracle E-Business Suite with the Oracle Endeca PlatformOsama Elkady, Muhannad Obeidat, Oracle Tuesday, Oct 2, 11:45 AM - 12:45 PM - Moscone West 2018 The Oracle Endeca platform includes a leading unstructured data correlation and analytics engine, together with a best-in class catalog search and guided navigation solution, to improve the productivity of all types of users in your enterprise. This development session focuses on the details behind the Oracle Endeca platform’s integration into Oracle E-Business Suite. It demonstrates how easily you can extend the use of the Oracle Endeca platform into other areas of Oracle E-Business Suite and how you can bring in your own data and build new Oracle Endeca applications for Oracle E-Business Suite. CON9005 - Oracle E-Business Suite Integration Best PracticesVeshaal Singh, Oracle, Jeffrey Hand, Zebra Technologies Tuesday, Oct 2, 1:15 PM - 2:15 PM - Moscone West 2018 Oracle is investing across applications and technologies to make the application integration experience easier for customers. Today Oracle has certified Oracle E-Business Suite on Oracle Fusion Middleware 11g and provides a comprehensive set of integration technologies. Learn about Oracle’s integration offering across data- and process-centric integrations. These technologies can be used to address various application integration challenges and styles. In this session, you will get an understanding of how, when, and where you can leverage Oracle’s integration technologies to connect end-to-end business processes across your enterprise, including your Oracle Applications portfolio.  CON9026 - Latest Oracle E-Business Suite 12.1 User Interface and Usability EnhancementsPadmaprabodh Ambale, Oracle Tuesday, Oct 2, 1:15 PM - 2:15 PM - Moscone West 2016 This Oracle development session details the latest UI enhancements to Oracle Application Framework in Oracle E-Business Suite 12.1. Developers will get a detailed look at new features to enhance usability, offer more capabilities for personalization and extensions, and support the development and use of dashboards and Web services. Topics include new rich UI capabilities such as new home page features, Navigator and Favorites pull-down menus, REST interface, embedded widgets for analytics content, Oracle Application Development Framework (Oracle ADF) task flows, third-party widgets, a look-ahead list of values, inline attachments, pop-ups, personalization and extensibility enhancements, business layer extensions, Oracle ADF integration, and mobile devices. CON8805 - Planning Your Oracle E-Business Suite Upgrade from 11i to Release 12.1 and BeyondAnne Carlson, Oracle Tuesday, Oct 2, 5:00 PM - 6:00 PM - Moscone West 3002/3004 Attend this session to hear the latest Oracle E-Business Suite 12.1 upgrade planning tips from Oracle’s support, consulting, development, and IT organizations. You’ll get specific cross-product advice on how to understand the factors that affect your project’s duration, decide on your project’s scope, develop a robust testing strategy, leverage Oracle Support resources, and more. In a nutshell, this session tells you things you need to know before embarking upon your Release 12.1 upgrade project. CON9053 - Advanced Management of Oracle E-Business Suite with Oracle Enterprise ManagerAngelo Rosado, Oracle Tuesday, Oct 2, 5:00 PM - 6:00 PM - Moscone West 2016 The task of managing and monitoring Oracle E-Business Suite environments can be very challenging. Oracle Enterprise Manager is the only product on the market that is designed to monitor and manage all the different technologies that constitute Oracle E-Business Suite applications, including end user, midtier, configuration, host, and database management—to name just a few. Customers that have implemented Oracle Enterprise Manager have experienced dramatic improvements in system visibility and diagnostic capability as well as administrator productivity. The purpose of this session is to highlight the key features and benefits of Oracle Enterprise Manager and Oracle Application Management Suite for Oracle E-Business Suite. CON8809 - Oracle E-Business Suite 12.1 Upgrade Best Practices: Technical InsightIsam Alyousfi, Udayan Parvate, Oracle Wednesday, Oct 3, 10:15 AM - 11:15 AM - Moscone West 3011 This session is ideal for organizations thinking about upgrading to Oracle E-Business Suite 12.1. It covers the fundamentals of upgrading to Release 12.1, including the technology stack components and supported upgrade paths. Hear from Oracle Development about the set of best practices for patching in general and executing the Release 12.1 technical upgrade, with special considerations for minimizing your downtime. Also get to know about relatively recent upgrade resources. CON9032 - Upgrading Your Customizations of Oracle E-Business Suite 12.1Sara Woodhull, Oracle Wednesday, Oct 3, 10:15 AM - 11:15 AM - Moscone West 2016 Have you personalized Oracle Forms or Oracle Application Framework screens in Oracle E-Business Suite? Have you used mod_plsql in Release 11i? Have you extended or customized your Release 11i environment with other tools? The technical options for upgrading these customizations as part of your Oracle E-Business Suite Release 12.1 upgrade can be bewildering. Come to this Oracle development session to learn about selecting the best upgrade approach for your existing customizations. The session will help you understand customization scenarios and use cases, tools, and technologies to ensure that your Oracle E-Business Suite Release 12.1 environment fits your users’ needs closely and that any future customizations will be easy to upgrade. CON9259 - Oracle E-Business Suite Internationalization and Multilingual FeaturesMaher Al-Nubani, Oracle Wednesday, Oct 3, 10:15 AM - 11:15 AM - Moscone West 2018 Oracle E-Business Suite supports more countries, languages, and regions than ever. Come to this Oracle development session to get an overview of internationalization features and capabilities and see new Release 12 features such as calendar support for Hijra and Thai, new group separators, lightweight multilingual support (MLS) setup, new character sets such as AL32UTF, newly supported languages, Mac certifications, Oracle iSetup support for moving MLS setups, new file export options for Unicode, new MLS number spelling options, and more. CON7188 - Mobile Apps for Oracle E-Business Suite with Oracle ADF Mobile and Oracle SOA SuiteSrikant Subramaniam, Joe Huang, Veshaal Singh, Oracle Wednesday, Oct 3, 10:15 AM - 11:15 AM - Moscone West 3001 Follow your mobile customers, employees, and partners with Oracle Fusion Middleware. See how native iPhone and iPad applications can easily be built for Oracle E-Business Suite with the new Oracle ADF Mobile and Oracle SOA Suite. Using Oracle ADF Mobile, developers can quickly develop native applications for Apple iOS and other mobile platforms. The Oracle SOA Suite/Oracle ADF Mobile combination can execute business transactions on Oracle E-Business Suite. This session includes a demo in which a mobile user approves a business transaction in Oracle E-Business Suite and a demo of the tools used to build a native on-device solution. These concepts for mobile applications also apply to other Oracle applications.CON9029 - Oracle E-Business Suite Directions: Slashing Downtimes with Online PatchingKevin Hudson, Oracle Wednesday, Oct 3, 11:45 AM - 12:45 PM - Moscone West 2016 Oracle E-Business Suite will soon include online patching (based on the Oracle Database 11g Release 2 Edition-Based Redefinition feature), which will reduce your database patching downtimes to however long it takes to bounce your database server. This Oracle development session details how online patching works, with special attention to what’s happening at a database object level when database patches are applied to an Oracle E-Business Suite environment that’s still running. Come learn about the operational and system management implications for minimizing maintenance downtimes when applying database patches with this new technology and the related impact on customizations you might have built on top of Oracle E-Business Suite. CON8806 - Upgrading to Oracle E-Business Suite 12.1: Technical and Functional PanelAndrew Katz, Komori America Corporation; Sandra Vucinic, VLAD Group, Inc. ;Srini Chavali, Cummins Inc.; Amrita Mehrok, Nadia Bendjedou, Anne Carlson Oracle Wednesday, Oct 3, 1:15 PM - 2:15 PM - Moscone West 2018 In this panel discussion, Oracle experts, customers, and partners share their experiences in upgrading to the latest release of Oracle E-Business Suite, Release 12.1. The panelists cover aspects of a typical Release 12 upgrade, technical (upgrading the technical infrastructure) as well as functional (upgrading to the new financial infrastructure). Hear directly from the experts who either develop the product or support, implement, or upgrade it, and find out how to apply their lessons learned to your organization. CON9027 - Personalize and Extend Oracle E-Business Suite Applications with Rich MashupsGustavo Jimenez, Padmaprabodh Ambale, Oracle Wednesday, Oct 3, 1:15 PM - 2:15 PM - Moscone West 2016 This session covers the use of several Oracle Fusion Middleware technologies to personalize and extend your existing Oracle E-Business Suite applications. The Oracle Fusion Middleware technologies covered include Oracle Application Development Framework (Oracle ADF), Oracle WebCenter, Oracle Endeca applications, and Oracle Business Intelligence Enterprise Edition with Oracle E-Business Suite Oracle Application Framework applications. CON9036 - Advanced Oracle E-Business Suite Architectures: Maximum Availability, Security, and MoreElke Phelps, Oracle Wednesday, Oct 3, 3:30 PM - 4:30 PM - Moscone West 2016 This session includes architecture diagrams and configuration instructions for building a maximum availability architecture (MAA) that will help you design a disaster recovery solution that fits the needs of your business. Database and application high-availability features it describes include Oracle Data Guard, Oracle Real Application Clusters (Oracle RAC), Oracle Active Data Guard, load-balancing Web and forms services, parallel concurrent processing, and the use of Oracle Exalogic and Oracle Exadata to provide a highly available environment. The session also covers the latest updates to systems management tools, AutoConfig, cloud computing, virtualization, and Oracle WebLogic Server and provides sneak previews of upcoming functionality. CON9047 - Efficiently Scaling Oracle E-Business Suite on Oracle Exadata and Oracle ExalogicIsam Alyousfi, Nishit Rao, Oracle Wednesday, Oct 3, 5:00 PM - 6:00 PM - Moscone West 2016 Oracle Exadata and Oracle Exalogic are designed from the ground up with optimizations in software and hardware to deliver superfast performance for mission-critical applications such as Oracle E-Business Suite. Oracle E-Business Suite applications run three to eight times as fast on the Oracle Exadata/Oracle Exalogic platform in standard benchmark tests. Besides performance, customers benefit from simplified support, enhanced manageability, and the ability to consolidate multiple Oracle E-Business Suite instances. Attend this session to understand best practices for Oracle E-Business Suite deployment on Oracle Exalogic and Oracle Exadata through customer case studies. Learn how adopting the Exa* platform increases efficiency, simplifies scaling, and boosts performance for peak loads. CON8716 - Web Services and SOA Integration Options for Oracle E-Business SuiteRekha Ayothi, Veshaal Singh, Oracle Thursday, Oct 4, 11:15 AM - 12:15 PM - Moscone West 2016 This Oracle development session provides a deep dive into a subset of the Web services and SOA-related integration options available to Oracle E-Business Suite systems integrators. It offers a technical look at Oracle E-Business Suite Integrated SOA Gateway, Oracle SOA Suite, Oracle Application Adapters for Data Integration for Oracle E-Business Suite, and other Web services options for integrating Oracle E-Business Suite with other applications. Systems integrators and developers will get an overview of the latest integration capabilities and technologies available out of the box with Oracle E-Business Suite and possibly a sneak preview of upcoming functionality and features. CON9030 - Recommendations for Oracle E-Business Suite Performance TuningIsam Alyousfi, Samer Barakat, Oracle Thursday, Oct 4, 11:15 AM - 12:15 PM - Moscone West 2018 Need to squeeze more performance out of your existing servers? This packed Oracle development session summarizes practical tips and lessons learned from performance-tuning and benchmarking the world’s largest Oracle E-Business Suite environments. Apps sysadmins will learn concrete tips and techniques for identifying and resolving performance bottlenecks on all layers, with special attention to application- and database-tier servers. Learn about tuning Oracle Forms, Oracle Concurrent Manager, Apache, and Oracle Discoverer. Track down memory leaks and other issues at the Java and JVM layers. The session also covers Oracle E-Business Suite product-level tuning, including Oracle Workflow, Oracle Order Management, Oracle Payroll, and other modules. CON3429 - Using Oracle ADF with Oracle E-Business Suite: The Full Integration ViewSiva Puthurkattil, Lake County; Juan Camilo Ruiz, Sara Woodhull, Oracle Thursday, Oct 4, 11:15 AM - 12:15 PM - Moscone West 3003 Oracle E-Business Suite delivers functionality for handling the core business of your organization. However, user requirements and new technologies are driving an emerging need to implement new types of user interfaces for these applications. This session provides an overview of how to use Oracle Application Development Framework (Oracle ADF) to deliver cutting-edge Web 2.0 and mobile rich user interfaces that front existing Oracle E-Business Suite processes, and it also explores all the existing types of integration between the two worlds. CON9020 - Integrating Oracle E-Business Suite with Oracle Identity Management SolutionsSunil Ghosh, Elke Phelps, Oracle Thursday, Oct 4, 12:45 PM - 1:45 PM - Moscone West 2016 Need to integrate Oracle E-Business Suite with Microsoft Windows Kerberos, Active Directory, CA Netegrity SiteMinder, or other third-party authentication systems? Want to understand your options when Oracle Premier Support for Oracle Single Sign-On ends in December 2011? This Oracle Development session covers the latest certified integrations with Oracle Access Manager 11g and Oracle Internet Directory 11g, which can be used individually or as bridges for integrating with third-party authentication solutions. The session presents an architectural overview of how Oracle Access Manager, its WebGate and AccessGate components, and Oracle Internet Directory work together, with implications for Oracle Discoverer, Oracle Portal, and other Oracle Fusion identity management products. CON9019 - Troubleshooting, Diagnosing, and Optimizing Oracle E-Business Suite TechnologyGustavo Jimenez, Oracle Thursday, Oct 4, 2:15 PM - 3:15 PM - Moscone West 2016 This session covers how you can proactively diagnose Oracle E-Business Suite applications, including extensions built with Oracle Fusion Middleware technologies such as Oracle Application Development Framework (Oracle ADF) and Oracle WebCenter to catch potential issues in the middle tier before they become more serious. Topics include debugging, logging infrastructure, warning signs, performance tuning, information required when logging service requests, general JVM optimization, and an overall picture of all the moving parts that make it possible for Oracle E-Business Suite to isolate and fix problems. Also learn how Oracle Diagnostics Framework will help prevent downtime caused by failures. CON9031 - The Top 10 Things You Can Do to Secure Your Oracle E-Business Suite InstanceEric Bing, Erik Graversen, Oracle Thursday, Oct 4, 2:15 PM - 3:15 PM - Moscone West 2018 Learn the top 10 things you can do to secure your applications and your sensitive data. This Oracle development session for system administrators and security professionals explores some of the most important and overlooked things you can do to secure your Oracle E-Business Suite instance. It also covers data masking and other mechanisms for protecting sensitive data. Special Interest Groups (SIG) Some of our most senior staff have been invited to participate on the following SIG meetings as guest speakers: SIG10525 - OAUG - Archive & Purge SIGBrian Bent - Pre-Sales Engineer, TierData, Inc. Sunday, Sep 30, 10:30 AM - 12:00 PM - Moscone West 3011 The Archive and Purge SIG is an organization in which users can share their experiences and solicit functional and technical advice on archiving and purging data in Oracle E-Business Suite. This session provides an opportunity for users to network and share best practices, tips, and tricks. Guest: Oracle E-Business Suite Database Performance, Archive & Purging - Q&A SessionIsam Alyousfi, Senior Director, Applications Performance, Oracle SIG10547 - OAUG - Oracle E-Business (EBS) Applications Technology SIGSrini Chavali - IT Director, Cummins Inc Sunday, Sep 30, 10:30 AM - 12:00 PM - Moscone West 3018 The general purpose of the EBS Applications Technology SIG is to inform and educate its members about current and future components of the tech stack as they relate to Oracle E-Business Suite. Attend this meeting for networking and education and to share best practices. Guest: Oracle E-Business Suite Technology Certification Roadmap - Presentation and Q&ASteven Chan, Sr. Director, Applications Technology Group, Oracle SIG10559 - OAUG - User Management SIGSusan Behn - VP of Oracle Delivery, Infosemantics, Inc. Sunday, Sep 30, 10:30 AM - 12:00 PM - Moscone West 3024 The E-Business Suite User Management SIG focuses on the components of user management that enable Oracle E-Business Suite users to define administrative functions and manage users’ access to functions and data based on roles within an organization—rather than the user’s individual identity—which is referred to as role-based access control (RBAC). This meeting includes an introduction to Oracle User Management that covers the Oracle User Management building blocks and presents an example of creating a security policy.Guest: Security and User Management - Q&A SessionEric Bing, Sr. Director, EBS Security, OracleSara Woodhull, Principal Product Manager, Applications Technology Group, Oracle SIG10515 - OAUG – Upgrade SIGBarbara Matthews - Consultant, On Call DBASandra Vucinic, VLAD Group, Inc. Sunday, Sep 30, 12:00 PM - 2:00 PM - Moscone West 3009 This Upgrade SIG session starts with a business meeting and then features a Q&A panel discussion on Oracle E-Business Suite upgrade topics. The session• Reviews Upgrade SIG goals and objectives• Provides answers, during the Q&A session, to questions related to Oracle E-Business Suite upgrades• Shares “real world” experiences, tips, and techniques for Oracle E-Business Suite upgrades to Release 12.1. Guest: Oracle E-Business Suite Upgrade - Q&A SessionAnne Carlson - Sr. Director, Oracle E-Business Suite Product Strategy, OracleUdayan Parvate - Director, EBS Release Engineering, OracleSuzana Ferrari, Sr. Principal Consultant, OracleIsam Alyousfi, Sr. Director, Applications Performance, Oracle SIG10552 - OAUG - Oracle E-Business Suite SIGDonna Rosentrater - Manager, Global Sourcing & Procurement Systems, TJX Sunday, Sep 30, 12:15 PM - 1:45 PM - Moscone West 3020 The E-Business Suite SIG, affiliated with OAUG, supports Oracle E-Business Suite users through networking, education, and sharing of best practices. This SIG meeting will feature a general discussion of Oracle E-Business Suite product strategies in Release 12 and migration to Oracle Fusion Applications. Guest: Oracle E-Business Suite - Q&A SessionJeanne Lowell, Vice President, EBS Product Strategy, OracleNadia Bendjedou, Sr. Director, Product Strategy, Oracle SIG10556 - OAUG - SysAdmin SIGRandy Giefer - Sr Systems and Security Architect, Solution Beacon, LLC Sunday, Sep 30, 12:15 PM - 1:45 PM - Moscone West 3022 The SysAdmin SIG provides a forum in which OAUG members and participants can share updates, tips, and successful practices relating to system administration in an Oracle applications environment. The SysAdmin SIG strives to enable system administrators to become more effective and efficient in their jobs by providing them with access to people and information that can increase their system administration knowledge and experience. Attend this meeting to network, share best practices, and benefit from educational content. Guest: Oracle E-Business Suite 12.2 Online Patching- Presentation and Q&AKevin Hudson, Sr. Director, Applications Technology Group, Oracle SIG10553 - OAUG - Database SIGMichael Brown - Senior DBA, COLIBRI LTD LC Sunday, Sep 30, 2:00 PM - 3:15 PM - Moscone West 3020 The OAUG Database SIG provides an opportunity for applications database administrators to learn from and share their experiences with supporting the various Oracle applications environments. This session will include a brief business meeting followed by a short presentation. It will end with an open discussion among the attendees about items of interest to those present. Guest: Oracle E-Business Suite Database Performance - Presentation and Q&AIsam Alyousfi, Sr. Director, Applications Performance, Oracle Meet the Experts We're planning two round-table discussions where you can review your questions with senior E-Business Suite ATG staff: MTE9648 - Meet the Experts for Oracle E-Business Suite: Planning Your Upgrade Jeanne Lowell - VP, EBS Product Strategy, Oracle John Abraham - Sr. Principal Product Manager, Oracle Nadia Bendjedou - Sr. Director - Product Strategy, Oracle Anne Carlson - Sr. Director, Applications Technology Group, Oracle Udayan Parvate - Director, EBS Release Engineering, Oracle Isam Alyousfi, Sr. Director, Applications Performance, Oracle Monday, Oct 1, 3:15 PM - 4:15 PM - Moscone West 2001A Don’t miss this Oracle Applications Meet the Experts session with experts who specialize in Oracle E-Business Suite upgrade best practices. This is the place where attendees can have informal and semistructured but open one-on-one discussions with Strategy and Development regarding Oracle Applications strategy and your specific business and IT strategy. The experts will be available to discuss the value of the latest releases and share insights into the best path for your enterprise, so come ready with your questions. Space is limited, so make sure you register. MTE9649 - Meet the Oracle E-Business Suite Tools and Technology Experts Lisa Parekh - Vice President, Technology Integration, Oracle Steven Chan - Sr. Director, Oracle Elke Phelps - Sr. Principal Product Manager, Applications Technology Group, Oracle Max Arderius - Manager, Applications Technology Group, Oracle Tuesday, Oct 2, 1:15 PM - 2:15 PM - Moscone West 2001A Don’t miss this Oracle Applications Meet the Experts session with experts who specialize in Oracle E-Business Suite technology. This is the place where attendees can have informal and semistructured but open one-on-one discussions with Strategy and Development regarding Oracle Applications strategy and your specific business and IT strategy. The experts will be available to discuss the value of the latest releases and share insights into the best path for your enterprise, so come ready with your questions. Space is limited, so make sure you register. Demos We have five booths in the exhibition demogrounds this year, where you can try ATG technologies firsthand and get your questions answered. Please stop by and meet our staff at the following locations: Advanced Architecture and Technology Stack for Oracle E-Business Suite (W-067) New User Productivity Capabilities in Oracle E-Business Suite (W-065) End-to-End Management of Oracle E-Business Suite (W-063) Oracle E-Business Suite 12.1 Technical Upgrade Best Practices (W-066) SOA-Based Integration for Oracle E-Business Suite (W-064)

    Read the article

  • Improving Partitioned Table Join Performance

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

    Read the article

  • C#/.NET Little Wonders: The ConcurrentDictionary

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  In this series of posts, we will discuss how the concurrent collections have been developed to help alleviate these multi-threading concerns.  Last week’s post began with a general introduction and discussed the ConcurrentStack<T> and ConcurrentQueue<T>.  Today's post discusses the ConcurrentDictionary<T> (originally I had intended to discuss ConcurrentBag this week as well, but ConcurrentDictionary had enough information to create a very full post on its own!).  Finally next week, we shall close with a discussion of the ConcurrentBag<T> and BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. Recap As you'll recall from the previous post, the original collections were object-based containers that accomplished synchronization through a Synchronized member.  While these were convenient because you didn't have to worry about writing your own synchronization logic, they were a bit too finely grained and if you needed to perform multiple operations under one lock, the automatic synchronization didn't buy much. With the advent of .NET 2.0, the original collections were succeeded by the generic collections which are fully type-safe, but eschew automatic synchronization.  This cuts both ways in that you have a lot more control as a developer over when and how fine-grained you want to synchronize, but on the other hand if you just want simple synchronization it creates more work. With .NET 4.0, we get the best of both worlds in generic collections.  A new breed of collections was born called the concurrent collections in the System.Collections.Concurrent namespace.  These amazing collections are fine-tuned to have best overall performance for situations requiring concurrent access.  They are not meant to replace the generic collections, but to simply be an alternative to creating your own locking mechanisms. Among those concurrent collections were the ConcurrentStack<T> and ConcurrentQueue<T> which provide classic LIFO and FIFO collections with a concurrent twist.  As we saw, some of the traditional methods that required calls to be made in a certain order (like checking for not IsEmpty before calling Pop()) were replaced in favor of an umbrella operation that combined both under one lock (like TryPop()). Now, let's take a look at the next in our series of concurrent collections!For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this wonderful whitepaper by the Microsoft Parallel Computing Platform team here. ConcurrentDictionary – the fully thread-safe dictionary The ConcurrentDictionary<TKey,TValue> is the thread-safe counterpart to the generic Dictionary<TKey, TValue> collection.  Obviously, both are designed for quick – O(1) – lookups of data based on a key.  If you think of algorithms where you need lightning fast lookups of data and don’t care whether the data is maintained in any particular ordering or not, the unsorted dictionaries are generally the best way to go. Note: as a side note, there are sorted implementations of IDictionary, namely SortedDictionary and SortedList which are stored as an ordered tree and a ordered list respectively.  While these are not as fast as the non-sorted dictionaries – they are O(log2 n) – they are a great combination of both speed and ordering -- and still greatly outperform a linear search. Now, once again keep in mind that if all you need to do is load a collection once and then allow multi-threaded reading you do not need any locking.  Examples of this tend to be situations where you load a lookup or translation table once at program start, then keep it in memory for read-only reference.  In such cases locking is completely non-productive. However, most of the time when we need a concurrent dictionary we are interleaving both reads and updates.  This is where the ConcurrentDictionary really shines!  It achieves its thread-safety with no common lock to improve efficiency.  It actually uses a series of locks to provide concurrent updates, and has lockless reads!  This means that the ConcurrentDictionary gets even more efficient the higher the ratio of reads-to-writes you have. ConcurrentDictionary and Dictionary differences For the most part, the ConcurrentDictionary<TKey,TValue> behaves like it’s Dictionary<TKey,TValue> counterpart with a few differences.  Some notable examples of which are: Add() does not exist in the concurrent dictionary. This means you must use TryAdd(), AddOrUpdate(), or GetOrAdd().  It also means that you can’t use a collection initializer with the concurrent dictionary. TryAdd() replaced Add() to attempt atomic, safe adds. Because Add() only succeeds if the item doesn’t already exist, we need an atomic operation to check if the item exists, and if not add it while still under an atomic lock. TryUpdate() was added to attempt atomic, safe updates. If we want to update an item, we must make sure it exists first and that the original value is what we expected it to be.  If all these are true, we can update the item under one atomic step. TryRemove() was added to attempt atomic, safe removes. To safely attempt to remove a value we need to see if the key exists first, this checks for existence and removes under an atomic lock. AddOrUpdate() was added to attempt an thread-safe “upsert”. There are many times where you want to insert into a dictionary if the key doesn’t exist, or update the value if it does.  This allows you to make a thread-safe add-or-update. GetOrAdd() was added to attempt an thread-safe query/insert. Sometimes, you want to query for whether an item exists in the cache, and if it doesn’t insert a starting value for it.  This allows you to get the value if it exists and insert if not. Count, Keys, Values properties take a snapshot of the dictionary. Accessing these properties may interfere with add and update performance and should be used with caution. ToArray() returns a static snapshot of the dictionary. That is, the dictionary is locked, and then copied to an array as a O(n) operation.  GetEnumerator() is thread-safe and efficient, but allows dirty reads. Because reads require no locking, you can safely iterate over the contents of the dictionary.  The only downside is that, depending on timing, you may get dirty reads. Dirty reads during iteration The last point on GetEnumerator() bears some explanation.  Picture a scenario in which you call GetEnumerator() (or iterate using a foreach, etc.) and then, during that iteration the dictionary gets updated.  This may not sound like a big deal, but it can lead to inconsistent results if used incorrectly.  The problem is that items you already iterated over that are updated a split second after don’t show the update, but items that you iterate over that were updated a split second before do show the update.  Thus you may get a combination of items that are “stale” because you iterated before the update, and “fresh” because they were updated after GetEnumerator() but before the iteration reached them. Let’s illustrate with an example, let’s say you load up a concurrent dictionary like this: 1: // load up a dictionary. 2: var dictionary = new ConcurrentDictionary<string, int>(); 3:  4: dictionary["A"] = 1; 5: dictionary["B"] = 2; 6: dictionary["C"] = 3; 7: dictionary["D"] = 4; 8: dictionary["E"] = 5; 9: dictionary["F"] = 6; Then you have one task (using the wonderful TPL!) to iterate using dirty reads: 1: // attempt iteration in a separate thread 2: var iterationTask = new Task(() => 3: { 4: // iterates using a dirty read 5: foreach (var pair in dictionary) 6: { 7: Console.WriteLine(pair.Key + ":" + pair.Value); 8: } 9: }); And one task to attempt updates in a separate thread (probably): 1: // attempt updates in a separate thread 2: var updateTask = new Task(() => 3: { 4: // iterates, and updates the value by one 5: foreach (var pair in dictionary) 6: { 7: dictionary[pair.Key] = pair.Value + 1; 8: } 9: }); Now that we’ve done this, we can fire up both tasks and wait for them to complete: 1: // start both tasks 2: updateTask.Start(); 3: iterationTask.Start(); 4:  5: // wait for both to complete. 6: Task.WaitAll(updateTask, iterationTask); Now, if I you didn’t know about the dirty reads, you may have expected to see the iteration before the updates (such as A:1, B:2, C:3, D:4, E:5, F:6).  However, because the reads are dirty, we will quite possibly get a combination of some updated, some original.  My own run netted this result: 1: F:6 2: E:6 3: D:5 4: C:4 5: B:3 6: A:2 Note that, of course, iteration is not in order because ConcurrentDictionary, like Dictionary, is unordered.  Also note that both E and F show the value 6.  This is because the output task reached F before the update, but the updates for the rest of the items occurred before their output (probably because console output is very slow, comparatively). If we want to always guarantee that we will get a consistent snapshot to iterate over (that is, at the point we ask for it we see precisely what is in the dictionary and no subsequent updates during iteration), we should iterate over a call to ToArray() instead: 1: // attempt iteration in a separate thread 2: var iterationTask = new Task(() => 3: { 4: // iterates using a dirty read 5: foreach (var pair in dictionary.ToArray()) 6: { 7: Console.WriteLine(pair.Key + ":" + pair.Value); 8: } 9: }); The atomic Try…() methods As you can imagine TryAdd() and TryRemove() have few surprises.  Both first check the existence of the item to determine if it can be added or removed based on whether or not the key currently exists in the dictionary: 1: // try add attempts an add and returns false if it already exists 2: if (dictionary.TryAdd("G", 7)) 3: Console.WriteLine("G did not exist, now inserted with 7"); 4: else 5: Console.WriteLine("G already existed, insert failed."); TryRemove() also has the virtue of returning the value portion of the removed entry matching the given key: 1: // attempt to remove the value, if it exists it is removed and the original is returned 2: int removedValue; 3: if (dictionary.TryRemove("C", out removedValue)) 4: Console.WriteLine("Removed C and its value was " + removedValue); 5: else 6: Console.WriteLine("C did not exist, remove failed."); Now TryUpdate() is an interesting creature.  You might think from it’s name that TryUpdate() first checks for an item’s existence, and then updates if the item exists, otherwise it returns false.  Well, note quite... It turns out when you call TryUpdate() on a concurrent dictionary, you pass it not only the new value you want it to have, but also the value you expected it to have before the update.  If the item exists in the dictionary, and it has the value you expected, it will update it to the new value atomically and return true.  If the item is not in the dictionary or does not have the value you expected, it is not modified and false is returned. 1: // attempt to update the value, if it exists and if it has the expected original value 2: if (dictionary.TryUpdate("G", 42, 7)) 3: Console.WriteLine("G existed and was 7, now it's 42."); 4: else 5: Console.WriteLine("G either didn't exist, or wasn't 7."); The composite Add methods The ConcurrentDictionary also has composite add methods that can be used to perform updates and gets, with an add if the item is not existing at the time of the update or get. The first of these, AddOrUpdate(), allows you to add a new item to the dictionary if it doesn’t exist, or update the existing item if it does.  For example, let’s say you are creating a dictionary of counts of stock ticker symbols you’ve subscribed to from a market data feed: 1: public sealed class SubscriptionManager 2: { 3: private readonly ConcurrentDictionary<string, int> _subscriptions = new ConcurrentDictionary<string, int>(); 4:  5: // adds a new subscription, or increments the count of the existing one. 6: public void AddSubscription(string tickerKey) 7: { 8: // add a new subscription with count of 1, or update existing count by 1 if exists 9: var resultCount = _subscriptions.AddOrUpdate(tickerKey, 1, (symbol, count) => count + 1); 10:  11: // now check the result to see if we just incremented the count, or inserted first count 12: if (resultCount == 1) 13: { 14: // subscribe to symbol... 15: } 16: } 17: } Notice the update value factory Func delegate.  If the key does not exist in the dictionary, the add value is used (in this case 1 representing the first subscription for this symbol), but if the key already exists, it passes the key and current value to the update delegate which computes the new value to be stored in the dictionary.  The return result of this operation is the value used (in our case: 1 if added, existing value + 1 if updated). Likewise, the GetOrAdd() allows you to attempt to retrieve a value from the dictionary, and if the value does not currently exist in the dictionary it will insert a value.  This can be handy in cases where perhaps you wish to cache data, and thus you would query the cache to see if the item exists, and if it doesn’t you would put the item into the cache for the first time: 1: public sealed class PriceCache 2: { 3: private readonly ConcurrentDictionary<string, double> _cache = new ConcurrentDictionary<string, double>(); 4:  5: // adds a new subscription, or increments the count of the existing one. 6: public double QueryPrice(string tickerKey) 7: { 8: // check for the price in the cache, if it doesn't exist it will call the delegate to create value. 9: return _cache.GetOrAdd(tickerKey, symbol => GetCurrentPrice(symbol)); 10: } 11:  12: private double GetCurrentPrice(string tickerKey) 13: { 14: // do code to calculate actual true price. 15: } 16: } There are other variations of these two methods which vary whether a value is provided or a factory delegate, but otherwise they work much the same. Oddities with the composite Add methods The AddOrUpdate() and GetOrAdd() methods are totally thread-safe, on this you may rely, but they are not atomic.  It is important to note that the methods that use delegates execute those delegates outside of the lock.  This was done intentionally so that a user delegate (of which the ConcurrentDictionary has no control of course) does not take too long and lock out other threads. This is not necessarily an issue, per se, but it is something you must consider in your design.  The main thing to consider is that your delegate may get called to generate an item, but that item may not be the one returned!  Consider this scenario: A calls GetOrAdd and sees that the key does not currently exist, so it calls the delegate.  Now thread B also calls GetOrAdd and also sees that the key does not currently exist, and for whatever reason in this race condition it’s delegate completes first and it adds its new value to the dictionary.  Now A is done and goes to get the lock, and now sees that the item now exists.  In this case even though it called the delegate to create the item, it will pitch it because an item arrived between the time it attempted to create one and it attempted to add it. Let’s illustrate, assume this totally contrived example program which has a dictionary of char to int.  And in this dictionary we want to store a char and it’s ordinal (that is, A = 1, B = 2, etc).  So for our value generator, we will simply increment the previous value in a thread-safe way (perhaps using Interlocked): 1: public static class Program 2: { 3: private static int _nextNumber = 0; 4:  5: // the holder of the char to ordinal 6: private static ConcurrentDictionary<char, int> _dictionary 7: = new ConcurrentDictionary<char, int>(); 8:  9: // get the next id value 10: public static int NextId 11: { 12: get { return Interlocked.Increment(ref _nextNumber); } 13: } Then, we add a method that will perform our insert: 1: public static void Inserter() 2: { 3: for (int i = 0; i < 26; i++) 4: { 5: _dictionary.GetOrAdd((char)('A' + i), key => NextId); 6: } 7: } Finally, we run our test by starting two tasks to do this work and get the results… 1: public static void Main() 2: { 3: // 3 tasks attempting to get/insert 4: var tasks = new List<Task> 5: { 6: new Task(Inserter), 7: new Task(Inserter) 8: }; 9:  10: tasks.ForEach(t => t.Start()); 11: Task.WaitAll(tasks.ToArray()); 12:  13: foreach (var pair in _dictionary.OrderBy(p => p.Key)) 14: { 15: Console.WriteLine(pair.Key + ":" + pair.Value); 16: } 17: } If you run this with only one task, you get the expected A:1, B:2, ..., Z:26.  But running this in parallel you will get something a bit more complex.  My run netted these results: 1: A:1 2: B:3 3: C:4 4: D:5 5: E:6 6: F:7 7: G:8 8: H:9 9: I:10 10: J:11 11: K:12 12: L:13 13: M:14 14: N:15 15: O:16 16: P:17 17: Q:18 18: R:19 19: S:20 20: T:21 21: U:22 22: V:23 23: W:24 24: X:25 25: Y:26 26: Z:27 Notice that B is 3?  This is most likely because both threads attempted to call GetOrAdd() at roughly the same time and both saw that B did not exist, thus they both called the generator and one thread got back 2 and the other got back 3.  However, only one of those threads can get the lock at a time for the actual insert, and thus the one that generated the 3 won and the 3 was inserted and the 2 got discarded.  This is why on these methods your factory delegates should be careful not to have any logic that would be unsafe if the value they generate will be pitched in favor of another item generated at roughly the same time.  As such, it is probably a good idea to keep those generators as stateless as possible. Summary The ConcurrentDictionary is a very efficient and thread-safe version of the Dictionary generic collection.  It has all the benefits of type-safety that it’s generic collection counterpart does, and in addition is extremely efficient especially when there are more reads than writes concurrently. Tweet Technorati Tags: C#, .NET, Concurrent Collections, Collections, Little Wonders, Black Rabbit Coder,James Michael Hare

    Read the article

  • How to declare a(n) vector/array of reducer objects in Cilk++?

    - by Jin
    Hi All, I had a problem when I am using Cilk++, an extension to C++ for parallel computing. I found that I can't declare a vector of reducer objects: typedef cilk::reducer_opadd<int> T_reducer; vector<T_reducer> bitmiss_vec; for (int i = 0; i < 24; ++i) { T_reducer r; bitmiss_vec.push_back(r); } However, when I compile the code with Cilk++, it complains at the push_back() line: cilk++ geneAttack.cilk -O1 -g -lcilkutil -o geneAttack /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h: In member function ‘void __gnu_cxx::new_allocator<_Tp>::construct(_Tp*, const _Tp&) [with _Tp = cilk::reducer_opadd<int>]’: /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:601: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:229: error: ‘cilk::reducer_opadd<Type>::reducer_opadd(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/ext/new_allocator.h:107: error: within this context /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h: In member function ‘void std::vector<_Tp, _Alloc>::_M_insert_aux(__gnu_cxx::__normal_iterator<typename std::_Vector_base<_Tp, _Alloc>::_Tp_alloc_type::pointer, std::vector<_Tp, _Alloc> >, const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’: /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:605: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:229: error: ‘cilk::reducer_opadd<Type>::reducer_opadd(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/vector.tcc:252: error: within this context /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:605: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:230: error: ‘cilk::reducer_opadd<Type>& cilk::reducer_opadd<Type>::operator=(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/vector.tcc:256: error: within this context /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h: In static member function ‘static _BI2 std::__copy_backward<_BoolType, std::random_access_iterator_tag>::__copy_b(_BI1, _BI1, _BI2) [with _BI1 = cilk::reducer_opadd<int>*, _BI2 = cilk::reducer_opadd<int>*, bool _BoolType = false]’: /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_algobase.h:465: instantiated from ‘_BI2 std::__copy_backward_aux(_BI1, _BI1, _BI2) [with _BI1 = cilk::reducer_opadd<int>*, _BI2 = cilk::reducer_opadd<int>*]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_algobase.h:474: instantiated from ‘static _BI2 std::__copy_backward_normal<<anonymous>, <anonymous> >::__copy_b_n(_BI1, _BI1, _BI2) [with _BI1 = cilk::reducer_opadd<int>*, _BI2 = cilk::reducer_opadd<int>*, bool <anonymous> = false, bool <anonymous> = false]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_algobase.h:540: instantiated from ‘_BI2 std::copy_backward(_BI1, _BI1, _BI2) [with _BI1 = cilk::reducer_opadd<int>*, _BI2 = cilk::reducer_opadd<int>*]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/vector.tcc:253: instantiated from ‘void std::vector<_Tp, _Alloc>::_M_insert_aux(__gnu_cxx::__normal_iterator<typename std::_Vector_base<_Tp, _Alloc>::_Tp_alloc_type::pointer, std::vector<_Tp, _Alloc> >, const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:605: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:230: error: ‘cilk::reducer_opadd<Type>& cilk::reducer_opadd<Type>::operator=(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_algobase.h:433: error: within this context /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h: In function ‘void std::_Construct(_T1*, const _T2&) [with _T1 = cilk::reducer_opadd<int>, _T2 = cilk::reducer_opadd<int>]’: /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_uninitialized.h:87: instantiated from ‘_ForwardIterator std::__uninitialized_copy_aux(_InputIterator, _InputIterator, _ForwardIterator, std::__false_type) [with _InputIterator = cilk::reducer_opadd<int>*, _ForwardIterator = cilk::reducer_opadd<int>*]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_uninitialized.h:114: instantiated from ‘_ForwardIterator std::uninitialized_copy(_InputIterator, _InputIterator, _ForwardIterator) [with _InputIterator = cilk::reducer_opadd<int>*, _ForwardIterator = cilk::reducer_opadd<int>*]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_uninitialized.h:254: instantiated from ‘_ForwardIterator std::__uninitialized_copy_a(_InputIterator, _InputIterator, _ForwardIterator, std::allocator<_Tp>) [with _InputIterator = cilk::reducer_opadd<int>*, _ForwardIterator = cilk::reducer_opadd<int>*, _Tp = cilk::reducer_opadd<int>]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/vector.tcc:275: instantiated from ‘void std::vector<_Tp, _Alloc>::_M_insert_aux(__gnu_cxx::__normal_iterator<typename std::_Vector_base<_Tp, _Alloc>::_Tp_alloc_type::pointer, std::vector<_Tp, _Alloc> >, const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:605: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:229: error: ‘cilk::reducer_opadd<Type>::reducer_opadd(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_construct.h:81: error: within this context make: *** [geneAttack] Error 1 jinchen@galactica:~/workspace/biometrics/genAttack$ make cilk++ geneAttack.cilk -O1 -g -lcilkutil -o geneAttack geneAttack.cilk: In function ‘int cilk cilk_main(int, char**)’: geneAttack.cilk:670: error: expected primary-expression before ‘,’ token geneAttack.cilk:670: error: expected primary-expression before ‘}’ token geneAttack.cilk:674: error: ‘bitmiss_vec’ was not declared in this scope make: *** [geneAttack] Error 1 The Cilk++ manule says it supports array/vector of reducers, although there are performance issues to consider: "If you create a large number of reducers (for example, an array or vector of reducers) you must be aware that there is an overhead at steal and reduce that is proportional to the number of reducers in the program. " Anyone knows what is going on? How should I declare/use vector of reducers? Thank you

    Read the article

  • How to declare a vector or array of reducer objects in Cilk++?

    - by Jin
    Hi All, I had a problem when I am using Cilk++, an extension to C++ for parallel computing. I found that I can't declare a vector of reducer objects: typedef cilk::reducer_opadd<int> T_reducer; vector<T_reducer> bitmiss_vec; for (int i = 0; i < 24; ++i) { T_reducer r; bitmiss_vec.push_back(r); } However, when I compile the code with Cilk++, it complains at the push_back() line: cilk++ geneAttack.cilk -O1 -g -lcilkutil -o geneAttack /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h: In member function ‘void __gnu_cxx::new_allocator<_Tp>::construct(_Tp*, const _Tp&) [with _Tp = cilk::reducer_opadd<int>]’: /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:601: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:229: error: ‘cilk::reducer_opadd<Type>::reducer_opadd(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/ext/new_allocator.h:107: error: within this context /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h: In member function ‘void std::vector<_Tp, _Alloc>::_M_insert_aux(__gnu_cxx::__normal_iterator<typename std::_Vector_base<_Tp, _Alloc>::_Tp_alloc_type::pointer, std::vector<_Tp, _Alloc> >, const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’: /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:605: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:229: error: ‘cilk::reducer_opadd<Type>::reducer_opadd(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/vector.tcc:252: error: within this context /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:605: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:230: error: ‘cilk::reducer_opadd<Type>& cilk::reducer_opadd<Type>::operator=(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/vector.tcc:256: error: within this context /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h: In static member function ‘static _BI2 std::__copy_backward<_BoolType, std::random_access_iterator_tag>::__copy_b(_BI1, _BI1, _BI2) [with _BI1 = cilk::reducer_opadd<int>*, _BI2 = cilk::reducer_opadd<int>*, bool _BoolType = false]’: /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_algobase.h:465: instantiated from ‘_BI2 std::__copy_backward_aux(_BI1, _BI1, _BI2) [with _BI1 = cilk::reducer_opadd<int>*, _BI2 = cilk::reducer_opadd<int>*]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_algobase.h:474: instantiated from ‘static _BI2 std::__copy_backward_normal<<anonymous>, <anonymous> >::__copy_b_n(_BI1, _BI1, _BI2) [with _BI1 = cilk::reducer_opadd<int>*, _BI2 = cilk::reducer_opadd<int>*, bool <anonymous> = false, bool <anonymous> = false]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_algobase.h:540: instantiated from ‘_BI2 std::copy_backward(_BI1, _BI1, _BI2) [with _BI1 = cilk::reducer_opadd<int>*, _BI2 = cilk::reducer_opadd<int>*]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/vector.tcc:253: instantiated from ‘void std::vector<_Tp, _Alloc>::_M_insert_aux(__gnu_cxx::__normal_iterator<typename std::_Vector_base<_Tp, _Alloc>::_Tp_alloc_type::pointer, std::vector<_Tp, _Alloc> >, const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:605: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:230: error: ‘cilk::reducer_opadd<Type>& cilk::reducer_opadd<Type>::operator=(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_algobase.h:433: error: within this context /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h: In function ‘void std::_Construct(_T1*, const _T2&) [with _T1 = cilk::reducer_opadd<int>, _T2 = cilk::reducer_opadd<int>]’: /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_uninitialized.h:87: instantiated from ‘_ForwardIterator std::__uninitialized_copy_aux(_InputIterator, _InputIterator, _ForwardIterator, std::__false_type) [with _InputIterator = cilk::reducer_opadd<int>*, _ForwardIterator = cilk::reducer_opadd<int>*]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_uninitialized.h:114: instantiated from ‘_ForwardIterator std::uninitialized_copy(_InputIterator, _InputIterator, _ForwardIterator) [with _InputIterator = cilk::reducer_opadd<int>*, _ForwardIterator = cilk::reducer_opadd<int>*]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_uninitialized.h:254: instantiated from ‘_ForwardIterator std::__uninitialized_copy_a(_InputIterator, _InputIterator, _ForwardIterator, std::allocator<_Tp>) [with _InputIterator = cilk::reducer_opadd<int>*, _ForwardIterator = cilk::reducer_opadd<int>*, _Tp = cilk::reducer_opadd<int>]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/vector.tcc:275: instantiated from ‘void std::vector<_Tp, _Alloc>::_M_insert_aux(__gnu_cxx::__normal_iterator<typename std::_Vector_base<_Tp, _Alloc>::_Tp_alloc_type::pointer, std::vector<_Tp, _Alloc> >, const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_vector.h:605: instantiated from ‘void std::vector<_Tp, _Alloc>::push_back(const _Tp&) [with _Tp = cilk::reducer_opadd<int>, _Alloc = std::allocator<cilk::reducer_opadd<int> >]’ geneAttack.cilk:667: instantiated from here /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/cilk++/reducer_opadd.h:229: error: ‘cilk::reducer_opadd<Type>::reducer_opadd(const cilk::reducer_opadd<Type>&) [with Type = int]’ is private /usr/local/cilk/bin/../lib/gcc/x86_64-unknown-linux-gnu/4.2.4/../../../../include/c++/4.2.4/bits/stl_construct.h:81: error: within this context make: *** [geneAttack] Error 1 jinchen@galactica:~/workspace/biometrics/genAttack$ make cilk++ geneAttack.cilk -O1 -g -lcilkutil -o geneAttack geneAttack.cilk: In function ‘int cilk cilk_main(int, char**)’: geneAttack.cilk:670: error: expected primary-expression before ‘,’ token geneAttack.cilk:670: error: expected primary-expression before ‘}’ token geneAttack.cilk:674: error: ‘bitmiss_vec’ was not declared in this scope make: *** [geneAttack] Error 1 The Cilk++ manule says it supports array/vector of reducers, although there are performance issues to consider: "If you create a large number of reducers (for example, an array or vector of reducers) you must be aware that there is an overhead at steal and reduce that is proportional to the number of reducers in the program. " Anyone knows what is going on? How should I declare/use vector of reducers? Thank you

    Read the article

  • g++ SSE intrinsics dilemma - value from intrinsic "saturates"

    - by Sriram
    Hi, I wrote a simple program to implement SSE intrinsics for computing the inner product of two large (100000 or more elements) vectors. The program compares the execution time for both, inner product computed the conventional way and using intrinsics. Everything works out fine, until I insert (just for the fun of it) an inner loop before the statement that computes the inner product. Before I go further, here is the code: //this is a sample Intrinsics program to compute inner product of two vectors and compare Intrinsics with traditional method of doing things. #include <iostream> #include <iomanip> #include <xmmintrin.h> #include <stdio.h> #include <time.h> #include <stdlib.h> using namespace std; typedef float v4sf __attribute__ ((vector_size(16))); double innerProduct(float* arr1, int len1, float* arr2, int len2) { //assume len1 = len2. float result = 0.0; for(int i = 0; i < len1; i++) { for(int j = 0; j < len1; j++) { result += (arr1[i] * arr2[i]); } } //float y = 1.23e+09; //cout << "y = " << y << endl; return result; } double sse_v4sf_innerProduct(float* arr1, int len1, float* arr2, int len2) { //assume that len1 = len2. if(len1 != len2) { cout << "Lengths not equal." << endl; exit(1); } /*steps: * 1. load a long-type (4 float) into a v4sf type data from both arrays. * 2. multiply the two. * 3. multiply the same and store result. * 4. add this to previous results. */ v4sf arr1Data, arr2Data, prevSums, multVal, xyz; //__builtin_ia32_xorps(prevSums, prevSums); //making it equal zero. //can explicitly load 0 into prevSums using loadps or storeps (Check). float temp[4] = {0.0, 0.0, 0.0, 0.0}; prevSums = __builtin_ia32_loadups(temp); float result = 0.0; for(int i = 0; i < (len1 - 3); i += 4) { for(int j = 0; j < len1; j++) { arr1Data = __builtin_ia32_loadups(&arr1[i]); arr2Data = __builtin_ia32_loadups(&arr2[i]); //store the contents of two arrays. multVal = __builtin_ia32_mulps(arr1Data, arr2Data); //multiply. xyz = __builtin_ia32_addps(multVal, prevSums); prevSums = xyz; } } //prevSums will hold the sums of 4 32-bit floating point values taken at a time. Individual entries in prevSums also need to be added. __builtin_ia32_storeups(temp, prevSums); //store prevSums into temp. cout << "Values of temp:" << endl; for(int i = 0; i < 4; i++) cout << temp[i] << endl; result += temp[0] + temp[1] + temp[2] + temp[3]; return result; } int main() { clock_t begin, end; int length = 100000; float *arr1, *arr2; double result_Conventional, result_Intrinsic; // printStats("Allocating memory."); arr1 = new float[length]; arr2 = new float[length]; // printStats("End allocation."); srand(time(NULL)); //init random seed. // printStats("Initializing array1 and array2"); begin = clock(); for(int i = 0; i < length; i++) { // for(int j = 0; j < length; j++) { // arr1[i] = rand() % 10 + 1; arr1[i] = 2.5; // arr2[i] = rand() % 10 - 1; arr2[i] = 2.5; // } } end = clock(); cout << "Time to initialize array1 and array2 = " << ((double) (end - begin)) / CLOCKS_PER_SEC << endl; // printStats("Finished initialization."); // printStats("Begin inner product conventionally."); begin = clock(); result_Conventional = innerProduct(arr1, length, arr2, length); end = clock(); cout << "Time to compute inner product conventionally = " << ((double) (end - begin)) / CLOCKS_PER_SEC << endl; // printStats("End inner product conventionally."); // printStats("Begin inner product using Intrinsics."); begin = clock(); result_Intrinsic = sse_v4sf_innerProduct(arr1, length, arr2, length); end = clock(); cout << "Time to compute inner product with intrinsics = " << ((double) (end - begin)) / CLOCKS_PER_SEC << endl; //printStats("End inner product using Intrinsics."); cout << "Results: " << endl; cout << " result_Conventional = " << result_Conventional << endl; cout << " result_Intrinsics = " << result_Intrinsic << endl; return 0; } I use the following g++ invocation to build this: g++ -W -Wall -O2 -pedantic -march=i386 -msse intrinsics_SSE_innerProduct.C -o innerProduct Each of the loops above, in both the functions, runs a total of N^2 times. However, given that arr1 and arr2 (the two floating point vectors) are loaded with a value 2.5, the length of the array is 100,000, the result in both cases should be 6.25e+10. The results I get are: Results: result_Conventional = 6.25e+10 result_Intrinsics = 5.36871e+08 This is not all. It seems that the value returned from the function that uses intrinsics "saturates" at the value above. I tried putting other values for the elements of the array and different sizes too. But it seems that any value above 1.0 for the array contents and any size above 1000 meets with the same value we see above. Initially, I thought it might be because all operations within SSE are in floating point, but floating point should be able to store a number that is of the order of e+08. I am trying to see where I could be going wrong but cannot seem to figure it out. I am using g++ version: g++ (GCC) 4.4.1 20090725 (Red Hat 4.4.1-2). Any help on this is most welcome. Thanks, Sriram.

    Read the article

  • Node.js Adventure - Storage Services and Service Runtime

    - by Shaun
    When I described on how to host a Node.js application on Windows Azure, one of questions might be raised about how to consume the vary Windows Azure services, such as the storage, service bus, access control, etc.. Interact with windows azure services is available in Node.js through the Windows Azure Node.js SDK, which is a module available in NPM. In this post I would like to describe on how to use Windows Azure Storage (a.k.a. WAS) as well as the service runtime.   Consume Windows Azure Storage Let’s firstly have a look on how to consume WAS through Node.js. As we know in the previous post we can host Node.js application on Windows Azure Web Site (a.k.a. WAWS) as well as Windows Azure Cloud Service (a.k.a. WACS). In theory, WAWS is also built on top of WACS worker roles with some more features. Hence in this post I will only demonstrate for hosting in WACS worker role. The Node.js code can be used when consuming WAS when hosted on WAWS. But since there’s no roles in WAWS, the code for consuming service runtime mentioned in the next section cannot be used for WAWS node application. We can use the solution that I created in my last post. Alternatively we can create a new windows azure project in Visual Studio with a worker role, add the “node.exe” and “index.js” and install “express” and “node-sqlserver” modules, make all files as “Copy always”. In order to use windows azure services we need to have Windows Azure Node.js SDK, as knows as a module named “azure” which can be installed through NPM. Once we downloaded and installed, we need to include them in our worker role project and make them as “Copy always”. You can use my “Copy all always” tool mentioned in my last post to update the currently worker role project file. You can also find the source code of this tool here. The source code of Windows Azure SDK for Node.js can be found in its GitHub page. It contains two parts. One is a CLI tool which provides a cross platform command line package for Mac and Linux to manage WAWS and Windows Azure Virtual Machines (a.k.a. WAVM). The other is a library for managing and consuming vary windows azure services includes tables, blobs, queues, service bus and the service runtime. I will not cover all of them but will only demonstrate on how to use tables and service runtime information in this post. You can find the full document of this SDK here. Back to Visual Studio and open the “index.js”, let’s continue our application from the last post, which was working against Windows Azure SQL Database (a.k.a. WASD). The code should looks like this. 1: var express = require("express"); 2: var sql = require("node-sqlserver"); 3:  4: var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:ac6271ya9e.database.windows.net,1433;Database=synctile;Uid=shaunxu@ac6271ya9e;Pwd={PASSWORD};Encrypt=yes;Connection Timeout=30;"; 5: var port = 80; 6:  7: var app = express(); 8:  9: app.configure(function () { 10: app.use(express.bodyParser()); 11: }); 12:  13: app.get("/", function (req, res) { 14: sql.open(connectionString, function (err, conn) { 15: if (err) { 16: console.log(err); 17: res.send(500, "Cannot open connection."); 18: } 19: else { 20: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 21: if (err) { 22: console.log(err); 23: res.send(500, "Cannot retrieve records."); 24: } 25: else { 26: res.json(results); 27: } 28: }); 29: } 30: }); 31: }); 32:  33: app.get("/text/:key/:culture", function (req, res) { 34: sql.open(connectionString, function (err, conn) { 35: if (err) { 36: console.log(err); 37: res.send(500, "Cannot open connection."); 38: } 39: else { 40: var key = req.params.key; 41: var culture = req.params.culture; 42: var command = "SELECT * FROM [Resource] WHERE [Key] = '" + key + "' AND [Culture] = '" + culture + "'"; 43: conn.queryRaw(command, function (err, results) { 44: if (err) { 45: console.log(err); 46: res.send(500, "Cannot retrieve records."); 47: } 48: else { 49: res.json(results); 50: } 51: }); 52: } 53: }); 54: }); 55:  56: app.get("/sproc/:key/:culture", function (req, res) { 57: sql.open(connectionString, function (err, conn) { 58: if (err) { 59: console.log(err); 60: res.send(500, "Cannot open connection."); 61: } 62: else { 63: var key = req.params.key; 64: var culture = req.params.culture; 65: var command = "EXEC GetItem '" + key + "', '" + culture + "'"; 66: conn.queryRaw(command, function (err, results) { 67: if (err) { 68: console.log(err); 69: res.send(500, "Cannot retrieve records."); 70: } 71: else { 72: res.json(results); 73: } 74: }); 75: } 76: }); 77: }); 78:  79: app.post("/new", function (req, res) { 80: var key = req.body.key; 81: var culture = req.body.culture; 82: var val = req.body.val; 83:  84: sql.open(connectionString, function (err, conn) { 85: if (err) { 86: console.log(err); 87: res.send(500, "Cannot open connection."); 88: } 89: else { 90: var command = "INSERT INTO [Resource] VALUES ('" + key + "', '" + culture + "', N'" + val + "')"; 91: conn.queryRaw(command, function (err, results) { 92: if (err) { 93: console.log(err); 94: res.send(500, "Cannot retrieve records."); 95: } 96: else { 97: res.send(200, "Inserted Successful"); 98: } 99: }); 100: } 101: }); 102: }); 103:  104: app.listen(port); Now let’s create a new function, copy the records from WASD to table service. 1. Delete the table named “resource”. 2. Create a new table named “resource”. These 2 steps ensures that we have an empty table. 3. Load all records from the “resource” table in WASD. 4. For each records loaded from WASD, insert them into the table one by one. 5. Prompt to user when finished. In order to use table service we need the storage account and key, which can be found from the developer portal. Just select the storage account and click the Manage Keys button. Then create two local variants in our Node.js application for the storage account name and key. Since we need to use WAS we need to import the azure module. Also I created another variant stored the table name. In order to work with table service I need to create the storage client for table service. This is very similar as the Windows Azure SDK for .NET. As the code below I created a new variant named “client” and use “createTableService”, specified my storage account name and key. 1: var azure = require("azure"); 2: var storageAccountName = "synctile"; 3: var storageAccountKey = "/cOy9L7xysXOgPYU9FjDvjrRAhaMX/5tnOpcjqloPNDJYucbgTy7MOrAW7CbUg6PjaDdmyl+6pkwUnKETsPVNw=="; 4: var tableName = "resource"; 5: var client = azure.createTableService(storageAccountName, storageAccountKey); Now create a new function for URL “/was/init” so that we can trigger it through browser. Then in this function we will firstly load all records from WASD. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: } 18: } 19: }); 20: } 21: }); 22: }); When we succeed loaded all records we can start to transform them into table service. First I need to recreate the table in table service. This can be done by deleting and creating the table through table client I had just created previously. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: // transform the records 26: } 27: }); 28: }); 29: } 30: } 31: }); 32: } 33: }); 34: }); As you can see, the azure SDK provide its methods in callback pattern. In fact, almost all modules in Node.js use the callback pattern. For example, when I deleted a table I invoked “deleteTable” method, provided the name of the table and a callback function which will be performed when the table had been deleted or failed. Underlying, the azure module will perform the table deletion operation in POSIX async threads pool asynchronously. And once it’s done the callback function will be performed. This is the reason we need to nest the table creation code inside the deletion function. If we perform the table creation code after the deletion code then they will be invoked in parallel. Next, for each records in WASD I created an entity and then insert into the table service. Finally I send the response to the browser. Can you find a bug in the code below? I will describe it later in this post. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: // transform the records 26: for (var i = 0; i < results.rows.length; i++) { 27: var entity = { 28: "PartitionKey": results.rows[i][1], 29: "RowKey": results.rows[i][0], 30: "Value": results.rows[i][2] 31: }; 32: client.insertEntity(tableName, entity, function (error) { 33: if (error) { 34: error["target"] = "insertEntity"; 35: res.send(500, error); 36: } 37: else { 38: console.log("entity inserted"); 39: } 40: }); 41: } 42: // send the 43: console.log("all done"); 44: res.send(200, "All done!"); 45: } 46: }); 47: }); 48: } 49: } 50: }); 51: } 52: }); 53: }); Now we can publish it to the cloud and have a try. But normally we’d better test it at the local emulator first. In Node.js SDK there are three build-in properties which provides the account name, key and host address for local storage emulator. We can use them to initialize our table service client. We also need to change the SQL connection string to let it use my local database. The code will be changed as below. 1: // windows azure sql database 2: //var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:ac6271ya9e.database.windows.net,1433;Database=synctile;Uid=shaunxu@ac6271ya9e;Pwd=eszqu94XZY;Encrypt=yes;Connection Timeout=30;"; 3: // sql server 4: var connectionString = "Driver={SQL Server Native Client 11.0};Server={.};Database={Caspar};Trusted_Connection={Yes};"; 5:  6: var azure = require("azure"); 7: var storageAccountName = "synctile"; 8: var storageAccountKey = "/cOy9L7xysXOgPYU9FjDvjrRAhaMX/5tnOpcjqloPNDJYucbgTy7MOrAW7CbUg6PjaDdmyl+6pkwUnKETsPVNw=="; 9: var tableName = "resource"; 10: // windows azure storage 11: //var client = azure.createTableService(storageAccountName, storageAccountKey); 12: // local storage emulator 13: var client = azure.createTableService(azure.ServiceClient.DEVSTORE_STORAGE_ACCOUNT, azure.ServiceClient.DEVSTORE_STORAGE_ACCESS_KEY, azure.ServiceClient.DEVSTORE_TABLE_HOST); Now let’s run the application and navigate to “localhost:12345/was/init” as I hosted it on port 12345. We can find it transformed the data from my local database to local table service. Everything looks fine. But there is a bug in my code. If we have a look on the Node.js command window we will find that it sent response before all records had been inserted, which is not what I expected. The reason is that, as I mentioned before, Node.js perform all IO operations in non-blocking model. When we inserted the records we executed the table service insert method in parallel, and the operation of sending response was also executed in parallel, even though I wrote it at the end of my logic. The correct logic should be, when all entities had been copied to table service with no error, then I will send response to the browser, otherwise I should send error message to the browser. To do so I need to import another module named “async”, which helps us to coordinate our asynchronous code. Install the module and import it at the beginning of the code. Then we can use its “forEach” method for the asynchronous code of inserting table entities. The first argument of “forEach” is the array that will be performed. The second argument is the operation for each items in the array. And the third argument will be invoked then all items had been performed or any errors occurred. Here we can send our response to browser. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: async.forEach(results.rows, 26: // transform the records 27: function (row, callback) { 28: var entity = { 29: "PartitionKey": row[1], 30: "RowKey": row[0], 31: "Value": row[2] 32: }; 33: client.insertEntity(tableName, entity, function (error) { 34: if (error) { 35: callback(error); 36: } 37: else { 38: console.log("entity inserted."); 39: callback(null); 40: } 41: }); 42: }, 43: // send reponse 44: function (error) { 45: if (error) { 46: error["target"] = "insertEntity"; 47: res.send(500, error); 48: } 49: else { 50: console.log("all done"); 51: res.send(200, "All done!"); 52: } 53: } 54: ); 55: } 56: }); 57: }); 58: } 59: } 60: }); 61: } 62: }); 63: }); Run it locally and now we can find the response was sent after all entities had been inserted. Query entities against table service is simple as well. Just use the “queryEntity” method from the table service client and providing the partition key and row key. We can also provide a complex query criteria as well, for example the code here. In the code below I queried an entity by the partition key and row key, and return the proper localization value in response. 1: app.get("/was/:key/:culture", function (req, res) { 2: var key = req.params.key; 3: var culture = req.params.culture; 4: client.queryEntity(tableName, culture, key, function (error, entity) { 5: if (error) { 6: res.send(500, error); 7: } 8: else { 9: res.json(entity); 10: } 11: }); 12: }); And then tested it on local emulator. Finally if we want to publish this application to the cloud we should change the database connection string and storage account. For more information about how to consume blob and queue service, as well as the service bus please refer to the MSDN page.   Consume Service Runtime As I mentioned above, before we published our application to the cloud we need to change the connection string and account information in our code. But if you had played with WACS you should have known that the service runtime provides the ability to retrieve configuration settings, endpoints and local resource information at runtime. Which means we can have these values defined in CSCFG and CSDEF files and then the runtime should be able to retrieve the proper values. For example we can add some role settings though the property window of the role, specify the connection string and storage account for cloud and local. And the can also use the endpoint which defined in role environment to our Node.js application. In Node.js SDK we can get an object from “azure.RoleEnvironment”, which provides the functionalities to retrieve the configuration settings and endpoints, etc.. In the code below I defined the connection string variants and then use the SDK to retrieve and initialize the table client. 1: var connectionString = ""; 2: var storageAccountName = ""; 3: var storageAccountKey = ""; 4: var tableName = ""; 5: var client; 6:  7: azure.RoleEnvironment.getConfigurationSettings(function (error, settings) { 8: if (error) { 9: console.log("ERROR: getConfigurationSettings"); 10: console.log(JSON.stringify(error)); 11: } 12: else { 13: console.log(JSON.stringify(settings)); 14: connectionString = settings["SqlConnectionString"]; 15: storageAccountName = settings["StorageAccountName"]; 16: storageAccountKey = settings["StorageAccountKey"]; 17: tableName = settings["TableName"]; 18:  19: console.log("connectionString = %s", connectionString); 20: console.log("storageAccountName = %s", storageAccountName); 21: console.log("storageAccountKey = %s", storageAccountKey); 22: console.log("tableName = %s", tableName); 23:  24: client = azure.createTableService(storageAccountName, storageAccountKey); 25: } 26: }); In this way we don’t need to amend the code for the configurations between local and cloud environment since the service runtime will take care of it. At the end of the code we will listen the application on the port retrieved from SDK as well. 1: azure.RoleEnvironment.getCurrentRoleInstance(function (error, instance) { 2: if (error) { 3: console.log("ERROR: getCurrentRoleInstance"); 4: console.log(JSON.stringify(error)); 5: } 6: else { 7: console.log(JSON.stringify(instance)); 8: if (instance["endpoints"] && instance["endpoints"]["nodejs"]) { 9: var endpoint = instance["endpoints"]["nodejs"]; 10: app.listen(endpoint["port"]); 11: } 12: else { 13: app.listen(8080); 14: } 15: } 16: }); But if we tested the application right now we will find that it cannot retrieve any values from service runtime. This is because by default, the entry point of this role was defined to the worker role class. In windows azure environment the service runtime will open a named pipeline to the entry point instance, so that it can connect to the runtime and retrieve values. But in this case, since the entry point was worker role and the Node.js was opened inside the role, the named pipeline was established between our worker role class and service runtime, so our Node.js application cannot use it. To fix this problem we need to open the CSDEF file under the azure project, add a new element named Runtime. Then add an element named EntryPoint which specify the Node.js command line. So that the Node.js application will have the connection to service runtime, then it’s able to read the configurations. Start the Node.js at local emulator we can find it retrieved the connections, storage account for local. And if we publish our application to azure then it works with WASD and storage service through the configurations for cloud.   Summary In this post I demonstrated how to use Windows Azure SDK for Node.js to interact with storage service, especially the table service. I also demonstrated on how to use WACS service runtime, how to retrieve the configuration settings and the endpoint information. And in order to make the service runtime available to my Node.js application I need to create an entry point element in CSDEF file and set “node.exe” as the entry point. I used five posts to introduce and demonstrate on how to run a Node.js application on Windows platform, how to use Windows Azure Web Site and Windows Azure Cloud Service worker role to host our Node.js application. I also described how to work with other services provided by Windows Azure platform through Windows Azure SDK for Node.js. Node.js is a very new and young network application platform. But since it’s very simple and easy to learn and deploy, as well as, it utilizes single thread non-blocking IO model, Node.js became more and more popular on web application and web service development especially for those IO sensitive projects. And as Node.js is very good at scaling-out, it’s more useful on cloud computing platform. Use Node.js on Windows platform is new, too. The modules for SQL database and Windows Azure SDK are still under development and enhancement. It doesn’t support SQL parameter in “node-sqlserver”. It does support using storage connection string to create the storage client in “azure”. But Microsoft is working on make them easier to use, working on add more features and functionalities.   PS, you can download the source code here. You can download the source code of my “Copy all always” tool here.   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.

    Read the article

  • HDFS some datanodes of cluster are suddenly disconnected while reducers are running

    - by user1429825
    I have 8 slave computers and 1 master computer for running Hadoop (ver 0.21) some datanodes of cluster are suddenly disconnected while I was running MapReduce code on 10GB data After all mappers finished and around 80% of reducers was processed, randomly one or more datanode disconned from network. and then the other datanodes start to disappear from network even if I killed the MapReduce job when I found some datanode was disconnected. I've tried to change dfs.datanode.max.xcievers to 4096, turned off fire-walls of all computing node, disabled selinux and increased the number of file open limit to 20000 but they didn't work at all... anyone have a idea to solve this problem? followings are error log from mapreduce 12/06/01 12:31:29 INFO mapreduce.Job: Task Id : attempt_201206011227_0001_r_000006_0, Status : FAILED java.io.IOException: Bad connect ack with firstBadLink as ***.***.***.148:20010 at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.createBlockOutputStream(DFSOutputStream.java:889) at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:820) at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:427) and followings are logs from datanode 2012-06-01 13:01:01,118 INFO org.apache.hadoop.hdfs.server.datanode.DataNode: Receiving block blk_-5549263231281364844_3453 src: /*.*.*.147:56205 dest: /*.*.*.142:20010 2012-06-01 13:01:01,136 INFO org.apache.hadoop.hdfs.server.datanode.DataNode: DatanodeRegistration(*.*.*.142:20010, storageID=DS-1534489105-*.*.*.142-20010-1337757934836, infoPort=20075, ipcPort=20020) Starting thread to transfer block blk_-3849519151985279385_5906 to *.*.*.147:20010 2012-06-01 13:01:19,135 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: DatanodeRegistration(*.*.*.142:20010, storageID=DS-1534489105-*.*.*.142-20010-1337757934836, infoPort=20075, ipcPort=20020):Failed to transfer blk_-5797481564121417802_3453 to *.*.*.146:20010 got java.net.ConnectException: > Connection timed out at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method) at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:701) at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206) at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:373) at org.apache.hadoop.hdfs.server.datanode.DataNode$DataTransfer.run(DataNode.java:1257) at java.lang.Thread.run(Thread.java:722) 2012-06-01 13:06:20,342 INFO org.apache.hadoop.hdfs.server.datanode.DataBlockScanner: Verification succeeded for blk_6674438989226364081_3453 2012-06-01 13:09:01,781 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: DatanodeRegistration(*.*.*.142:20010, storageID=DS-1534489105-*.*.*.142-20010-1337757934836, infoPort=20075, ipcPort=20020):Failed to transfer blk_-3849519151985279385_5906 to *.*.*.147:20010 got java.net.SocketTimeoutException: 480000 millis timeout while waiting for channel to be ready for write. ch : java.nio.channels.SocketChannel[connected local=/*.*.*.142:60057 remote=/*.*.*.147:20010] at org.apache.hadoop.net.SocketIOWithTimeout.waitForIO(SocketIOWithTimeout.java:246) at org.apache.hadoop.net.SocketOutputStream.waitForWritable(SocketOutputStream.java:164) at org.apache.hadoop.net.SocketOutputStream.transferToFully(SocketOutputStream.java:203) at org.apache.hadoop.hdfs.server.datanode.BlockSender.sendChunks(BlockSender.java:388) at org.apache.hadoop.hdfs.server.datanode.BlockSender.sendBlock(BlockSender.java:476) at org.apache.hadoop.hdfs.server.datanode.DataNode$DataTransfer.run(DataNode.java:1284) at java.lang.Thread.run(Thread.java:722) hdfs-site.xml <configuration> <property> <name>dfs.name.dir</name> <value>/home/hadoop/data/name</value> </property> <property> <name>dfs.data.dir</name> <value>/home/hadoop/data/hdfs1,/home/hadoop/data/hdfs2,/home/hadoop/data/hdfs3,/home/hadoop/data/hdfs4,/home/hadoop/data/hdfs5</value> </property> <property> <name>dfs.replication</name> <value>3</value> </property> <property> <name>dfs.datanode.max.xcievers</name> <value>4096</value> </property> <property> <name>dfs.http.address</name> <value>0.0.0.0:20070</value> <description>50070 The address and the base port where the dfs namenode web ui will listen on. If the port is 0 then the server will start on a free port. </description> </property> <property> <name>dfs.datanode.http.address</name> <value>0.0.0.0:20075</value> <description>50075 The datanode http server address and port. If the port is 0 then the server will start on a free port. </description> </property> <property> <name>dfs.secondary.http.address</name> <value>0.0.0.0:20090</value> <description>50090 The secondary namenode http server address and port. If the port is 0 then the server will start on a free port. </description> </property> <property> <name>dfs.datanode.address</name> <value>0.0.0.0:20010</value> <description>50010 The address where the datanode server will listen to. If the port is 0 then the server will start on a free port. </description> <property> <name>dfs.datanode.ipc.address</name> <value>0.0.0.0:20020</value> <description>50020 The datanode ipc server address and port. If the port is 0 then the server will start on a free port. </description> </property> <property> <name>dfs.datanode.https.address</name> <value>0.0.0.0:20475</value> </property> <property> <name>dfs.https.address</name> <value>0.0.0.0:20470</value> </property> </configuration> mapred-site.xml <configuration> <property> <name>mapred.job.tracker</name> <value>masternode:29001</value> </property> <property> <name>mapred.system.dir</name> <value>/home/hadoop/data/mapreduce/system</value> </property> <property> <name>mapred.local.dir</name> <value>/home/hadoop/data/mapreduce/local</value> </property> <property> <name>mapred.map.tasks</name> <value>32</value> <description> default number of map tasks per job.</description> </property> <property> <name>mapred.tasktracker.map.tasks.maximum</name> <value>4</value> </property> <property> <name>mapred.reduce.tasks</name> <value>8</value> <description> default number of reduce tasks per job.</description> </property> <property> <name>mapred.map.child.java.opts</name> <value>-Xmx2048M</value> </property> <property> <name>io.sort.mb</name> <value>500</value> </property> <property> <name>mapred.task.timeout</name> <value>1800000</value> <!-- 30 minutes --> </property> <property> <name>mapred.job.tracker.http.address</name> <value>0.0.0.0:20030</value> <description> 50030 The job tracker http server address and port the server will listen on. If the port is 0 then the server will start on a free port. </description> </property> <property> <name>mapred.task.tracker.http.address</name> <value>0.0.0.0:20060</value> <description> 50060 </property> </configuration>

    Read the article

  • Is there a Telecommunications Reference Architecture?

    - by raul.goycoolea
    @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpFirst, li.MsoListParagraphCxSpFirst, div.MsoListParagraphCxSpFirst { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpMiddle, li.MsoListParagraphCxSpMiddle, div.MsoListParagraphCxSpMiddle { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpLast, li.MsoListParagraphCxSpLast, div.MsoListParagraphCxSpLast { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Abstract   Reference architecture provides needed architectural information that can be provided in advance to an enterprise to enable consistent architectural best practices. Enterprise Reference Architecture helps business owners to actualize their strategies, vision, objectives, and principles. It evaluates the IT systems, based on Reference Architecture goals, principles, and standards. It helps to reduce IT costs by increasing functionality, availability, scalability, etc. Telecom Reference Architecture provides customers with the flexibility to view bundled service bills online with the provision of multiple services. It provides real-time, flexible billing and charging systems, to handle complex promotions, discounts, and settlements with multiple parties. This paper attempts to describe the Reference Architecture for the Telecom Enterprises. It lays the foundation for a Telecom Reference Architecture by articulating the requirements, drivers, and pitfalls for telecom service providers. It describes generic reference architecture for telecom enterprises and moves on to explain how to achieve Enterprise Reference Architecture by using SOA.   Introduction   A Reference Architecture provides a methodology, set of practices, template, and standards based on a set of successful solutions implemented earlier. These solutions have been generalized and structured for the depiction of both a logical and a physical architecture, based on the harvesting of a set of patterns that describe observations in a number of successful implementations. It helps as a reference for the various architectures that an enterprise can implement to solve various problems. It can be used as the starting point or the point of comparisons for various departments/business entities of a company, or for the various companies for an enterprise. It provides multiple views for multiple stakeholders.   Major artifacts of the Enterprise Reference Architecture are methodologies, standards, metadata, documents, design patterns, etc.   Purpose of Reference Architecture   In most cases, architects spend a lot of time researching, investigating, defining, and re-arguing architectural decisions. It is like reinventing the wheel as their peers in other organizations or even the same organization have already spent a lot of time and effort defining their own architectural practices. This prevents an organization from learning from its own experiences and applying that knowledge for increased effectiveness.   Reference architecture provides missing architectural information that can be provided in advance to project team members to enable consistent architectural best practices.   Enterprise Reference Architecture helps an enterprise to achieve the following at the abstract level:   ·       Reference architecture is more of a communication channel to an enterprise ·       Helps the business owners to accommodate to their strategies, vision, objectives, and principles. ·       Evaluates the IT systems based on Reference Architecture Principles ·       Reduces IT spending through increasing functionality, availability, scalability, etc ·       A Real-time Integration Model helps to reduce the latency of the data updates Is used to define a single source of Information ·       Provides a clear view on how to manage information and security ·       Defines the policy around the data ownership, product boundaries, etc. ·       Helps with cost optimization across project and solution portfolios by eliminating unused or duplicate investments and assets ·       Has a shorter implementation time and cost   Once the reference architecture is in place, the set of architectural principles, standards, reference models, and best practices ensure that the aligned investments have the greatest possible likelihood of success in both the near term and the long term (TCO).     Common pitfalls for Telecom Service Providers   Telecom Reference Architecture serves as the first step towards maturity for a telecom service provider. During the course of our assignments/experiences with telecom players, we have come across the following observations – Some of these indicate a lack of maturity of the telecom service provider:   ·       In markets that are growing and not so mature, it has been observed that telcos have a significant amount of in-house or home-grown applications. In some of these markets, the growth has been so rapid that IT has been unable to cope with business demands. Telcos have shown a tendency to come up with workarounds in their IT applications so as to meet business needs. ·       Even for core functions like provisioning or mediation, some telcos have tried to manage with home-grown applications. ·       Most of the applications do not have the required scalability or maintainability to sustain growth in volumes or functionality. ·       Applications face interoperability issues with other applications in the operator's landscape. Integrating a new application or network element requires considerable effort on the part of the other applications. ·       Application boundaries are not clear, and functionality that is not in the initial scope of that application gets pushed onto it. This results in the development of the multiple, small applications without proper boundaries. ·       Usage of Legacy OSS/BSS systems, poor Integration across Multiple COTS Products and Internal Systems. Most of the Integrations are developed on ad-hoc basis and Point-to-Point Integration. ·       Redundancy of the business functions in different applications • Fragmented data across the different applications and no integrated view of the strategic data • Lot of performance Issues due to the usage of the complex integration across OSS and BSS systems   However, this is where the maturity of the telecom industry as a whole can be of help. The collaborative efforts of telcos to overcome some of these problems have resulted in bodies like the TM Forum. They have come up with frameworks for business processes, data, applications, and technology for telecom service providers. These could be a good starting point for telcos to clean up their enterprise landscape.   Industry Trends in Telecom Reference Architecture   Telecom reference architectures are evolving rapidly because telcos are facing business and IT challenges.   “The reality is that there probably is no killer application, no silver bullet that the telcos can latch onto to carry them into a 21st Century.... Instead, there are probably hundreds – perhaps thousands – of niche applications.... And the only way to find which of these works for you is to try out lots of them, ramp up the ones that work, and discontinue the ones that fail.” – Martin Creaner President & CTO TM Forum.   The following trends have been observed in telecom reference architecture:   ·       Transformation of business structures to align with customer requirements ·       Adoption of more Internet-like technical architectures. The Web 2.0 concept is increasingly being used. ·       Virtualization of the traditional operations support system (OSS) ·       Adoption of SOA to support development of IP-based services ·       Adoption of frameworks like Service Delivery Platforms (SDPs) and IP Multimedia Subsystem ·       (IMS) to enable seamless deployment of various services over fixed and mobile networks ·       Replacement of in-house, customized, and stove-piped OSS/BSS with standards-based COTS products ·       Compliance with industry standards and frameworks like eTOM, SID, and TAM to enable seamless integration with other standards-based products   Drivers of Reference Architecture   The drivers of the Reference Architecture are Reference Architecture Goals, Principles, and Enterprise Vision and Telecom Transformation. The details are depicted below diagram. @font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoCaption, li.MsoCaption, div.MsoCaption { margin: 0cm 0cm 10pt; font-size: 9pt; font-family: "Times New Roman"; color: rgb(79, 129, 189); font-weight: bold; }div.Section1 { page: Section1; } Figure 1. Drivers for Reference Architecture @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpFirst, li.MsoListParagraphCxSpFirst, div.MsoListParagraphCxSpFirst { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpMiddle, li.MsoListParagraphCxSpMiddle, div.MsoListParagraphCxSpMiddle { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpLast, li.MsoListParagraphCxSpLast, div.MsoListParagraphCxSpLast { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Today’s telecom reference architectures should seamlessly integrate traditional legacy-based applications and transition to next-generation network technologies (e.g., IP multimedia subsystems). This has resulted in new requirements for flexible, real-time billing and OSS/BSS systems and implications on the service provider’s organizational requirements and structure.   Telecom reference architectures are today expected to:   ·       Integrate voice, messaging, email and other VAS over fixed and mobile networks, back end systems ·       Be able to provision multiple services and service bundles • Deliver converged voice, video and data services ·       Leverage the existing Network Infrastructure ·       Provide real-time, flexible billing and charging systems to handle complex promotions, discounts, and settlements with multiple parties. ·       Support charging of advanced data services such as VoIP, On-Demand, Services (e.g.  Video), IMS/SIP Services, Mobile Money, Content Services and IPTV. ·       Help in faster deployment of new services • Serve as an effective platform for collaboration between network IT and business organizations ·       Harness the potential of converging technology, networks, devices and content to develop multimedia services and solutions of ever-increasing sophistication on a single Internet Protocol (IP) ·       Ensure better service delivery and zero revenue leakage through real-time balance and credit management ·       Lower operating costs to drive profitability   Enterprise Reference Architecture   The Enterprise Reference Architecture (RA) fills the gap between the concepts and vocabulary defined by the reference model and the implementation. Reference architecture provides detailed architectural information in a common format such that solutions can be repeatedly designed and deployed in a consistent, high-quality, supportable fashion. This paper attempts to describe the Reference Architecture for the Telecom Application Usage and how to achieve the Enterprise Level Reference Architecture using SOA.   • Telecom Reference Architecture • Enterprise SOA based Reference Architecture   Telecom Reference Architecture   Tele Management Forum’s New Generation Operations Systems and Software (NGOSS) is an architectural framework for organizing, integrating, and implementing telecom systems. NGOSS is a component-based framework consisting of the following elements:   ·       The enhanced Telecom Operations Map (eTOM) is a business process framework. ·       The Shared Information Data (SID) model provides a comprehensive information framework that may be specialized for the needs of a particular organization. ·       The Telecom Application Map (TAM) is an application framework to depict the functional footprint of applications, relative to the horizontal processes within eTOM. ·       The Technology Neutral Architecture (TNA) is an integrated framework. TNA is an architecture that is sustainable through technology changes.   NGOSS Architecture Standards are:   ·       Centralized data ·       Loosely coupled distributed systems ·       Application components/re-use  ·       A technology-neutral system framework with technology specific implementations ·       Interoperability to service provider data/processes ·       Allows more re-use of business components across multiple business scenarios ·       Workflow automation   The traditional operator systems architecture consists of four layers,   ·       Business Support System (BSS) layer, with focus toward customers and business partners. Manages order, subscriber, pricing, rating, and billing information. ·       Operations Support System (OSS) layer, built around product, service, and resource inventories. ·       Networks layer – consists of Network elements and 3rd Party Systems. ·       Integration Layer – to maximize application communication and overall solution flexibility.   Reference architecture for telecom enterprises is depicted below. @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoCaption, li.MsoCaption, div.MsoCaption { margin: 0cm 0cm 10pt; font-size: 9pt; font-family: "Times New Roman"; color: rgb(79, 129, 189); font-weight: bold; }p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpFirst, li.MsoListParagraphCxSpFirst, div.MsoListParagraphCxSpFirst { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpMiddle, li.MsoListParagraphCxSpMiddle, div.MsoListParagraphCxSpMiddle { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpLast, li.MsoListParagraphCxSpLast, div.MsoListParagraphCxSpLast { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Figure 2. Telecom Reference Architecture   The major building blocks of any Telecom Service Provider architecture are as follows:   1. Customer Relationship Management   CRM encompasses the end-to-end lifecycle of the customer: customer initiation/acquisition, sales, ordering, and service activation, customer care and support, proactive campaigns, cross sell/up sell, and retention/loyalty.   CRM also includes the collection of customer information and its application to personalize, customize, and integrate delivery of service to a customer, as well as to identify opportunities for increasing the value of the customer to the enterprise.   The key functionalities related to Customer Relationship Management are   ·       Manage the end-to-end lifecycle of a customer request for products. ·       Create and manage customer profiles. ·       Manage all interactions with customers – inquiries, requests, and responses. ·       Provide updates to Billing and other south bound systems on customer/account related updates such as customer/ account creation, deletion, modification, request bills, final bill, duplicate bills, credit limits through Middleware. ·       Work with Order Management System, Product, and Service Management components within CRM. ·       Manage customer preferences – Involve all the touch points and channels to the customer, including contact center, retail stores, dealers, self service, and field service, as well as via any media (phone, face to face, web, mobile device, chat, email, SMS, mail, the customer's bill, etc.). ·       Support single interface for customer contact details, preferences, account details, offers, customer premise equipment, bill details, bill cycle details, and customer interactions.   CRM applications interact with customers through customer touch points like portals, point-of-sale terminals, interactive voice response systems, etc. The requests by customers are sent via fulfillment/provisioning to billing system for ordering processing.   2. Billing and Revenue Management   Billing and Revenue Management handles the collection of appropriate usage records and production of timely and accurate bills – for providing pre-bill usage information and billing to customers; for processing their payments; and for performing payment collections. In addition, it handles customer inquiries about bills, provides billing inquiry status, and is responsible for resolving billing problems to the customer's satisfaction in a timely manner. This process grouping also supports prepayment for services.   The key functionalities provided by these applications are   ·       To ensure that enterprise revenue is billed and invoices delivered appropriately to customers. ·       To manage customers’ billing accounts, process their payments, perform payment collections, and monitor the status of the account balance. ·       To ensure the timely and effective fulfillment of all customer bill inquiries and complaints. ·       Collect the usage records from mediation and ensure appropriate rating and discounting of all usage and pricing. ·       Support revenue sharing; split charging where usage is guided to an account different from the service consumer. ·       Support prepaid and post-paid rating. ·       Send notification on approach / exceeding the usage thresholds as enforced by the subscribed offer, and / or as setup by the customer. ·       Support prepaid, post paid, and hybrid (where some services are prepaid and the rest of the services post paid) customers and conversion from post paid to prepaid, and vice versa. ·       Support different billing function requirements like charge prorating, promotion, discount, adjustment, waiver, write-off, account receivable, GL Interface, late payment fee, credit control, dunning, account or service suspension, re-activation, expiry, termination, contract violation penalty, etc. ·       Initiate direct debit to collect payment against an invoice outstanding. ·       Send notification to Middleware on different events; for example, payment receipt, pre-suspension, threshold exceed, etc.   Billing systems typically get usage data from mediation systems for rating and billing. They get provisioning requests from order management systems and inquiries from CRM systems. Convergent and real-time billing systems can directly get usage details from network elements.   3. Mediation   Mediation systems transform/translate the Raw or Native Usage Data Records into a general format that is acceptable to billing for their rating purposes.   The following lists the high-level roles and responsibilities executed by the Mediation system in the end-to-end solution.   ·       Collect Usage Data Records from different data sources – like network elements, routers, servers – via different protocol and interfaces. ·       Process Usage Data Records – Mediation will process Usage Data Records as per the source format. ·       Validate Usage Data Records from each source. ·       Segregates Usage Data Records coming from each source to multiple, based on the segregation requirement of end Application. ·       Aggregates Usage Data Records based on the aggregation rule if any from different sources. ·       Consolidates multiple Usage Data Records from each source. ·       Delivers formatted Usage Data Records to different end application like Billing, Interconnect, Fraud Management, etc. ·       Generates audit trail for incoming Usage Data Records and keeps track of all the Usage Data Records at various stages of mediation process. ·       Checks duplicate Usage Data Records across files for a given time window.   4. Fulfillment   This area is responsible for providing customers with their requested products in a timely and correct manner. It translates the customer's business or personal need into a solution that can be delivered using the specific products in the enterprise's portfolio. This process informs the customers of the status of their purchase order, and ensures completion on time, as well as ensuring a delighted customer. These processes are responsible for accepting and issuing orders. They deal with pre-order feasibility determination, credit authorization, order issuance, order status and tracking, customer update on customer order activities, and customer notification on order completion. Order management and provisioning applications fall into this category.   The key functionalities provided by these applications are   ·       Issuing new customer orders, modifying open customer orders, or canceling open customer orders; ·       Verifying whether specific non-standard offerings sought by customers are feasible and supportable; ·       Checking the credit worthiness of customers as part of the customer order process; ·       Testing the completed offering to ensure it is working correctly; ·       Updating of the Customer Inventory Database to reflect that the specific product offering has been allocated, modified, or cancelled; ·       Assigning and tracking customer provisioning activities; ·       Managing customer provisioning jeopardy conditions; and ·       Reporting progress on customer orders and other processes to customer.   These applications typically get orders from CRM systems. They interact with network elements and billing systems for fulfillment of orders.   5. Enterprise Management   This process area includes those processes that manage enterprise-wide activities and needs, or have application within the enterprise as a whole. They encompass all business management processes that   ·       Are necessary to support the whole of the enterprise, including processes for financial management, legal management, regulatory management, process, cost, and quality management, etc.;   ·       Are responsible for setting corporate policies, strategies, and directions, and for providing guidelines and targets for the whole of the business, including strategy development and planning for areas, such as Enterprise Architecture, that are integral to the direction and development of the business;   ·       Occur throughout the enterprise, including processes for project management, performance assessments, cost assessments, etc.     (i) Enterprise Risk Management:   Enterprise Risk Management focuses on assuring that risks and threats to the enterprise value and/or reputation are identified, and appropriate controls are in place to minimize or eliminate the identified risks. The identified risks may be physical or logical/virtual. Successful risk management ensures that the enterprise can support its mission critical operations, processes, applications, and communications in the face of serious incidents such as security threats/violations and fraud attempts. Two key areas covered in Risk Management by telecom operators are:   ·       Revenue Assurance: Revenue assurance system will be responsible for identifying revenue loss scenarios across components/systems, and will help in rectifying the problems. The following lists the high-level roles and responsibilities executed by the Revenue Assurance system in the end-to-end solution. o   Identify all usage information dropped when networks are being upgraded. o   Interconnect bill verification. o   Identify where services are routinely provisioned but never billed. o   Identify poor sales policies that are intensifying collections problems. o   Find leakage where usage is sent to error bucket and never billed for. o   Find leakage where field service, CRM, and network build-out are not optimized.   ·       Fraud Management: Involves collecting data from different systems to identify abnormalities in traffic patterns, usage patterns, and subscription patterns to report suspicious activity that might suggest fraudulent usage of resources, resulting in revenue losses to the operator.   The key roles and responsibilities of the system component are as follows:   o   Fraud management system will capture and monitor high usage (over a certain threshold) in terms of duration, value, and number of calls for each subscriber. The threshold for each subscriber is decided by the system and fixed automatically. o   Fraud management will be able to detect the unauthorized access to services for certain subscribers. These subscribers may have been provided unauthorized services by employees. The component will raise the alert to the operator the very first time of such illegal calls or calls which are not billed. o   The solution will be to have an alarm management system that will deliver alarms to the operator/provider whenever it detects a fraud, thus minimizing fraud by catching it the first time it occurs. o   The Fraud Management system will be capable of interfacing with switches, mediation systems, and billing systems   (ii) Knowledge Management   This process focuses on knowledge management, technology research within the enterprise, and the evaluation of potential technology acquisitions.   Key responsibilities of knowledge base management are to   ·       Maintain knowledge base – Creation and updating of knowledge base on ongoing basis. ·       Search knowledge base – Search of knowledge base on keywords or category browse ·       Maintain metadata – Management of metadata on knowledge base to ensure effective management and search. ·       Run report generator. ·       Provide content – Add content to the knowledge base, e.g., user guides, operational manual, etc.   (iii) Document Management   It focuses on maintaining a repository of all electronic documents or images of paper documents relevant to the enterprise using a system.   (iv) Data Management   It manages data as a valuable resource for any enterprise. For telecom enterprises, the typical areas covered are Master Data Management, Data Warehousing, and Business Intelligence. It is also responsible for data governance, security, quality, and database management.   Key responsibilities of Data Management are   ·       Using ETL, extract the data from CRM, Billing, web content, ERP, campaign management, financial, network operations, asset management info, customer contact data, customer measures, benchmarks, process data, e.g., process inputs, outputs, and measures, into Enterprise Data Warehouse. ·       Management of data traceability with source, data related business rules/decisions, data quality, data cleansing data reconciliation, competitors data – storage for all the enterprise data (customer profiles, products, offers, revenues, etc.) ·       Get online update through night time replication or physical backup process at regular frequency. ·       Provide the data access to business intelligence and other systems for their analysis, report generation, and use.   (v) Business Intelligence   It uses the Enterprise Data to provide the various analysis and reports that contain prospects and analytics for customer retention, acquisition of new customers due to the offers, and SLAs. It will generate right and optimized plans – bolt-ons for the customers.   The following lists the high-level roles and responsibilities executed by the Business Intelligence system at the Enterprise Level:   ·       It will do Pattern analysis and reports problem. ·       It will do Data Analysis – Statistical analysis, data profiling, affinity analysis of data, customer segment wise usage patterns on offers, products, service and revenue generation against services and customer segments. ·       It will do Performance (business, system, and forecast) analysis, churn propensity, response time, and SLAs analysis. ·       It will support for online and offline analysis, and report drill down capability. ·       It will collect, store, and report various SLA data. ·       It will provide the necessary intelligence for marketing and working on campaigns, etc., with cost benefit analysis and predictions.   It will advise on customer promotions with additional services based on loyalty and credit history of customer   ·       It will Interface with Enterprise Data Management system for data to run reports and analysis tasks. It will interface with the campaign schedules, based on historical success evidence.   (vi) Stakeholder and External Relations Management   It manages the enterprise's relationship with stakeholders and outside entities. Stakeholders include shareholders, employee organizations, etc. Outside entities include regulators, local community, and unions. Some of the processes within this grouping are Shareholder Relations, External Affairs, Labor Relations, and Public Relations.   (vii) Enterprise Resource Planning   It is used to manage internal and external resources, including tangible assets, financial resources, materials, and human resources. Its purpose is to facilitate the flow of information between all business functions inside the boundaries of the enterprise and manage the connections to outside stakeholders. ERP systems consolidate all business operations into a uniform and enterprise wide system environment.   The key roles and responsibilities for Enterprise System are given below:   ·        It will handle responsibilities such as core accounting, financial, and management reporting. ·       It will interface with CRM for capturing customer account and details. ·       It will interface with billing to capture the billing revenue and other financial data. ·       It will be responsible for executing the dunning process. Billing will send the required feed to ERP for execution of dunning. ·       It will interface with the CRM and Billing through batch interfaces. Enterprise management systems are like horizontals in the enterprise and typically interact with all major telecom systems. E.g., an ERP system interacts with CRM, Fulfillment, and Billing systems for different kinds of data exchanges.   6. External Interfaces/Touch Points   The typical external parties are customers, suppliers/partners, employees, shareholders, and other stakeholders. External interactions from/to a Service Provider to other parties can be achieved by a variety of mechanisms, including:   ·       Exchange of emails or faxes ·       Call Centers ·       Web Portals ·       Business-to-Business (B2B) automated transactions   These applications provide an Internet technology driven interface to external parties to undertake a variety of business functions directly for themselves. These can provide fully or partially automated service to external parties through various touch points.   Typical characteristics of these touch points are   ·       Pre-integrated self-service system, including stand-alone web framework or integration front end with a portal engine ·       Self services layer exposing atomic web services/APIs for reuse by multiple systems across the architectural environment ·       Portlets driven connectivity exposing data and services interoperability through a portal engine or web application   These touch points mostly interact with the CRM systems for requests, inquiries, and responses.   7. Middleware   The component will be primarily responsible for integrating the different systems components under a common platform. It should provide a Standards-Based Platform for building Service Oriented Architecture and Composite Applications. The following lists the high-level roles and responsibilities executed by the Middleware component in the end-to-end solution.   ·       As an integration framework, covering to and fro interfaces ·       Provide a web service framework with service registry. ·       Support SOA framework with SOA service registry. ·       Each of the interfaces from / to Middleware to other components would handle data transformation, translation, and mapping of data points. ·       Receive data from the caller / activate and/or forward the data to the recipient system in XML format. ·       Use standard XML for data exchange. ·       Provide the response back to the service/call initiator. ·       Provide a tracking until the response completion. ·       Keep a store transitional data against each call/transaction. ·       Interface through Middleware to get any information that is possible and allowed from the existing systems to enterprise systems; e.g., customer profile and customer history, etc. ·       Provide the data in a common unified format to the SOA calls across systems, and follow the Enterprise Architecture directive. ·       Provide an audit trail for all transactions being handled by the component.   8. Network Elements   The term Network Element means a facility or equipment used in the provision of a telecommunications service. Such terms also includes features, functions, and capabilities that are provided by means of such facility or equipment, including subscriber numbers, databases, signaling systems, and information sufficient for billing and collection or used in the transmission, routing, or other provision of a telecommunications service.   Typical network elements in a GSM network are Home Location Register (HLR), Intelligent Network (IN), Mobile Switching Center (MSC), SMS Center (SMSC), and network elements for other value added services like Push-to-talk (PTT), Ring Back Tone (RBT), etc.   Network elements are invoked when subscribers use their telecom devices for any kind of usage. These elements generate usage data and pass it on to downstream systems like mediation and billing system for rating and billing. They also integrate with provisioning systems for order/service fulfillment.   9. 3rd Party Applications   3rd Party systems are applications like content providers, payment gateways, point of sale terminals, and databases/applications maintained by the Government.   Depending on applicability and the type of functionality provided by 3rd party applications, the integration with different telecom systems like CRM, provisioning, and billing will be done.   10. Service Delivery Platform   A service delivery platform (SDP) provides the architecture for the rapid deployment, provisioning, execution, management, and billing of value added telecom services. SDPs are based on the concept of SOA and layered architecture. They support the delivery of voice, data services, and content in network and device-independent fashion. They allow application developers to aggregate network capabilities, services, and sources of content. SDPs typically contain layers for web services exposure, service application development, and network abstraction.   SOA Reference Architecture   SOA concept is based on the principle of developing reusable business service and building applications by composing those services, instead of building monolithic applications in silos. It’s about bridging the gap between business and IT through a set of business-aligned IT services, using a set of design principles, patterns, and techniques.   In an SOA, resources are made available to participants in a value net, enterprise, line of business (typically spanning multiple applications within an enterprise or across multiple enterprises). It consists of a set of business-aligned IT services that collectively fulfill an organization’s business processes and goals. We can choreograph these services into composite applications and invoke them through standard protocols. SOA, apart from agility and reusability, enables:   ·       The business to specify processes as orchestrations of reusable services ·       Technology agnostic business design, with technology hidden behind service interface ·       A contractual-like interaction between business and IT, based on service SLAs ·       Accountability and governance, better aligned to business services ·       Applications interconnections untangling by allowing access only through service interfaces, reducing the daunting side effects of change ·       Reduced pressure to replace legacy and extended lifetime for legacy applications, through encapsulation in services   ·       A Cloud Computing paradigm, using web services technologies, that makes possible service outsourcing on an on-demand, utility-like, pay-per-usage basis   The following section represents the Reference Architecture of logical view for the Telecom Solution. The new custom built application needs to align with this logical architecture in the long run to achieve EA benefits.   Packaged implementation applications, such as ERP billing applications, need to expose their functions as service providers (as other applications consume) and interact with other applications as service consumers.   COT applications need to expose services through wrappers such as adapters to utilize existing resources and at the same time achieve Enterprise Architecture goal and objectives.   The following are the various layers for Enterprise level deployment of SOA. This diagram captures the abstract view of Enterprise SOA layers and important components of each layer. Layered architecture means decomposition of services such that most interactions occur between adjacent layers. However, there is no strict rule that top layers should not directly communicate with bottom layers.   The diagram below represents the important logical pieces that would result from overall SOA transformation. @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoCaption, li.MsoCaption, div.MsoCaption { margin: 0cm 0cm 10pt; font-size: 9pt; font-family: "Times New Roman"; color: rgb(79, 129, 189); font-weight: bold; }p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpFirst, li.MsoListParagraphCxSpFirst, div.MsoListParagraphCxSpFirst { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpMiddle, li.MsoListParagraphCxSpMiddle, div.MsoListParagraphCxSpMiddle { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpLast, li.MsoListParagraphCxSpLast, div.MsoListParagraphCxSpLast { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Figure 3. Enterprise SOA Reference Architecture 1.          Operational System Layer: This layer consists of all packaged applications like CRM, ERP, custom built applications, COTS based applications like Billing, Revenue Management, Fulfilment, and the Enterprise databases that are essential and contribute directly or indirectly to the Enterprise OSS/BSS Transformation.   ERP holds the data of Asset Lifecycle Management, Supply Chain, and Advanced Procurement and Human Capital Management, etc.   CRM holds the data related to Order, Sales, and Marketing, Customer Care, Partner Relationship Management, Loyalty, etc.   Content Management handles Enterprise Search and Query. Billing application consists of the following components:   ·       Collections Management, Customer Billing Management, Invoices, Real-Time Rating, Discounting, and Applying of Charges ·       Enterprise databases will hold both the application and service data, whether structured or unstructured.   MDM - Master data majorly consists of Customer, Order, Product, and Service Data.     2.          Enterprise Component Layer:   This layer consists of the Application Services and Common Services that are responsible for realizing the functionality and maintaining the QoS of the exposed services. This layer uses container-based technologies such as application servers to implement the components, workload management, high availability, and load balancing.   Application Services: This Service Layer enables application, technology, and database abstraction so that the complex accessing logic is hidden from the other service layers. This is a basic service layer, which exposes application functionalities and data as reusable services. The three types of the Application access services are:   ·       Application Access Service: This Service Layer exposes application level functionalities as a reusable service between BSS to BSS and BSS to OSS integration. This layer is enabled using disparate technology such as Web Service, Integration Servers, and Adaptors, etc.   ·       Data Access Service: This Service Layer exposes application data services as a reusable reference data service. This is done via direct interaction with application data. and provides the federated query.   ·       Network Access Service: This Service Layer exposes provisioning layer as a reusable service from OSS to OSS integration. This integration service emphasizes the need for high performance, stateless process flows, and distributed design.   Common Services encompasses management of structured, semi-structured, and unstructured data such as information services, portal services, interaction services, infrastructure services, and security services, etc.   3.          Integration Layer:   This consists of service infrastructure components like service bus, service gateway for partner integration, service registry, service repository, and BPEL processor. Service bus will carry the service invocation payloads/messages between consumers and providers. The other important functions expected from it are itinerary based routing, distributed caching of routing information, transformations, and all qualities of service for messaging-like reliability, scalability, and availability, etc. Service registry will hold all contracts (wsdl) of services, and it helps developers to locate or discover service during design time or runtime.   • BPEL processor would be useful in orchestrating the services to compose a complex business scenario or process. • Workflow and business rules management are also required to support manual triggering of certain activities within business process. based on the rules setup and also the state machine information. Application, data, and service mediation layer typically forms the overall composite application development framework or SOA Framework.   4.          Business Process Layer: These are typically the intermediate services layer and represent Shared Business Process Services. At Enterprise Level, these services are from Customer Management, Order Management, Billing, Finance, and Asset Management application domains.   5.          Access Layer: This layer consists of portals for Enterprise and provides a single view of Enterprise information management and dashboard services.   6.          Channel Layer: This consists of various devices; applications that form part of extended enterprise; browsers through which users access the applications.   7.          Client Layer: This designates the different types of users accessing the enterprise applications. The type of user typically would be an important factor in determining the level of access to applications.   8.          Vertical pieces like management, monitoring, security, and development cut across all horizontal layers Management and monitoring involves all aspects of SOA-like services, SLAs, and other QoS lifecycle processes for both applications and services surrounding SOA governance.     9.          EA Governance, Reference Architecture, Roadmap, Principles, and Best Practices:   EA Governance is important in terms of providing the overall direction to SOA implementation within the enterprise. This involves board-level involvement, in addition to business and IT executives. At a high level, this involves managing the SOA projects implementation, managing SOA infrastructure, and controlling the entire effort through all fine-tuned IT processes in accordance with COBIT (Control Objectives for Information Technology).   Devising tools and techniques to promote reuse culture, and the SOA way of doing things needs competency centers to be established in addition to training the workforce to take up new roles that are suited to SOA journey.   Conclusions   Reference Architectures can serve as the basis for disparate architecture efforts throughout the organization, even if they use different tools and technologies. Reference architectures provide best practices and approaches in the independent way a vendor deals with technology and standards. Reference Architectures model the abstract architectural elements for an enterprise independent of the technologies, protocols, and products that are used to implement an SOA. Telecom enterprises today are facing significant business and technology challenges due to growing competition, a multitude of services, and convergence. Adopting architectural best practices could go a long way in meeting these challenges. The use of SOA-based architecture for communication to each of the external systems like Billing, CRM, etc., in OSS/BSS system has made the architecture very loosely coupled, with greater flexibility. Any change in the external systems would be absorbed at the Integration Layer without affecting the rest of the ecosystem. The use of a Business Process Management (BPM) tool makes the management and maintenance of the business processes easy, with better performance in terms of lead time, quality, and cost. Since the Architecture is based on standards, it will lower the cost of deploying and managing OSS/BSS applications over their lifecycles.

    Read the article

  • Unable to ping local machines by name in Windows 7

    - by aardvarkk
    I'm having a strange (and persistent!) problem with pinging local machines on my network by name. I believe my machine (Windows 7 64-bit) is the only one having this issue. This is over a wireless connection. As an example, consider a device on my network by the name of WDTVLiveHub. It's a Western Digital Live Hub (surprise!). If I go to my router's DHCP Client Table in the browser (my router is a WRT400N), I see this entry: WDTVLiveHub 192.168.1.101 Great. So I try to ping that IP address: ping 192.168.1.101 Pinging 192.168.1.101 with 32 bytes of data: Reply from 192.168.1.101: bytes=32 time=9ms TTL=64 Reply from 192.168.1.101: bytes=32 time=16ms TTL=64 Reply from 192.168.1.101: bytes=32 time=16ms TTL=64 Reply from 192.168.1.101: bytes=32 time=16ms TTL=64 Ping statistics for 192.168.1.101: Packets: Sent = 4, Received = 4, Lost = 0 (0% loss), Approximate round trip times in milli-seconds: Minimum = 9ms, Maximum = 16ms, Average = 14ms OK, still looking good. Now I try to ping it by name: ping WDTVLiveHub Ping request could not find host WDTVLiveHub. Please check the name and try again. From what I've read, this implies a problem with DNS servers and host name lookups. Interestingly, if I type the following: pathping 192.168.1.101 I get this output: Tracing route to WDTVLIVEHUB [192.168.1.101] over a maximum of 30 hops: 0 Scotty [192.168.1.103] 1 WDTVLIVEHUB [192.168.1.101] Computing statistics for 25 seconds... Source to Here This Node/Link Hop RTT Lost/Sent = Pct Lost/Sent = Pct Address 0 Scotty [192.168.1.103] 1/ 100 = 1% | 1 12ms 1/ 100 = 1% 0/ 100 = 0% WDTVLIVEHUB [192.168.1.101] Trace complete. Scotty is obviously the name of my local machine. So it's able to find the name somehow when I do that approach... ipconfig /all shows the following under DNS servers: DNS Servers . . . . . . . . . . . : 192.168.1.1 ***.***.***.*** ***.***.***.*** Where the * represents the same DNS servers that show up in my router under DNS 1 and DNS 2 through the Internet. For completeness, here's the whole output of ipconfig /all: Windows IP Configuration Host Name . . . . . . . . . . . . : Scotty Primary Dns Suffix . . . . . . . : Node Type . . . . . . . . . . . . : Peer-Peer IP Routing Enabled. . . . . . . . : No WINS Proxy Enabled. . . . . . . . : No Wireless LAN adapter Wireless Network Connection: Connection-specific DNS Suffix . : Description . . . . . . . . . . . : Dell Wireless 1397 WLAN Mini-Card Physical Address. . . . . . . . . : 0C-EE-E6-D1-07-E8 DHCP Enabled. . . . . . . . . . . : Yes Autoconfiguration Enabled . . . . : Yes IPv6 Address. . . . . . . . . . . : 2002:d83a:31e5:1234:5592:398e:8968:43d1(Preferred) Temporary IPv6 Address. . . . . . : 2002:d83a:31e5:1234:ecce:2f79:72a5:5273(Preferred) Link-local IPv6 Address . . . . . : fe80::5592:398e:8968:43d1%26(Preferred) IPv4 Address. . . . . . . . . . . : 192.168.1.103(Preferred) Subnet Mask . . . . . . . . . . . : 255.255.255.0 Lease Obtained. . . . . . . . . . : September-17-12 11:05:57 PM Lease Expires . . . . . . . . . . : September-18-12 11:05:57 PM Default Gateway . . . . . . . . . : fe80::200:ff:fe00:0%26 192.168.1.1 DHCP Server . . . . . . . . . . . : 192.168.1.1 DHCPv6 IAID . . . . . . . . . . . : 537718502 DHCPv6 Client DUID. . . . . . . . : 00-01-00-01-12-80-3D-D7-00-26-B9-0D-08-70 DNS Servers . . . . . . . . . . . : 192.168.1.1 ***.***.***.*** ***.***.***.*** NetBIOS over Tcpip. . . . . . . . : Enabled Ethernet adapter VirtualBox Host-Only Network: Connection-specific DNS Suffix . : Description . . . . . . . . . . . : VirtualBox Host-Only Ethernet Adapter Physical Address. . . . . . . . . : 08-00-27-00-98-9A DHCP Enabled. . . . . . . . . . . : Yes Autoconfiguration Enabled . . . . : Yes Link-local IPv6 Address . . . . . : fe80::b48a:916b:c0f:fb29%23(Preferred) Autoconfiguration IPv4 Address. . : 169.254.251.41(Preferred) Subnet Mask . . . . . . . . . . . : 255.255.0.0 Default Gateway . . . . . . . . . : DHCPv6 IAID . . . . . . . . . . . : 570949671 DHCPv6 Client DUID. . . . . . . . : 00-01-00-01-12-80-3D-D7-00-26-B9-0D-08-70 DNS Servers . . . . . . . . . . . : fec0:0:0:ffff::1%1 fec0:0:0:ffff::2%1 fec0:0:0:ffff::3%1 NetBIOS over Tcpip. . . . . . . . : Enabled Tunnel adapter Local Area Connection* 15: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Description . . . . . . . . . . . : Teredo Tunneling Pseudo-Interface Physical Address. . . . . . . . . : 00-00-00-00-00-00-00-E0 DHCP Enabled. . . . . . . . . . . : No Autoconfiguration Enabled . . . . : Yes Tunnel adapter isatap.{55899375-C31D-4173-A529-4427D63FD28B}: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Description . . . . . . . . . . . : Microsoft ISATAP Adapter #2 Physical Address. . . . . . . . . : 00-00-00-00-00-00-00-E0 DHCP Enabled. . . . . . . . . . . : No Autoconfiguration Enabled . . . . : Yes Tunnel adapter isatap.{64B8F35F-A6AB-4D6B-B1D5-DD95F57B1458}: Media State . . . . . . . . . . . : Media disconnected Connection-specific DNS Suffix . : Description . . . . . . . . . . . : Microsoft ISATAP Adapter #3 Physical Address. . . . . . . . . : 00-00-00-00-00-00-00-E0 DHCP Enabled. . . . . . . . . . . : No Autoconfiguration Enabled . . . . : Yes Not sure exactly how to diagnose exactly what's going on... but the problem is really frustrating! The biggest problem is that my mapped network drives have to be done by IP, and then any time the router assigns new IP addresses to those devices, all of my network shares break again. Stinks! Would love some assistance on possible solutions. I've tried all of this netsh catalog resetting and that didn't seem to fix anything at all. Would love an explanation of what's going wrong, too, rather than blindly resetting things! Thanks!

    Read the article

< Previous Page | 87 88 89 90 91