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• Customer Feature: "Know Who. Know How."

  Learn how Oracle CRM On Demand can help organizations find out more about their customers.

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• ????——???????????

  - by hamsun

  user12619775,2014?8?7? - ??:??????????? ??????????????????????????,???????????????????????????????????????? ???????? Managing Oracle Database on Oracle Solaris 11 Oracle Solaris 11 System Administration for Experienced UNIX/Linux Administrators Oracle Database 12c: RAC Administration Oracle Database 12c: Implement Partitioning Oracle WebCenter Portal 11g for Developers Oracle Hyperion PSPB 11.1.2: Create & Manage Applications (11.1.2.3) R12.x Oracle Financials Accounting Hub Fundamentals Oracle Demantra 7.3.1 Demand Management Fundamentals RPAS Administration and Configuration Fundamentals 14.0 PeopleSoft PeopleTools I Rel 8.53 (Training On Demand) ????education.oracle.com? ???Oracle??????

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• How do I stop Sophos anti virus from scanning directories that are under source control

  - by user26453

  From googling it seems its well known that SophosAV as well as other AV programs have issues with how they interact and can inhibit source control utilities like TortoiseHG or TortoiseSVN. One solution is to exclude directories under source control from on-access scanning as detailed here on Sophos's support site. There is a corollary article that mentions some issues related to this, namely the need to place multiple entries for exclusions based on the possibility of the location being accessed through the short vs. long name (e.g., Progra~1 vs. "Program Files"). One other twist is I am using a junction to relocate my user directory, C:\Users\Username, to a second hard drive, E:. Since I am not sure how this interacts I have included the source control directory as they are nested in both locations. As a result, I have included the two exclusions for the on-access scanning exclusions (and to be on the safe side on-demand exclusions as well, although this should only come into play when I select a parent directory of the exclusion to be scanned on-demand, but still). You'll notice I have no need to add extra exclusions for those locations based on short vs. long name distinctions. The two exclusion I have then, for both on-access and on-demand scanning exclusions are: C:\Users\Username\source-control-directory E:\source-control-directory However, this does not seem to work as TortoiseHG still lags terribly in response to any request as AV software starts scanning when the directory is accessed via TortoiseHG. I can verify without a doubt that Sophos is causing the problems: I can completely disable on-access scanning. Once this is done TortoiseHG responds very fast to all operations. I cannot leave this disabled obviously, but since the exclusion don't seem to be working, what next?

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• How to stop SophosAV from scanning directories under source control

  - by user26453

  From googling it seems its well known that SophosAV as well as other AV programs have issues with how they interact and can inhibit source control utilities like TortoiseHG or TortoiseSVN. One solution is to exclude directories under source control from on-access scanning as detailed here on Sophos's support site. There is a corollary article that mentions some issues related to this, namely need to place multiple entries for exclusions based on the possibility of the location being accessed through the short vs. long name (e.g., Progra~1 vs. "Program Files"). One other twist is I am using a junction to relocate my user directory, C:\Users\Username, to a second hard drive, E:. Since I am not sure how this interacts I have included the source control directory as they are nested in both locations. As a result, I have included the two exclusions for the on-access scanning exclusions (and to be on the safe side on-demand exclusions as well, although this should only come into play when I select a parent directory of the exclusion to be scanned on-demand, but still). You'll notice I have no need to add extra exclusions for those locations based on short vs. long name distinctions. The two exclusion I have then, for both on-access and on-demand scanning exclusions are: C:\Users\Username\source-control-directory E:\source-control-directory However, this does not seem to work as TortoiseHG still lags terribly in response to any request as AV software starts scanning when the directory is accessed via TortoiseHG. I can verify without a doubt that Sophos is causing the problems: I can completely disable on-access scanning. Once this is done TortoiseHG responds very fast to all operations. I cannot leave this disabled obviously, but since the exclusion don't seem to be working, what next?

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• Assistance on setup to Connect an offsite server to the LAN via RRAS VPN - Server 2008 R2

  - by Paul D'Ambra

  I have an office LAN protected using a Zyxel Zywall USG 300. I've set up an L2TP/ipsec VPN on that which accepts connections using a shared secret and I've tested this from multiple clients. I have a server offsite and want to set up RRAS to use a persistent connection to the VPN so that it can carry out network jobs even with no one logged in (I'm using it for Micorosft DPM secondary backup). If I create a vpn as if I were setting up a users laptop it can dial in no problem but if I set up a demand dial interface in RRAS it errors. I enable RRAS ticking only demand dial interface (branch office routing) Select network interfaces, right click and choose new demand dial interface Name the VPN ToCompany Select connect using VPN And then L2TP as the vpn type enter the IP address (double-checked for typos!) select Route IP packets on this interface specify static route to remote network as 10.0.0.0/24 with metric of 1 add dial out credentials (again double checked for typos and confirmed with other vpn connections click finish now I right-click on the new interface and choose properties and then the security tab I change Data encryption to optional select only PAP for Authentication (both as per manufacturer of Zywall) click advanced settings against type of vpn and set shared secret then I select the new interface, right-click and choose connect this dials and then errors with either 720 or 811 as the error codes. However, if I create a VPN by going to Network & Sharing center and setting up as if I was creating a VPN from my laptop to the office (say) it dials successfully so I know the VPN settings are correct and the machine can connect to the VPN. Suggests very strongly the problem is how I'm setting up RRAS. Can anyone help?

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• Need some help synch'ing outer loop counter with dialog.onconfirm()

  - by Chris Barnhill

  I am writing a game for Facebook. IN the following code, I have a problem. I have a for loop executing, and in that loop, I call a dialog and implement 'onconfirm' for the dialog. The problem is that I need to access th e loop counter inside of the onconfirm function. But because the onconfirm is called outside of the scope of the for loop, the counter value is no longer valid because it's been incremented. I need some way to pass the counter value to the dialog onconfirm as it was at the time the dialog was displayed, not after the loop has finished. Or maybe someone has a better solution. Any help would be appreciated. Thanks. function unloadCargo() { //debugger; var actionPrompt = document.getElementById('action-prompt'); actionPrompt.setTextValue('Unloading cargo...'); var ajax = new Ajax(); ajax.responseType = Ajax.JSON; ajax.ondone = function(data) { debugger; if(data.unloadableCargo.length == 0) { loadCargo(); } else { //console.log('unloadable cargo='+dump(data.unloadableCargo)); var i = 0; var j = 0; var ucCount = data.unloadableCargo.length; for(i = 0; i < ucCount; i++) { cargoDialog = new Dialog(); cargoDialog.showChoice('Unload Cargo', 'Unload ' + data.unloadableCargo[i].goods_name + ' at ' + data.unloadableCargo[i].city_name + ' for ' + data.unloadableCargo[i].payoff + 'M euros?'); cargoDialog.onconfirm = function() { //console.log('unloadable cargo onconfirm='+dump(data.unloadableCargo)); var ajax = new Ajax(); var param = {"city_id": data.unloadableCargo[i].city_id, "goods_id": data.unloadableCargo[i].goods_id, "payoff": data.unloadableCargo[i].payoff}; ajax.ondone = function(demandData) { var demands = document.getElementById('demands'); var innerXhtml = '<span>'; for(var j = 0; j < demandData.demands.length; j++) { innerXhtml = innerXhtml + ' <div class="demand-item"><div class="demand-city">' + demandData.demands[j].city + '</div><div class="demand-pay">' + demandData.demands[j].cost + '</div><div class="demand-goods">' + demandData.demands[j].goods + '</div></div>'; } innerXtml = innerXhtml + ' </span>'; demands.setInnerXHTML(innerXhtml); // update balance loadCargo(); } ajax.post(baseURL + "/turn/do-unload-cargo", param); } cargoDialog.oncancel = function() { loadCargo(); } } //loadCargo(); } } ajax.post(baseURL + '/turn/unload-cargo'); }

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• grails mockFor closure wierdness

  - by hvgotcodes

  Right, so when I set up my mock using the testing plugin's mockFor method, I expect a method that returns null. If I do myControl.demand.theMethod {return null} in the debugger, the value that I set the 'theMethod' call result to is some closure in the debugger. If I do myControl.demand.theMethod {->return null} the value is null, as expected. I dont understand the difference....

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• ESXI guests not using available CPU resources

  - by Alan M

  I have a VMWare ESXI 5.0.0 (it's a bit old, I know) host with three guest VMs on it. For reasons unknown, the guests will not use much of the availble CPU resources. I have all three guests in a single pool, with the hosts all configured to use the same amount of resource shares, so they're basically 33% each. The three guests are basically identically configured as far as their VM resources go. So the problem is, even when the guests are performing what should be very 'busy' activitites, such as at bootup, the actual host CPU consumed is something tiny, like 33mhz, when seen via vSphere console's "Virtual Machines" tab when viewing properties for the pool. And of course, the performance of the guest VMs is terrible. The host has plenty of CPU to spare. I've tried tinkering with individual guest VM resource settings; cranking up the reservation, etc. No matter. The guests just refuse to make use of the abundant CPU available to them, and insist on using a sliver of the available resources. Any suggestions? Update after reading various comments below Per the suggestions below, I did remove the guests from the application pool; this didn't make any difference. I do understand that the guests are not going to consume resources they do not need. I have tried to do a remote perfmon on the guest which is experiencing long boot times, but I cannot connect to the guest remotely with perfmon (guest is w2k8r2 server). Host graphs for CPU, Mem, Disk are basically flatlining; very little demand. Same is true for the guest stats; while the guest itself seems to be crawling, the guest resource graphing shows very little activity across CPU, Mem, Disk. Host is a Dell PowerEdge 2900, has 2 physical CPU,20gb RAM. (it's a test/dev environment using surplus gear) Guest1 has: VM ver. 7, 2vCPU, 4gb RAM, 140gb storage which lives on a RAID-5 array on the host. Guest2 has: VM ver. 7, 2vCPU, 4gb RAM, 140gb storage which lives on a RAID-5 array on the host. Guest3 has: VM ver. 7, 1vCPU, 2gb RAM, 2tb storage which lives on a RAID-5 ISCSI NAS box Perhaps I am making a false assumption that if a guest has a demand for CPU (e.g. Windows Task Manager shows 100% CPU), the host would supply the guest with more CPU (mem, disk) on demand. Another Update After checking the stats, it would appear that the host is indeed not busy at all, neither is the guest. I believe I have a good idea on the issue, though; a messed-up VMWare Tools install. The guest has VMware Tools on it, but the host says it does not. VMWare Tools refuses to uninstall, refuses to be upgraded, refuses to be recognized. While I cannot say with authority, this would appear to be something worth investigation. I do not know the origin of the guest itself, nor the specifics on the original VMWare Tools install. Following various bits of googling, I did come up with a few suggestions that went nowhere. To that end, I was going to delete this question, but was prompted not to do so since so many folks answered. My suspicion right now is; the problem truly is the guest; the guest is not making a demand on the host, and as a natural result, the host is treating the guest accordingly. My Final Update I am 99% certain the guest VM had something fundamentally wrong with it re VMWare Tools. I created a clone of a different VM with a near-identical OS config, but a properly working install of VMWare tools. The guest runs just great, and takes up it's allotment of resources when it needs to; e.g. it eats up about 850mhz CPU during startup, then ticks down to idle once the guest OS is stable.

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• Cloud MBaaS : The Next Big Thing in Enterprise Mobility

  - by shiju

  In this blog post, I will take a look at Cloud Mobile Backend as a Service (MBaaS) and how we can leverage Cloud based Mobile Backend as a Service for building enterprise mobile apps. Today, mobile apps are incredibly significant in both consumer and enterprise space and the demand for the mobile apps is unbelievably increasing in day to day business. An enterprise can’t survive in business without a proper mobility strategy. A better mobility strategy and faster delivery of your mobile apps will give you an extra mileage for your business and IT strategy. So organizations and mobile developers are looking for different strategy for meeting this demand and adopting different development strategy for their mobile apps. Some developers are adopting hybrid mobile app development platforms, for delivering their products for multiple platforms, for fast time-to-market. Others are adopting a Mobile enterprise application platform (MEAP) such as Kony for their enterprise mobile apps for fast time-to-market and better business integration. The Challenges of Enterprise Mobility The real challenge of enterprise mobile apps, is not about creating the front-end environment or developing front-end for multiple platforms. The most important thing of enterprise mobile apps is to expose your enterprise data to mobile devices where the real pain is your business data might be residing in lot of different systems including legacy systems, ERP systems etc., and these systems will be deployed with lot of security restrictions. Exposing your data from the on-premises servers, is not a easy thing for most of the business organizations. Many organizations are spending too much time for their front-end development strategy, but they are really lacking for building a strategy on their back-end for exposing the business data to mobile apps. So building a REST services layer and mobile back-end services, on the top of legacy systems and existing middleware systems, is the key part of most of the enterprise mobile apps, where multiple mobile platforms can easily consume these REST services and other mobile back-end services for building mobile apps. For some mobile apps, we can’t predict its user base, especially for products where customers can gradually increase at any time. And for today’s mobile apps, faster time-to-market is very critical so that spending too much time for mobile app’s scalability, will not be worth. The real power of Cloud is the agility and on-demand scalability, where we can scale-up and scale-down our applications very easily. It would be great if we could use the power of Cloud to mobile apps. So using Cloud for mobile apps is a natural fit, where we can use Cloud as the storage for mobile apps and hosting mechanism for mobile back-end services, where we can enjoy the full power of Cloud with greater level of on-demand scalability and operational agility. So Cloud based Mobile Backend as a Service is great choice for building enterprise mobile apps, where enterprises can enjoy the massive scalability power of their mobile apps, provided by public cloud vendors such as Microsoft Windows Azure. Mobile Backend as a Service (MBaaS) We have discussed the key challenges of enterprise mobile apps and how we can leverage Cloud for hosting mobile backend services. MBaaS is a set of cloud-based, server-side mobile services for multiple mobile platforms and HTML5 platform, which can be used as a backend for your mobile apps with the scalability power of Cloud. The information below provides the key features of a typical MBaaS platform: Cloud based storage for your application data. Automatic REST API services on the application data, for CRUD operations. Native push notification services with massive scalability power. User management services for authenticate users. User authentication via Social accounts such as Facebook, Google, Microsoft, and Twitter. Scheduler services for periodically sending data to mobile devices. Native SDKs for multiple mobile platforms such as Windows Phone and Windows Store, Android, Apple iOS, and HTML5, for easily accessing the mobile services from mobile apps, with better security.  Typically, a MBaaS platform will provide native SDKs for multiple mobile platforms so that we can easily consume the server-side mobile services. MBaaS based REST APIs can use for integrating to enterprise backend systems. We can use the same mobile services for multiple platform so hat we can reuse the application logic to multiple mobile platforms. Public cloud vendors are building the mobile services on the top of their PaaS offerings. Windows Azure Mobile Services is a great platform for a MBaaS offering that is leveraging Windows Azure Cloud platform’s PaaS capabilities. Hybrid mobile development platform Titanium provides their own MBaaS services. LoopBack is a new MBaaS service provided by Node.js consulting firm StrongLoop, which can be hosted on multiple cloud platforms and also for on-premises servers. The Challenges of MBaaS Solutions If you are building your mobile apps with a new data storage, it will be very easy, since there is not any integration challenges you have to face. But most of the use cases, you have to extract your application data in which stored in on-premises servers which might be under VPNs and firewalls. So exposing these data to your MBaaS solution with a proper security would be a big challenge. The capability of your MBaaS vendor is very important as you have to interact with your legacy systems for many enterprise mobile apps. So you should be very careful about choosing for MBaaS vendor. At the same time, you should have a proper strategy for mobilizing your application data which stored in on-premises legacy systems, where your solution architecture and strategy is more important than platforms and tools.  Windows Azure Mobile Services Windows Azure Mobile Services is an MBaaS offerings from Windows Azure cloud platform. IMHO, Microsoft Windows Azure is the best PaaS platform in the Cloud space. Windows Azure Mobile Services extends the PaaS capabilities of Windows Azure, to mobile devices, which can be used as a cloud backend for your mobile apps, which will provide global availability and reach for your mobile apps. Windows Azure Mobile Services provides storage services, user management with social network integration, push notification services and scheduler services and provides native SDKs for all major mobile platforms and HTML5. In Windows Azure Mobile Services, you can write server-side scripts in Node.js where you can enjoy the full power of Node.js including the use of NPM modules for your server-side scripts. In the previous section, we had discussed some challenges of MBaaS solutions. You can leverage Windows Azure Cloud platform for solving many challenges regarding with enterprise mobility. The entire Windows Azure platform can play a key role for working as the backend for your mobile apps where you can leverage the entire Windows Azure platform for your mobile apps. With Windows Azure, you can easily connect to your on-premises systems which is a key thing for mobile backend solutions. Another key point is that Windows Azure provides better integration with services like Active Directory, which makes Windows Azure as the de facto platform for enterprise mobility, for enterprises, who have been leveraging Microsoft ecosystem for their application and IT infrastructure. Windows Azure Mobile Services  is going to next evolution where you can expect some exciting features in near future. One area, where Windows Azure Mobile Services should definitely need an improvement, is about the default storage mechanism in which currently it is depends on SQL Server. IMHO, developers should be able to choose multiple default storage option when creating a new mobile service instance. Let’s say, there should be a different storage providers such as SQL Server storage provider and Table storage provider where developers should be able to choose their choice of storage provider when creating a new mobile services project. I have been used Windows Azure and Windows Azure Mobile Services as the backend for production apps for mobile, where it performed very well. MBaaS Over MEAP Recently, many larger enterprises has been adopted Mobile enterprise application platform (MEAP) for their mobile apps. I haven’t worked on any production MEAP solution, but I heard that developers are really struggling with MEAP in different way. The learning curve for a proprietary MEAP platform is very high. I am completely against for using larger proprietary ecosystem for mobile apps. For enterprise mobile apps, I highly recommend to use native iOS/Android/Windows Phone or HTML5  for front-end with a cloud hosted MBaaS solution as the middleware. A MBaaS service can be consumed from multiple mobile apps where REST APIs are using to integrating with enterprise backend systems. Enterprise mobility should start with exposing REST APIs on the enterprise backend systems and these REST APIs can host on Cloud where we can enjoy the power of Cloud for our services. If you are having REST APIs for your enterprise data, then you can easily build mobile frontends for multiple platforms.   You can follow me on Twitter @shijucv

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• Master Data Management and Cloud Computing

  - by david.butler(at)oracle.com

  Cloud Computing is all the rage these days. There are many reasons why this is so. But like its predecessor, Service Oriented Architecture, it can fall on hard times if the underlying data is left unmanaged. Master Data Management is the perfect Cloud companion. It can materially increase the chances for successful Cloud initiatives. In this blog, I'll review the nature of the Cloud and show how MDM fits in.   Here's the National Institute of Standards and Technology Cloud definition: •          Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction.   Cloud architectures have three main layers: applications or Software as a Service (SaaS), Platforms as a Service (PaaS), and Infrastructure as a Service (IaaS). SaaS generally refers to applications that are delivered to end-users over the Internet. Oracle CRM On Demand is an example of a SaaS application. Today there are hundreds of SaaS providers covering a wide variety of applications including Salesforce.com, Workday, and Netsuite. Oracle MDM applications are located in this layer of Oracle's On Demand enterprise Cloud platform. We call it Master Data as a Service (MDaaS). PaaS generally refers to an application deployment platform delivered as a service. They are often built on a grid computing architecture and include database and middleware. Oracle Fusion Middleware is in this category and includes the SOA and Data Integration products used to connect SaaS applications including MDM. Finally, IaaS generally refers to computing hardware (servers, storage and network) delivered as a service.  This typically includes the associated software as well: operating systems, virtualization, clustering, etc.    Cloud Computing benefits are compelling for a large number of organizations. These include significant cost savings, increased flexibility, and fast deployments. Cost advantages include paying for just what you use. This is especially critical for organizations with variable or seasonal usage. Companies don't have to invest to support peak computing periods. Costs are also more predictable and controllable. Increased agility includes access to the latest technology and experts without making significant up front investments.   While Cloud Computing is certainly very alluring with a clear value proposition, it is not without its challenges. An IDC survey of 244 IT executives/CIOs and their line-of-business (LOB) colleagues identified a number of issues:   Security - 74% identified security as an issue involving data privacy and resource access control. Integration - 61% found that it is hard to integrate Cloud Apps with in-house applications. Operational Costs - 50% are worried that On Demand will actually cost more given the impact of poor data quality on the rest of the enterprise. Compliance - 49% felt that compliance with required regulatory, legal and general industry requirements (such as PCI, HIPAA and Sarbanes-Oxley) would be a major issue. When control is lost, the ability of a provider to directly manage how and where data is deployed, used and destroyed is negatively impacted.  There are others, but I singled out these four top issues because Master Data Management, properly incorporated into a Cloud Computing infrastructure, can significantly ameliorate all of these problems. Cloud Computing can literally rain raw data across the enterprise.   According to fellow blogger, Mike Ferguson, "the fracturing of data caused by the adoption of cloud computing raises the importance of MDM in keeping disparate data synchronized."   David Linthicum, CTO Blue Mountain Labs blogs that "the lack of MDM will become more of an issue as cloud computing rises. We're moving from complex federated on-premise systems, to complex federated on-premise and cloud-delivered systems."    Left unmanaged, non-standard, inconsistent, ungoverned data with questionable quality can pollute analytical systems, increase operational costs, and reduce the ROI in Cloud and On-Premise applications. As cloud computing becomes more relevant, and more data, applications, services, and processes are moved out to cloud computing platforms, the need for MDM becomes ever more important. Oracle's MDM suite is designed to deal with all four of the above Cloud issues listed in the IDC survey.   Security - MDM manages all master data attribute privacy and resource access control issues. Integration - MDM pre-integrates Cloud Apps with each other and with On Premise applications at the data level. Operational Costs - MDM significantly reduces operational costs by increasing data quality, thereby improving enterprise business processes efficiency. Compliance - MDM, with its built in Data Governance capabilities, insures that the data is governed according to organizational standards. This facilitates rapid and accurate reporting for compliance purposes. Oracle MDM creates governed high quality master data. A unified cleansed and standardized data view is produced. The Oracle Customer Hub creates a single view of the customer. The Oracle Product Hub creates high quality product data designed to support all go-to-market processes. Oracle Supplier Hub dramatically reduces the chances of 'supplier exceptions'. Oracle Site Hub masters locations. And Oracle Hyperion Data Relationship Management masters financial reference data and manages enterprise hierarchies across operational areas from ERP to EPM and CRM to SCM. Oracle Fusion Middleware connects Cloud and On Premise applications to MDM Hubs and brings high quality master data to your enterprise business processes.   An independent analyst once said "Poor data quality is like dirt on the windshield. You may be able to drive for a long time with slowly degrading vision, but at some point, you either have to stop and clear the windshield or risk everything."  Cloud Computing has the potential to significantly degrade data quality across the enterprise over time. Deploying a Master Data Management solution prior to or in conjunction with a move to the Cloud can insure that the data flowing into the enterprise from the Cloud is clean and governed. This will in turn insure that expected returns on the investment in Cloud Computing will be realized.       Oracle MDM has proven its metal in this area and has the customers to back that up. In fact, I will be hosting a webcast on Tuesday, April 10th at 10 am PT with one of our top Cloud customers, the Church Pension Group. They have moved all mainline applications to a hosted model and use Oracle MDM to insure the master data is managed and cleansed before it is propagated to other cloud and internal systems. I invite you join Martin Hossfeld, VP, IT Operations, and Danette Patterson, Enterprise Data Manager as they review business drivers for MDM and hosted applications, how they did it, the benefits achieved, and lessons learned. You can register for this free webcast here.  Hope to see you there.

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• Keeping up with Technology

  - by kennedysteve

  If you're like me, you have a hard time keeping up with all the technologies out there. The reality is there's too many new technologies (languages, methodologies,  tools, etc). One of the ways I try to keep up with everything is by using good ol' RSS feeds in conjunction with Google Reader. Google Reader is both an online aggregator of RSS feeds, and it also has a good companion app on Google Android. The nicest part of Google Reader for me is the "All Listings" view which gives me a reverse chronological view of ALL articles (mixed together) regardless of the actual RSS feed.  This way, I get to see the newest articles first. I can then choose to hide the articles I've viewed, etc. Here is a list of my RSS feeds. Admittedly, some of these are all over the spectrum. But you might find one or two interesting. .NET Rocks! RSS = http://feeds.feedburner.com/netRocksFullMp3Downloads Main Web Site = http://www.dotnetrocks.com Channel 9 RSS = http://channel9.msdn.com/Feeds/RSS Main Web Site = http://channel9.msdn.com/ CodePlex  RSS = http://www.codeplex.com/site/feeds/rss Main Web Site = http://www.codeplex.com/site/feeds/rss Connected Show Developer Podcast! RSS = http://feeds.connectedshow.com/ConnectedShow Main Web Site = http://www.ConnectedShow.com/ dnrTV RSS = http://feeds.feedburner.com/DnrtvWmv?format=xml Main Web Site = http://dnrtv.com ebookshare RSS = http://www.ebookshare.net/feed/ Main Web Site = http://www.ebookshare.net Geekswithblogs.net RSS = http://feeds.feedburner.com/geekswithblogs Main Web Site = http://geekswithblogs.net/mainfeed.aspx Gmail Blog RSS = http://feeds.feedburner.com/OfficialGmailBlog?format=xml Main Web Site = http://gmailblog.blogspot.com/ Google Mobile Blog RSS = http://feeds.feedburner.com/OfficialGoogleMobileBlog Main Web Site = http://googlemobile.blogspot.com/ Herding Code RSS = http://feeds.feedburner.com/herdingcode Main Web Site = http://herdingcode.com LearnVisualStudio.NET Videos RSS = http://www.learnvisualstudio.net/videos.rss Main Web Site = http://www.learnvisualstudio.net/ Microsoft Learning Upcoming = Microsoft Learning Upcoming Titles RSS = http://learning.microsoft.com/rss/en-US/upcomingtitles?brand=Learning Main Web Site = http://learning.microsoft.com:80/rss/en-US/upcomingtitles?brand=Learning MS On-demand Webcasts RSS = http://www.microsoft.com/communities/rss.aspx?&Title=On-Demand+Webcasts&RssTitle=Microsoft+Webcasts%3A+On-Demand+Webcasts&CMTYSvcSource=MSCOMMedia&WebNewsURL=http%3A%2F%2Fwww.microsoft.com%2Fevents%2FEventDetails.aspx&CMTYRawShape=list&Params=+%0D%0A%09~CMTYDataSvcParams%5E%0D%0A%09~arg+Name%3D'EventType'+Value%3D'OnDemandWebcast'%2F%5E%0D%0A%09~arg+Name%3D'ProviderID'+Value%3D'A6B43178-497C-4225-BA42-DF595171F04C'%2F%5E%0D%0A%09~arg+Name%3D'StartDate'+Value%3D'06%2F30%2F2006'%2F%5E%0D%0A%09~arg+Name%3D'EndDate'+Value%3D'Now%2B0'%2F%5E%0D%0A%09~%2FCMTYDataSvcParams%5E+&NumberOfItems=100 Main Web Site = http://www.microsoft.com/events/default.mspx MS Podcasts for Devs RSS = http://www.microsoft.com/events/podcasts/default.aspx?podcast=rss&audience=Audience-e5381407-359f-4922-97d0-0237af790eee&pageId=x40 Main Web Site = http://www.microsoft.com/events/podcasts/default.aspx?audience=Audience-e5381407-359f-4922-97d0-0237af790eee&pageId=x40&WT.rss_ev=f MSDN Blogs RSS = http://blogs.msdn.com/b/mainfeed.aspx?Type=BlogsOnly Main Web Site = http://blogs.msdn.com/b/ MSDN Radio RSS = http://www.microsoft.com/events/podcasts/default.aspx?topic=&audience=&view=&pageId=x73&seriesID=Series-b9139976-8d48-4249-9b89-ccd17891de1e.xml&podcast=rss&type=wma Main Web Site = http://www.microsoft.com/events/podcasts/default.aspx?seriesID=Series-b9139976-8d48-4249-9b89-ccd17891de1e.xml&pageId=x73&WT.rss_ev=f O'Reilly Deal of the Day RSS = http://feeds.feedburner.com/oreilly/ebookdealoftheday Main Web Site = http://oreilly.com O'Reilly New RSS = http://feeds.feedburner.com/oreilly/newbooks Main Web Site = http://oreilly.com/ Safari Books Online RSS = http://my.safaribooksonline.com/rss Main Web Site = http://my.safaribooksonline.com/ ScottGu's Blog RSS = http://weblogs.asp.net/scottgu/rss.aspx Main Web Site = http://weblogs.asp.net/scottgu/default.aspx SourceForge Community Blog RSS = http://sourceforge.net/blog/feed/ Main Web Site = http://sourceforge.net/blog Stack Overflow RSS = http://blog.stackoverflow.com/feed/ Main Web Site = http://blog.stackoverflow.com Stepcase Lifehack RSS = http://www.lifehack.org/feed/ Main Web Site = http://www.lifehack.org TechNet Radio RSS = http://www.microsoft.com/events/podcasts/default.aspx?topic=&audience=&view=&pageId=x73&seriesID=Series-cc4e3db2-9212-43c5-a57b-d43fa31e6452.xml&podcast=rss&type=wma Main Web Site = http://www.microsoft.com/events/podcasts/default.aspx?seriesID=Series-cc4e3db2-9212-43c5-a57b-d43fa31e6452.xml&pageId=x73&WT.rss_ev=f Wrox All New Titles RSS = http://www.wrox.com/WileyCDA/feed/RSS_WROX_ALLNEW.xml Main Web Site = http://www.wrox.com

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• The new Auto Scaling Service in Windows Azure

  - by shiju

  One of the key features of the Cloud is the on-demand scalability, which lets the cloud application developers to scale up or scale down the number of compute resources hosted on the Cloud. Auto Scaling provides the capability to dynamically scale up and scale down your compute resources based on user-defined policies, Key Performance Indicators (KPI), health status checks, and schedules, without any manual intervention. Auto Scaling is an important feature to consider when designing and architecting cloud based solutions, which can unleash the real power of Cloud to the apps for providing truly on-demand scalability and can also guard the organizational budget for cloud based application deployment. In the past, you have had to leverage the the Microsoft Enterprise Library Autoscaling Application Block (WASABi) or a services like  MetricsHub for implementing Automatic Scaling for your cloud apps hosted on the Windows Azure. The WASABi required to host your auto scaling block in a Windows Azure Worker Role for effectively implementing the auto scaling behaviour to your Windows Azure apps. The newly announced Auto Scaling service in Windows Azure lets you add automatic scaling capability to your Windows Azure Compute Services such as Cloud Services, Web Sites and Virtual Machine. Unlike WASABi hosted on a Worker Role, you don’t need to host any monitoring service for using the new Auto Scaling service and the Auto Scaling service will be available to individual Windows Azure Compute Services as part of the Scaling. Configure Auto Scaling for a Windows Azure Cloud Service Currently the Auto Scaling service supports Cloud Services, Web Sites and Virtual Machine. In this demo, I will be used a Cloud Services app with a Web Role and a Worker Role. To enable the Auto Scaling, select t your Windows Azure app in the Windows Azure management portal, and choose “SCLALE” tab. The Scale tab will show the all information regards with Auto Scaling. The below image shows that we have currently disabled the AutoScale service. To enable Auto Scaling, you need to choose either CPU or QUEUE. The QUEUE option is not available for Web Sites. The image below demonstrates how to configure Auto Scaling for a Web Role based on the utilization of CPU. We have configured the web role app for running with 1 to 5 Virtual Machine instances based on the CPU utilization with a range of 50 to 80%. If the aggregate utilization is becoming above above 80%, it will scale up instances and it will scale down instances when utilization is becoming below 50%. The image below demonstrates how to configure Auto Scaling for a Worker Role app based on the messages added into the Windows Azure storage Queue. We configured the worker role app for running with 1 to 3 Virtual Machine instances based on the Queue messages added into the Windows Azure storage Queue. Here we have specified the number of messages target per machine is 2000. The image below shows the summary of the Auto Scaling for the Cloud Service after configuring auto scaling service. Summary Auto Scaling is an extremely important behaviour of the Cloud applications for providing on-demand scalability without any manual intervention. Windows Azure provides greater support for enabling Auto Scaling for the apps deployed on the Windows Azure cloud platform. The new Auto Scaling service in Windows Azure lets you add automatic scaling capability to your Windows Azure Compute Services such as Cloud Services, Web Sites and Virtual Machine. In the new Auto Scaling service, you don’t have to host any monitor service like you have had in WASABi block. The Auto Scaling service is an excellent alternative to the manually hosting WASABi block in a Worker Role app.

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• Release 17 is here!

  - by Cheryl

  Our training development team has been busy updating courses to keep pace with the new release of CRM On Demand. Release 17 is here! And I heard recently that it's one of our biggest releases ever. A lot of new features and functionality for you to take advantage of - too much for me to cover in this blog post. But, I thought I'd tell you about a few of my favorites - be sure to take a look at the What's New in Release 17 recording to see the full list, though...because I'm only going to touch on a few. Create your own look - okay, I'm starting with the fun stuff. But, there is a new customizable themes feature so that you can change the look of the application; colors, logo, the shape of the tabs. And it's really easy. There's also a whole new library of ready-made themes for you to pick from if you just want to go with one of those. Use this new feature to match the look of your company logo and color scheme. Or blaze new trails. You can create the look for the whole company, or a different look for each CRM On Demand role. This might especially come in handy if you're using the Partner Relationship Management (PRM) capabilities of CRM On Demand - you can create themes for your partner-facing roles to provide branded partner portals. Speaking of PRM - there are enhancements in this release to help companies better manage their partner relationships. A new Deal Registration object, which is separate from the Opportunity record, and better Special Pricing Request and Marketing Development Fund Request processes, give a lot more flexibility in how companies can build and manage their relationships with partners. Some new options for Forecasts in in Release 17, too. You can now have more than one type of forecast generated each forecast period. For example, you might need to see a forecast of the total opportunity revenue for your sales team, as well as on that breaks down revenue by product. The forecast definition now lets you do that. Other options allow you to make submitting forecasts easier, split opportunity revenue across the team and forecast that split appropriately. And - look for the new Forecast subject area in Answers, for building custom forecast reports. Ever wish you could use Workflow Rules to automatically reassign leads if they haven't been followed up on...or to email a manager if the status of a service request isn't changed after a specified period of time? Then check out the new Wait action for workflows. I think you'll be happy. Ok, enough for today. There is a lot to Release 17 that I didn't mention - a lot has been added for our Life Science industry edition, some new data visibility options, a new Data Loader tool, and more. Stay tuned for more blog posts about these and other Release 17 features in the coming weeks. In the meantime, don't forget about all of the resources we have for you to learn more (see my Learning About Release 17 blog post for details).

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• The Evolution of Television and Home Entertainment

  - by Bill Evjen

  This is a group that is focused on entertainment in the aviation industry. I am attending their conference for the first time as it relates to my job at Swank Motion Pictures and what we do for our various markets. I will post my notes here. The Evolution of Television and Home Entertainment by Patrick Cosson, Veebeam TV has been the center of living rooms for sometime. Conversations and culture evolve around the TV. The way we consume this content has dramatically been changing. After TV, we had the MTV revolution of TV. It has created shorter attention spans, it made us more materialistic, narcissistic, and not easily impressed. Then we came to the Internet. The amount of content has expanded. It contains a ton of user-generated content, provides filtering, organization, distribution. We now have a problem. We are in the age of digital excess. We can access whatever we want. In conjunction with this – we are moving. The challenge we have now is curation. The trends  we see: rapid shift from scheduled to on demand consumption. A move to Internet protocols from cable Rapid fragmentation of media a transition from the TV set to a variety of screens Social connections bring mediators and amplifiers. TiVo – the shift to on demand It is because of a time-crunch Provides personal experiences Once old consumption habits are changed, there is no way back! Experiences are that people are loading up content and then bringing it with them on planes, to hotels, etc. Rapid fragmentation of media sources Many new professional content sources and channels, the rise of digital distribution, and the rise of user-generated content contribute to the wealth of content sources and abundant choice. Netflix, BBC iPlayer, hulu, Pandora, iTunes, Amazon Video, Vudu, Voddler, Spotify (these companies didn’t exist 5 years ago). People now expect this kind of consumption. People are now thinking how to deliver all these tools. Transition from the TV set to multi-screens The TV screen has traditionally been the dominant consumption screen for TV and video. Now the PC, game consoles, and various mobile devices are rapidly becoming common video devices. Multi-screens are now the norm. Social connections becoming key mediators What increasingly funnels traffic on the web, social networking enablers, will become an integral part of the discovery, consumption and sharing model for Television. The revolution will be broadcasted on Facebook and Twitter. There is business disruption There are a lot of new entrants Rapid internationalization Increasing competition from existing media players A fragmenting audience base Web browser Freedom to access any site The fight over the walled garden Most devices are not powerful enough to support a full browser PC will always be present in the living room Wireless link between PC and TV Output 1080p, plays anything, secure Key players and their challenges Services Internet media is increasingly interconnected to social media and publicly shared UGC Content delivery moving to IPTV Rights management issues are creating silos and hindering a great user experience and growth Devices Devices are becoming people’s windows into all kinds of media from all kinds of sources There won’t be a consolidation of the device landscape, rather the opposite Finding the right niche makes the most sense. We are moving to an on demand world of streaming world. People want full access to anything.

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• Analytics in an Omni-Channel World

  - by David Dorf

  Retail has been around ever since mankind started bartering.  The earliest transactions were very specific to the individuals buying and selling, then someone had the bright idea to open a store.  Those transactions were a little more generic, but the store owner still knew his customers and what they wanted.  As the chains rolled out, customer intimacy was sacrificed for scale, and retailers began to rely on segments and clusters.  But thanks to the widespread availability of data and the technology to convert said data into information, retailers are getting back to details. The retail industry is following a maturity model for analytics that is has progressed through five stages, each delivering more value than the previous. Store Analytics Brick-and-mortar retailers (and pure-play catalogers as well) that collect anonymous basket-level data are able to get some sense of demand to help with allocation decisions.  Promotions and foot-traffic can be measured to understand marketing effectiveness and perhaps focus groups can help test ideas.  But decisions are influenced by the majority, using faceless customer segments and aggregated industry data points.  Loyalty programs help a little, but in many cases the cost outweighs the benefits. Web Analytics The Web made it much easier to collect data on specific, yet still anonymous consumers using cookies to track visits. Clickstreams and product searches are analyzed to understand the purchase journey, gauge demand, and better understand up-selling opportunities.  Personalization begins to allow retailers target market consumers with recommendations. Cross-Channel Analytics This phase is a minor one, but where most retailers probably sit today.  They are able to use information from one channel to bolster activities in another. However, there are technical challenges combining data silos so its not an easy task.  But for those retailers that are able to perform analytics on both sources of data, the pay-off is pretty nice.  Revenue per customer begins to go up as customers have a better brand experience. Mobile & Social Analytics Big data technologies are enabling a 360-degree view of the customer by incorporating psychographic data from social sites alongside traditional demographic data.  Retailers can track individual preferences, opinions, hobbies, etc. in order to understand a consumer's motivations.  Using mobile devices, consumers can interact with brands anywhere, anytime, accessing deep product information and reviews.  Mobile, combined with a loyalty program, presents an opportunity to put shopping into geographic context, understanding paths to the store, patterns within the store, and be an always-on advertising conduit. Omni-Channel Analytics All this data along with the proper technology represents a new paradigm in which the clock is turned back and retail becomes very personal once again.  Rich, individualized data better illuminates demand, allows for highly localized assortments, and helps tailor up-selling.  Interactions with all channels help build an accurate profile of each consumer, and allows retailers to tailor the retail experience to meet the heightened expectations of today's sophisticated shopper.  And of course this culminates in greater customer satisfaction and business profitability.

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• Custom Templates: Using user exits

  - by Anthony Shorten

  One of the features of Oracle Utilities Application Framework V4.1 is the ability to use templates and user exits to extend the base configuration files. The configuration files used by the product are based upon a set of templates shipped with the product. When the configureEnv utility asks for configuration settings they are stored in a configuration file ENVIRON.INI which outlines the environment settings. These settings are then used by the initialSetup utility to populate the various configuration files used by the product using templates located in the templates directory of the installation. Now, whilst the majority of the installations at any site are non-production and the templates provided are generally adequate for that need, there are circumstances where extension of templates are needed to take advantage of more advanced facilities (such as advanced security and environment settings). The issue then becomes that if you alter the configuration files manually (directly or indirectly) then you may lose all your custom settings the next time you run initialSetup. To counter this we allow customers to either override templates with their own template or we now provide user exits in the templates to add fragments of configuration unique to that part of the configuration file. The latter means that the base template is still used but additions are included to provide the extensions. The provision of custom templates is supported but as soon as you use a custom template you are then responsible for reflecting any changes we put in the base template over time. Not a big task but annoying if you have to do it for multiple copies of the product. I prefer to use user exits as they seem to represent the least effort solution. The way to find the user exits available is to either read the Server Administration Guide that comes with your product or look at individual templates and look for the lines: #ouaf_user_exit <user exit name> Where <user exit name> is the name of the user exit. User exits are not always present but are in places that we feel are the most likely to be changed. If a user exit does not exist the you can always use a custom template instead. Now lets show an example. By default, the product generates a config.xml file to be used with Oracle WebLogic. This configuration file has the basic setting contained in it to manage the product. If you want to take advantage of the Oracle WebLogic advanced settings, you can use the console to make those changes and it will be reflected in the config.xml automatically. To retain those changes across invocations of initialSetup, you need to alter the template that generates the config.xml or use user exits. The technique is this. Make the change in the console and when you save the change, WebLogic will reflect it in the config.xml for you. Compare the old version and new version of the config.xml and determine what to add and then find the user exit to put it in by examining the base template. For example, by default, the console is not automatically deployed (it is deployed on demand) in the base config.xml. To make the console deploy, you can add the following line to the templates/CM_config.xml.win.exit_3.include file (for windows) or templates/CM_config.xml.exit_3.include file (for linux/unix): <internal-apps-deploy-on-demand-enabled>false</internal-apps-deploy-on-demand-enabled> Now run initialSetup to reflect the change and if you check the splapp/config/config.xml file you will see the change applied for you. Now how did I know which include file? I check the template for config.xml and found there was an user exit at the right place. I prefixed my include filename with "CM_" to denote it as a custom user exit. This will tell the upgrade tools to leave that file alone whenever you decide to upgrade (or even apply fixes). User exits can be powerful and allow customizations to be added for advanced configuration. You will see products using Oracle Utilities Application Framework use this exits themselves (usually prefixed with the product code). You are also taking advantage of them.

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• October 2013 Oracle University Round-Up: New Training & Certifications

  - by Breanne Cooley

  Here are the highlights of what is happening this month at Oracle University.  New Technology Overview Courses: Cloud, Big Data and Security Learn about the latest technology solutions that can transform your business. These three Training On Demand courses are taught by industry experts. These courses help you develop an understanding of how Oracle technologies can make a positive impact on your organization.  Oracle Cloud Overview  Oracle Big Data Overview Oracle Security Overview  New Cloud Application Foundation Courses Check out our brand new 12c courses for WebLogic Server administrators and Coherence developers:  Oracle WebLogic Server 12c: Administration I Oracle WebLogic Server 12c: Administration II Oracle Coherence 12c: New Features  Oracle Database 12c Courses Our Oracle Database 12c training is becoming very popular. Here are this month's featured courses:  Oracle Database 12c: New Features for Administrators Oracle Database 12c: Administration Workshop  Oracle Database 12c: Install and Upgrade Workshop Oracle Database 12c: Admin, Install and Upgrade Accelerated  Validate your expertise and add value by earning an Oracle Database 12c Certification.  New Certifications for MySQL Watch our two new videos to find out what's new with Oracle MySQL Certifications. 1) Oracle MySQL 5.6 Certification: What's New for Database Administrators  Recommended training:  MySQL for Beginners MySQL for Database Administrators  2) Oracle MySQL 5.6 Certification: What's New for Developers Recommended training:  MySQL for Beginners MySQL for Developers New Training & Certification for Oracle Applications JD Edwards 9.1 Training Additional JD Edwards Enterprise One 9.1 training is now available for administrators, developers and implementation team members. Cross Application Training  JD Edwards Enterprise One Common Foundation Rel 9.x  Human Capital Management Training  JD Edwards EnterpriseOne Payroll for Canada Rel 9.x JD Edwards EnterpriseOne Payroll for US Rel 9.x JD Edwards EnterpriseOne Payroll Accelerated for Canada Rel 9.x JD Edwards EnterpriseOne Payroll Accelerated for US Rel 9.x  Financial  Management Training  JD Edwards EnterpriseOne Accounts Receivable Rel 9.x JD Edwards EnterpriseOne Financial Report Writing Rel 9.x  Knowledge Management 8.5 Training Oracle Knowledge 8.5 training is now available for analysts interested in learning how to quickly spot trends in content processing and system usage with analytics dashboards. Knowledge Analytics Rel 8.5  Taleo Training Updated Taleo training is now available. Taleo Business Edition (TEE) business users can learn how to create more efficient reports. Recruiters will learn how to efficiently and effectively use Taleo Business Edition (TBE) Recruit.  Taleo (TEE): Advanced Reporting Taleo (TBE): Recruit - End User Fundamentals  New Training for Oracle Retail 13.4.1 Updated training for Retail Predictive Application Server and Retail Demand Forecasting is now available.  RPAS Administration and Configuration Fundamentals RPAS Technical Essentials: Fusion Client 13.4.1 Retail Demand Forecasting (RDF) Business Essentials 13.4.1  View all available training courses, learning paths and certifications at education.oracle.com, or contact your local education representative to learn more about Oracle University's education solutions. See you in class!  -Oracle University Marketing Team 

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• Five Key Trends in Enterprise 2.0 for 2011

  - by kellsey.ruppel(at)oracle.com

  We recently sat down with Andy MacMillan, an industry veteran and vice president of product management for Enterprise 2.0 at Oracle, to get his take on the year ahead in Enterprise 2.0 (E2.0). He offered us his five predictions about the ways he believes E2.0 technologies will transform business in 2011. 1. Forward-thinking organizations will achieve an unprecedented level of organizational awareness. Enterprise 2.0 and Web 2.0 technologies have already transformed the ways customers, employees, partners, and suppliers communicate and stay informed. But this year we are anticipating that organizations will go to the next step and integrate social activities with business applications to deliver rich contextual "activity streams." Activity streams are a new way for enterprise users to get relevant information as quickly as it happens, by navigating to that information in context directly from their portal. We don't mean syndicating social activities limited to a single application. Instead, we believe back-office systems will be combined with social media tools to drive how users make informed business decisions in brand new ways. For example, an account manager might log into the company portal and automatically receive notification that colleagues are closing business around a certain product in his market segment. With a single click, he can reach out instantly to these colleagues via social media and learn from their successes to drive new business opportunities in his own area. 2. Online customer engagement will become a high priority for CMOs. A growing number of chief marketing officers (CMOs) have created a new direct report called "head of online"--a senior marketing executive responsible for all engagements with customers and prospects via the Web, mobile, and social media. This new field has been dubbed "Web experience management" or "online customer engagement" by firms and analyst organizations. It is likely to rapidly increase demand for a host of new business objectives and metrics from Web content management solutions. As companies interface with customers more and more over the Web, Web experience management solutions will help deliver more targeted interactions to ensure increased customer loyalty while meeting sales and business objectives. 3. Real composite applications will be widely adopted. We expect organizations to move from the concept of a single "uber-portal" that encompasses all the necessary features to a more modular, component-based concept for composite applications. This approach is now possible as IT and power users are empowered to assemble new, purpose-built composite applications quickly from existing components. 4. Records management will drive ECM consolidation. We continue to see a significant shift in the approach to records management. Several years ago initiatives were focused on overlaying records management across a set of electronic repositories and physical storage locations. We believe federated records management will continue, but we also expect to see records management driving conversations around single-platform content management consolidation. 5. Organizations will demand ECM at extreme scale. We have already seen a trend within IT organizations to provide a common, highly scalable infrastructure to consolidate and support content and information needs. But as data sizes grow exponentially, ECM at an extreme scale is likely to spread at unprecedented speeds this year. This makes sense as regulations and transparency requirements rise. The model in which ECM and lightweight CMS systems provide basic content services such as check-in, update, delete, and search has converged around a set of industry best practices and has even been coded into new industry standards such as content management interoperability services. As these services converge and the demand for them accelerates, organizations are beginning to rationalize investments into a single, highly scalable infrastructure. Is your organization ready for Enterprise 2.0 in 2011? Learn more.

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• Improving Partitioned Table Join Performance

  - by Paul White

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

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• Crashing HVM domain, what do I do?

  - by rassie

  My DomUs on a Xen 3.4 on an RHEL5 are crashing when too much memory is needed: (XEN) p2m_pod_demand_populate: Out of populate-on-demand memory! (XEN) domain_crash called from p2m.c:1091 (XEN) Domain 15 (vcpu#3) crashed on cpu#2: (XEN) ----[ Xen-3.4.0 x86_64 debug=n Not tainted ]---- (XEN) CPU: 2 (XEN) RIP: 0010:[<ffffffff80062c02>] (XEN) RFLAGS: 0000000000010216 CONTEXT: hvm guest (XEN) rax: 0000000000000000 rbx: 0000000000000001 rcx: 000000000000003f (XEN) rdx: 0000000004812000 rsi: ffff810001000000 rdi: ffff810004812000 (XEN) rbp: 0000000000000282 rsp: ffff810007635cf0 r8: ffff810037c0288e (XEN) r9: 00000000000023e1 r10: 0000000000000000 r11: 0000000000000001 (XEN) r12: ffff81000000cb00 r13: ffff8100007e43f0 r14: ffff81000000fc10 (XEN) r15: 00000000000280d2 cr0: 0000000080050033 cr4: 00000000000006e0 (XEN) cr3: 0000000006760000 cr2: 0000000003d47078 (XEN) ds: 0000 es: 0000 fs: 0000 gs: 0000 ss: 0000 cs: 0010 Can I disable populate-on-demand for HVM somehow? Xen 3.3 didn't exhibit such behaviour...

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• Password problem while creating domain

  - by Murdock

  Hi, I'm freshman so far in server management stuff but this seems to be clearly against logic. After updating my Windows Server 2008 Standard 32bit, installing DNS server and AD DS I wanted to create domain via using CMD and dcpromo.exe setup. But no matter if I disable demand for comlex password in Password policies or create a password which fully comply with requirements for strong and complex password, still I can't get any further and it says that my password doesn't meet requirements. I'm also asked there to activate password demand by NET USER -passwordreq:yes and when I do so, this password doesn't work any more and I have to remove it from other admin account to be at least able to login with proper Administrator account.

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• L2TP Site to Site VPN issues

  - by Chris Lively

  I have a windows 2008 r2 server that needs to establish a VPN connection to a remote VPN server. We're using the L2TP protocol with a pre-shared key. I initially used the New Demand Dial interface wizard. Then I went into properties on the interface and set the type of VPn to L2TP/IPSec and put the key under the advanced settings. The error I received when attempting to connect is: An error occured during connection of the interface. A Demand Dial Router attempted to connect over a port that was reserved for Remote Access Clients only.

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• Enterprise SharePoint 2010 Hosting, SharePoint Foundation 2010 Hosting, SharePoint Standard 2010 Hos

  - by Michael J. Hamilton, Sr.

  Enterprise SharePoint 2010 Hosting, SharePoint Foundation 2010 Hosting, SharePoint Standard 2010 Hosting, Michigan Sclera, a Microsoft Hosted Services Provider Partner, is offering key Service Offerings around the Microsoft SharePoint Server 2010 stack. Specifically – if you’re looking for SharePoint Foundation, SharePoint Standard or Enterprise 2010 hosting provisions, checkout the Service Offerings from Sclera Hosting (www.sclerahosting.com) and compare with some of the lowest prices available on the web today. I wanted to post this so you could shot around and compare. There are a couple of the larger on demand hosting agencies (247hosting, and fpweb hosting) – that charge outrageous fees  - like $350 a month for SharePoint Foundation 2010 hosting. The most incredible part? This is on a shared domain name – not the client’s domain. It’s hosting on something like .sharepointsites.com">.sharepointsites.com">http://<yourSiteName>.sharepointsites.com – or something crazy like that. Sclera Hosting provides you on demand – SharePoint Foundation, SharePoint Server Standard/Enterprise – 2010 RTM bits – within minutes of your order – ON YOUR DOMAIN – and that is a major perk for me. You have complete SharePoint Designer 2010 integration; complete support for custom assemblies, web parts, you name it – this hosting provider gives you more bang for buck than any provider on the Net today. Now – some teasers – I was in a meeting this week and I heard – SharePoint Foundation – 2010 RTM bits – unlimited users, 10 GB content database quota, full SharePoint Designer 2010 integration/support, all on the client’s domain – sit down and soak this up - $175.00 per month – no kidding. Now, I do not know about you – but – I have not seen a deal like that EVER on the Net – so – get over to www.sclerahosting.com – or email the Sales Team at Sclera Design, Inc. today for more details. Have a great weekend!

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• Ajax Control Toolkit November 2011 Release

  - by Stephen Walther

  I’m happy to announce the November 2011 Release of the Ajax Control Toolkit. This release introduces a new Balloon Popup control and several enhancements to the existing Tabs control including support for on-demand loading of tab content, support for vertical tabs, and support for keyboard tab navigation. We also fixed the top-voted bugs associated with the Tabs control reported at CodePlex.com. You can download the new release by visiting the CodePlex website: http://AjaxControlToolkit.CodePlex.com Alternatively, the fast and easy way to get the latest release of the Ajax Control Toolkit is to use NuGet. Open your Library Package Manager console in Visual Studio 2010 and type: After you install the Ajax Control Toolkit through NuGet, please do a Rebuild of your project (the menu option Build, Rebuild). After you do a Rebuild, the ajaxToolkit prefix will appear in Intellisense: Using the Balloon Popup Control Why a new Balloon Popup control? The Balloon Popup control is the second most requested new feature for the Ajax Control Toolkit according to CodePlex votes: The Balloon Popup displays a message in a balloon when you shift focus to a control, click a control, or hover over a control. You can use the Balloon Popup, for example, to display instructions for TextBoxes which appear in a form: Here’s the code used to create the Balloon Popup: <ajaxToolkit:ToolkitScriptManager ID="tsm1" runat="server" /> <asp:TextBox ID="txtFirstName" Runat="server" /> <asp:Panel ID="pnlFirstNameHelp" runat="server"> Please enter your first name </asp:Panel> <ajaxToolkit:BalloonPopupExtender TargetControlID="txtFirstName" BalloonPopupControlID="pnlFirstNameHelp" BalloonSize="Small" UseShadow="true" runat="server" /> You also can use the Balloon Popup to explain hard to understand words in a text document: Here’s how you display the Balloon Popup when you hover over the link: The point of the conversation was <asp:HyperLink ID="lnkObfuscate" Text="obfuscated" CssClass="hardWord" runat="server" /> by his incessant coughing. <ajaxToolkit:ToolkitScriptManager ID="tsm1" runat="server" /> <asp:Panel id="pnlObfuscate" Runat="server"> To bewilder or render something obscure </asp:Panel> <ajaxToolkit:BalloonPopupExtender TargetControlID="lnkObfuscate" BalloonPopupControlID="pnlObfuscate" BalloonStyle="Cloud" UseShadow="true" DisplayOnMouseOver="true" Runat="server" />   There are four important properties which you need to know about when using the Balloon Popup control: BalloonSize – The three balloon sizes are Small, Medium, and Large. BalloonStyle -- The two built-in styles are Rectangle and Cloud. UseShadow – When true, a drop shadow appears behind the popup. Position – Can have the values Auto, BottomLeft, BottomRight, TopLeft, TopRight. When set to Auto, which is the default, the Balloon Popup will appear where it has the most screen real estate. The following screenshots illustrates how these settings affect the appearance of the Balloon Popup: Customizing the Balloon Popup You can customize the appearance of the Balloon Popup by creating your own Cascading Style Sheet and Sprite. The Ajax Control Toolkit sample site includes a sample of a custom Oval Balloon Popup style: This custom style was created by using a custom Cascading Style Sheet and image. You point the Balloon Popup at a custom Cascading Style Sheet and Cascading Style Sheet class by using the CustomCssUrl and CustomClassName properties like this: <asp:TextBox ID="txtCustom" autocomplete="off" runat="server" /> <br /> <asp:Panel ID="Panel3" runat="server"> This is a custom BalloonPopupExtender style created with a custom Cascading Style Sheet. </asp:Panel> <ajaxToolkit:BalloonPopupExtender ID="bpe1" TargetControlID="txtCustom" BalloonPopupControlID="Panel3" BalloonStyle="Custom" CustomCssUrl="CustomStyle/BalloonPopupOvalStyle.css" CustomClassName="oval" UseShadow="true" runat="server" />   Learn More about the Balloon Popup To learn more about the Balloon Popup control, visit the sample page for the Balloon Popup at the Ajax Control Toolkit sample site: http://www.asp.net/ajaxLibrary/AjaxControlToolkitSampleSite/BalloonPopup/BalloonPopupExtender.aspx Improvements to the Tabs Control In this release, we introduced several important new features for the existing Tabs control. We also fixed all of the top-voted bugs for the Tabs control. On-Demand Loading of Tab Content Here is the scenario. Imagine that you are using the Tabs control in a Web Forms page. The Tabs control displays two tabs: Customers and Products. When you click the Customers tab then you want to see a list of customers and when you click on the Products tab then you want to see a list of products. In this scenario, you don’t want the list of customers and products to be retrieved from the database when the page is initially opened. The user might never click on the Products tab and all of the work to load the list of products from the database would be wasted. In this scenario, you want the content of a tab panel to be loaded on demand. The products should only be loaded from the database and rendered to the browser when you click the Products tab and not before. The Tabs control in the November 2011 Release of the Ajax Control Toolkit includes a new property named OnDemand. When OnDemand is set to the value True, a tab panel won’t be loaded until you click its associated tab. Here is the code for the aspx page: <ajaxToolkit:ToolkitScriptManager ID="tsm1" runat="server" /> <ajaxToolkit:TabContainer ID="tabs" OnDemand="false" runat="server"> <ajaxToolkit:TabPanel HeaderText="Customers" runat="server"> <ContentTemplate> <h2>Customers</h2> <asp:GridView ID="grdCustomers" DataSourceID="srcCustomers" runat="server" /> <asp:SqlDataSource ID="srcCustomers" SelectCommand="SELECT * FROM Customers" ConnectionString="<%$ ConnectionStrings:StoreDB %>" runat="server" /> </ContentTemplate> </ajaxToolkit:TabPanel> <ajaxToolkit:TabPanel HeaderText="Products" runat="server"> <ContentTemplate> <h2>Products</h2> <asp:GridView ID="grdProducts" DataSourceID="srcProducts" runat="server" /> <asp:SqlDataSource ID="srcProducts" SelectCommand="SELECT * FROM Products" ConnectionString="<%$ ConnectionStrings:StoreDB %>" runat="server" /> </ContentTemplate> </ajaxToolkit:TabPanel> </ajaxToolkit:TabContainer> Notice that the TabContainer includes an OnDemand=”True” property. The Tabs control contains two Tab Panels. The first tab panel uses a DataGrid and SqlDataSource to display a list of customers and the second tab panel uses a DataGrid and SqlDataSource to display a list of products. And here is the code-behind for the page: using System; using System.Diagnostics; using System.Web.UI.WebControls; namespace ACTSamples { public partial class TabsOnDemand : System.Web.UI.Page { protected override void OnInit(EventArgs e) { srcProducts.Selecting += new SqlDataSourceSelectingEventHandler(srcProducts_Selecting); } void srcProducts_Selecting(object sender, SqlDataSourceSelectingEventArgs e) { Debugger.Break(); } } } The code-behind file includes an event handler for the Products SqlDataSource Selecting event. The handler breaks into the debugger by calling the Debugger.Break() method. That way, we can know when the Products SqlDataSource actually retrieves the list of products. When the OnDemand property has the value False then the Selecting event handler is called immediately when the page is first loaded. The contents of all of the tabs are loaded (and the contents of the unselected tabs are hidden) when the page is first loaded. When the OnDemand property has the value True then the Selecting event handler is not called when the page is first loaded. The event handler is not called until you click on the Products tab. If you never click on the Products tab then the list of products is never retrieved from the database. If you want even more control over when the contents of a tab panel gets loaded then you can use the TabPanel OnDemandMode property. This property accepts the following three values: None – Never load the contents of the tab panel again after the page is first loaded. Once – Wait until the tab is selected to load the contents of the tab panel Always – Load the contents of the tab panel each and every time you select the tab. There is a live demonstration of the OnDemandMode property here in the sample page for the Tabs control: http://www.asp.net/ajaxLibrary/AjaxControlToolkitSampleSite/Tabs/Tabs.aspx Displaying Vertical Tabs With the November 2011 Release, the Tabs control now supports vertical tabs. To create vertical tabs, just set the TabContainer UserVerticalStripPlacement property to the value True like this: <ajaxToolkit:TabContainer ID="tabs" OnDemand="false" UseVerticalStripPlacement="true" runat="server"> <ajaxToolkit:TabPanel ID="TabPanel1" HeaderText="First Tab" runat="server"> <ContentTemplate> <p> Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna. </p> </ContentTemplate> </ajaxToolkit:TabPanel> <ajaxToolkit:TabPanel ID="TabPanel2" HeaderText="Second Tab" runat="server"> <ContentTemplate> <p> Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Maecenas porttitor congue massa. Fusce posuere, magna sed pulvinar ultricies, purus lectus malesuada libero, sit amet commodo magna eros quis urna. </p> </ContentTemplate> </ajaxToolkit:TabPanel> </ajaxToolkit:TabContainer> In addition, you can use the TabStripPlacement property to control whether the tab strip appears at the left or right or top or bottom of the tab panels: Tab Keyboard Navigation Another highly requested feature for the Tabs control is support for keyboard navigation. The Tabs control now supports the arrow keys and the Home and End keys. In order for the arrow keys to work, you must first move focus to the tab control on the page by either clicking on a tab with your mouse or repeatedly hitting the Tab key. You can try out the new keyboard navigation support by trying any of the demos included in the Tabs sample page: http://www.asp.net/ajaxLibrary/AjaxControlToolkitSampleSite/Tabs/Tabs.aspx Summary I hope that you take advantage of the new Balloon Popup control and the new features which we introduced for the Tabs control. We added a lot of new features to the Tabs control in this release including support for on-demand tabs, support for vertical tabs, and support for tab keyboard navigation. I want to thank the developers on the Superexpert team for all of the hard work which they put into this release.

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• Security exception in Twitterizer

  - by Raghu

  Hi, We are using Twitterizer for Twitter integration to get the Tweets details. When making call to the method OAuthUtility.GetRequestToken, following exception is coming. System.Security.SecurityException: Request for the permission of type 'System.Net.WebPermission, System, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089' failed. When the application is hosted on IIS 5, the application works fine and the above error is coming only when the application is hosted in IIS 7 on Windows 2008 R2. and the method OAuthUtility.GetRequestToken throws above exception. It seems the issue is something with code access security. Please suggest what kind of permissions should be given to fix the security exception. The application has the Full Trust and I have even tried by registering the Twitterizer DLL in GAC and still the same error is coming. I am not sure what makes the difference between IIS 5 and IIS 7 with regards to code access security to cause that exception. Following is the stack track of the exception. [SecurityException: Request for the permission of type 'System.Net.WebPermission, System, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089' failed.] System.Security.CodeAccessSecurityEngine.Check(Object demand, StackCrawlMark& stackMark, Boolean isPermSet) +0 System.Security.CodeAccessPermission.Demand() +54 Twitterizer.OAuthUtility.ExecuteRequest(String baseUrl, Dictionary`2 parameters, HTTPVerb verb, String consumerKey, String consumerSecret, String token, String tokenSecret, WebProxy proxy) +224 Twitterizer.OAuthUtility.GetRequestToken(String consumerKey, String consumerSecret, String callbackAddress, WebProxy proxy) +238 Twitter._Default.btnSubmit_Click(Object sender, EventArgs e) +94 System.Web.UI.WebControls.Button.OnClick(EventArgs e) +115 System.Web.UI.WebControls.Button.RaisePostBackEvent(String eventArgument) +140 System.Web.UI.Page.RaisePostBackEvent(IPostBackEventHandler sourceControl, String eventArgument) +29 System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) +11045655 System.Web.UI.Page.ProcessRequest(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) +11045194 System.Web.UI.Page.ProcessRequest() +91 System.Web.UI.Page.ProcessRequest(HttpContext context) +240 ASP.authorization_aspx.ProcessRequest(HttpContext context) in c:\Windows\Microsoft.NET\Framework64\v2.0.50727\Temporary ASP.NET Files\twitter\c2fd5853\dcb96ae9\App_Web_y_ada-ix.0.cs:0 System.Web.CallHandlerExecutionStep.System.Web.HttpApplication.IExecutionStep.Execute() +599 System.Web.HttpApplication.ExecuteStep(IExecutionStep step, Boolean& completedSynchronously) +171 Any help would be greatly appreciated. Thanks in advance. Regards, Raghu

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