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  • Distributed and/or Parallel SSIS processing

    - by Jeff
    Background: Our company hosts SaaS DSS applications, where clients provide us data Daily and/or Weekly, which we process & merge into their existing database. During business hours, load in the servers are pretty minimal as it's mostly users running simple pre-defined queries via the website, or running drill-through reports that mostly hit the SSAS OLAP cube. I manage the IT Operations Team, and so far this has presented an interesting "scaling" issue for us. For our daily-refreshed clients, the server is only "busy" for about 4-6 hrs at night. For our weekly-refresh clients, the server is only "busy" for maybe 8-10 hrs per week! We've done our best to use some simple methods of distributing the load by spreading the daily clients evenly among the servers such that we're not trying to process daily clients back-to-back over night. But long-term this scaling strategy creates two notable issues. First, it's going to consume a pretty immense amount of hardware that sits idle for large periods of time. Second, it takes significant Production Support over-head to basically "schedule" the ETL such that they don't over-lap, and move clients/schedules around if they out-grow the resources on a particular server or allocated time-slot. As the title would imply, one option we've tried is running multiple SSIS packages in parallel, but in most cases this has yielded VERY inconsistent results. The most common failures are DTExec, SQL, and SSAS fighting for physical memory and throwing out-of-memory errors, and ETLs running 3,4,5x longer than expected. So from my practical experience thus far, it seems like running multiple ETL packages on the same hardware isn't a good idea, but I can't be the first person that doesn't want to scale multiple ETLs around manual scheduling, and sequential processing. One option we've considered is virtualizing the servers, which obviously doesn't give you any additional resources, but moves the resource contention onto the hypervisor, which (from my experience) seems to manage simultaneous CPU/RAM/Disk I/O a little more gracefully than letting DTExec, SQL, and SSAS battle it out within Windows. Question to the forum: So my question to the forum is, are we missing something obvious here? Are there tools out there that can help manage running multiple SSIS packages on the same hardware? Would it be more "efficient" in terms of parallel execution if instead of running DTExec, SQL, and SSAS same machine (with every machine running that configuration), we run in pairs of three machines with SSIS running on one machine, SQL on another, and SSAS on a third? Obviously that would only make sense if we could process more than the three ETL we were able to process on the machine independently. Another option we've considered is completely re-architecting our SSIS package to have one "master" package for all clients that attempts to intelligently chose a server based off how "busy" it already is in terms of CPU/Memory/Disk utilization, but that would be a herculean effort, and seems like we're trying to reinvent something that you would think someone would sell (although I haven't had any luck finding it). So in summary, are we missing an obvious solution for this, and does anyone know if any tools (for free or for purchase, doesn't matter) that facilitate running multiple SSIS ETL packages in parallel and on multiple servers? (What I would call a "queue & node based" system, but that's not an official term). Ultimately VMWare's Distributed Resource Scheduler addresses this as you simply run a consistent number of clients per VM that you know will never conflict scheduleing-wise, then leave it up to VMWare to move the VMs around to balance out hardware usage. I'm definitely not against using VMWare to do this, but since we're a 100% Microsoft app stack, it seems like -someone- out there would have solved this problem at the application layer instead of the hypervisor layer by checking on resource utilization at the OS, SQL, SSAS levels. I'm open to ANY discussion on this, and remember no suggestion is too crazy or radical! :-) Right now, VMWare is the only option we've found to get away from "manually" balancing our resources, so any suggestions that leave us on a pure Microsoft stack would be great. Thanks guys, Jeff

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  • How to obtain a random sub-datatable from another data table

    - by developerit
    Introduction In this article, I’ll show how to get a random subset of data from a DataTable. This is useful when you already have queries that are filtered correctly but returns all the rows. Analysis I came across this situation when I wanted to display a random tag cloud. I already had the query to get the keywords ordered by number of clicks and I wanted to created a tag cloud. Tags that are the most popular should have more chance to get picked and should be displayed larger than less popular ones. Implementation In this code snippet, there is everything you need. ' Min size, in pixel for the tag Private Const MIN_FONT_SIZE As Integer = 9 ' Max size, in pixel for the tag Private Const MAX_FONT_SIZE As Integer = 14 ' Basic function that retreives Tags from a DataBase Public Shared Function GetTags() As MediasTagsDataTable ' Simple call to the TableAdapter, to get the Tags ordered by number of clicks Dim dt As MediasTagsDataTable = taMediasTags.GetDataValide ' If the query returned no result, return an empty DataTable If dt Is Nothing OrElse dt.Rows.Count < 1 Then Return New MediasTagsDataTable End If ' Set the font-size of the group of data ' We are dividing our results into sub set, according to their number of clicks ' Example: 10 results -> [0,2] will get font size 9, [3,5] will get font size 10, [6,8] wil get 11, ... ' This is the number of elements in one group Dim groupLenth As Integer = CType(Math.Floor(dt.Rows.Count / (MAX_FONT_SIZE - MIN_FONT_SIZE)), Integer) ' Counter of elements in the same group Dim counter As Integer = 0 ' Counter of groups Dim groupCounter As Integer = 0 ' Loop througt the list For Each row As MediasTagsRow In dt ' Set the font-size in a custom column row.c_FontSize = MIN_FONT_SIZE + groupCounter ' Increment the counter counter += 1 ' If the group counter is less than the counter If groupLenth <= counter Then ' Start a new group counter = 0 groupCounter += 1 End If Next ' Return the new DataTable with font-size Return dt End Function ' Function that generate the random sub set Public Shared Function GetRandomSampleTags(ByVal KeyCount As Integer) As MediasTagsDataTable ' Get the data Dim dt As MediasTagsDataTable = GetTags() ' Create a new DataTable that will contains the random set Dim rep As MediasTagsDataTable = New MediasTagsDataTable ' Count the number of row in the new DataTable Dim count As Integer = 0 ' Random number generator Dim rand As New Random() While count < KeyCount Randomize() ' Pick a random row Dim r As Integer = rand.Next(0, dt.Rows.Count - 1) Dim tmpRow As MediasTagsRow = dt(r) ' Import it into the new DataTable rep.ImportRow(tmpRow) ' Remove it from the old one, to be sure not to pick it again dt.Rows.RemoveAt(r) ' Increment the counter count += 1 End While ' Return the new sub set Return rep End Function Pro’s This method is good because it doesn’t require much work to get it work fast. It is a good concept when you are working with small tables, let says less than 100 records. Con’s If you have more than 100 records, out of memory exception may occur since we are coping and duplicating rows. I would consider using a stored procedure instead.

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  • SQL SERVER – Out of the Box – Activty and Performance Reports from SSSMS

    - by pinaldave
    SQL Server management Studio 2008 is wonderful tool and has many different features. Many times, an average user does not use them as they are not aware about these features. Today, we will learn one such feature. SSMS comes with many inbuilt performance and activity reports, but we do not use it to the full potential. Let us see how we can access these standard reports. Connect to SQL Server Node >> Right Click on it >> Go to Reports >> Click on Standard Reports >> Pick Any Report. Click to Enlarge You can see there are many reports, which an average users needs right away, are available there. Let me list all the reports available. Server Dashboard Configuration Changes History Schema Changes History Scheduler Health Memory Consumption Activity – All Blocking Transactions Activity – All Cursors Activity – All Sessions Activity – Top Sessions Activity – Dormant Sessions Activity -  Top Connections Top Transactions by Age Top Transactions by Blocked Transactions Count Top Transactions by Locks Count Performance – Batch Execution Statistics Performance – Object Execution Statistics Performance – Top Queries by Average CPU Time Performance – Top Queries by Average IO Performance – Top Queries by Total CPU Time Performance – Top Queries by Total IO Service Broker Statistics Transactions Log Shipping Status In fact, when you look at the above list, it is fairly clear that they are very thought out and commonly needed reports that are available in SQL Server 2008. Let us run a couple of reports and observe their result. Performance – Top Queries by Total CPU Time Click to Enlarge Memory Consumption Click to Enlarge There are options for custom reports as well, which we can configure. We will learn about them in some other post. Additionally, you can right click on the reports and export in Excel or PDF. I think this tool can really help those who are just looking for some quick details. Does any of you use this feature, or this feature has some limitations and You would like to see more features? Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology

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  • HTC to launch Windows 7 phone in India

    - by samsudeen
    It is a good news for the Indian smart phone users as the wait is finally over for Windows 7 mobile.The Taiwanese  mobile giant HTC is all set to release its Windows 7 based Smartphone series in India from January. HTC HD7 & HTC Mozart , the two smart phones running on Windows 7 OS started appearing on the HTC Indian website (HTC India) from last week.Though Flip kart (Indian online e-commerce website)  has started getting pre -orders for HTC HD7 a month ago , the buzz has started from last week after the introduction of “HTC Mozart”. The complete feature comparison between both the smart phones is given below. Feature Comparison HTC Mozart HTC HD 7 Microsoft Windows 7 Microsoft Windows 7 Qualcomm Snapdragon Processor QSD 8250 1 GHz CPU Qualcomm Snapdragon Processor QSD 8250 1 GHz CPU 8MegaPixel camera with Xenon Flash 5 MP, 2592?1944 pixels, autofocus, dual-LED flash, 480 x 800 pixels, 3.7 inches 480 x 800 pixels, 4.3 inches 11.9mm thick and Weighs 130g 11.2 mm thick and Weighs 162 g Bluetooth 2.1 Bluetooth 2.1 8 GB of internal storage memory 8 GB of internal storage memory 512MB of ROM and 576 of RAM 512MB of ROM and 576 of RAM 3G HSDPA 7.2 Mbps and HSUPA 2 Mbps 3G HSDPA 7.2 Mbps; HSUPA 2 Mbps Wi-Fi 802.11 b/g/n Wi-Fi 802.11 b/g/n Micro-USB interconnector Micro-USB interconnector 3.5mm audio jack 3.5mm audio jack GPS antenna GPS antenna Standard battery Li-Po 1300 MA Standard battery, Li-Ion 1230 MA Standby 360 h (2G) up to 435 h (3G) Up to 310 h (2G) / Up to 320 h (3G) Talk time Up to 6 h 40 min (2G) and 5 h 30 min (3G) Up to 6 h 20 min (2G) / Up to 5 h 20 min (3G) Estimated Price “HTC HD 7″ is priced between  INR 27855 to 32000. though the price of “HDT Mozart” is officially not announced it is estimated to be around INR 30000. Where to Buy The Windows 7 phone is not yet available in stores directly, but most of the leading mobile stores are getting pre -orders. I have given some of the online store links below. Flip kart UniverCell This article titled,HTC to launch Windows 7 phone in India, was originally published at Tech Dreams. Grab our rss feed or fan us on Facebook to get updates from us.

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  • The best algorithm enhancing alpha-beta?

    - by Risa
    I'm studying AI. My teacher gave us source code of a chess-like game and asked us to enhance it. My exercise is to improve the alpha/beta algorithm implementing in that game. The programmer already uses transposition tables, MTD(f) with alpha/beta+memory (MTD(f) is the best algorithm I know by far). So is there any better algorithm to enhance alpha-beta search or a good way to implement MTD(f) in coding a game?

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  • Looking ahead at 2011-with Gartner

    - by andrea.mulder
    Speaking of forecasting the future. Gartner highlighted the top 10 technologies and trends that will be strategic for most organizations in 2011. While Gartner's predictions are not specific to CRM, you just cannot help but notice some of the common themes in store for 2011. The top 10 strategic technologies for 2011 include: Cloud Computing Mobile Applications and Media Tablets Social Communications and Collaborations Video Next Generation Analytics Social Analytics Context-Aware Computing Storage Class Memory Ubiquitous Computing Fabric-Based Infrastructure and Computers

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  • SSIS - XML Source Script

    - by simonsabin
    The XML Source in SSIS is great if you have a 1 to 1 mapping between entity and table. You can do more complex mapping but it becomes very messy and won't perform. What other options do you have? The challenge with XML processing is to not need a huge amount of memory. I remember using the early versions of Biztalk with loaded the whole document into memory to map from one document type to another. This was fine for small documents but was an absolute killer for large documents. You therefore need a streaming approach. For flexibility however you want to be able to generate your rows easily, and if you've ever used the XmlReader you will know its ugly code to write. That brings me on to LINQ. The is an implementation of LINQ over XML which is really nice. You can write nice LINQ queries instead of the XMLReader stuff. The downside is that by default LINQ to XML requires a whole XML document to work with. No streaming. Your code would look like this. We create an XDocument and then enumerate over a set of annoymous types we generate from our LINQ statement XDocument x = XDocument.Load("C:\\TEMP\\CustomerOrders-Attribute.xml");   foreach (var xdata in (from customer in x.Elements("OrderInterface").Elements("Customer")                        from order in customer.Elements("Orders").Elements("Order")                        select new { Account = customer.Attribute("AccountNumber").Value                                   , OrderDate = order.Attribute("OrderDate").Value }                        )) {     Output0Buffer.AddRow();     Output0Buffer.AccountNumber = xdata.Account;     Output0Buffer.OrderDate = Convert.ToDateTime(xdata.OrderDate); } As I said the downside to this is that you are loading the whole document into memory. I did some googling and came across some helpful videos from a nice UK DPE Mike Taulty http://www.microsoft.com/uk/msdn/screencasts/screencast/289/LINQ-to-XML-Streaming-In-Large-Documents.aspx. Which show you how you can combine LINQ and the XmlReader to get a semi streaming approach. I took what he did and implemented it in SSIS. What I found odd was that when I ran it I got different numbers between using the streamed and non streamed versions. I found the cause was a little bug in Mikes code that causes the pointer in the XmlReader to progress past the start of the element and thus foreach (var xdata in (from customer in StreamReader("C:\\TEMP\\CustomerOrders-Attribute.xml","Customer")                                from order in customer.Elements("Orders").Elements("Order")                                select new { Account = customer.Attribute("AccountNumber").Value                                           , OrderDate = order.Attribute("OrderDate").Value }                                ))         {             Output0Buffer.AddRow();             Output0Buffer.AccountNumber = xdata.Account;             Output0Buffer.OrderDate = Convert.ToDateTime(xdata.OrderDate);         } These look very similiar and they are the key element is the method we are calling, StreamReader. This method is what gives us streaming, what it does is return a enumerable list of elements, because of the way that LINQ works this results in the data being streamed in. static IEnumerable<XElement> StreamReader(String filename, string elementName) {     using (XmlReader xr = XmlReader.Create(filename))     {         xr.MoveToContent();         while (xr.Read()) //Reads the first element         {             while (xr.NodeType == XmlNodeType.Element && xr.Name == elementName)             {                 XElement node = (XElement)XElement.ReadFrom(xr);                   yield return node;             }         }         xr.Close();     } } This code is specifically designed to return a list of the elements with a specific name. The first Read reads the root element and then the inner while loop checks to see if the current element is the type we want. If not we do the xr.Read() again until we find the element type we want. We then use the neat function XElement.ReadFrom to read an element and all its sub elements into an XElement. This is what is returned and can be consumed by the LINQ statement. Essentially once one element has been read we need to check if we are still on the same element type and name (the inner loop) This was Mikes mistake, if we called .Read again we would advance the XmlReader beyond the start of the Element and so the ReadFrom method wouldn't work. So with the code above you can use what ever LINQ statement you like to flatten your XML into the rowsets you want. You could even have multiple outputs and generate your own surrogate keys.        

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  • Mark Hurd and Balaji Yelamanchili present Oracle’s Business Analytics Strategy

    - by swalker
    Join Mark Hurd and Balaji Yelamanchili as they unveil the latest advances in Oracle’s strategy for placing analytics into the hands of every decision-makers—so that they can see more, think smarter, and act faster. Wednesday, April 4, 2012 at 1.0 pm UK BST / 2.0 pm CET Register HERE today for this online event Agenda Keynote: Oracle’s Business Analytics StrategyMark Hurd, President, Oracle, and Balaji Yelamanchili, Senior Vice President, Analytics and Performance Management, Oracle Plus Breakout Sessions: Achieving Predictable Performance with Oracle Hyperion Enterprise Performance Managemen Explore All Relevant Data—Introducing Oracle Endeca Information Discovery Run Your Business Faster and Smarter with Oracle Business Intelligence Applications on Oracle Exalytics In-Memory Machine Analyzing and Deciding with Big Data

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  • Refreshing Your PC Won’t Help: Why Bloatware is Still a Problem on Windows 8

    - by Chris Hoffman
    Bloatware is still a big problem on new Windows 8 and 8.1 PCs. Some websites will tell you that you can easily get rid of manufacturer-installed bloatware with Windows 8′s Reset feature, but they’re generally wrong. This junk software often turns the process of powering on your new PC from what could be a delightful experience into a tedious slog, forcing you to spend hours cleaning up your new PC before you can enjoy it. Why Refreshing Your PC (Probably) Won’t Help Manufacturers install software along with Windows on their new PCs. In addition to hardware drivers that allow the PC’s hardware to work properly, they install more questionable things like trial antivirus software and other nagware. Much of this software runs at boot, cluttering the system tray and slowing down boot times, often dramatically. Software companies pay computer manufacturers to include this stuff. It’s installed to make the PC manufacturer money at the cost of making the Windows computer worse for actual users. Windows 8 includes “Refresh Your PC” and “Reset Your PC” features that allow Windows users to quickly get their computers back to a fresh state. It’s essentially a quick, streamlined way of reinstalling Windows.  If you install Windows 8 or 8.1 yourself, the Refresh operation will give your PC a clean Windows system without any additional third-party software. However, Microsoft allows computer manufacturers to customize their Refresh images. In other words, most computer manufacturers will build their drivers, bloatware, and other system customizations into the Refresh image. When you Refresh your computer, you’ll just get back to the factory-provided system complete with bloatware. It’s possible that some computer manufacturers aren’t building bloatware into their refresh images in this way. It’s also possible that, when Windows 8 came out, some computer manufacturer didn’t realize they could do this and that refreshing a new PC would strip the bloatware. However, on most Windows 8 and 8.1 PCs, you’ll probably see bloatware come back when you refresh your PC. It’s easy to understand how PC manufacturers do this. You can create your own Refresh images on Windows 8 and 8.1 with just a simple command, replacing Microsoft’s image with a customized one. Manufacturers can install their own refresh images in the same way. Microsoft doesn’t lock down the Refresh feature. Desktop Bloatware is Still Around, Even on Tablets! Not only is typical Windows desktop bloatware not gone, it has tagged along with Windows as it moves to new form factors. Every Windows tablet currently on the market — aside from Microsoft’s own Surface and Surface 2 tablets — runs on a standard Intel x86 chip. This means that every Windows 8 and 8.1 tablet you see in stores has a full desktop with the capability to run desktop software. Even if that tablet doesn’t come with a keyboard, it’s likely that the manufacturer has preinstalled bloatware on the tablet’s desktop. Yes, that means that your Windows tablet will be slower to boot and have less memory because junk and nagging software will be on its desktop and in its system tray. Microsoft considers tablets to be PCs, and PC manufacturers love installing their bloatware. If you pick up a Windows tablet, don’t be surprised if you have to deal with desktop bloatware on it. Microsoft Surfaces and Signature PCs Microsoft is now selling their own Surface PCs that they built themselves — they’re now a “devices and services” company after all, not a software company. One of the nice things about Microsoft’s Surface PCs is that they’re free of the typical bloatware. Microsoft won’t take money from Norton to include nagging software that worsens the experience. If you pick up a Surface device that provides Windows 8.1 and 8 as Microsoft intended it — or install a fresh Windows 8.1 or 8 system — you won’t see any bloatware. Microsoft is also continuing their Signature program. New PCs purchased from Microsoft’s official stores are considered “Signature PCs” and don’t have the typical bloatware. For example, the same laptop could be full of bloatware in a traditional computer store and clean, without the nasty bloatware when purchased from a Microsoft Store. Microsoft will also continue to charge you $99 if you want them to remove your computer’s bloatware for you — that’s the more questionable part of the Signature program. Windows 8 App Bloatware is an Improvement There’s a new type of bloatware on new Windows 8 systems, which is thankfully less harmful. This is bloatware in the form of included “Windows 8-style”, “Store-style”, or “Modern” apps in the new, tiled interface. For example, Amazon may pay a computer manufacturer to include the Amazon Kindle app from the Windows Store. (The manufacturer may also just receive a cut of book sales for including it. We’re not sure how the revenue sharing works — but it’s clear PC manufacturers are getting money from Amazon.) The manufacturer will then install the Amazon Kindle app from the Windows Store by default. This included software is technically some amount of clutter, but it doesn’t cause the problems older types of bloatware does. It won’t automatically load and delay your computer’s startup process, clutter your system tray, or take up memory while you’re using your computer. For this reason, a shift to including new-style apps as bloatware is a definite improvement over older styles of bloatware. Unfortunately, this type of bloatware has not replaced traditional desktop bloatware, and new Windows PCs will generally have both. Windows RT is Immune to Typical Bloatware, But… Microsoft’s Windows RT can’t run Microsoft desktop software, so it’s immune to traditional bloatware. Just as you can’t install your own desktop programs on it, the Windows RT device’s manufacturer can’t install their own desktop bloatware. While Windows RT could be an antidote to bloatware, this advantage comes at the cost of being able to install any type of desktop software at all. Windows RT has also seemingly failed — while a variety of manufacturers came out with their own Windows RT devices when Windows 8 was first released, they’ve all since been withdrawn from the market. Manufacturers who created Windows RT devices have criticized it in the media and stated they have no plans to produce any future Windows RT devices. The only Windows RT devices still on the market are Microsoft’s Surface (originally named Surface RT) and Surface 2. Nokia is also coming out with their own Windows RT tablet, but they’re in the process of being purchased by Microsoft. In other words, Windows RT just isn’t a factor when it comes to bloatware — you wouldn’t get a Windows RT device unless you purchased a Surface, but those wouldn’t come with bloatware anyway. Removing Bloatware or Reinstalling Windows 8.1 While bloatware is still a problem on new Windows systems and the Refresh option probably won’t help you, you can still eliminate bloatware in the traditional way. Bloatware can be uninstalled from the Windows Control Panel or with a dedicated removal tool like PC Decrapifier, which tries to automatically uninstall the junk for you. You can also do what Windows geeks have always tended to do with new computers — reinstall Windows 8 or 8.1 from scratch with installation media from Microsoft. You’ll get a clean Windows system and you can install only the hardware drivers and other software you need. Unfortunately, bloatware is still a big problem for Windows PCs. Windows 8 tries to do some things to address bloatware, but it ultimately comes up short. Most Windows PCs sold in most stores to most people will still have the typical bloatware slowing down the boot process, wasting memory, and adding clutter. Image Credit: LG on Flickr, Intel Free Press on Flickr, Wilson Hui on Flickr, Intel Free Press on Flickr, Vernon Chan on Flickr     

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  • Psychonauts crashes right after entering load save door

    - by user67974
    Psychonauts crashes right after entering the 'Load Save' door. Here is the terminal output: Shader assembly time: 0.88 seconds Found OpenAL device: 'Simple Directmedia Layer' Found OpenAL device: 'ALSA Software' Found OpenAL device: 'OSS Software' Found OpenAL device: 'PulseAudio Software' Opened OpenAL Device: '(null)' ERROR: CAudioDrv::CAudioDrv->alGenSources reports AL_INVALID_VALUE error. PSYCHONAUTS UNIX FILENAME: corrected 'workresource/sounds/commonfx.isb' to 'WorkResource/Sounds/commonfx.isb' PSYCHONAUTS UNIX FILENAME: corrected 'workresource/sounds/commonvoice.isb' to 'WorkResource/Sounds/commonvoice.isb' PSYCHONAUTS UNIX FILENAME: corrected 'workresource/sounds/commonmusic.isb' to 'WorkResource/Sounds/commonmusic.isb' PSYCHONAUTS UNIX FILENAME: corrected 'workresource/sounds/commonmentalfx.isb' to 'WorkResource/Sounds/commonmentalfx.isb' PSYCHONAUTS UNIX FILENAME: corrected 'workresource/sounds/commonmenfxmem.isb' to 'WorkResource/Sounds/commonmenfxmem.isb' PSYCHONAUTS UNIX FILENAME: corrected 'workresource/sounds/commonfxmem.isb' to 'WorkResource/Sounds/commonfxmem.isb' GameApp::StartUp InitSoundFiles() completed in 0.15 seconds GameApp::StartUp Load some common textures completed in 0.00 seconds WARN: ENGINE: Lua garbage collection starting FreeUnusedBlocksInBuckets released 0 Kb GameApp::StartUp InitEntities() completed in 0.02 seconds PSYCHONAUTS UNIX FILENAME: corrected 'WorkResource/SavedGames/savegameprefs.ini' to 'WorkResource/SAVEDGAMES/savegameprefs.ini' PSYCHONAUTS UNIX FILENAME: corrected 'WorkResource/SavedGames/savegameprefs.ini' to 'WorkResource/SAVEDGAMES/savegameprefs.ini' GameApp::StartUp m_pSaveLoadInterface->Startup() completed in 0.00 seconds GameApp::StartUp m_UserInterface.Setup() completed in 0.00 seconds STUBBED: multisample at EDisplayOptionsWidget (/home/icculus/projects/psychonauts/Source/game/luatest/Game/UIPCDisplayOptions.cpp:97) STUBBED: VK_* at CheckVirtualKey (/home/icculus/projects/psychonauts/Source/CommonLibs/DirectX/SDLInput.cpp:1443) Game: Engine Running hook startup Game: Engine -> SetupGlobalObjects Game: Engine -> SetupLevelMenu Game: Engine -> InitMath GameApp::StartUp InitLua2() completed in 0.00 seconds GameApp::StartUp SetupLevelMenu() completed in 0.00 seconds STUBBED: do we even use this? at InitSocket (/home/icculus/projects/psychonauts/Source/game/luatest/Game/Gameplaylogger.cpp:210) GameApp::StartUp Post-Install total completed in 0.20 seconds Start Up completed in 1.57 seconds UnixMain: StartUp successful.. Working directory: /opt/psychonauts STUBBED: dispatch SDL events at PCMainHandleAnyWindowsMessages (/home/icculus/projects/psychonauts/Source/game/luatest/UnixMain.cpp:56) STUBBED: write me at GetJoystickInput (/home/icculus/projects/psychonauts/Source/CommonLibs/DirectX/SDLInput.cpp:428) STUBBED: write me at GetJoystickActionValue (/home/icculus/projects/psychonauts/Source/CommonLibs/DirectX/SDLInput.cpp:613) PSYCHONAUTS UNIX FILENAME: corrected 'workresource/cutScenes/prerendered/dflogo.bik' to 'WorkResource/cutscenes/prerendered/DFLogo.bik' Prerender subtitle file: workresource\cutScenes\prerendered\dflogo.dfs not found PSYCHONAUTS UNIX FILENAME: corrected 'workresource/cutScenes/prerendered/dflogo.bik' to 'WorkResource/cutscenes/prerendered/DFLogo.bik' STUBBED: fixed function pipeline? at setColorOp (/home/icculus/projects/psychonauts/Source/CommonLibs/DFGraphics/Texture.cpp:2097) STUBBED: fixed function pipeline? at setColorArg1 (/home/icculus/projects/psychonauts/Source/CommonLibs/DFGraphics/Texture.cpp:2106) STUBBED: fixed function pipeline? at setColorArg2 (/home/icculus/projects/psychonauts/Source/CommonLibs/DFGraphics/Texture.cpp:2115) STUBBED: fixed function pipeline? at setAlphaOp (/home/icculus/projects/psychonauts/Source/CommonLibs/DFGraphics/Texture.cpp:2124) STUBBED: fixed function pipeline? at setAlphaArg1 (/home/icculus/projects/psychonauts/Source/CommonLibs/DFGraphics/Texture.cpp:2133) STUBBED: fixed function pipeline? at setAlphaArg2 (/home/icculus/projects/psychonauts/Source/CommonLibs/DFGraphics/Texture.cpp:2142) STUBBED: fixed function pipeline? at setProjected (/home/icculus/projects/psychonauts/Source/CommonLibs/DFGraphics/Texture.cpp:2223) LOC WARN: Could not open Localization file 'Localization/English/_StringTable.lub' STUBBED: memory status at UpdateMemoryTracking (/home/icculus/projects/psychonauts/Source/game/luatest/Game/GameApp.cpp:4884) WARN: Couldn't resize array to 128; out-of-bounds elements are still in use: Vertex Pool, 188 Loading new level 'STMU' STUBBED: Need multithreaded GL at DisplayLoadingScreen (/home/icculus/projects/psychonauts/Source/game/luatest/Game/LoadingScreen.cpp:83) ========================= Memory post unload level ========================= ========================= LOC WARN: Could not open Localization file 'Localization/English/ST_StringTable.lub' DaveD: Info: Texture pack file contains 137 textures Doing a texture readback for locking! Game: Engine Saved[GLOBAL]: InstaHintFord_HostileRecord = [table] Game: Engine Saved[GLOBAL]: InstaHintFord_HostileOrder = [table] WARN: Redundant packfile read: anims\thought_bubble\bubblefirestarting.jan WARN: Redundant packfile read: anims\thought_bubble\bubbleintothemind.jan WARN: Redundant packfile read: anims\thought_bubble\bubbleinvisibility.jan WARN: Redundant packfile read: anims\thought_bubble\bubblepopperfill.jan WARN: Redundant packfile read: anims\thought_bubble\bubbletelekinesis.jan Initializing level script (if there is one) PSYCHONAUTS UNIX FILENAME: corrected 'workresource/sounds/stfx.isb' to 'WorkResource/Sounds/stfx.isb' Game: Engine Reloading goals: Game: Engine Saved[GLOBAL]: NextEncouragement = '/GLZF014TO/ 10' Game: Engine Saved[GLOBAL]: bUsedSalts = 0 Game: Engine Saved[GLOBAL]: bSTEntered = 1 Game: Engine Saved[GLOBAL]: memoriesST = 1 Game: Engine Saved[GLOBAL]: PsiBallColor = 'red' Game: Engine Saved[ST]: lastSubLevel = 'STMU' Game: Engine LOADING LEVEL st.STMU Game: Engine Saved[CA]: CALevelState = 1 Game: Engine Cutscene progression: CS Script moving from state nil to state nil, resultant state nil. Time: 0.124746672809124. * Stack Trace 1: (null) (line -1, file '(none)) () 2: SpawnScript (line -1, file 'C) (global) 3: onBeginLevel (line -1, file '(none)) (field) 4: (null) (line -1, file '(none)) () WARN: Cannot call GetDirectoryListing when running from the DVD Game: Engine Raz spawning at DartStart startpoint VM : LevelScript could not find script 'doorrimlight1' * Stack Trace 1: (null) (line -1, file '(none)) () WARN: (none(-1) SetEntityAlpha LevelScript: NULL script object passed Game: Engine Saved[GLOBAL]: bLoadedFromMainMenu = 1 Game: Engine Saved[GLOBAL]: NextEncouragement = '/GLZF014TO/ 10' Game: Engine Saved[GLOBAL]: NeedRankIncrement = 0 STUBBED: Need multithreaded GL at HideLoadingScreen (/home/icculus/projects/psychonauts/Source/game/luatest/Game/LoadingScreen.cpp:110) WARN: ENGINE: Lua garbage collection starting FreeUnusedBlocksInBuckets released 0 Kb Game: Engine Saved[GLOBAL]: SplineFigmentTVSizex = 4.51434326171875 Game: Engine Saved[GLOBAL]: SplineFigmentTVSizey = 46.38104248046875 Game: Engine Saved[GLOBAL]: SplineFigmentTVSizez = 47.08810424804688 WARN: (none(-1) SetNewAction LevelScript: no string passed ====================== Asset load progression ====================== Initial: 2.518 MB Vertex, 8.688 MB Texture Level : 3.719 MB Vertex, 22.535 MB Texture Scripts: 3.747 MB Vertex, 22.848 MB Texture ====================== ====================== Memory post level load ====================== ====================== WARN: ENGINE: Lua garbage collection starting FreeUnusedBlocksInBuckets released 0 Kb DaveD: Level loaded in 0.14 seconds Anim: anims\objects\tk_arrow_idle.jan: loaded (1 frames latency) Anim: anims\dartnew\helmet\darthelmetdn.jan: loaded (1 frames latency) Anim: anims\thought_bubble\shieldloop.jan: loaded (1 frames latency) Anim: anims\dartnew\standready.jan: loaded (1 frames latency) Anim: anims\dartnew\walkmove.jan: loaded (1 frames latency) Anim: anims\janitor\hint_end.jan: loaded (1 frames latency) Anim: anims\thought_bubble\ballstatic.jan: loaded (1 frames latency) Anim: anims\dartnew\actionfall.jan: loaded (1 frames latency) Anim: anims\dartnew\standstill.jan: loaded (1 frames latency) Anim: anims\dartnew\pack\packbounce_lf_rt.jan: loaded (1 frames latency) Anim: anims\dartnew\pack\packbounce_up_dn.jan: loaded (1 frames latency) Anim: anims\dartnew\helmet\darthelmetdefpose.jan: loaded (1 frames latency) 1: 1 (number) 1: 1 (number) STUBBED: This is probably wrong at GetDt (/home/icculus/projects/psychonauts/Source/CommonLibs/DFUtil/Profiler.cpp:181) STUBBED: set specular highlights at setSpecularEnable (/home/icculus/projects/psychonauts/Source/CommonLibs/DFGraphics/Renderer.cpp:2035) Anim: anims\dartnew\trnrtcycle.jan: loaded (1 frames latency) Anim: anims\dartnew\run.jan: loaded (1 frames latency) Anim: anims\dartnew\walk.jan: loaded (1 frames latency) Anim: anims\thought_bubble\bubbledoublejump.jan: loaded (1 frames latency) Anim: anims\dartnew\longjump.jan: loaded (1 frames latency) Anim: anims\menubrain\door1crack.jan: loaded (1 frames latency) Anim: anims\menubrain\door1crackedidle.jan: loaded (1 frames latency) Anim: anims\menubrain\door1closedidle.jan: loaded (1 frames latency) Anim: anims\dartnew\180.jan: loaded (1 frames latency) Anim: anims\menubrain\door3crack.jan: loaded (1 frames latency) Anim: anims\menubrain\door3crackedidle.jan: loaded (1 frames latency) Anim: anims\menubrain\door3closedidle.jan: loaded (1 frames latency) Anim: anims\dartnew\railslide45angle.jan: loaded (1 frames latency) Anim: anims\dartnew\railslideflat.jan: loaded (1 frames latency) Anim: anims\dartnew\trnlfcycle.jan: loaded (1 frames latency) WARN: (none(-1) SetNewAction LevelScript: no string passed Anim: anims\dartnew\mainmenu_jump.jan: loaded (1 frames latency) Anim: anims\menubrain\door1open.jan: loaded (1 frames latency) ERROR: Assert in /home/icculus/projects/psychonauts/Source/game/luatest/../../CommonLibs/Include/../DFGraphics/Color.h, line 96 v.x >= 0.0f && v.x <= 1.0f && v.y >= 0.0f && v.y <= 1.0f && v.z >= 0.0f && v.z <= 1.0f && v.w >= 0.0f && v.w <= 1.0f Encountered Error: Psychonauts has encountered an error /home/icculus/projects/psychonauts/Source/game/luatest/../../CommonLibs/Include/../DFGraphics/Color.h, line 96 v.x >= 0.0f && v.x <= 1.0f && v.y >= 0.0f && v.y <= 1.0f && v.z >= 0.0f && v.z <= 1.0f && v.w >= 0.0f && v.w <= 1.0f Please contact technical support at http://www.doublefine.com. I am currently using Bumblebee for hybrid graphics, if that helps in any way.

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  • Sixeyed.Caching available now on NuGet and GitHub!

    - by Elton Stoneman
    Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/22/sixeyed.caching-available-now-on-nuget-and-github.aspxThe good guys at Pluralsight have okayed me to publish my caching framework (as seen in Caching in the .NET Stack: Inside-Out) as an open-source library, and it’s out now. You can get it here: Sixeyed.Caching source code on GitHub, and here: Sixeyed.Caching package v1.0.0 on NuGet. If you haven’t seen the course, there’s a preview here on YouTube: In-Process and Out-of-Process Caches, which gives a good flavour. The library is a wrapper around various cache providers, including the .NET MemoryCache, AppFabric cache, and  memcached*. All the wrappers inherit from a base class which gives you a set of common functionality against all the cache implementations: •    inherits OutputCacheProvider, so you can use your chosen cache provider as an ASP.NET output cache; •    serialization and encryption, so you can configure whether you want your cache items serialized (XML, JSON or binary) and encrypted; •    instrumentation, you can optionally use performance counters to monitor cache attempts and hits, at a low level. The framework wraps up different caches into an ICache interface, and it lets you use a provider directly like this: Cache.Memory.Get<RefData>(refDataKey); - or with configuration to use the default cache provider: Cache.Default.Get<RefData>(refDataKey); The library uses Unity’s interception framework to implement AOP caching, which you can use by flagging methods with the [Cache] attribute: [Cache] public RefData GetItem(string refDataKey) - and you can be more specific on the required cache behaviour: [Cache(CacheType=CacheType.Memory, Days=1] public RefData GetItem(string refDataKey) - or really specific: [Cache(CacheType=CacheType.Disk, SerializationFormat=SerializationFormat.Json, Hours=2, Minutes=59)] public RefData GetItem(string refDataKey) Provided you get instances of classes with cacheable methods from the container, the attributed method results will be cached, and repeated calls will be fetched from the cache. You can also set a bunch of cache defaults in application config, like whether to use encryption and instrumentation, and whether the cache system is enabled at all: <sixeyed.caching enabled="true"> <performanceCounters instrumentCacheTotalCounts="true" instrumentCacheTargetCounts="true" categoryNamePrefix ="Sixeyed.Caching.Tests"/> <encryption enabled="true" key="1234567890abcdef1234567890abcdef" iv="1234567890abcdef"/> <!-- key must be 32 characters, IV must be 16 characters--> </sixeyed.caching> For AOP and methods flagged with the cache attribute, you can override the compile-time cache settings at runtime with more config (keyed by the class and method name): <sixeyed.caching enabled="true"> <targets> <target keyPrefix="MethodLevelCachingStub.GetRandomIntCacheConfiguredInternal" enabled="false"/> <target keyPrefix="MethodLevelCachingStub.GetRandomIntCacheExpiresConfiguredInternal" seconds="1"/> </targets> It’s released under the MIT license, so you can use it freely in your own apps and modify as required. I’ll be adding more content to the GitHub wiki, which will be the main source of documentation, but for now there’s an FAQ to get you started. * - in the course the framework library also wraps NCache Express, but there's no public redistributable library that I can find, so it's not in Sixeyed.Caching.

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  • Converting From CommunityServer to DotNetNuke Intro

    - by Chris Hammond
    ( originally posted on DNNDaily ) So I have been trying to figure out how best to do this blog post for a while now, though I think I will be better off doing it as a series of blog posts rather than one individual one. So this post will be the starting point for the conversion. I will update it with links to the other blog posts in the series as they get created and added. Background (all in my opinion and based on my memory, as inaccurate as that may be) : Back in the early days of ASP.NET there...(read more)

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  • 64-bit 13.10 shows 1GB less RAM than 64-bit 13.04 did

    - by kiloseven
    Multiple 64-bit versions (Kubuntu, Lubuntu and Xubuntu) once installed on my ThinkPad R60 show 3GB of RAM, not the correct 4GB of RAM. Last week with 13.04, I had 4GB of RAM (which matches the BIOS) and this week I have 3GB available. Inquiring minds want to know. Details follow: Linux R60 3.11.0-12-generic #19-Ubuntu SMP Wed Oct 9 16:20:46 UTC 2013 x86_64 x86_64 x86_64 GNU/Linux r60 free -m reports: _ total used free shared buffers cached Mem: 3001 854 2146 0 22 486 -/+ buffers/cache: 346 2655 Swap: 0 0 0 . . . . . . lshw shows: description: Notebook product: 9459AT8 () vendor: LENOVO version: ThinkPad R60/R60i serial: redacted width: 64 bits capabilities: smbios-2.4 dmi-2.4 vsyscall32 configuration: administrator_password=disabled boot=normal chassis=notebook family=ThinkPad R60/R60i frontpanel_password=unknown keyboard_password=disabled power-on_password=disabled uuid=126E4001-48CA-11CB-9D53-B982AE0D1ABB *-core description: Motherboard product: 9459AT8 vendor: LENOVO physical id: 0 version: Not Available *-firmware description: BIOS vendor: LENOVO physical id: 0 version: 7CETC1WW (2.11 ) date: 01/09/2007 size: 144KiB capacity: 1984KiB capabilities: pci pcmcia pnp upgrade shadowing escd cdboot bootselect socketedrom edd acpi usb biosbootspecification {snip} *-memory description: System Memory physical id: 29 slot: System board or motherboard size: 4GiB *-bank:0 description: SODIMM DDR2 Synchronous physical id: 0 slot: DIMM 1 size: 2GiB width: 64 bits *-bank:1 description: SODIMM DDR2 Synchronous physical id: 1 slot: DIMM 2 size: 2GiB width: 64 bits dpkg -l linux-* returns: Desired=Unknown/Install/Remove/Purge/Hold | Status=Not/Inst/Conf-files/Unpacked/halF-conf/Half-inst/trig-aWait/Trig-pend |/ Err?=(none)/Reinst-required (Status,Err: uppercase=bad) ||/ Name Version Description +++-======================================-=======================================-========================================================================== un linux-doc-3.2.0 (no description available) ii linux-firmware 1.79.6 Firmware for Linux kernel drivers ii linux-generic 3.2.0.52.62 Complete Generic Linux kernel un linux-headers (no description available) un linux-headers-3 (no description available) un linux-headers-3.0 (no description available) un linux-headers-3.2.0-23 (no description available) un linux-headers-3.2.0-23-generic (no description available) ii linux-headers-3.2.0-52 3.2.0-52.78 Header files related to Linux kernel version 3.2.0 ii linux-headers-3.2.0-52-generic 3.2.0-52.78 Linux kernel headers for version 3.2.0 on 64 bit x86 SMP ii linux-headers-generic 3.2.0.52.62 Generic Linux kernel headers un linux-image (no description available) un linux-image-3.0 (no description available) ii linux-image-3.2.0-52-generic 3.2.0-52.78 Linux kernel image for version 3.2.0 on 64 bit x86 SMP ii linux-image-generic 3.2.0.52.62 Generic Linux kernel image un linux-initramfs-tool (no description available) un linux-kernel-headers (no description available) un linux-kernel-log-daemon (no description available) ii linux-libc-dev 3.2.0-52.78 Linux Kernel Headers for development un linux-restricted-common (no description available) ii linux-sound-base 1.0.25+dfsg-0ubuntu1.1 base package for ALSA and OSS sound systems un linux-source-3.2.0 (no description available) un linux-tools (no description available)

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  • How to get over “Did I lock the door?” syndrome

    - by Boonei
    I am person who always asks myself  ”Did I lock the house door?”,  And I do ask that question when I have almost reached office. I don’t have a bad memory or I am not a “forget it all after a min person”. Infact I have a fantastic memory of things. This problem has been haunting me for a very long time. My wife used to always have a angry face after we had get down from the car. Because after we have walked for about 20 yards I would run back to the car to check if I had locked the car, you see this problem exists for all locked objects. This happens everyday all round the year. Now a days I don’t have the problem ! I did not get the solution from any doctor or any book that that talks about my inner mind. It was a practical advice given by my aunt….. When I told her that I had this problem, she smiled and said its very very easy to get around this. I was stunned. The solution she gave me was simple. After I had locked the door, should hold the lock and look at it for 5 sec and say to myself   “I have locked the door”. Believe me it works like a charm. The reason why it works is my aunt goes to explain, that your mind always thinks twice of important things that we do on our daily life and raises doubts after sometime. The only way to stop is it by looking at it, holding it and telling yourself that its ok and its done. This holds good for all the things that you generally doubt like, did I turn off the AC?, did I turn off the lights in the house when I left?. Just look at it for 5 sec, hold it tell yourself its done. You will not look back. Image credit [Håkan Dahlström]   This article titled,How to get over “Did I lock the door?” syndrome, was originally published at Tech Dreams. Grab our rss feed or fan us on Facebook to get updates from us.

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  • New Netra SPARC T3 Servers

    - by Ferhat Hatay
    Today at the Mobile World Congress 2011, Oracle announced two new carrier-grade NEBS Level 3- certified servers: Oracle’s Netra SPARC T3-1 rackmount server and Oracle’s Netra SPARC T3-1BA ATCA blade server bringing the performance, scalability and power efficiency of the newest SPARC T3 processor to the communications market.    The Netra SPARC T3-1 server enclosure has a compact 20inch-deep carrier-grade rack-optimized design The new Netra SPARC T3 servers further expand Oracle’s complete portfolio for the communications industry, which includes carrier-grade servers, storage and application software to run operations support systems and service delivery platforms with easy migration capabilities and unmatched investment protection via the binary compatibility guarantee of the Oracle Solaris operating system. With advanced reliability, networking and security features built-in to Oracle Solaris – the most widely deployed carrier-grade OS – the systems announced today are uniquely suited for mission-critical core network infrastructure and service delivery. The world’s first carrier-grade system using the 16-core, 128-thread SPARC T3 processor, the Netra SPARC T3-1 server supports 2x the I/O bandwidth, 2x the memory and is 35 percent faster than the previous generation. With integrated on-chip 10 Gigabit Ethernet, on-chip cryptographic acceleration, and built-in, no-cost Oracle VM Server for SPARC and Oracle Solaris Containers for virtualization, the Netra SPARC T3-1 server is an ideal platform for consolidation, offering 128 virtual systems in a single server. As the next generation Netra SPARC ATCA blade, Netra SPARC T3-1BA ATCA blade server brings the PICMG 3.0 compatibility, NEBS Level 3 Certification, ETSI compliance and the Netra business practices to the customer solution. The Netra SPARC T3-1BA ATCA blade server can be mixed in the Sun Netra CT900 blade chassis with other ATCA UltraSPARC and x86 blades.     The Netra SPARC T3-1BA ATCA blade server   The Netra SPARC T3-1BA ATCA blade server delivers industry-leading scalability, density and cost efficiency with up to 36 SPARC T3 processors (3456 processing threads) in a single rack – a 50 percent increase over the previous generation. The Netra SPARC T3-1BA blade server also offers high-bandwidth and high-capacity I/O, with greater memory capacity to tackle the increasing business demands of the communications industry. For service providers faced with the rapid growth of broadband networks and the dramatic surge in global smartphone adoption, the new Netra SPARC T3 systems deliver continuous availability with massive scalability, tested and certified to run in the harshest conditions. More information Oracle’s Sun Netra Servers Scaling Throughput and Managing TCO with Oracle’s Netra SPARC T3-1 Servers Enabling End-to-End 10 Gigabit Ethernet in Oracle's Sun Netra ATCA Product Family Data Sheet: Netra SPARC T3-1BA ATCA Blade Server Data Sheet: Netra SPARC T3-1 Server Oracle Solaris: The Carrier Grade Operating System

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  • Week 21: FY10 in the Rear View Mirror

    - by sandra.haan
    FY10 is coming to a close and before we dive into FY11 we thought we would take a walk down memory lane and reminisce on some of our favorite Oracle PartnerNetwork activities. June 2009 brought One Red Network to partners offering access to the same virtual kickoff environment used by Oracle employees. It was a new way to deliver valuable content to key stakeholders (and without the 100+ degree temperatures). Speaking of hot, Oracle also announced in June new licensing options for our ISV partners. This model enables an even broader community of ISVs to build, deploy and manage SaaS applications on the same platform. While some people took the summer off, the OPN Program team was working away to deliver a brand new partner program - Oracle PartnerNetwork Specialized - at Oracle OpenWorld in October. Specialized. Recognized. Preferred. If you haven't gotten the message yet, we may need an emergency crew to pull you out from that rock you've been hiding under. But seriously, the announcement at the OPN Forum drew a big crowd and our FY11 event is shaping up to be just as exciting. OPN Specialized was announced in October and opened our doors for enrollment in December 2009. To mark our grand opening we held our first ever social webcast allowing partners from around the world to interact with us live throughout the day. We had a lot of great conversations and really enjoyed the chance to speak with so many of you. After a short holiday break we were back at it - just a small announcement - Oracle's acquisition of Sun. In case you missed it, here is a short field report from Ted Bereswill, SVP North America Alliances & Channels on the partner events to support the announcement: And while we're announcing things - did we mention that both Ted Bereswill and Judson Althoff were named Channel Chiefs by CRN? Not only do we have a couple of Channel Chiefs, but Oracle also won the Partner Program 5 Star Programs Award and took top honors at the CRN Channel Champion Awards for Financial Factors/Financial Performance in the category of Data and Information Management and the and Xchange Solution Provider event in March 2010. We actually caught up with Judson at this event for a quick recap of our participation: But awards aside, let's not forget our main focus in FY10 and that is Specialization. In April we announced that we had over 35 Specializations available for partners and a plan to deliver even more in FY11. We are just days away from the end of FY10 but hope you enjoyed our walk down memory lane. We are already planning lots of activity for our partners in FY11 starting with our Partner Kickoff event on June 29th. Join us to hear the vision and strategy for FY11 and interact with regional A&C leaders. We look forward to talking with you then. The OPN Communications Team

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  • How Assassin’s Creed Should Have Ended [Video]

    - by Asian Angel
    Altair is on the run yet again from Italy’s finest and keeps managing to hide in plain sight. But will his luck hold out or will his final attempt to escape end in tragedy? How It Should Have Ended: Video…: Assassin’s Creed [via Dorkly Bits] How To Properly Scan a Photograph (And Get An Even Better Image) The HTG Guide to Hiding Your Data in a TrueCrypt Hidden Volume Make Your Own Windows 8 Start Button with Zero Memory Usage

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  • MySQL – Scalability on Amazon RDS: Scale out to multiple RDS instances

    - by Pinal Dave
    Today, I’d like to discuss getting better MySQL scalability on Amazon RDS. The question of the day: “What can you do when a MySQL database needs to scale write-intensive workloads beyond the capabilities of the largest available machine on Amazon RDS?” Let’s take a look. In a typical EC2/RDS set-up, users connect to app servers from their mobile devices and tablets, computers, browsers, etc.  Then app servers connect to an RDS instance (web/cloud services) and in some cases they might leverage some read-only replicas.   Figure 1. A typical RDS instance is a single-instance database, with read replicas.  This is not very good at handling high write-based throughput. As your application becomes more popular you can expect an increasing number of users, more transactions, and more accumulated data.  User interactions can become more challenging as the application adds more sophisticated capabilities. The result of all this positive activity: your MySQL database will inevitably begin to experience scalability pressures. What can you do? Broadly speaking, there are four options available to improve MySQL scalability on RDS. 1. Larger RDS Instances – If you’re not already using the maximum available RDS instance, you can always scale up – to larger hardware.  Bigger CPUs, more compute power, more memory et cetera. But the largest available RDS instance is still limited.  And they get expensive. “High-Memory Quadruple Extra Large DB Instance”: 68 GB of memory 26 ECUs (8 virtual cores with 3.25 ECUs each) 64-bit platform High I/O Capacity Provisioned IOPS Optimized: 1000Mbps 2. Provisioned IOPs – You can get provisioned IOPs and higher throughput on the I/O level. However, there is a hard limit with a maximum instance size and maximum number of provisioned IOPs you can buy from Amazon and you simply cannot scale beyond these hardware specifications. 3. Leverage Read Replicas – If your application permits, you can leverage read replicas to offload some reads from the master databases. But there are a limited number of replicas you can utilize and Amazon generally requires some modifications to your existing application. And read-replicas don’t help with write-intensive applications. 4. Multiple Database Instances – Amazon offers a fourth option: “You can implement partitioning,thereby spreading your data across multiple database Instances” (Link) However, Amazon does not offer any guidance or facilities to help you with this. “Multiple database instances” is not an RDS feature.  And Amazon doesn’t explain how to implement this idea. In fact, when asked, this is the response on an Amazon forum: Q: Is there any documents that describe the partition DB across multiple RDS? I need to use DB with more 1TB but exist a limitation during the create process, but I read in the any FAQ that you need to partition database, but I don’t find any documents that describe it. A: “DB partitioning/sharding is not an official feature of Amazon RDS or MySQL, but a technique to scale out database by using multiple database instances. The appropriate way to split data depends on the characteristics of the application or data set. Therefore, there is no concrete and specific guidance.” So now what? The answer is to scale out with ScaleBase. Amazon RDS with ScaleBase: What you get – MySQL Scalability! ScaleBase is specifically designed to scale out a single MySQL RDS instance into multiple MySQL instances. Critically, this is accomplished with no changes to your application code.  Your application continues to “see” one database.   ScaleBase does all the work of managing and enforcing an optimized data distribution policy to create multiple MySQL instances. With ScaleBase, data distribution, transactions, concurrency control, and two-phase commit are all 100% transparent and 100% ACID-compliant, so applications, services and tooling continue to interact with your distributed RDS as if it were a single MySQL instance. The result: now you can cost-effectively leverage multiple MySQL RDS instance to scale out write-intensive workloads to an unlimited number of users, transactions, and data. Amazon RDS with ScaleBase: What you keep – Everything! And how does this change your Amazon environment? 1. Keep your application, unchanged – There is no change your application development life-cycle at all.  You still use your existing development tools, frameworks and libraries.  Application quality assurance and testing cycles stay the same. And, critically, you stay with an ACID-compliant MySQL environment. 2. Keep your RDS value-added services – The value-added services that you rely on are all still available. Amazon will continue to handle database maintenance and updates for you. You can still leverage High Availability via Multi A-Z.  And, if it benefits youra application throughput, you can still use read replicas. 3. Keep your RDS administration – Finally the RDS monitoring and provisioning tools you rely on still work as they did before. With your one large MySQL instance, now split into multiple instances, you can actually use less expensive, smallersmaller available RDS hardware and continue to see better database performance. Conclusion Amazon RDS is a tremendous service, but it doesn’t offer solutions to scale beyond a single MySQL instance. Larger RDS instances get more expensive.  And when you max-out on the available hardware, you’re stuck.  Amazon recommends scaling out your single instance into multiple instances for transaction-intensive apps, but offers no services or guidance to help you. This is where ScaleBase comes in to save the day. It gives you a simple and effective way to create multiple MySQL RDS instances, while removing all the complexities typically caused by “DIY” sharding andwith no changes to your applications . With ScaleBase you continue to leverage the AWS/RDS ecosystem: commodity hardware and value added services like read replicas, multi A-Z, maintenance/updates and administration with monitoring tools and provisioning. SCALEBASE ON AMAZON If you’re curious to try ScaleBase on Amazon, it can be found here – Download NOW. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: MySQL, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Linux Live USB Media

    <b>Jamie's Random Musings:</b> "It is pretty common these days for laptops, and even desktops, to be able to boot from a USB flash memory drive. So you can save a little time and a little money by converting various Linux distributions ISO images to bootable USB devices, rather than burning them to CD/DVD."

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  • The kernel column by Jon Masters #87

    <b>Linux User and Developer:</b> "The past month saw steady progress toward the final 2.6.34 kernel release, including the announcement of initial Release Candidate kernels 2.6.34-rc1 through 2.6.34-rc4. The latter had an interesting virtual memory bug that added a week of delay..."

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  • Week in Geek: Internet Service Providers to Implement New Anti-Piracy Monitoring in July

    - by Asian Angel
    Our latest edition of WIG is filled with news link goodness such as Google’s plans for a Metro version of Chrome, Microsoft’s seeking of a patent for TV-viewing tolls, Encyclopaedia Britannica’s switch to a digital only format, and more. Screenshot by Asian Angel. Make Your Own Windows 8 Start Button with Zero Memory Usage Reader Request: How To Repair Blurry Photos HTG Explains: What Can You Find in an Email Header?

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  • Storage Configuration

    - by jchang
    Storage performance is not inherently complicated subject. The concepts are relatively simple. In fact, scaling storage performance is far easier compared with the difficulties encounters in scaling processor performance in NUMA systems. Storage performance is achieved by properly distributing IO over: 1) multiple independent PCI-E ports (system memory and IO bandwith is key) 2) multiple RAID controllers or host bus adapters (HBAs) 3) multiple storage IO channels (SAS or FC, complete path) most importantly,...(read more)

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  • Scaling-out Your Services by Message Bus based WCF Transport Extension &ndash; Part 1 &ndash; Background

    - by Shaun
    Cloud computing gives us more flexibility on the computing resource, we can provision and deploy an application or service with multiple instances over multiple machines. With the increment of the service instances, how to balance the incoming message and workload would become a new challenge. Currently there are two approaches we can use to pass the incoming messages to the service instances, I would like call them dispatcher mode and pulling mode.   Dispatcher Mode The dispatcher mode introduces a role which takes the responsible to find the best service instance to process the request. The image below describes the sharp of this mode. There are four clients communicate with the service through the underlying transportation. For example, if we are using HTTP the clients might be connecting to the same service URL. On the server side there’s a dispatcher listening on this URL and try to retrieve all messages. When a message came in, the dispatcher will find a proper service instance to process it. There are three mechanism to find the instance: Round-robin: Dispatcher will always send the message to the next instance. For example, if the dispatcher sent the message to instance 2, then the next message will be sent to instance 3, regardless if instance 3 is busy or not at that moment. Random: Dispatcher will find a service instance randomly, and same as the round-robin mode it regardless if the instance is busy or not. Sticky: Dispatcher will send all related messages to the same service instance. This approach always being used if the service methods are state-ful or session-ful. But as you can see, all of these approaches are not really load balanced. The clients will send messages at any time, and each message might take different process duration on the server side. This means in some cases, some of the service instances are very busy while others are almost idle. For example, if we were using round-robin mode, it could be happened that most of the simple task messages were passed to instance 1 while the complex ones were sent to instance 3, even though instance 1 should be idle. This brings some problem in our architecture. The first one is that, the response to the clients might be longer than it should be. As it’s shown in the figure above, message 6 and 9 can be processed by instance 1 or instance 2, but in reality they were dispatched to the busy instance 3 since the dispatcher and round-robin mode. Secondly, if there are many requests came from the clients in a very short period, service instances might be filled by tons of pending tasks and some instances might be crashed. Third, if we are using some cloud platform to host our service instances, for example the Windows Azure, the computing resource is billed by service deployment period instead of the actual CPU usage. This means if any service instance is idle it is wasting our money! Last one, the dispatcher would be the bottleneck of our system since all incoming messages must be routed by the dispatcher. If we are using HTTP or TCP as the transport, the dispatcher would be a network load balance. If we wants more capacity, we have to scale-up, or buy a hardware load balance which is very expensive, as well as scaling-out the service instances. Pulling Mode Pulling mode doesn’t need a dispatcher to route the messages. All service instances are listening to the same transport and try to retrieve the next proper message to process if they are idle. Since there is no dispatcher in pulling mode, it requires some features on the transportation. The transportation must support multiple client connection and server listening. HTTP and TCP doesn’t allow multiple clients are listening on the same address and port, so it cannot be used in pulling mode directly. All messages in the transportation must be FIFO, which means the old message must be received before the new one. Message selection would be a plus on the transportation. This means both service and client can specify some selection criteria and just receive some specified kinds of messages. This feature is not mandatory but would be very useful when implementing the request reply and duplex WCF channel modes. Otherwise we must have a memory dictionary to store the reply messages. I will explain more about this in the following articles. Message bus, or the message queue would be best candidate as the transportation when using the pulling mode. First, it allows multiple application to listen on the same queue, and it’s FIFO. Some of the message bus also support the message selection, such as TIBCO EMS, RabbitMQ. Some others provide in memory dictionary which can store the reply messages, for example the Redis. The principle of pulling mode is to let the service instances self-managed. This means each instance will try to retrieve the next pending incoming message if they finished the current task. This gives us more benefit and can solve the problems we met with in the dispatcher mode. The incoming message will be received to the best instance to process, which means this will be very balanced. And it will not happen that some instances are busy while other are idle, since the idle one will retrieve more tasks to make them busy. Since all instances are try their best to be busy we can use less instances than dispatcher mode, which more cost effective. Since there’s no dispatcher in the system, there is no bottleneck. When we introduced more service instances, in dispatcher mode we have to change something to let the dispatcher know the new instances. But in pulling mode since all service instance are self-managed, there no extra change at all. If there are many incoming messages, since the message bus can queue them in the transportation, service instances would not be crashed. All above are the benefits using the pulling mode, but it will introduce some problem as well. The process tracking and debugging become more difficult. Since the service instances are self-managed, we cannot know which instance will process the message. So we need more information to support debug and track. Real-time response may not be supported. All service instances will process the next message after the current one has done, if we have some real-time request this may not be a good solution. Compare with the Pros and Cons above, the pulling mode would a better solution for the distributed system architecture. Because what we need more is the scalability, cost-effect and the self-management.   WCF and WCF Transport Extensibility Windows Communication Foundation (WCF) is a framework for building service-oriented applications. In the .NET world WCF is the best way to implement the service. In this series I’m going to demonstrate how to implement the pulling mode on top of a message bus by extending the WCF. I don’t want to deep into every related field in WCF but will highlight its transport extensibility. When we implemented an RPC foundation there are many aspects we need to deal with, for example the message encoding, encryption, authentication and message sending and receiving. In WCF, each aspect is represented by a channel. A message will be passed through all necessary channels and finally send to the underlying transportation. And on the other side the message will be received from the transport and though the same channels until the business logic. This mode is called “Channel Stack” in WCF, and the last channel in the channel stack must always be a transport channel, which takes the responsible for sending and receiving the messages. As we are going to implement the WCF over message bus and implement the pulling mode scaling-out solution, we need to create our own transport channel so that the client and service can exchange messages over our bus. Before we deep into the transport channel, let’s have a look on the message exchange patterns that WCF defines. Message exchange pattern (MEP) defines how client and service exchange the messages over the transportation. WCF defines 3 basic MEPs which are datagram, Request-Reply and Duplex. Datagram: Also known as one-way, or fire-forgot mode. The message sent from the client to the service, and no need any reply from the service. The client doesn’t care about the message result at all. Request-Reply: Very common used pattern. The client send the request message to the service and wait until the reply message comes from the service. Duplex: The client sent message to the service, when the service processing the message it can callback to the client. When callback the service would be like a client while the client would be like a service. In WCF, each MEP represent some channels associated. MEP Channels Datagram IInputChannel, IOutputChannel Request-Reply IRequestChannel, IReplyChannel Duplex IDuplexChannel And the channels are created by ChannelListener on the server side, and ChannelFactory on the client side. The ChannelListener and ChannelFactory are created by the TransportBindingElement. The TransportBindingElement is created by the Binding, which can be defined as a new binding or from a custom binding. For more information about the transport channel mode, please refer to the MSDN document. The figure below shows the transport channel objects when using the request-reply MEP. And this is the datagram MEP. And this is the duplex MEP. After investigated the WCF transport architecture, channel mode and MEP, we finally identified what we should do to extend our message bus based transport layer. They are: Binding: (Optional) Defines the channel elements in the channel stack and added our transport binding element at the bottom of the stack. But we can use the build-in CustomBinding as well. TransportBindingElement: Defines which MEP is supported in our transport and create the related ChannelListener and ChannelFactory. This also defines the scheme of the endpoint if using this transport. ChannelListener: Create the server side channel based on the MEP it’s. We can have one ChannelListener to create channels for all supported MEPs, or we can have ChannelListener for each MEP. In this series I will use the second approach. ChannelFactory: Create the client side channel based on the MEP it’s. We can have one ChannelFactory to create channels for all supported MEPs, or we can have ChannelFactory for each MEP. In this series I will use the second approach. Channels: Based on the MEPs we want to support, we need to implement the channels accordingly. For example, if we want our transport support Request-Reply mode we should implement IRequestChannel and IReplyChannel. In this series I will implement all 3 MEPs listed above one by one. Scaffold: In order to make our transport extension works we also need to implement some scaffold stuff. For example we need some classes to send and receive message though out message bus. We also need some codes to read and write the WCF message, etc.. These are not necessary but would be very useful in our example.   Message Bus There is only one thing remained before we can begin to implement our scaling-out support WCF transport, which is the message bus. As I mentioned above, the message bus must have some features to fulfill all the WCF MEPs. In my company we will be using TIBCO EMS, which is an enterprise message bus product. And I have said before we can use any message bus production if it’s satisfied with our requests. Here I would like to introduce an interface to separate the message bus from the WCF. This allows us to implement the bus operations by any kinds bus we are going to use. The interface would be like this. 1: public interface IBus : IDisposable 2: { 3: string SendRequest(string message, bool fromClient, string from, string to = null); 4:  5: void SendReply(string message, bool fromClient, string replyTo); 6:  7: BusMessage Receive(bool fromClient, string replyTo); 8: } There are only three methods for the bus interface. Let me explain one by one. The SendRequest method takes the responsible for sending the request message into the bus. The parameters description are: message: The WCF message content. fromClient: Indicates if this message was came from the client. from: The channel ID that this message was sent from. The channel ID will be generated when any kinds of channel was created, which will be explained in the following articles. to: The channel ID that this message should be received. In Request-Reply and Duplex MEP this is necessary since the reply message must be received by the channel which sent the related request message. The SendReply method takes the responsible for sending the reply message. It’s very similar as the previous one but no “from” parameter. This is because it’s no need to reply a reply message again in any MEPs. The Receive method takes the responsible for waiting for a incoming message, includes the request message and specified reply message. It returned a BusMessage object, which contains some information about the channel information. The code of the BusMessage class is 1: public class BusMessage 2: { 3: public string MessageID { get; private set; } 4: public string From { get; private set; } 5: public string ReplyTo { get; private set; } 6: public string Content { get; private set; } 7:  8: public BusMessage(string messageId, string fromChannelId, string replyToChannelId, string content) 9: { 10: MessageID = messageId; 11: From = fromChannelId; 12: ReplyTo = replyToChannelId; 13: Content = content; 14: } 15: } Now let’s implement a message bus based on the IBus interface. Since I don’t want you to buy and install the TIBCO EMS or any other message bus products, I will implement an in process memory bus. This bus is only for test and sample purpose. It can only be used if the service and client are in the same process. Very straightforward. 1: public class InProcMessageBus : IBus 2: { 3: private readonly ConcurrentDictionary<Guid, InProcMessageEntity> _queue; 4: private readonly object _lock; 5:  6: public InProcMessageBus() 7: { 8: _queue = new ConcurrentDictionary<Guid, InProcMessageEntity>(); 9: _lock = new object(); 10: } 11:  12: public string SendRequest(string message, bool fromClient, string from, string to = null) 13: { 14: var entity = new InProcMessageEntity(message, fromClient, from, to); 15: _queue.TryAdd(entity.ID, entity); 16: return entity.ID.ToString(); 17: } 18:  19: public void SendReply(string message, bool fromClient, string replyTo) 20: { 21: var entity = new InProcMessageEntity(message, fromClient, null, replyTo); 22: _queue.TryAdd(entity.ID, entity); 23: } 24:  25: public BusMessage Receive(bool fromClient, string replyTo) 26: { 27: InProcMessageEntity e = null; 28: while (true) 29: { 30: lock (_lock) 31: { 32: var entity = _queue 33: .Where(kvp => kvp.Value.FromClient == fromClient && (kvp.Value.To == replyTo || string.IsNullOrWhiteSpace(kvp.Value.To))) 34: .FirstOrDefault(); 35: if (entity.Key != Guid.Empty && entity.Value != null) 36: { 37: _queue.TryRemove(entity.Key, out e); 38: } 39: } 40: if (e == null) 41: { 42: Thread.Sleep(100); 43: } 44: else 45: { 46: return new BusMessage(e.ID.ToString(), e.From, e.To, e.Content); 47: } 48: } 49: } 50:  51: public void Dispose() 52: { 53: } 54: } The InProcMessageBus stores the messages in the objects of InProcMessageEntity, which can take some extra information beside the WCF message itself. 1: public class InProcMessageEntity 2: { 3: public Guid ID { get; set; } 4: public string Content { get; set; } 5: public bool FromClient { get; set; } 6: public string From { get; set; } 7: public string To { get; set; } 8:  9: public InProcMessageEntity() 10: : this(string.Empty, false, string.Empty, string.Empty) 11: { 12: } 13:  14: public InProcMessageEntity(string content, bool fromClient, string from, string to) 15: { 16: ID = Guid.NewGuid(); 17: Content = content; 18: FromClient = fromClient; 19: From = from; 20: To = to; 21: } 22: }   Summary OK, now I have all necessary stuff ready. The next step would be implementing our WCF message bus transport extension. In this post I described two scaling-out approaches on the service side especially if we are using the cloud platform: dispatcher mode and pulling mode. And I compared the Pros and Cons of them. Then I introduced the WCF channel stack, channel mode and the transport extension part, and identified what we should do to create our own WCF transport extension, to let our WCF services using pulling mode based on a message bus. And finally I provided some classes that need to be used in the future posts that working against an in process memory message bus, for the demonstration purpose only. In the next post I will begin to implement the transport extension step by step.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • New Themes New Benefits (WinForms)

    We believe that working hard on something can be great fun at the end when everything is done and the seeds have resulted in the sweetest fruits. This is the case with the new Theming Mechanism and the new Visual Style Builder which we introduced as of Q1 2010.   I am not going to dive into any details on the new concepts behind all this stuff, but will simply focus on the numbers: both in terms of loading speed and memory usage. As you may already know, the new approach we use to style our controls uses the so called Style Repository which stores style settings that can be reused throughout the whole theme. As a result, we have estimated that the size of our themes has been significantly reduced. For instance, the size of all XML files of the Desert theme sums up to 1.83 MB. The case with the new version of the Desert theme is drastically different. Despite the fact that the new theme consists of more XML files compared to the old, its size is only 707 KB!   Furthermore, we have performed a simple performance test since the common sense tells us that such a great improvement in terms of memory footprint should be followed by a great improvement in terms of speed. We have estimated that loading and applying the new Desert theme to a form containing all RadControls for WinForms takes roughly 30% less time compared to the same operation with the old version of the Desert theme. The following screenshots briefly demonstrate the scenario which we used to estimate the loading time difference between the old and the new Desert theme:     Here, the old Desert theme is applied to all controls on the Form which takes almost 1,3 seconds.     Applying the new Desert theme (based on the new Theming Mechanism) takes about 0,78 seconds.   On top of all these great improvements, we can add the fact that the new Visual Style Builder significantly reduces the time needed to style a control by entirely changing the approach compared to the old version of this tool. You can be sure that we have already prepared some great new stuff for Q1 2010 SP1 that will simplify things further so that designing themes with the new VSB will become more fun than ever!Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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