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  • Talend Enterprise Data Integration overperforms on Oracle SPARC T4

    - by Amir Javanshir
    The SPARC T microprocessor, released in 2005 by Sun Microsystems, and now continued at Oracle, has a good track record in parallel execution and multi-threaded performance. However it was less suited for pure single-threaded workloads. The new SPARC T4 processor is now filling that gap by offering a 5x better single-thread performance over previous generations. Following our long-term relationship with Talend, a fast growing ISV positioned by Gartner in the “Visionaries” quadrant of the “Magic Quadrant for Data Integration Tools”, we decided to test some of their integration components with the T4 chip, more precisely on a T4-1 system, in order to verify first hand if this new processor stands up to its promises. Several tests were performed, mainly focused on: Single-thread performance of the new SPARC T4 processor compared to an older SPARC T2+ processor Overall throughput of the SPARC T4-1 server using multiple threads The tests consisted in reading large amounts of data --ten's of gigabytes--, processing and writing them back to a file or an Oracle 11gR2 database table. They are CPU, memory and IO bound tests. Given the main focus of this project --CPU performance--, bottlenecks were removed as much as possible on the memory and IO sub-systems. When possible, the data to process was put into the ZFS filesystem cache, for instance. Also, two external storage devices were directly attached to the servers under test, each one divided in two ZFS pools for read and write operations. Multi-thread: Testing throughput on the Oracle T4-1 The tests were performed with different number of simultaneous threads (1, 2, 4, 8, 12, 16, 32, 48 and 64) and using different storage devices: Flash, Fibre Channel storage, two stripped internal disks and one single internal disk. All storage devices used ZFS as filesystem and volume management. Each thread read a dedicated 1GB-large file containing 12.5M lines with the following structure: customerID;FirstName;LastName;StreetAddress;City;State;Zip;Cust_Status;Since_DT;Status_DT 1;Ronald;Reagan;South Highway;Santa Fe;Montana;98756;A;04-06-2006;09-08-2008 2;Theodore;Roosevelt;Timberlane Drive;Columbus;Louisiana;75677;A;10-05-2009;27-05-2008 3;Andrew;Madison;S Rustle St;Santa Fe;Arkansas;75677;A;29-04-2005;09-02-2008 4;Dwight;Adams;South Roosevelt Drive;Baton Rouge;Vermont;75677;A;15-02-2004;26-01-2007 […] The following graphs present the results of our tests: Unsurprisingly up to 16 threads, all files fit in the ZFS cache a.k.a L2ARC : once the cache is hot there is no performance difference depending on the underlying storage. From 16 threads upwards however, it is clear that IO becomes a bottleneck, having a good IO subsystem is thus key. Single-disk performance collapses whereas the Sun F5100 and ST6180 arrays allow the T4-1 to scale quite seamlessly. From 32 to 64 threads, the performance is almost constant with just a slow decline. For the database load tests, only the best IO configuration --using external storage devices-- were used, hosting the Oracle table spaces and redo log files. Using the Sun Storage F5100 array allows the T4-1 server to scale up to 48 parallel JVM processes before saturating the CPU. The final result is a staggering 646K lines per second insertion in an Oracle table using 48 parallel threads. Single-thread: Testing the single thread performance Seven different tests were performed on both servers. Given the fact that only one thread, thus one file was read, no IO bottleneck was involved, all data being served from the ZFS cache. Read File ? Filter ? Write File: Read file, filter data, write the filtered data in a new file. The filter is set on the “Status” column: only lines with status set to “A” are selected. This limits each output file to about 500 MB. Read File ? Load Database Table: Read file, insert into a single Oracle table. Average: Read file, compute the average of a numeric column, write the result in a new file. Division & Square Root: Read file, perform a division and square root on a numeric column, write the result data in a new file. Oracle DB Dump: Dump the content of an Oracle table (12.5M rows) into a CSV file. Transform: Read file, transform, write the result data in a new file. The transformations applied are: set the address column to upper case and add an extra column at the end, which is the concatenation of two columns. Sort: Read file, sort a numeric and alpha numeric column, write the result data in a new file. The following table and graph present the final results of the tests: Throughput unit is thousand lines per second processed (K lines/second). Improvement is the % of improvement between the T5140 and T4-1. Test T4-1 (Time s.) T5140 (Time s.) Improvement T4-1 (Throughput) T5140 (Throughput) Read/Filter/Write 125 806 645% 100 16 Read/Load Database 195 1111 570% 64 11 Average 96 557 580% 130 22 Division & Square Root 161 1054 655% 78 12 Oracle DB Dump 164 945 576% 76 13 Transform 159 1124 707% 79 11 Sort 251 1336 532% 50 9 The improvement of single-thread performance is quite dramatic: depending on the tests, the T4 is between 5.4 to 7 times faster than the T2+. It seems clear that the SPARC T4 processor has gone a long way filling the gap in single-thread performance, without sacrifying the multi-threaded capability as it still shows a very impressive scaling on heavy-duty multi-threaded jobs. Finally, as always at Oracle ISV Engineering, we are happy to help our ISV partners test their own applications on our platforms, so don't hesitate to contact us and let's see what the SPARC T4-based systems can do for your application! "As describe in this benchmark, Talend Enterprise Data Integration has overperformed on T4. I was generally happy to see that the T4 gave scaling opportunities for many scenarios like complex aggregations. Row by row insertion in Oracle DB is faster with more than 650,000 rows per seconds without using any bulk Oracle capabilities !" Cedric Carbone, Talend CTO.

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  • ORACLE RIGHTNOW DYNAMIC AGENT DESKTOP CLOUD SERVICE - Putting the Dynamite into Dynamic Agent Desktop

    - by Andreea Vaduva
    Untitled Document There’s a mountain of evidence to prove that a great contact centre experience results in happy, profitable and loyal customers. The very best Contact Centres are those with high first contact resolution, customer satisfaction and agent productivity. But how many companies really believe they are the best? And how many believe that they can be? We know that with the right tools, companies can aspire to greatness – and achieve it. Core to this is ensuring their agents have the best tools that give them the right information at the right time, so they can focus on the customer and provide a personalised, professional and efficient service. Today there are multiple channels through which customers can communicate with you; phone, web, chat, social to name a few but regardless of how they communicate, customers expect a seamless, quality experience. Most contact centre agents need to switch between lots of different systems to locate the right information. This hampers their productivity, frustrates both the agent and the customer and increases call handling times. With this in mind, Oracle RightNow has designed and refined a suite of add-ins to optimize the Agent Desktop. Each is designed to simplify and adapt the agent experience for any given situation and unify the customer experience across your media channels. Let’s take a brief look at some of the most useful tools available and see how they make a difference. Contextual Workspaces: The screen where agents do their job. Agents don’t want to be slowed down by busy screens, scrolling through endless tabs or links to find what they’re looking for. They want quick, accurate and easy. Contextual Workspaces are fully configurable and through workspace rules apply if, then, else logic to display only the information the agent needs for the issue at hand . Assigned at the Profile level, different levels of agent, from a novice to the most experienced, get a screen that is relevant to their role and responsibilities and ensures their job is done quickly and efficiently the first time round. Agent Scripting: Sometimes, agents need to deliver difficult or sensitive messages while maximising the opportunity to cross-sell and up-sell. After all, contact centres are now increasingly viewed as revenue generators. Containing sophisticated branching logic, scripting helps agents to capture the right level of information and guides the agent step by step, ensuring no mistakes, inconsistencies or missed opportunities. Guided Assistance: This is typically used to solve common troubleshooting issues, displaying a series of question and answer sets in a decision-tree structure. This means agents avoid having to bookmark favourites or rely on written notes. Agents find particular value in these guides - to quickly craft chat and email responses. What’s more, by publishing guides in answers on support pages customers, can resolve issues themselves, without needing to contact your agents. And b ecause it can also accelerate agent ramp-up time, it ensures that even novice agents can solve customer problems like an expert. Desktop Workflow: Take a step back and look at the full customer interaction of your agents. It probably spans multiple systems and multiple tasks. With Desktop Workflows you control the design workflows that span the full customer interaction from start to finish. As sequences of decisions and actions, workflows are unique in that they can create or modify different records and provide automation behind the scenes. This means your agents can save time and provide better quality of service by having the tools they need and the relevant information as required. And doing this boosts satisfaction among your customers, your agents and you – so win, win, win! I have highlighted above some of the tools which can be used to optimise the desktop; however, this is by no means an exhaustive list. In approaching your design, it’s important to understand why and how your customers contact you in the first place. Once you have this list of “whys” and “hows”, you can design effective policies and procedures to handle each category of problem, and then implement the right agent desktop user interface to support them. This will avoid duplication and wasted effort. Five Top Tips to take away: Start by working out “why” and “how” customers are contacting you. Implement a clean and relevant agent desktop to support your agents. If your workspaces are getting complicated consider using Desktop Workflow to streamline the interaction. Enhance your Knowledgebase with Guides. Agents can access them proactively and can be published on your web pages for customers to help themselves. Script any complex, critical or sensitive interactions to ensure consistency and accuracy. Desktop optimization is an ongoing process so continue to monitor and incorporate feedback from your agents and your customers to keep your Contact Centre successful.   Want to learn more? Having attending the 3-day Oracle RightNow Customer Service Administration class your next step is to attend the Oracle RightNow Customer Portal Design and 2-day Dynamic Agent Desktop Administration class. Here you’ll learn not only how to leverage the Agent Desktop tools but also how to optimise your self-service pages to enhance your customers’ web experience.   Useful resources: Review the Best Practice Guide Review the tune-up guide   About the Author: Angela Chandler joined Oracle University as a Senior Instructor through the RightNow Customer Experience Acquisition. Her other areas of expertise include Business Intelligence and Knowledge Management.  She currently delivers the following Oracle RightNow courses in the classroom and as a Live Virtual Class: RightNow Customer Service Administration (3 days) RightNow Customer Portal Design and Dynamic Agent Desktop Administration (2 days) RightNow Analytics (2 days) Rightnow Chat Cloud Service Administration (2 days)

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  • Big Data – Buzz Words: What is Hadoop – Day 6 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is NoSQL. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – Hadoop. What is Hadoop? Apache Hadoop is an open-source, free and Java based software framework offers a powerful distributed platform to store and manage Big Data. It is licensed under an Apache V2 license. It runs applications on large clusters of commodity hardware and it processes thousands of terabytes of data on thousands of the nodes. Hadoop is inspired from Google’s MapReduce and Google File System (GFS) papers. The major advantage of Hadoop framework is that it provides reliability and high availability. What are the core components of Hadoop? There are two major components of the Hadoop framework and both fo them does two of the important task for it. Hadoop MapReduce is the method to split a larger data problem into smaller chunk and distribute it to many different commodity servers. Each server have their own set of resources and they have processed them locally. Once the commodity server has processed the data they send it back collectively to main server. This is effectively a process where we process large data effectively and efficiently. (We will understand this in tomorrow’s blog post). Hadoop Distributed File System (HDFS) is a virtual file system. There is a big difference between any other file system and Hadoop. When we move a file on HDFS, it is automatically split into many small pieces. These small chunks of the file are replicated and stored on other servers (usually 3) for the fault tolerance or high availability. (We will understand this in the day after tomorrow’s blog post). Besides above two core components Hadoop project also contains following modules as well. Hadoop Common: Common utilities for the other Hadoop modules Hadoop Yarn: A framework for job scheduling and cluster resource management There are a few other projects (like Pig, Hive) related to above Hadoop as well which we will gradually explore in later blog posts. A Multi-node Hadoop Cluster Architecture Now let us quickly see the architecture of the a multi-node Hadoop cluster. A small Hadoop cluster includes a single master node and multiple worker or slave node. As discussed earlier, the entire cluster contains two layers. One of the layer of MapReduce Layer and another is of HDFC Layer. Each of these layer have its own relevant component. The master node consists of a JobTracker, TaskTracker, NameNode and DataNode. A slave or worker node consists of a DataNode and TaskTracker. It is also possible that slave node or worker node is only data or compute node. The matter of the fact that is the key feature of the Hadoop. In this introductory blog post we will stop here while describing the architecture of Hadoop. In a future blog post of this 31 day series we will explore various components of Hadoop Architecture in Detail. Why Use Hadoop? There are many advantages of using Hadoop. Let me quickly list them over here: Robust and Scalable – We can add new nodes as needed as well modify them. Affordable and Cost Effective – We do not need any special hardware for running Hadoop. We can just use commodity server. Adaptive and Flexible – Hadoop is built keeping in mind that it will handle structured and unstructured data. Highly Available and Fault Tolerant – When a node fails, the Hadoop framework automatically fails over to another node. Why Hadoop is named as Hadoop? In year 2005 Hadoop was created by Doug Cutting and Mike Cafarella while working at Yahoo. Doug Cutting named Hadoop after his son’s toy elephant. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – MapReduce. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Answers to “What source control system do you use?” (and some winners)

    - by jamiet
    About a month ago I posed a question here on my blog SQL Server devs–what source control system do you use, if any? (answer and maybe win free stuff) in which I asked SQL Server developers to answer the following questions: Are you putting your SQL Server code into a source control system? If so, what source control server software (e.g. TFS, Git, SVN, Mercurial, SourceSafe, Perforce) are you using? What source control client software are you using (e.g. TFS Team Explorer, Tortoise, Red Gate SQL Source Control, Red Gate SQL Connect, Git Bash, etc…)? Why did you make those particular software choices? Any interesting anecdotes to share in regard to your use of source control and SQL Server? I had some really great responses (I highly recommend going and reading them). I promised that the five best, most thought-provoking, responses (as determined by me) would win one of five pairs of licenses for Red Gate SQL Source Control and Red Gate SQL Connect; here are the five that I chose (note that if you responded but did not leave a means of getting in touch then you weren’t considered for one of the prizes – sorry): In general, I don't think the management overhead and licensing cost associated with TFS is worthwhile if all you're doing is using source control. To get value from TFS, at a minimum you need to be using team build, and possibly other stuff as well, such as the sharepoint integration. If that's all you need, then svn with Tortoise would be my first choice. If you want to add build automation later, you can do this with cruisecontrol (is it still called that?), JetBrains, etc. For a long time I thought that Redgate's claims about "bridging the SSMS-VS divide" were a load of hot air, since in my experience anyone who knew what they were doing was using Visual Studio, in particular SSDT and its predecessors. However, on a recent client I was putting in source control for the first time, and I discovered that the "divide" really does exist. That client has ended up using svn with Redgate SQL Source Control, with no build automation, but with scope to add it in the future. Gavin Campbell I think putting the DB under source control is a great idea.  I have issues with the earlier versions of SQL Source Control in that it provides little help in versioning the DB. I think the latest version merges SQL Compare and SQL Source Control together.  Which is how it should have been all along. Sure I have the DB scripts in SVN, but I can't automate DB builds and changes without more tools.  Frankly I'm surprised databases don't have some sort of versioning built into them. Nick Portelli Source control has been immensely useful and saved me from a lot of rework on more than one occasion.  I have learned that you have to be extremely careful checking in data.  Our system is internal only so during the system production run once a week, if there is a problem that I can fix easily(for example, a control table points to a file in the wrong environment), I'll do it directly in production so the run can continue as soon as possible since we have a specified time window.  We do full test runs to minimize this but it has come up once or twice.  We use Red-Gate source control to "push" from the test environment to the production environment.  There have been a couple of occasions where the test environment with the wrong setting was pushed back over the production environment because the change was made only in production.  Gotta keep an eye on that. Alan Dykes Goodness is it manual.  And can be extremely painful at times.  Not only are we running thin, we are constrained on the tools we can get ($$ must mean free).  Certainly no excuse, and a great opportunity to improve my skills by learning new things.  But...  Getting buy in a on a proven process or methodology is hard, takes time, and diverts us from development.  If SQL Source Control is easy to use and proven oh boy could you get some serious fans around here!  Seriously though, as the "accidental dba" of this shop any new ideas / easy to implement tools can make a world of difference in productivity and most importantly accuracy.  Manual = bad. :) John Hennesey (who left his email address) The one thing I would love to know more about is the unique challenges of working with databases as source code - you can store scripts, but are they written as deployment scripts with all the logic about how to apply them to an existing DB? Where is that baseline DB? Where's the data? How does a team share the data and the code? It's a real challenge. Merrill Aldrich Congratulations to the five of you. Red Gate will be in touch with you soon about your free licenses. Thank you to all those that responded. And again, go and check out all the responses – those above are only small proportion from what is a very interesting comment thread. @Jamiet

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  • NDepend 4 – First Steps

    - by Ricardo Peres
    Introduction Thanks to Patrick Smacchia I had the chance to test NDepend 4. I can only say: awesome! This will be the first of a series of posts on NDepend, where I will talk about my discoveries. Keep in mind that I am just starting to use it, so more experienced users may find these too basic, I just hope I don’t say anything foolish! I must say that I am in no way affiliated with NDepend and I never actually met Patrick. Installation No installation program – a curious decision, I’m not against it -, just unzip the files to a folder and run the executable. It will optionally register itself with Visual Studio 2008, 2010 and 11 as well as RedGate’s Reflector; also, it automatically looks for updates. NDepend can either be used as a stand-alone program (with or without a GUI) or from within Visual Studio or Reflector. Getting Started One thing that really pleases me is the Getting Started section of the stand-alone, with links to pages on NDepend’s web site, featuring detailed explanations, which usually include screenshots and small videos (<5 minutes). There’s also an How do I with hierarchical navigation that guides us to through the major features so that we can easily find what we want. Usage There are two basic ways to use NDepend: Analyze .NET solutions, projects or assemblies; Compare two versions of the same assembly. I have so far not used NDepend to compare assemblies, so I will first talk about the first option. After selecting a solution and some of its projects, it generates a single HTML page with an highly detailed report of the analysis it produced. This includes some metrics such as number of lines of code, IL instructions, comments, types, methods and properties, the calculation of the cyclomatic complexity, coupling and lots of others indicators, typically grouped by type, namespace and assembly. The HTML also includes some nice diagrams depicting assembly dependencies, type and method relative proportions (according to the number of IL instructions, I guess) and assembly analysis relating to abstractness and stability. Useful, I would say. Then there’s the rules; NDepend tests the target assemblies against a set of more than 120 rules, grouped in categories Code Quality, Object Oriented Design, Design, Architecture and Layering, Dead Code, Visibility, Naming Conventions, Source Files Organization and .NET Framework Usage. The full list can be configured on the application, and an explanation of each rule can be found on the web site. Rules can be validated, violated and violated in a critical manner, and the HTML will contain the violated rules, their queries – more on this later - and results. The HTML uses some nice JavaScript effects, which allow paging and sorting of tables, so its nice to use. Similar to the rules, there are some queries that display results for a number (about 200) questions grouped as Object Oriented Design, API Breaking Changes (for assembly version comparison), Code Diff Summary (also for version comparison) and Dead Code. The difference between queries and rules is that queries are not classified as passes, violated or critically violated, just present results. The queries and rules are expressed through CQLinq, which is a very powerful LINQ derivative specific to code analysis. All of the included rules and queries can be enabled or disabled and new ones can be added, with intellisense to help. Besides the HTML report file, the NDepend application can be used to explore all analysis results, compare different versions of analysis reports and to run custom queries. Comparison to Other Analysis Tools Unlike StyleCop, NDepend only works with assemblies, not source code, so you can’t expect it to be able to enforce brackets placement, for example. It is more similar to FxCop, but you don’t have the option to analyze at the IL level, that is, other that the number of IL instructions and the complexity. What’s Next In the next days I’ll continue my exploration with a real-life test case. References The NDepend web site is http://www.ndepend.com/. Patrick keeps an updated blog on http://codebetter.com/patricksmacchia/ and he regularly monitors StackOverflow for questions tagged NDepend, which you can find on http://stackoverflow.com/questions/tagged/ndepend. The default list of CQLinq rules, queries and statistics can be found at http://www.ndepend.com/DefaultRules/webframe.html. The syntax itself is described at http://www.ndepend.com/Doc_CQLinq_Syntax.aspx and its features at http://www.ndepend.com/Doc_CQLinq_Features.aspx.

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  • Dynamically switching the theme in Orchard

    - by Bertrand Le Roy
    It may sound a little puzzling at first, but in Orchard CMS, more than one theme can be active at any given time. The reason for that is that we have an extensibility point that allows a module (or a theme) to participate in the choice of the theme to use, for each request. The motivation for building the theme engine this way was to enable developers to switch themes based on arbitrary criteria, such as user preferences or the user agent (if you want to serve a mobile theme for phones for example). The choice is made between the active themes, which is why there is a difference between the default theme and the active themes. In order to have a say in the choice of the theme, all you have to do is implement IThemeSelector. That interface is quite simple as it only has one method, GetTheme, that takes the current RequestContext and returns a ThemeSelectorResult or null if the implementation of the interface does not want to participate in the current request (we'll see an example in a moment). ThemeSelectorResult itself is just a ThemeName string property and an integer Priority. We're using a priority so that an arbitrary number of implementations of IThemeSelector can contribute to the choice of a theme. If you look for existing implementations of the interface in Orchard, you'll find four: AdminThemeSelector: selects the TheAdmin theme with a very high priority (100) if the current request is for a page that is part of the admin. Otherwise, null is returned, which enables other implementations to choose the theme. PreviewThemeSelector: selects the preview theme if there is one, with a high priority (90), and null otherwise. This enables administrators to view the site under a different theme while everybody else continues to see the current default theme. SiteThemeSelector: this is the implementation that is doing what you expect most of the time, which is to get the current theme from site settings and set it with a priority of –5. SafeModeThemeSelector: this is the fallback implementation, which should almost never win. It sets the theme as the safe mode theme, which has no style and just uses the default templates for everything. The priority is very low (-100). While this extensibility mechanism is great to have, I wanted to bring that level of choice into the hands of the site administrator rather than just developers. In order to achieve that, I built the Vandelay Theme Picker module. The module provides administration UI to create rules for theme selection. It provides its own extensibility point (the IThemeSelectionRule interface) and one implementation of a rule: UserAgentThemeSelectorRule. This rule gets the current user agent from the context and tries to match it with a regular expression that the administrator can configure in the admin UI. You can for example configure a rule with a regular expression that matches IE6 and serve a different subtheme where the stylesheet has been tweaked for such an antique browser. Another possible configuration is to detect mobile devices from their agent string and serve the mobile theme. All those operations can be done with this module entirely from the admin UI, without writing a line of code. The module also offers the administrator the opportunity to inject a link into the front-end in a specific zone and with a specific position that enables the user to switch to the default theme if he wishes to. This is especially useful for sites that use a mobile theme but still want to allow users to use the full desktop site. While the module is nice and flexible, it may be overkill. On my own personal blog, I have only two active themes: the desktop theme and the mobile theme. I'm fine with going into code to change the criteria on which to switch the theme, so I'm not using my own Theme Picker module. Instead, I made the mobile theme a theme with code (in other words there is a csproj file in the theme). The project includes a single C# file, my MobileThemeSelector for which the code is the following: public class MobileThemeSelector : IThemeSelector { private static readonly Regex _Msie678 = new Regex(@"^Mozilla\/4\.0 \(compatible; MSIE [678]" + @"\.0; Windows NT \d\.\d(.*)\)$", RegexOptions.IgnoreCase); private ThemeSelectorResult _requestCache; private bool _requestCached; public ThemeSelectorResult GetTheme(RequestContext context) { if (_requestCached) return _requestCache; _requestCached = true; var userAgent = context.HttpContext.Request.UserAgent; if (userAgent.IndexOf("phone", StringComparison.OrdinalIgnoreCase) != -1 || _Msie678.IsMatch(userAgent) || userAgent.IndexOf("windows live writer", StringComparison.OrdinalIgnoreCase) != -1) { _requestCache = new ThemeSelectorResult { Priority = 10, ThemeName = "VuLuMobile" }; } return _requestCache; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } The theme selector selects the current theme for Internet Explorer versions 6 to 8, for phones, and for Windows Live Writer (so that the theme that is used when I write posts is as simple as possible). What's interesting here is that it's the theme that selects itself here, based on its own criteria. This should give you a good panorama of what's possible in terms of dynamic theme selection in Orchard. I hope you find some fun uses for it. As usual, I can't wait to see what you're going to come up with…

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  • ASSIMP in my program is much slower to import than ASSIMP view program

    - by Marco
    The problem is really simple: if I try to load with the function aiImportFileExWithProperties a big model in my software (around 200.000 vertices), it takes more than one minute. If I try to load the very same model with ASSIMP view, it takes 2 seconds. For this comparison, both my software and Assimp view are using the dll version of the library at 64 bit, compiled by myself (Assimp64.dll). This is the relevant piece of code in my software // default pp steps unsigned int ppsteps = aiProcess_CalcTangentSpace | // calculate tangents and bitangents if possible aiProcess_JoinIdenticalVertices | // join identical vertices/ optimize indexing aiProcess_ValidateDataStructure | // perform a full validation of the loader's output aiProcess_ImproveCacheLocality | // improve the cache locality of the output vertices aiProcess_RemoveRedundantMaterials | // remove redundant materials aiProcess_FindDegenerates | // remove degenerated polygons from the import aiProcess_FindInvalidData | // detect invalid model data, such as invalid normal vectors aiProcess_GenUVCoords | // convert spherical, cylindrical, box and planar mapping to proper UVs aiProcess_TransformUVCoords | // preprocess UV transformations (scaling, translation ...) aiProcess_FindInstances | // search for instanced meshes and remove them by references to one master aiProcess_LimitBoneWeights | // limit bone weights to 4 per vertex aiProcess_OptimizeMeshes | // join small meshes, if possible; aiProcess_SplitByBoneCount | // split meshes with too many bones. Necessary for our (limited) hardware skinning shader 0; cout << "Loading " << pFile << "... "; aiPropertyStore* props = aiCreatePropertyStore(); aiSetImportPropertyInteger(props,AI_CONFIG_IMPORT_TER_MAKE_UVS,1); aiSetImportPropertyFloat(props,AI_CONFIG_PP_GSN_MAX_SMOOTHING_ANGLE,80.f); aiSetImportPropertyInteger(props,AI_CONFIG_PP_SBP_REMOVE, aiPrimitiveType_LINE | aiPrimitiveType_POINT); aiSetImportPropertyInteger(props,AI_CONFIG_GLOB_MEASURE_TIME,1); //aiSetImportPropertyInteger(props,AI_CONFIG_PP_PTV_KEEP_HIERARCHY,1); // Call ASSIMPs C-API to load the file scene = (aiScene*)aiImportFileExWithProperties(pFile.c_str(), ppsteps | /* default pp steps */ aiProcess_GenSmoothNormals | // generate smooth normal vectors if not existing aiProcess_SplitLargeMeshes | // split large, unrenderable meshes into submeshes aiProcess_Triangulate | // triangulate polygons with more than 3 edges //aiProcess_ConvertToLeftHanded | // convert everything to D3D left handed space aiProcess_SortByPType | // make 'clean' meshes which consist of a single typ of primitives 0, NULL, props); aiReleasePropertyStore(props); if(!scene){ cout << aiGetErrorString() << endl; return 0; } this is the relevant piece of code in assimp view code // default pp steps unsigned int ppsteps = aiProcess_CalcTangentSpace | // calculate tangents and bitangents if possible aiProcess_JoinIdenticalVertices | // join identical vertices/ optimize indexing aiProcess_ValidateDataStructure | // perform a full validation of the loader's output aiProcess_ImproveCacheLocality | // improve the cache locality of the output vertices aiProcess_RemoveRedundantMaterials | // remove redundant materials aiProcess_FindDegenerates | // remove degenerated polygons from the import aiProcess_FindInvalidData | // detect invalid model data, such as invalid normal vectors aiProcess_GenUVCoords | // convert spherical, cylindrical, box and planar mapping to proper UVs aiProcess_TransformUVCoords | // preprocess UV transformations (scaling, translation ...) aiProcess_FindInstances | // search for instanced meshes and remove them by references to one master aiProcess_LimitBoneWeights | // limit bone weights to 4 per vertex aiProcess_OptimizeMeshes | // join small meshes, if possible; aiProcess_SplitByBoneCount | // split meshes with too many bones. Necessary for our (limited) hardware skinning shader 0; aiPropertyStore* props = aiCreatePropertyStore(); aiSetImportPropertyInteger(props,AI_CONFIG_IMPORT_TER_MAKE_UVS,1); aiSetImportPropertyFloat(props,AI_CONFIG_PP_GSN_MAX_SMOOTHING_ANGLE,g_smoothAngle); aiSetImportPropertyInteger(props,AI_CONFIG_PP_SBP_REMOVE,nopointslines ? aiPrimitiveType_LINE | aiPrimitiveType_POINT : 0 ); aiSetImportPropertyInteger(props,AI_CONFIG_GLOB_MEASURE_TIME,1); //aiSetImportPropertyInteger(props,AI_CONFIG_PP_PTV_KEEP_HIERARCHY,1); // Call ASSIMPs C-API to load the file g_pcAsset->pcScene = (aiScene*)aiImportFileExWithProperties(g_szFileName, ppsteps | /* configurable pp steps */ aiProcess_GenSmoothNormals | // generate smooth normal vectors if not existing aiProcess_SplitLargeMeshes | // split large, unrenderable meshes into submeshes aiProcess_Triangulate | // triangulate polygons with more than 3 edges aiProcess_ConvertToLeftHanded | // convert everything to D3D left handed space aiProcess_SortByPType | // make 'clean' meshes which consist of a single typ of primitives 0, NULL, props); aiReleasePropertyStore(props); As you can see the code is nearly identical because I copied from assimp view. What could be the reason for such a difference in performance? The two software are using the same dll Assimp64.dll (compiled in my computer with vc++ 2010 express) and the same function aiImportFileExWithProperties to load the model, so I assume that the actual code employed is the same. How is it possible that the function aiImportFileExWithProperties is 100 times slower when called by my sotware than when called by assimp view? What am I missing? I am not good with dll, dynamic and static libraries so I might be missing something obvious. ------------------------------ UPDATE I found out the reason why the code is going slower. Basically I was running my software with "Start debugging" in VC++ 2010 Express. If I run the code outside VC++ 2010 I get same performance of assimp view. However now I have a new question. Why does the dll perform slower in VC++ debugging? I compiled it in release mode without debugging information. Is there any way to have the dll go fast in debugmode i.e. not debugging the dll? Because I am interested in debugging only my own code, not the dll that I assume is already working fine. I do not want to wait 2 minutes every time I want to load my software to debug. Does this request make sense?

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  • Node.js Adventure - Storage Services and Service Runtime

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

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  • IBM "per core" comparisons for SPECjEnterprise2010

    - by jhenning
    I recently stumbled upon a blog entry from Roman Kharkovski (an IBM employee) comparing some SPECjEnterprise2010 results for IBM vs. Oracle. Mr. Kharkovski's blog claims that SPARC delivers half the transactions per core vs. POWER7. Prior to any argument, I should say that my predisposition is to like Mr. Kharkovski, because he says that his blog is intended to be factual; that the intent is to try to avoid marketing hype and FUD tactic; and mostly because he features a picture of himself wearing a bike helmet (me too). Therefore, in a spirit of technical argument, rather than FUD fight, there are a few areas in his comparison that should be discussed. Scaling is not free For any benchmark, if a small system scores 13k using quantity R1 of some resource, and a big system scores 57k using quantity R2 of that resource, then, sure, it's tempting to divide: is  13k/R1 > 57k/R2 ? It is tempting, but not necessarily educational. The problem is that scaling is not free. Building big systems is harder than building small systems. Scoring  13k/R1  on a little system provides no guarantee whatsoever that one can sustain that ratio when attempting to handle more than 4 times as many users. Choosing the denominator radically changes the picture When ratios are used, one can vastly manipulate appearances by the choice of denominator. In this case, lots of choices are available for the resource to be compared (R1 and R2 above). IBM chooses to put cores in the denominator. Mr. Kharkovski provides some reasons for that choice in his blog entry. And yet, it should be noted that the very concept of a core is: arbitrary: not necessarily comparable across vendors; fluid: modern chips shift chip resources in response to load; and invisible: unless you have a microscope, you can't see it. By contrast, one can actually see processor chips with the naked eye, and they are a bit easier to count. If we put chips in the denominator instead of cores, we get: 13161.07 EjOPS / 4 chips = 3290 EjOPS per chip for IBM vs 57422.17 EjOPS / 16 chips = 3588 EjOPS per chip for Oracle The choice of denominator makes all the difference in the appearance. Speaking for myself, dividing by chips just seems to make more sense, because: I can see chips and count them; and I can accurately compare the number of chips in my system to the count in some other vendor's system; and Tthe probability of being able to continue to accurately count them over the next 10 years of microprocessor development seems higher than the probability of being able to accurately and comparably count "cores". SPEC Fair use requirements Speaking as an individual, not speaking for SPEC and not speaking for my employer, I wonder whether Mr. Kharkovski's blog article, taken as a whole, meets the requirements of the SPEC Fair Use rule www.spec.org/fairuse.html section I.D.2. For example, Mr. Kharkovski's footnote (1) begins Results from http://www.spec.org as of 04/04/2013 Oracle SUN SPARC T5-8 449 EjOPS/core SPECjEnterprise2010 (Oracle's WLS best SPECjEnterprise2010 EjOPS/core result on SPARC). IBM Power730 823 EjOPS/core (World Record SPECjEnterprise2010 EJOPS/core result) The questionable tactic, from a Fair Use point of view, is that there is no such metric at the designated location. At www.spec.org, You can find the SPEC metric 57422.17 SPECjEnterprise2010 EjOPS for Oracle and You can also find the SPEC metric 13161.07 SPECjEnterprise2010 EjOPS for IBM. Despite the implication of the footnote, you will not find any mention of 449 nor anything that says 823. SPEC says that you can, under its fair use rule, derive your own values; but it emphasizes: "The context must not give the appearance that SPEC has created or endorsed the derived value." Substantiation and transparency Although SPEC disclaims responsibility for non-SPEC information (section I.E), it says that non-SPEC data and methods should be accurate, should be explained, should be substantiated. Unfortunately, it is difficult or impossible for the reader to independently verify the pricing: Were like units compared to like (e.g. list price to list price)? Were all components (hw, sw, support) included? Were all fees included? Note that when tpc.org shows IBM pricing, there are often items such as "PROCESSOR ACTIVATION" and "MEMORY ACTIVATION". Without the transparency of a detailed breakdown, the pricing claims are questionable. T5 claim for "Fastest Processor" Mr. Kharkovski several times questions Oracle's claim for fastest processor, writing You see, when you publish industry benchmarks, people may actually compare your results to other vendor's results. Well, as we performance people always say, "it depends". If you believe in performance-per-core as the primary way of looking at the world, then yes, the POWER7+ is impressive, spending its chip resources to support up to 32 threads (8 cores x 4 threads). Or, it just might be useful to consider performance-per-chip. Each SPARC T5 chip allows 128 hardware threads to be simultaneously executing (16 cores x 8 threads). The Industry Standard Benchmark that focuses specifically on processor chip performance is SPEC CPU2006. For this very well known and popular benchmark, SPARC T5: provides better performance than both POWER7 and POWER7+, for 1 chip vs. 1 chip, for 8 chip vs. 8 chip, for integer (SPECint_rate2006) and floating point (SPECfp_rate2006), for Peak tuning and for Base tuning. For example, at the 8-chip level, integer throughput (SPECint_rate2006) is: 3750 for SPARC 2170 for POWER7+. You can find the details at the March 2013 BestPerf CPU2006 page SPEC is a trademark of the Standard Performance Evaluation Corporation, www.spec.org. The two specific results quoted for SPECjEnterprise2010 are posted at the URLs linked from the discussion. Results for SPEC CPU2006 were verified at spec.org 1 July 2013, and can be rechecked here.

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  • SQLCMD Mode: give it one more chance

    - by Maria Zakourdaev
      - Click on me. Choose me. - asked one forgotten feature when some bored DBA was purposelessly wondering through the Management Studio menu at the end of her long and busy working day. - Why would I use you? I have heard of no one who does. What are you for? - perplexedly wondered aged and wise DBA. At least that DBA thought she was aged and wise though each day tried to prove to her that she wasn't. - I know you. You are quite lazy. Why would you do additional clicks to move from window to window? From Tool to tool ? This is irritating, isn't it? I can run windows system commands, sql statements and much more from the same script, from the same query window! - I have all my tools that I‘m used to, I have Management Studio, Cmd, Powershell. They can do anything for me. I don’t need additional tools. - I promise you, you will like me. – the thing continued to whine . - All right, show me. – she gave up. It’s always this way, she thought sadly, - easier to agree than to explain why you don’t want. - Enable me and then think about anything that you always couldn’t do through the management studio and had to use other tools. - Ok. Google for me the list of greatest features of SQL SERVER 2012. - Well... I’m not sure... Think about something else. - Ok, here is something easy for you. I want to check if file folder exists or if file is there. Though, I can easily do this using xp_cmdshell … - This is easy for me. – rejoiced the feature. By the way, having the items of the menu talking to you usually means you should stop working and go home. Or drink coffee. Or both. Well, aged and wise dba wasn’t thinking about the weirdness of the situation at that moment. - After enabling me, – said unfairly forgotten feature (it was thinking of itself in such manner) – after enabling me you can use all command line commands in the same management studio query window by adding two exclamation marks !! at the beginning of the script line to denote that you want to use cmd command: -Just keep in mind that when using this feature, you are actually running the commands ON YOUR computer and not on SQL server that query window is connected to. This is main difference from using xp_cmdshell which is executing commands on sql server itself. Bottomline, use UNC path instead of local path. - Look, there are much more than that. - The SQLCMD feature was getting exited.- You can get IP of your servers, create, rename and drop folders. You can see the contents of any file anywhere and even start different tools from the same query window: Not so aged and wise DBA was getting interested: - I also want to run different scripts on different servers without changing connection of the query window. - Sure, sure! Another great feature that CMDmode is providing us with and giving more power to querying. Use “:” to use additional features, like :connect that allows you to change connection: - Now imagine, you have one script where you have all your changes, like creating staging table on the DWH staging server, adding fact table to DWH itself and updating stored procedures in the server where reporting database is located. - Now, give me more challenges! - Script out a list of stored procedures into the text files. - You can do it easily by using command :out which will write the query results into the specified text file. The output can be the code of the stored procedure or any data. Actually this is the same as changing the query output into the file instead of the grid. - Now, take all of the scripts and run all of them, one by one, on the different server.  - Easily - Come on... I’m sure that you can not... -Why not? Naturally, I can do it using :r commant which is opening a script and executing it. Look, I can also use :setvar command to define an environment variable in SQLCMD mode. Just note that you have to leave the empty string between :r commands, otherwise it’s not working although I have no idea why. - Wow.- She was really impressed. - Ok, I’ll go to try all those… -Wait, wait! I know how to google the SQL SERVER features for you! This example will open chrome explorer with search results for the “SQL server 2012 top features” ( change the path to suit your PC): “Well, this can be probably useful stuff, maybe this feature is really unfairly forgotten”, thought the DBA while going through the dark empty parking lot to her lonely car. “As someone really wise once said: “It is what we think we know that keeps us from learning. Learn, unlearn and relearn”.

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  • Sun Ray Hardware Last Order Dates & Extension of Premier Support for Desktop Virtualization Software

    - by Adam Hawley
    In light of the recent announcement  to end new feature development for Oracle Virtual Desktop Infrastructure Software (VDI), Oracle Sun Ray Software (SRS), Oracle Virtual Desktop Client (OVDC) Software, and Oracle Sun Ray Client hardware (3, 3i, and 3 Plus), there have been questions and concerns regarding what this means in terms of customers with new or existing deployments.  The following updates clarify some of these commonly asked questions. Extension of Premier Support for Software Though there will be no new feature additions to these products, customers will have access to maintenance update releases for Oracle Virtual Desktop Infrastructure and Sun Ray Software, including Oracle Virtual Desktop Client and Sun Ray Operating Software (SROS) until Premier Support Ends.  To ensure that customer investments for these products are protected, Oracle  Premier Support for these products has been extended by 3 years to following dates: Sun Ray Software - November 2017 Oracle Virtual Desktop Infrastructure - March 2017 Note that OVDC support is also extended to the above dates since OVDC is licensed by default as part the SRS and VDI products.   As a reminder, this only affects the products listed above.  Oracle Secure Global Desktop and Oracle VM VirtualBox will continue to be enhanced with new features from time-to-time and, as a result, they are not affected by the changes detailed in this message. The extension of support means that customers under a support contract will still be able to file service requests through Oracle Support, and Oracle will continue to provide the utmost level of support to our customers as expected,  until the published Premier Support end date.  Following the end of Premier Support, Sustaining Support remains an 'indefinite' period of time.   Sun Ray 3 Series Clients - Last Order Dates For Sun Ray Client hardware, customers can continue to purchase Sun Ray Client devices until the following last order dates: Product Marketing Part Number Last Order Date Last Ship Date Sun Ray 3 Plus TC3-P0Z-00, TC3-PTZ-00 (TAA) September 13, 2013 February 28, 2014 Sun Ray 3 Client TC3-00Z-00 February 28, 2014 August 31, 2014 Sun Ray 3i Client TC3-I0Z-00 February 28, 2014 August 31, 2014 Payflex Smart Cards X1403A-N, X1404A-N February 28, 2014 August 31, 2014 Note the difference in the Last Order Date for the Sun Ray 3 Plus (September 13, 2013) compared to the other products that have a Last Order Date of February 28, 2014. The rapidly approaching date for Sun Ray 3 Plus is due to a supplier phasing-out production of a key component of the 3 Plus.   Given September 13 is unfortunately quite soon, we strongly encourage you to place your last time buy as soon as possible to maximize Oracle's ability fulfill your order. Keep in mind you can schedule shipments to be delivered as late as the end of February 2014, but the last day to order is September 13, 2013. Customers wishing to purchase other models - Sun Ray 3 Clients and/or Sun Ray 3i Clients - have additional time (until February 28, 2014) to assess their needs and to allow fulfillment of last time orders.  Please note that availability of supply cannot be absolutely guaranteed up to the last order dates and we strongly recommend placing last time buys as early as possible.  Warranty replacements for Sun Ray Client hardware for customers covered by Oracle Hardware Systems Support contracts will be available beyond last order dates, per Oracle's policy found on Oracle.com here.  Per that policy, Oracle intends to provide replacement hardware for up to 5 years beyond the last ship date, but hardware may not be available beyond the 5 year period after the last ship date for reasons beyond Oracle's control. In any case, by design, Sun Ray Clients have an extremely long lifespan  and mean time between failures (MTBF) - much longer than PCs, and over the years we have continued to see first- and second generations of Sun Rays still in daily use.  This is no different for the Sun Ray 3, 3i, and 3 Plus.   Because of this, and in addition to Oracle's continued support for SRS, VDI, and SROS, Sun Ray and Oracle VDI deployments can continue to expand and exist as a viable solution for some time in the future. Continued Availability of Product Licenses and Support Oracle will continue to offer all existing software licenses, and software and hardware support including: Product licenses and Premier Support for Sun Ray Software and Oracle Virtual Desktop Infrastructure Premier Support for Operating Systems (for Sun Ray Operating Software maintenance upgrades/support)  Premier Support for Systems (for Sun Ray Operating Software maintenance upgrades/support and hardware warranty) Support renewals For More Information For more information, please refer to the following documents for specific dates and policies associated with the support of these products: Document 1478170.1 - Oracle Desktop Virtualization Software and Hardware Lifetime Support Schedule Document 1450710.1 - Sun Ray Client Hardware Lifetime schedule Document 1568808.1 - Document Support Policies for Discontinued Oracle Virtual Desktop Infrastructure, Sun Ray Software and Hardware and Oracle Virtual Desktop Client Development For Sales Orders and Questions Please contact your Oracle Sales Representative or Saurabh Vijay ([email protected])

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  • Video games, content strategy, and failure - oh my.

    - by Roger Hart
    Last night was the CS London group's event Content Strategy, Manhattan Style. Yes, it's a terrible title, feeling like a self-conscious grasp for chic, sadly commensurate with the venue. Fortunately, this was not commensurate with the event itself, which was lively, relevant, and engaging. Although mostly if you're a consultant. This is a strong strain in current content strategy discourse, and I think we're going to see it remedied quite soon. Not least in Paris on Friday. A lot of the bloggers, speakers, and commentators in the sphere are consultants, or part of agencies and other consulting organisations. A lot of the talk is about how you sell content strategy to your clients. This is completely acceptable. Of course it is. And it's actually useful if that's something you regularly have to do. To an extent, it's even portable to those of us who have to sell content strategy within an organisation. We're still competing for credibility and resource. What we're doing less is living in the beginning of a project. This was touched on by Jeffrey MacIntyre (albeit in a your-clients kind of a way) who described "the day two problem". Companies, he suggested, build websites for launch day, and forget about the need for them to be ongoing entities. Consultants, agencies, or even internal folks on short projects will live through Day Two quite often: the trainwreck moment where somebody realises that even if the content is right (which it often isn't), and on time (which it often isn't), it'll be redundant, outdated, or inaccurate by the end of the week/month/fickle social media attention cycle. The thing about living through a lot of Day Two is that you see a lot of failure. Nothing succeeds like failure? Failure is good. When it's structured right, it's an awesome tool for learning - that's kind of how video games work. I'm chewing over a whole blog post about this, but basically in game-like learning, you try, fail, go round the loop again. Success eventually yields joy. It's a relatively well-known phenomenon. It works best when that failing step is acutely felt, but extremely inexpensive. Dying in Portal is highly frustrating and surprisingly characterful, but the save-points are well designed and the reload unintrusive. The barrier to re-entry into the loop is very low, as is the cost of your failure out in meatspace. So it's easy (and fun) to learn. Yeah, spot the difference with business failure. As an external content strategist, you get to rock up with a big old folder full of other companies' Day Two (and ongoing day two hundred) failures. You can't send the client round the learning loop - although you may well be there because they've been round it once - but you can show other people's round trip. It's not as compelling, but it's not bad. What about internal content strategists? We can still point to things that are wrong, and there are some very compelling tools at our disposal - content inventories, user testing, and analytics, for instance. But if we're picking up big organically sprawling legacy content, Day Two may well be a distant memory, and the felt experience of web content failure is unlikely to be immediate to many people in the organisation. What to do? My hunch here is that the first task is to create something immediate and felt, but that it probably needs to be a success. Something quickly doable and visible - a content problem solved with a measurable business result. Now, that's a tall order; but scrape of the "quickly" and it's the whole reason we're here. At Red Gate, I've started with the text book fear and passion introduction to content strategy. In fact, I just typo'd that as "contempt strategy", and it isn't a bad description. Yelling "look at this, our website is rubbish!" gets you the initial attention, but it doesn't make you many friends. And if you don't produce something pretty sharp-ish, it's easy to lose the momentum you built up for change. The first thing I've done - after the visual content inventory - is to delete a bunch of stuff. About 70% of the SQL Compare web content has gone, in fact. This is a really, really cheap operation. It's visible, and it's powerful. It's cheap because you don't have to create any new content. It's not free, however, because you do have to validate your deletions. This means analytics, actually reading that content, and talking to people whose business purposes that content has to serve. If nobody outside the company uses it, and nobody inside the company thinks they ought to, that's a no-brainer for the delete list. The payoff here is twofold. There's the nebulous hard-to-illustrate "bad content does user experience and brand damage" argument; and there's the "nobody has to spend time (money) maintaining this now" argument. One or both are easily felt, and the second at least should be measurable. But that's just one approach, and I'd be interested to hear from any other internal content strategy folks about how they get buy-in, maintain momentum, and generally get things done.

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  • How to Achieve Real-Time Data Protection and Availabilty....For Real

    - by JoeMeeks
    There is a class of business and mission critical applications where downtime or data loss have substantial negative impact on revenue, customer service, reputation, cost, etc. Because the Oracle Database is used extensively to provide reliable performance and availability for this class of application, it also provides an integrated set of capabilities for real-time data protection and availability. Active Data Guard, depicted in the figure below, is the cornerstone for accomplishing these objectives because it provides the absolute best real-time data protection and availability for the Oracle Database. This is a bold statement, but it is supported by the facts. It isn’t so much that alternative solutions are bad, it’s just that their architectures prevent them from achieving the same levels of data protection, availability, simplicity, and asset utilization provided by Active Data Guard. Let’s explore further. Backups are the most popular method used to protect data and are an essential best practice for every database. Not surprisingly, Oracle Recovery Manager (RMAN) is one of the most commonly used features of the Oracle Database. But comparing Active Data Guard to backups is like comparing apples to motorcycles. Active Data Guard uses a hot (open read-only), synchronized copy of the production database to provide real-time data protection and HA. In contrast, a restore from backup takes time and often has many moving parts - people, processes, software and systems – that can create a level of uncertainty during an outage that critical applications can’t afford. This is why backups play a secondary role for your most critical databases by complementing real-time solutions that can provide both data protection and availability. Before Data Guard, enterprises used storage remote-mirroring for real-time data protection and availability. Remote-mirroring is a sophisticated storage technology promoted as a generic infrastructure solution that makes a simple promise – whatever is written to a primary volume will also be written to the mirrored volume at a remote site. Keeping this promise is also what causes data loss and downtime when the data written to primary volumes is corrupt – the same corruption is faithfully mirrored to the remote volume making both copies unusable. This happens because remote-mirroring is a generic process. It has no  intrinsic knowledge of Oracle data structures to enable advanced protection, nor can it perform independent Oracle validation BEFORE changes are applied to the remote copy. There is also nothing to prevent human error (e.g. a storage admin accidentally deleting critical files) from also impacting the remote mirrored copy. Remote-mirroring tricks users by creating a false impression that there are two separate copies of the Oracle Database. In truth; while remote-mirroring maintains two copies of the data on different volumes, both are part of a single closely coupled system. Not only will remote-mirroring propagate corruptions and administrative errors, but the changes applied to the mirrored volume are a result of the same Oracle code path that applied the change to the source volume. There is no isolation, either from a storage mirroring perspective or from an Oracle software perspective.  Bottom line, storage remote-mirroring lacks both the smarts and isolation level necessary to provide true data protection. Active Data Guard offers much more than storage remote-mirroring when your objective is protecting your enterprise from downtime and data loss. Like remote-mirroring, an Active Data Guard replica is an exact block for block copy of the primary. Unlike remote-mirroring, an Active Data Guard replica is NOT a tightly coupled copy of the source volumes - it is a completely independent Oracle Database. Active Data Guard’s inherent knowledge of Oracle data block and redo structures enables a separate Oracle Database using a different Oracle code path than the primary to use the full complement of Oracle data validation methods before changes are applied to the synchronized copy. These include: physical check sum, logical intra-block checking, lost write validation, and automatic block repair. The figure below illustrates the stark difference between the knowledge that remote-mirroring can discern from an Oracle data block and what Active Data Guard can discern. An Active Data Guard standby also provides a range of additional services enabled by the fact that it is a running Oracle Database - not just a mirrored copy of data files. An Active Data Guard standby database can be open read-only while it is synchronizing with the primary. This enables read-only workloads to be offloaded from the primary system and run on the active standby - boosting performance by utilizing all assets. An Active Data Guard standby can also be used to implement many types of system and database maintenance in rolling fashion. Maintenance and upgrades are first implemented on the standby while production runs unaffected at the primary. After the primary and standby are synchronized and all changes have been validated, the production workload is quickly switched to the standby. The only downtime is the time required for user connections to transfer from one system to the next. These capabilities further expand the expectations of availability offered by a data protection solution beyond what is possible to do using storage remote-mirroring. So don’t be fooled by appearances.  Storage remote-mirroring and Active Data Guard replication may look similar on the surface - but the devil is in the details. Only Active Data Guard has the smarts, the isolation, and the simplicity, to provide the best data protection and availability for the Oracle Database. Stay tuned for future blog posts that dive into the many differences between storage remote-mirroring and Active Data Guard along the dimensions of data protection, data availability, cost, asset utilization and return on investment. For additional information on Active Data Guard, see: Active Data Guard Technical White Paper Active Data Guard vs Storage Remote-Mirroring Active Data Guard Home Page on the Oracle Technology Network

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  • Master Data Management Implementation Styles

    - by david.butler(at)oracle.com
    In any Master Data Management solution deployment, one of the key decisions to be made is the choice of the MDM architecture. Gartner and other analysts describe some different Hub deployment styles, which must be supported by a best of breed MDM solution in order to guarantee the success of the deployment project.   Registry Style: In a Registry Style MDM Hub, the various source systems publish their data and a subscribing Hub stores only the source system IDs, the Foreign Keys (record IDs on source systems) and the key data values needed for matching. The Hub runs the cleansing and matching algorithms and assigns unique global identifiers to the matched records, but does not send any data back to the source systems. The Registry Style MDM Hub uses data federation capabilities to build the "virtual" golden view of the master entity from the connected systems.   Consolidation Style: The Consolidation Style MDM Hub has a physically instantiated, "golden" record stored in the central Hub. The authoring of the data remains distributed across the spoke systems and the master data can be updated based on events, but is not guaranteed to be up to date. The master data in this case is usually not used for transactions, but rather supports reporting; however, it can also be used for reference operationally.   Coexistence Style: The Coexistence Style MDM Hub involves master data that's authored and stored in numerous spoke systems, but includes a physically instantiated golden record in the central Hub and harmonized master data across the application portfolio. The golden record is constructed in the same manner as in the consolidation style, and, in the operational world, Consolidation Style MDM Hubs often evolve into the Coexistence Style. The key difference is that in this architectural style the master data stored in the central MDM system is selectively published out to the subscribing spoke systems.   Transaction Style: In this architecture, the Hub stores, enhances and maintains all the relevant (master) data attributes. It becomes the authoritative source of truth and publishes this valuable information back to the respective source systems. The Hub publishes and writes back the various data elements to the source systems after the linking, cleansing, matching and enriching algorithms have done their work. Upstream, transactional applications can read master data from the MDM Hub, and, potentially, all spoke systems subscribe to updates published from the central system in a form of harmonization. The Hub needs to support merging of master records. Security and visibility policies at the data attribute level need to be supported by the Transaction Style hub, as well.   Adaptive Transaction Style: This is similar to the Transaction Style, but additionally provides the capability to respond to diverse information and process requests across the enterprise. This style emerged most recently to address the limitations of the above approaches. With the Adaptive Transaction Style, the Hub is built as a platform for consolidating data from disparate third party and internal sources and for serving unified master entity views to operational applications, analytical systems or both. This approach delivers a real-time Hub that has a reliable, persistent foundation of master reference and relationship data, along with all the history and lineage of data changes needed for audit and compliance tracking. On top of this persistent master data foundation, the Hub can dynamically aggregate transaction data on demand from different source systems to deliver the unified golden view to downstream systems. Data can also be accessed through batch interfaces, published to a message bus or served through a real-time services layer. New data sources can be readily added in this approach by extending the data model and by configuring the new source mappings and the survivorship rules, meaning that all legacy data hubs can be leveraged to contribute their records/rules into the new transaction hub. Finally, through rich user interfaces for data stewardship, it allows exception handling by business analysts to keep it current with business rules/practices while maintaining the reliability of best-of-breed master records.   Confederation Style: In this architectural style, several Hubs are maintained at departmental and/or agency and/or territorial level, and each of them are connected to the other Hubs either directly or via a central Super-Hub. Each Domain level Hub can be implemented using any of the previously described styles, but normally the Central Super-Hub is a Registry Style one. This is particularly important for Public Sector organizations, where most of the time it is practically or legally impossible to store in a single central hub all the relevant constituent information from all departments.   Oracle MDM Solutions can be deployed according to any of the above MDM architectural styles, and have been specifically designed to fully support the Transaction and Adaptive Transaction styles. Oracle MDM Solutions provide strong data federation and integration capabilities which are key to enabling the use of the Confederated Hub as a possible architectural style approach. Don't lock yourself into a solution that cannot evolve with your needs. With Oracle's support for any type of deployment architecture, its ability to leverage the outstanding capabilities of the Oracle technology stack, and its open interfaces for non-Oracle technology stacks, Oracle MDM Solutions provide a low TCO and a quick ROI by enabling a phased implementation strategy.

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  • Cardinality Estimation Bug with Lookups in SQL Server 2008 onward

    - by Paul White
    Cost-based optimization stands or falls on the quality of cardinality estimates (expected row counts).  If the optimizer has incorrect information to start with, it is quite unlikely to produce good quality execution plans except by chance.  There are many ways we can provide good starting information to the optimizer, and even more ways for cardinality estimation to go wrong.  Good database people know this, and work hard to write optimizer-friendly queries with a schema and metadata (e.g. statistics) that reduce the chances of poor cardinality estimation producing a sub-optimal plan.  Today, I am going to look at a case where poor cardinality estimation is Microsoft’s fault, and not yours. SQL Server 2005 SELECT th.ProductID, th.TransactionID, th.TransactionDate FROM Production.TransactionHistory AS th WHERE th.ProductID = 1 AND th.TransactionDate BETWEEN '20030901' AND '20031231'; The query plan on SQL Server 2005 is as follows (if you are using a more recent version of AdventureWorks, you will need to change the year on the date range from 2003 to 2007): There is an Index Seek on ProductID = 1, followed by a Key Lookup to find the Transaction Date for each row, and finally a Filter to restrict the results to only those rows where Transaction Date falls in the range specified.  The cardinality estimate of 45 rows at the Index Seek is exactly correct.  The table is not very large, there are up-to-date statistics associated with the index, so this is as expected. The estimate for the Key Lookup is also exactly right.  Each lookup into the Clustered Index to find the Transaction Date is guaranteed to return exactly one row.  The plan shows that the Key Lookup is expected to be executed 45 times.  The estimate for the Inner Join output is also correct – 45 rows from the seek joining to one row each time, gives 45 rows as output. The Filter estimate is also very good: the optimizer estimates 16.9951 rows will match the specified range of transaction dates.  Eleven rows are produced by this query, but that small difference is quite normal and certainly nothing to worry about here.  All good so far. SQL Server 2008 onward The same query executed against an identical copy of AdventureWorks on SQL Server 2008 produces a different execution plan: The optimizer has pushed the Filter conditions seen in the 2005 plan down to the Key Lookup.  This is a good optimization – it makes sense to filter rows out as early as possible.  Unfortunately, it has made a bit of a mess of the cardinality estimates. The post-Filter estimate of 16.9951 rows seen in the 2005 plan has moved with the predicate on Transaction Date.  Instead of estimating one row, the plan now suggests that 16.9951 rows will be produced by each clustered index lookup – clearly not right!  This misinformation also confuses SQL Sentry Plan Explorer: Plan Explorer shows 765 rows expected from the Key Lookup (it multiplies a rounded estimate of 17 rows by 45 expected executions to give 765 rows total). Workarounds One workaround is to provide a covering non-clustered index (avoiding the lookup avoids the problem of course): CREATE INDEX nc1 ON Production.TransactionHistory (ProductID) INCLUDE (TransactionDate); With the Transaction Date filter applied as a residual predicate in the same operator as the seek, the estimate is again as expected: We could also force the use of the ultimate covering index (the clustered one): SELECT th.ProductID, th.TransactionID, th.TransactionDate FROM Production.TransactionHistory AS th WITH (INDEX(1)) WHERE th.ProductID = 1 AND th.TransactionDate BETWEEN '20030901' AND '20031231'; Summary Providing a covering non-clustered index for all possible queries is not always practical, and scanning the clustered index will rarely be optimal.  Nevertheless, these are the best workarounds we have today. In the meantime, watch out for poor cardinality estimates when a predicate is applied as part of a lookup. The worst thing is that the estimate after the lookup join in the 2008+ plans is wrong.  It’s not hopelessly wrong in this particular case (45 versus 16.9951 is not the end of the world) but it easily can be much worse, and there’s not much you can do about it.  Any decisions made by the optimizer after such a lookup could be based on very wrong information – which can only be bad news. If you think this situation should be improved, please vote for this Connect item. © 2012 Paul White – All Rights Reserved twitter: @SQL_Kiwi email: [email protected]

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  • When does "proper" programming no longer matter?

    - by Kai Qing
    I've been a full time programmer for about 8 years now. Web based mostly, ranging in weird jobs for clients. Never anything I "want" to do. So my experience is limited to what I've been contracted to do, having no real incentive to master anything in particular. So here's my scenario and ultimately what I wonder about... I've been building an android game in my spare time. It's using the libgdx library so quite a bit of the heavy lifting is done for me. I don't read much of the docs cause unless it's in tutorial format I will just not care, and ultimately most of my questions have already been asked on stackoverflow. I get along fine and my game works as expected... Suspiciously well, even. So much so that I wonder why one should bother to be "proper" when coding if the end result is ultimately the same. To be more specific, I used a hashtable because I wanted something close to an associative array. Human readable key values. In other places to achieve similar things, I use a vector. I know libgdx has vector2 and vector3 classes, but I've never used them. When I come across weird problems and search stackoverflow for help, I see a lot of people just reaming the questions that use a certain datatype when another one is technically "proper." Like using an ArrayList because it does not require defined bounds versus re-defining an int[] with new known boundaries. Or even something trivial like this: for(int i = 0; i < items.length; i ++) { // do something } I know it evaluates item.length on every iteration. I just don't care. I know items will never be more than 15 to 20 items. So why bother caring if I evaluate items.length on every iteration? So I wonder - why does everyone get all up in arms over this? Who cares if I use a less efficient datatype to get the job done? I ran some tests to see how the app performs using the lazy, get it done fast and don't look back method I just described versus the proper, follow the tutorial and use the exact data types suggested by the community. The results: Same thing. Average 45 fps. I opened every app on the phone and galaxy tab. Same deal. No difference. My game is pretty graphic intensive. It's not like it's just a simple thing. I expected it to perform kind of badly since I don't care to optimize image assets or... well, you probably get the idea. I'm making the game for fun. As a joke, really. But in doing so I'm working outside the normal scope of my job, which is to always follow the rules and do it the right way. So to say, I am without bounds here and this has caused me to wonder why I ever really care to be "proper" So I guess my question to you is this: Is there a threshold when it no longer matters to be proper? Is there a lasting, longer term consequence to the lazy, get it done and don't look back route? Is it ok to say - "so long as it gets the job done, I don't care?" Disclaimer: When I program my game, I am almost always drunk. I do it to remember why I got into this stuff to begin with because the monotony of client based web work will make you hate being a programmer. I'm having a blast and my game is not crashing, tests well, performs well, looks good on all devices so far and has no noticeable negative impact on any of my testing devices. I expected failure because I was being so drunkenly careless with my code, but to my surprise, it had no noticeable impact. I am now starting to question the need to be careful. Help me regain the ability to care! ... or explain why it's not a bad thing to not care. Secondary disclaimer: I am aware of the benefits of maintainability. For myself and others. Agreed. But it's not like someone happening across my inefficient int[] loop won't know what it does. As an experienced programmer those kinds of things are just clear on sight. I document the complex stuff for myself knowing I was drunk and will probably need a reminder. Those notes would clarify any confusion for someone who might ever gaze upon my ridiculous game - though the reality is that either I maintain it myself or it fades into time. I'm ok with that. But if it doesn't slow the device down, or crash, then crossing the t's and dotting the i's might actually require more time than it's worth.

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  • Working with packed dates in SSIS

    - by Jim Giercyk
    One of the challenges recently thrown my way was to read an EBCDIC flat file, decode packed dates, and insert the dates into a SQL table.  For those unfamiliar with packed data, it is a way to store data at the nibble level (half a byte), and was often used by mainframe programmers to conserve storage space.  In the case of my input file, the dates were 2 bytes long and  represented the number of days that have past since 01/01/1950.  My first thought was, in the words of Scooby, Hmmmmph?  But, I love a good challenge, so I dove in. Reading in the flat file was rather simple.  The only difference between reading an EBCDIC and an ASCII file is the Code Page option in the connection manager.  In my case, I needed to use Code Page 1140 for EBCDIC (I could have also used Code Page 37).       Once the code page is set correctly, SSIS can understand what it is reading and it will convert the output to the default code page, 1252.  However, packed data is either unreadable or produces non-alphabetic characters, as we can see in the preview window.   Column 1 is actually the packed date, columns 0 and 2 are the values in the rest of the file.  We are only interested in Column 1, which is a 2 byte field representing a packed date.  We know that 2 bytes of packed data can be stored in 1 byte of character data, so we are working with 4 packed digits in 2 character bytes.  If you are confused, stay tuned….this will make sense in a minute.   Right-click on your Flat File Source shape and select “Show Advanced Editor”. Here is where the magic begins. By changing the properties of the output columns, we can access the packed digits from each byte. By default, the Output Column data type is DT_STR. Since we want to look at the bytes individually and not the entire string, change the data type to DT_BYTES. Next, and most important, set UseBinaryFormat to TRUE. This will write the HEX VALUES of the output string instead of writing the character values.  Now we are getting somewhere! Next, you will need to use a Data Conversion shape in your Data Flow to transform the 2 position byte stream to a 4 position Unicode string containing the packed data.  You need the string to be 4 bytes long because it will contain the 4 packed digits.  Here is what that should look like in the Data Conversion shape: Direct the output of your data flow to a test table or file to see the results.  In my case, I created a test table.  The results looked like this:     Hold on a second!  That doesn't look like a date at all.  No, of course not.  It is a hex number which represents the days which have passed between 01/01/1950 and the date.  We have to convert the Hex value to a decimal value, and use the DATEADD function to get a date value.  Luckily, I have created a function to convert Hex to Decimal:   -- ============================================= -- Author:        Jim Giercyk -- Create date: March, 2012 -- Description:    Converts a Hex string to a decimal value -- ============================================= CREATE FUNCTION [dbo].[ftn_HexToDec] (     @hexValue NVARCHAR(6) ) RETURNS DECIMAL AS BEGIN     -- Declare the return variable here DECLARE @decValue DECIMAL IF @hexValue LIKE '0x%' SET @hexValue = SUBSTRING(@hexValue,3,4) DECLARE @decTab TABLE ( decPos1 VARCHAR(2), decPos2 VARCHAR(2), decPos3 VARCHAR(2), decPos4 VARCHAR(2) ) DECLARE @pos1 VARCHAR(1) = SUBSTRING(@hexValue,1,1) DECLARE @pos2 VARCHAR(1) = SUBSTRING(@hexValue,2,1) DECLARE @pos3 VARCHAR(1) = SUBSTRING(@hexValue,3,1) DECLARE @pos4 VARCHAR(1) = SUBSTRING(@hexValue,4,1) INSERT @decTab VALUES (CASE               WHEN @pos1 = 'A' THEN '10'                 WHEN @pos1 = 'B' THEN '11'               WHEN @pos1 = 'C' THEN '12'               WHEN @pos1 = 'D' THEN '13'               WHEN @pos1 = 'E' THEN '14'               WHEN @pos1 = 'F' THEN '15'               ELSE @pos1              END, CASE               WHEN @pos2 = 'A' THEN '10'                 WHEN @pos2 = 'B' THEN '11'               WHEN @pos2 = 'C' THEN '12'               WHEN @pos2 = 'D' THEN '13'               WHEN @pos2 = 'E' THEN '14'               WHEN @pos2 = 'F' THEN '15'               ELSE @pos2              END, CASE               WHEN @pos3 = 'A' THEN '10'                 WHEN @pos3 = 'B' THEN '11'               WHEN @pos3 = 'C' THEN '12'               WHEN @pos3 = 'D' THEN '13'               WHEN @pos3 = 'E' THEN '14'               WHEN @pos3 = 'F' THEN '15'               ELSE @pos3              END, CASE               WHEN @pos4 = 'A' THEN '10'                 WHEN @pos4 = 'B' THEN '11'               WHEN @pos4 = 'C' THEN '12'               WHEN @pos4 = 'D' THEN '13'               WHEN @pos4 = 'E' THEN '14'               WHEN @pos4 = 'F' THEN '15'               ELSE @pos4              END) SET @decValue = (CONVERT(INT,(SELECT decPos4 FROM @decTab)))         +                 (CONVERT(INT,(SELECT decPos3 FROM @decTab))*16)      +                 (CONVERT(INT,(SELECT decPos2 FROM @decTab))*(16*16)) +                 (CONVERT(INT,(SELECT decPos1 FROM @decTab))*(16*16*16))     RETURN @decValue END GO     Making use of the function, I found the decimal conversion, added that number of days to 01/01/1950 and FINALLY arrived at my “unpacked relative date”.  Here is the query I used to retrieve the formatted date, and the result set which was returned: SELECT [packedDate] AS 'Hex Value',        dbo.ftn_HexToDec([packedDate]) AS 'Decimal Value',        CONVERT(DATE,DATEADD(day,dbo.ftn_HexToDec([packedDate]),'01/01/1950'),101) AS 'Relative String Date'   FROM [dbo].[Output Table]         This technique can be used any time you need to retrieve the hex value of a character string in SSIS.  The date example may be a bit difficult to understand at first, but with SSIS becoming the preferred tool for enterprise level integration for many companies, there is no doubt that developers will encounter these types of requirements with regularity in the future. Please feel free to contact me if you have any questions.

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  • Process Centric Banking: Loan Origination Solution

    - by Manish Palaparthy
    There is an old proverb that goes, "The difference between theory and practice is greater in practice than in theory". So, we keep doing numerous "Proof of Concepts" with our own products on various business cases to analyze them deeply, understand and explain to our customers. We then present our learnings as they happened. The awareness of each PoC should help readers increase the trustworthiness of the results coming out of these PoCs. I present one such PoC where we invested a lot of time&effort.  Process Centric Banking : Loan Origination Solution Loan Origination is a process by which a borrower applies for a new loan and the lender processes that application. Loan origination includes the series of steps taken by the bank from the point the customer shows interest in a loan product all the way to disbursal of funds. The Loan Origination process is relevant for many kind of lenders in Financial services: Banks, Credit Unions, NBFCs(Non Banking Financial Companies) and so on. For simplicity sake, I will use "Bank" as the lending institution in the rest of my article.  Loan Origination is one of the core processes for Banks as it is the process by which the it creates assets against which the Institution earns most of its profits from. A well tuned loan origination process can affect the Bank in many positive ways. Banks have always shown great interest in automating the loan origination process for the above reason. However, due the constant changes in customer environment, market dynamics, prevailing economic conditions, cost pressures & regulatory environment they run into lot of challenges. Let me categorize some of these challenges for you Customer Environment Multiple Channels: Customer can use any of the available channels (Internet Banking, Email, Fax, Branch, Phone Banking, ATM, Broker, Mobile, Snail Mail) to perform all or some of the activities related to her Visibility into the origination process: Expect immediate update on the status of loan processing & alert messages Reduced Turn Around Time: Expect loans to be processed with least turn around time Reduced loan processing fees: Partly due to market dynamics the customer expects the loan processing fee to be negligible Market Dynamics Competitive environment:  The competition keeps creating many variants of loan products to attract customers, the bank needs to create similar product variants with better offers to attract customers or keep existing ones Ability to migrate loans from one vendor to another: It has become really easy for retail customers to move from one bank to the other given the low fee of loan processing and highly attractive offers. How does the bank protect it's customer base while actively engaging with potential customers banking with competitor banks Flexibility to react to market developments: Market development greatly influence loan processing, underwriting, asset valuation, risk mitigation rules. Can the bank modify rules and policies, the idea is not just to react to market developments but to pro-actively manage new developments Economic conditions Constant change in various rates and their implications on the rates and rules applied when on-boarding a loan: How quickly can the bank apply changes to rates offered to customers when the central bank changes various rates Requirements of Audit by the central banker: Tough economic conditions have demanded much more stringent audit rules and tests. The banks needs to produce ready reports(historic & operational) for audit compliance Risk Mitigation: While risk mitigation has always been a key concern for the bank, this is the area where the bank's underwriters & risk analysts spend the maximum time when processing a loan application. In order to reduce TAT the bank cannot compromise on its risk mitigation strategies Cost pressures Reduce Cost of processing per application: To deliver a reduced loan processing fee to the customer, the bank needs to keep its cost per processing loan application low. Meet customer TAT expectations while reducing the queues and the systems being used to process the loan application: The loan application could potentially be spending a lot of time waiting in the queue for further processing. Different volumes & patterns of applications demand different queuing algorithms. The bank needs to have real-time visibility into these queues and have the flexibility to change queuing algorithms at runtime  Increase the use of electronic communication and reduce the branch channel usage: Lesser automation leads not only leads to Increased turn around time, it also impacts more costs to reach out to customers The objective of our PoC was to implement a Loan Origination Solution whose ownership lies with the bank and effectively meet the challenges listed above. We built a simple story board for the solution We then went about implementing our storyboard using Oracle BPM Suite, Webcenter Content : Imaging. The web UI has been built on ADF technolgies, while the integration with core-services has been implemented using the underlying SOA infrastructure. The BPM process model is quite exhaustive can meet all the challenges listed above to reasonable degree. A bank intending to implement an end-to-end Loan Origination Solution has multiple options at it's disposal. It can Develop a customer Loan Origination Application from scratch: Gives maximum opportunity to build what you want but inflexible to upgrade and maintain. Higher TCO in long term Buy a Packaged application & customize it: Customizing a generic loan application can be tedious and prove as difficult as above. Build it using many disparate & un-integrated tools: Initially seems easier than developing from scratch. But, without integrated tool sets this is not a viable approach either or A solution based on a Framework: Independent Services and Business Process Modeling provide decoupled architecture that is flexible. We built this framework end-to-end with processes the core process of loan origination & several sub-processes such as Analyse and define customer needs, customer credit verification, identity check processes, legal review process, New customer registration & risk assessment.

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  • SPARC T4-4 Delivers World Record Performance on Oracle OLAP Perf Version 2 Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered world record performance with subsecond response time on the Oracle OLAP Perf Version 2 benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 11. The SPARC T4-4 server achieved throughput of 430,000 cube-queries/hour with an average response time of 0.85 seconds and the median response time of 0.43 seconds. This was achieved by using only 60% of the available CPU resources leaving plenty of headroom for future growth. The SPARC T4-4 server operated on an Oracle OLAP cube with a 4 billion row fact table of sales data containing 4 dimensions. This represents as many as 90 quintillion aggregate rows (90 followed by 18 zeros). Performance Landscape Oracle OLAP Perf Version 2 Benchmark 4 Billion Fact Table Rows System Queries/hour Users* Response Time (sec) Average Median SPARC T4-4 430,000 7,300 0.85 0.43 * Users - the supported number of users with a given think time of 60 seconds Configuration Summary and Results Hardware Configuration: SPARC T4-4 server with 4 x SPARC T4 processors, 3.0 GHz 1 TB memory Data Storage 1 x Sun Fire X4275 (using COMSTAR) 2 x Sun Storage F5100 Flash Array (each with 80 FMODs) Redo Storage 1 x Sun Fire X4275 (using COMSTAR with 8 HDD) Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 (11.2.0.3) with Oracle OLAP option Benchmark Description The Oracle OLAP Perf Version 2 benchmark is a workload designed to demonstrate and stress the Oracle OLAP product's core features of fast query, fast update, and rich calculations on a multi-dimensional model to support enhanced Data Warehousing. The bulk of the benchmark entails running a number of concurrent users, each issuing typical multidimensional queries against an Oracle OLAP cube consisting of a number of years of sales data with fully pre-computed aggregations. The cube has four dimensions: time, product, customer, and channel. Each query user issues approximately 150 different queries. One query chain may ask for total sales in a particular region (e.g South America) for a particular time period (e.g. Q4 of 2010) followed by additional queries which drill down into sales for individual countries (e.g. Chile, Peru, etc.) with further queries drilling down into individual stores, etc. Another query chain may ask for yearly comparisons of total sales for some product category (e.g. major household appliances) and then issue further queries drilling down into particular products (e.g. refrigerators, stoves. etc.), particular regions, particular customers, etc. Results from version 2 of the benchmark are not comparable with version 1. The primary difference is the type of queries along with the query mix. Key Points and Best Practices Since typical BI users are often likely to issue similar queries, with different constants in the where clauses, setting the init.ora prameter "cursor_sharing" to "force" will provide for additional query throughput and a larger number of potential users. Except for this setting, together with making full use of available memory, out of the box performance for the OLAP Perf workload should provide results similar to what is reported here. For a given number of query users with zero think time, the main measured metrics are the average query response time, the median query response time, and the query throughput. A derived metric is the maximum number of users the system can support achieving the measured response time assuming some non-zero think time. The calculation of the maximum number of users follows from the well-known response-time law N = (rt + tt) * tp where rt is the average response time, tt is the think time and tp is the measured throughput. Setting tt to 60 seconds, rt to 0.85 seconds and tp to 119.44 queries/sec (430,000 queries/hour), the above formula shows that the T4-4 server will support 7,300 concurrent users with a think time of 60 seconds and an average response time of 0.85 seconds. For more information see chapter 3 from the book "Quantitative System Performance" cited below. -- See Also Quantitative System Performance Computer System Analysis Using Queueing Network Models Edward D. Lazowska, John Zahorjan, G. Scott Graham, Kenneth C. Sevcik external local Oracle Database 11g – Oracle OLAP oracle.com OTN SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 11/2/2012.

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  • Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

    - by aspiringgeek
    Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario Conventional Structures Columnstore ? SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

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  • Organization &amp; Architecture UNISA Studies &ndash; Chap 5

    - by MarkPearl
    Learning Outcomes Describe the operation of a memory cell Explain the difference between DRAM and SRAM Discuss the different types of ROM Explain the concepts of a hard failure and a soft error respectively Describe SDRAM organization Semiconductor Main Memory The two traditional forms of RAM used in computers are DRAM and SRAM DRAM (Dynamic RAM) Divided into two technologies… Dynamic Static Dynamic RAM is made with cells that store data as charge on capacitors. The presence or absence of charge in a capacitor is interpreted as a binary 1 or 0. Because capacitors have natural tendency to discharge, dynamic RAM requires periodic charge refreshing to maintain data storage. The term dynamic refers to the tendency of the stored charge to leak away, even with power continuously applied. Although the DRAM cell is used to store a single bit (0 or 1), it is essentially an analogue device. The capacitor can store any charge value within a range, a threshold value determines whether the charge is interpreted as a 1 or 0. SRAM (Static RAM) SRAM is a digital device that uses the same logic elements used in the processor. In SRAM, binary values are stored using traditional flip flop logic configurations. SRAM will hold its data as along as power is supplied to it. Unlike DRAM, no refresh is required to retain data. SRAM vs. DRAM DRAM is simpler and smaller than SRAM. Thus it is more dense and less expensive than SRAM. The cost of the refreshing circuitry for DRAM needs to be considered, but if the machine requires a large amount of memory, DRAM turns out to be cheaper than SRAM. SRAMS are somewhat faster than DRAM, thus SRAM is generally used for cache memory and DRAM is used for main memory. Types of ROM Read Only Memory (ROM) contains a permanent pattern of data that cannot be changed. ROM is non volatile meaning no power source is required to maintain the bit values in memory. While it is possible to read a ROM, it is not possible to write new data into it. An important application of ROM is microprogramming, other applications include library subroutines for frequently wanted functions, System programs, Function tables. A ROM is created like any other integrated circuit chip, with the data actually wired into the chip as part of the fabrication process. To reduce costs of fabrication, we have PROMS. PROMS are… Written only once Non-volatile Written after fabrication Another variation of ROM is the read-mostly memory, which is useful for applications in which read operations are far more frequent than write operations, but for which non volatile storage is required. There are three common forms of read-mostly memory, namely… EPROM EEPROM Flash memory Error Correction Semiconductor memory is subject to errors, which can be classed into two categories… Hard failure – Permanent physical defect so that the memory cell or cells cannot reliably store data Soft failure – Random error that alters the contents of one or more memory cells without damaging the memory (common cause includes power supply issues, etc.) Most modern main memory systems include logic for both detecting and correcting errors. Error detection works as follows… When data is to be read into memory, a calculation is performed on the data to produce a code Both the code and the data are stored When the previously stored word is read out, the code is used to detect and possibly correct errors The error checking provides one of 3 possible results… No errors are detected – the fetched data bits are sent out An error is detected, and it is possible to correct the error. The data bits plus error correction bits are fed into a corrector, which produces a corrected set of bits to be sent out An error is detected, but it is not possible to correct it. This condition is reported Hamming Code See wiki for detailed explanation. We will probably need to know how to do a hemming code – refer to the textbook (pg. 188 – 189) Advanced DRAM organization One of the most critical system bottlenecks when using high-performance processors is the interface to main memory. This interface is the most important pathway in the entire computer system. The basic building block of main memory remains the DRAM chip. In recent years a number of enhancements to the basic DRAM architecture have been explored, and some of these are now on the market including… SDRAM (Synchronous DRAM) DDR-DRAM RDRAM SDRAM (Synchronous DRAM) SDRAM exchanges data with the processor synchronized to an external clock signal and running at the full speed of the processor/memory bus without imposing wait states. SDRAM employs a burst mode to eliminate the address setup time and row and column line precharge time after the first access In burst mode a series of data bits can be clocked out rapidly after the first bit has been accessed SDRAM has a multiple bank internal architecture that improves opportunities for on chip parallelism SDRAM performs best when it is transferring large blocks of data serially There is now an enhanced version of SDRAM known as double data rate SDRAM or DDR-SDRAM that overcomes the once-per-cycle limitation of SDRAM

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  • Breaking through the class sealing

    - by Jason Crease
    Do you understand 'sealing' in C#?  Somewhat?  Anyway, here's the lowdown. I've done this article from a C# perspective, but I've occasionally referenced .NET when appropriate. What is sealing a class? By sealing a class in C#, you ensure that you ensure that no class can be derived from that class.  You do this by simply adding the word 'sealed' to a class definition: public sealed class Dog {} Now writing something like " public sealed class Hamster: Dog {} " you'll get a compile error like this: 'Hamster: cannot derive from sealed type 'Dog' If you look in an IL disassembler, you'll see a definition like this: .class public auto ansi sealed beforefieldinit Dog extends [mscorlib]System.Object Note the addition of the word 'sealed'. What about sealing methods? You can also seal overriding methods.  By adding the word 'sealed', you ensure that the method cannot be overridden in a derived class.  Consider the following code: public class Dog : Mammal { public sealed override void Go() { } } public class Mammal { public virtual void Go() { } } In this code, the method 'Go' in Dog is sealed.  It cannot be overridden in a subclass.  Writing this would cause a compile error: public class Dachshund : Dog { public override void Go() { } } However, we can 'new' a method with the same name.  This is essentially a new method; distinct from the 'Go' in the subclass: public class Terrier : Dog { public new void Go() { } } Sealing properties? You can also seal seal properties.  You add 'sealed' to the property definition, like so: public sealed override string Name {     get { return m_Name; }     set { m_Name = value; } } In C#, you can only seal a property, not the underlying setters/getters.  This is because C# offers no override syntax for setters or getters.  However, in underlying IL you seal the setter and getter methods individually - a property is just metadata. Why bother sealing? There are a few traditional reasons to seal: Invariance. Other people may want to derive from your class, even though your implementation may make successful derivation near-impossible.  There may be twisted, hacky logic that could never be second-guessed by another developer.  By sealing your class, you're protecting them from wasting their time.  The CLR team has sealed most of the framework classes, and I assume they did this for this reason. Security.  By deriving from your type, an attacker may gain access to functionality that enables him to hack your system.  I consider this a very weak security precaution. Speed.  If a class is sealed, then .NET doesn't need to consult the virtual-function-call table to find the actual type, since it knows that no derived type can exist.  Therefore, it could emit a 'call' instead of 'callvirt' or at least optimise the machine code, thus producing a performance benefit.  But I've done trials, and have been unable to demonstrate this If you have an example, please share! All in all, I'm not convinced that sealing is interesting or important.  Anyway, moving-on... What is automatically sealed? Value types and structs.  If they were not always sealed, all sorts of things would go wrong.  For instance, structs are laid-out inline within a class.  But what if you assigned a substruct to a struct field of that class?  There may be too many fields to fit. Static classes.  Static classes exist in C# but not .NET.  The C# compiler compiles a static class into an 'abstract sealed' class.  So static classes are already sealed in C#. Enumerations.  The CLR does not track the types of enumerations - it treats them as simple value types.  Hence, polymorphism would not work. What cannot be sealed? Interfaces.  Interfaces exist to be implemented, so sealing to prevent implementation is dumb.  But what if you could prevent interfaces from being extended (i.e. ban declarations like "public interface IMyInterface : ISealedInterface")?  There is no good reason to seal an interface like this.  Sealing finalizes behaviour, but interfaces have no intrinsic behaviour to finalize Abstract classes.  In IL you can create an abstract sealed class.  But C# syntax for this already exists - declaring a class as a 'static', so it forces you to declare it as such. Non-override methods.  If a method isn't declared as override it cannot be overridden, so sealing would make no difference.  Note this is stated from a C# perspective - the words are opposite in IL.  In IL, you have four choices in total: no declaration (which actually seals the method), 'virtual' (called 'override' in C#), 'sealed virtual' ('sealed override' in C#) and 'newslot virtual' ('new virtual' or 'virtual' in C#, depending on whether the method already exists in a base class). Methods that implement interface methods.  Methods that implement an interface method must be virtual, so cannot be sealed. Fields.  A field cannot be overridden, only hidden (using the 'new' keyword in C#), so sealing would make no sense.

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  • Deep in the Heart of Texas

    - by Applications User Experience
    Author: Erika Webb, Manager, Fusion Applications UX User Assistance When I was first working in the usability field, the only way I could consider conducting a usability study was to bring a potential user to a lab environment where I could show them whatever I was interested in learning more about and ask them questions. While I hate to reveal just how long I have been working in this field, let's just say that pads of paper and a stopwatch were key tools for any test I conducted. Over the years, I have worked in simple labs with basic video taping equipment and not much else, and I have worked in corporate environments with sophisticated usability labs and state-of-the-art equipment. Years ago, we conducted all usability studies at the location of the user. If we wanted to see if there were any differences between users in New York, Chicago, and Los Angeles, we went to those places to run the test. A lab environment is very useful for many test situations. However, there has always been a debate in the usability field about whether bringing someone into a lab environment, however friendly we make it, somehow intrinsically changes the behavior of the user as compared to having them work in their own environment, at their own desk, and on their own computer. We developed systems to create a portable usability lab, so that we could go to the users that we needed to test.  Do lab environments change user behavior patterns? Then 9/11 hit. You may not remember, but no planes flew for weeks afterwards. Companies all over the world couldn't fly-in employees for meetings. Suddenly, traveling to the location of the users had an additional difficulty. The company I was working for at the time had usability specialists stuck in New York for days before they could finally rent a car and drive home to Colorado. This changed the world pretty suddenly, and technology jumped on the change. Companies offering Internet meeting tools were strugglinguntil no one could travel. The Internet boomed with collaboration tools that enabled people to work together wherever they happened to be. This change in technology has made a huge difference in my world. We use collaborative tools to bring our product concepts and ideas to the user across the Internet. As a global company, we benefit from having users from all over the world inform our designs. We now run usability studies with users all over the world in a single day, a feat we couldn't have accomplished 10 years ago by plane! Other technology companies have started to do more of this type of usability testing, since the tools have improved so dramatically. Plus, in our busy world, it's not always easy to find users who can take the time away from their jobs to come to our labs. reaching users where it is convenient for them greatly improves the odds that people do participate. I manage a team of usability specialists who live in India and California, whlie I live in Colorado. We have wonderful labs that we bring users into to show them our products. But very often, we run our studies remotely. We used to take the lab to the users now we use the labs, but we let the users stay where they are. We gain users who might not have been able to leave work to come to our labs, and they get to use the system they are familiar with. And we gain users nearly anywhere that we can set up an Internet connection, as long as the users have a phone, a broadband connection, and a compatible Web browser (with no pop-up blockers). After we recruit participants in a traditional manner, we send them an invitation to participate through the use of a telephone conference call and Web conferencing tool. At Oracle, we use Oracle Web Conference part of Oracle Collaboration Suite, which enables us to give the user control of the mouse, while we present a prototype or wireframe pictures. We can record the sessions over the Web and phone conference. We send the users instructions, plus tips to ensure that we won't have problems sharing screens. In some cases, when time is tight, we even run a five-minute "test session" with users a day in advance to be sure that we can connect. Prior to the test, we send users a participant script that contains information about the study, including any questionnaires. This is exactly the same script we give to participants who come to the labs. We ask users to print this before the beginning of the session. We generally run these studies by having a usability engineer in our usability labs, so that we can record the session as though the user were in the lab with us. Roughly 80% of our application software usability testing at Oracle is performed using remote methods. The probability of getting a   remote test participant decreases the higher up the person is in the target organization. We have a methodology checklist available to help our usability engineers work through the remote processes.

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  • Ubutu 14.04 triple screen, third screen black and X cursor

    - by Horse
    I am having some issues getting my third screen working properly. I had triple screens working fine on 12.04, using 2 nvidia cards. Did a fresh install of 14.04 and having no end of problems getting it working. It either will just be disabled, or the screen is black with the cursor as an X. I can only enable it from the nvidia server settings tool. The Ubuntu native display settings won't even show the 3rd screen. I tried copying the xorg.conf from my old install, which upon restarting X worked fine on the login screen, but then it just sat there after I logged in and didn’t do anything (mouse was still working). I am using gnome-session-fallback instead of unity if that makes any difference. Still having these issues if I try unity though. How do I get my 3rd screen working and displaying a desktop? Here is my current xorg.conf # nvidia-settings: X configuration file generated by nvidia-settings # nvidia-settings: version 331.20 (buildd@roseapple) Mon Feb 3 15:07:22 UTC 2014 Section "ServerLayout" Identifier "Layout0" Screen 0 "Screen0" 0 0 Screen 1 "Screen1" RightOf "Screen0" InputDevice "Keyboard0" "CoreKeyboard" InputDevice "Mouse0" "CorePointer" Option "Xinerama" "0" EndSection Section "Files" EndSection Section "InputDevice" # generated from default Identifier "Mouse0" Driver "mouse" Option "Protocol" "auto" Option "Device" "/dev/psaux" Option "Emulate3Buttons" "no" Option "ZAxisMapping" "4 5" EndSection Section "InputDevice" # generated from default Identifier "Keyboard0" Driver "kbd" EndSection Section "Monitor" # HorizSync source: edid, VertRefresh source: edid Identifier "Monitor0" VendorName "Unknown" ModelName "DELL 1907FP" HorizSync 30.0 - 81.0 VertRefresh 56.0 - 76.0 Option "DPMS" EndSection Section "Monitor" # HorizSync source: unknown, VertRefresh source: unknown Identifier "Monitor1" VendorName "Unknown" ModelName "DELL 1907FP" HorizSync 0.0 - 0.0 VertRefresh 0.0 Option "DPMS" EndSection Section "Monitor" Identifier "Monitor2" VendorName "Unknown" ModelName "DELL 1907FP" HorizSync 30.0 - 81.0 VertRefresh 56.0 - 76.0 EndSection Section "Device" Identifier "Device0" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GTX 580" BusID "PCI:1:0:0" EndSection Section "Device" Identifier "Device1" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GT 520" BusID "PCI:3:0:0" EndSection Section "Device" Identifier "Device2" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GT 520" BusID "PCI:3:0:0" EndSection Section "Screen" # Removed Option "metamodes" "DVI-I-2: nvidia-auto-select +0+0, DVI-I-3: nvidia-auto-select +1280+0" # Removed Option "metamodes" "DVI-I-2: nvidia-auto-select +0+0" # Removed Option "SLI" "Off" # Removed Option "BaseMosaic" "off" # Removed Option "metamodes" "GPU-109d4eb8-b40b-87d7-3fd6-95830d1d5215.DVI-I-2: nvidia-auto-select +0+0, GPU-109d4eb8-b40b-87d7-3fd6-95830d1d5215.DVI-I-3: nvidia-auto-select +1280+0, GPU-82e96214-175e-5e6a-218c-5bdbc948daf2.DVI-I-1: nvidia-auto-select +3200+0" # Removed Option "SLI" "off" # Removed Option "BaseMosaic" "on" Identifier "Screen0" Device "Device0" Monitor "Monitor0" DefaultDepth 24 Option "Stereo" "0" Option "nvidiaXineramaInfoOrder" "DFP-0" Option "metamodes" "DVI-I-2: nvidia-auto-select +0+0, DVI-I-3: nvidia-auto-select +1280+0" Option "SLI" "Off" Option "MultiGPU" "Off" Option "BaseMosaic" "off" SubSection "Display" Depth 24 EndSubSection EndSection Section "Screen" # Removed Option "metamodes" "nvidia-auto-select +0+0" # Removed Option "metamodes" "DVI-I-3: nvidia-auto-select +0+0" Identifier "Screen1" Device "Device1" Monitor "Monitor1" DefaultDepth 24 Option "Stereo" "0" Option "metamodes" "nvidia-auto-select +0+0" Option "SLI" "Off" Option "MultiGPU" "Off" Option "BaseMosaic" "off" SubSection "Display" Depth 24 EndSubSection EndSection Section "Screen" Identifier "Screen2" Device "Device2" Monitor "Monitor2" DefaultDepth 24 Option "Stereo" "0" Option "metamodes" "nvidia-auto-select +0+0" Option "SLI" "Off" Option "MultiGPU" "Off" Option "BaseMosaic" "off" SubSection "Display" Depth 24 EndSubSection EndSection Here is my old 'working in 12.04' xorg.conf # nvidia-settings: X configuration file generated by nvidia-settings # nvidia-settings: version 310.19 ([email protected]) Thu Nov 8 02:08:55 PST 2012 Section "ServerLayout" # Removed Option "Xinerama" "0" Identifier "Layout0" Screen 0 "Screen0" 0 0 Screen 1 "Screen1" RightOf "Screen2" Screen 2 "Screen2" RightOf "Screen0" InputDevice "Keyboard0" "CoreKeyboard" InputDevice "Mouse0" "CorePointer" Option "Xinerama" "1" EndSection Section "Files" EndSection Section "InputDevice" # generated from default Identifier "Mouse0" Driver "mouse" Option "Protocol" "auto" Option "Device" "/dev/psaux" Option "Emulate3Buttons" "no" Option "ZAxisMapping" "4 5" EndSection Section "InputDevice" # generated from default Identifier "Keyboard0" Driver "kbd" EndSection Section "Monitor" # HorizSync source: edid, VertRefresh source: edid Identifier "Monitor0" VendorName "Unknown" ModelName "DELL 1907FP" HorizSync 30.0 - 81.0 VertRefresh 56.0 - 76.0 Option "DPMS" EndSection Section "Monitor" # HorizSync source: unknown, VertRefresh source: unknown Identifier "Monitor1" VendorName "Unknown" ModelName "DELL 1907FP" HorizSync 30.0 - 81.0 VertRefresh 56.0 - 76.0 Option "DPMS" EndSection Section "Monitor" Identifier "Monitor2" VendorName "Unknown" ModelName "Apple Cinema HD" HorizSync 74.0 - 74.6 VertRefresh 59.9 - 60.0 EndSection Section "Device" Identifier "Device0" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GTX 580" BusID "PCI:1:0:0" Screen 0 EndSection Section "Device" Identifier "Device1" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GT 520" BusID "PCI:3:0:0" EndSection Section "Device" Identifier "Device2" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GTX 580" BusID "PCI:1:0:0" Screen 1 EndSection Section "Screen" # Removed Option "metamodes" "DFP-0: nvidia-auto-select +0+0, DFP-2: nvidia-auto-select +1280+0" Identifier "Screen0" Device "Device0" Monitor "Monitor0" DefaultDepth 24 Option "Stereo" "0" Option "metamodes" "DFP-0: nvidia-auto-select +0+0; DFP-0: nvidia-auto-select +0+0; DFP-0: 1280x1024_75 +0+0; DFP-0: 1152x864 +0+0; DFP-0: 1024x768 +0+0; DFP-0: 1024x768_60 +0+0; DFP-0: 800x600 +0+0; DFP-0: 800x600_60 +0+0; DFP-0: 640x480 +0+0; DFP-0: 640x480_60 +0+0; DFP-0: nvidia-auto-select +0+0 {viewportout=1280x720+0+152}" SubSection "Display" Depth 24 EndSubSection EndSection Section "Screen" Identifier "Screen1" Device "Device1" Monitor "Monitor1" DefaultDepth 24 Option "Stereo" "0" Option "metamodes" "nvidia-auto-select +0+0" SubSection "Display" Depth 24 EndSubSection EndSection Section "Screen" Identifier "Screen2" Device "Device2" Monitor "Monitor2" DefaultDepth 24 Option "Stereo" "0" Option "metamodes" "DFP-2: nvidia-auto-select +0+0" SubSection "Display" Depth 24 EndSubSection EndSection Section "Extensions" Option "Composite" "Disable" EndSection

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  • Functional Adaptation

    - by Charles Courchaine
    In real life and OO programming we’re often faced with using adapters, DVI to VGA, 1/4” to 1/8” audio connections, 110V to 220V, wrapping an incompatible interface with a new one, and so on.  Where the adapter pattern is generally considered for interfaces and classes a similar technique can be applied to method signatures.  To be fair, this adaptation is generally used to reduce the number of parameters but I’m sure there are other clever possibilities to be had.  As Jan questioned in the last post, how can we use a common method to execute an action if the action has a differing number of parameters, going back to the greeting example it was suggested having an AddName method that takes a first and last name as parameters.  This is exactly what we’ll address in this post. Let’s set the stage with some review and some code changes.  First, our method that handles the setup/tear-down infrastructure for our WCF service: 1: private static TResult ExecuteGreetingFunc<TResult>(Func<IGreeting, TResult> theGreetingFunc) 2: { 3: IGreeting aGreetingService = null; 4: try 5: { 6: aGreetingService = GetGreetingChannel(); 7: return theGreetingFunc(aGreetingService); 8: } 9: finally 10: { 11: CloseWCFChannel((IChannel)aGreetingService); 12: } 13: } Our original AddName method: 1: private static string AddName(string theName) 2: { 3: return ExecuteGreetingFunc<string>(theGreetingService => theGreetingService.AddName(theName)); 4: } Our new AddName method: 1: private static int AddName(string firstName, string lastName) 2: { 3: return ExecuteGreetingFunc<int>(theGreetingService => theGreetingService.AddName(firstName, lastName)); 4: } Let’s change the AddName method, just a little bit more for this example and have it take the greeting service as a parameter. 1: private static int AddName(IGreeting greetingService, string firstName, string lastName) 2: { 3: return greetingService.AddName(firstName, lastName); 4: } The new signature of AddName using the Func delegate is now Func<IGreeting, string, string, int>, which can’t be used with ExecuteGreetingFunc as is because it expects Func<IGreeting, TResult>.  Somehow we have to eliminate the two string parameters before we can use this with our existing method.  This is where we need to adapt AddName to match what ExecuteGreetingFunc expects, and we’ll do so in the following progression. 1: Func<IGreeting, string, string, int> -> Func<IGreeting, string, int> 2: Func<IGreeting, string, int> -> Func<IGreeting, int>   For the first step, we’ll create a method using the lambda syntax that will “eliminate” the last name parameter: 1: string lastNameToAdd = "Smith"; 2: //Func<IGreeting, string, string, int> -> Func<IGreeting, string, int> 3: Func<IGreeting, string, int> addName = (greetingService, firstName) => AddName(greetingService, firstName, lastNameToAdd); The new addName method gets us one step close to the signature we need.  Let’s say we’re going to call this in a loop to add several names, we’ll take the final step from Func<IGreeting, string, int> -> Func<IGreeting, int> in line as a lambda passed to ExecuteGreetingFunc like so: 1: List<string> firstNames = new List<string>() { "Bob", "John" }; 2: int aID; 3: foreach (string firstName in firstNames) 4: { 5: //Func<IGreeting, string, int> -> Func<IGreeting, int> 6: aID = ExecuteGreetingFunc<int>(greetingService => addName(greetingService, firstName)); 7: Console.WriteLine(GetGreeting(aID)); 8: } If for some reason you needed to break out the lambda on line 6 you could replace it with 1: aID = ExecuteGreetingFunc<int>(ApplyAddName(addName, firstName)); and use this method: 1: private static Func<IGreeting, int> ApplyAddName(Func<IGreeting, string, int> addName, string lastName) 2: { 3: return greetingService => addName(greetingService, lastName); 4: } Splitting out a lambda into its own method is useful both in this style of coding as well as LINQ queries to improve the debugging experience.  It is not strictly necessary to break apart the steps & functions as was shown above; the lambda in line 6 (of the foreach example) could include both the last name and first name instead of being composed of two functions.  The process demonstrated above is one of partially applying functions, this could have also been done with Currying (also see Dustin Campbell’s excellent post on Currying for the canonical curried add example).  Matthew Podwysocki also has some good posts explaining both Currying and partial application and a follow up post that further clarifies the difference between Currying and partial application.  In either technique the ultimate goal is to reduce the number of parameters passed to a function.  Currying makes it a single parameter passed at each step, where partial application allows one to use multiple parameters at a time as we’ve done here.  This technique isn’t for everyone or every problem, but can be extremely handy when you need to adapt a call to something you don’t control.

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