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  • Procedural, Semi-Procedural and Declarative Programming in SQL

    A lot of the time, the key to making SQL databases perform well is to take a break from the keyboard and rethink the way of approaching the problem; and rethinking in terms of a set-based declarative approach. Joe takes a simple discussion abut a problem with a UDF to illustrate the point that ingrained procedural reflexes can often prevent us from seeing simpler set-based techniques.

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  • Development: SDK for Social Net

    - by loldop
    I have a task: development sdk for social networking service like facebook, twitter and etc. At now i'm developing facebook-extension-sdk which based on facebook-ios-sdk 3.0. But not all social networking services have good sdks. And all time i improved my facebook-extension-sdk, when i see ugly code :( Please, advise me good techniques to development these sdks (like design-patterns or your own experience or good books/sites). Thanks!

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  • Brendan Gregg's "Systems Performance: Enterprise and the Cloud"

    - by user12608550
    Long ago, the prerequisite UNIX performance book was Adrian Cockcroft's 1994 classic, Sun Performance and Tuning: Sparc & Solaris, later updated in 1998 as Java and the Internet. As Solaris evolved to include the invaluable DTrace observability features, new essential performance references have been published, such as Solaris Performance and Tools: DTrace and MDB Techniques for Solaris 10 and OpenSolaris (2006)  by McDougal, Mauro, and Gregg, and DTrace: Dynamic Tracing in Oracle Solaris, Mac OS X and FreeBSD (2011), also by Mauro and Gregg. Much has occurred in Solaris Land since those books appeared, notably Oracle's acquisition of Sun Microsystems in 2010 and the demise of the OpenSolaris community. But operating system technologies have continued to improve markedly in recent years, driven by stunning advances in multicore processor architecture, virtualization, and the massive scalability requirements of cloud computing. A new performance reference was needed, and I eagerly waited for something that thoroughly covered modern, distributed computing performance issues from the ground up. Well, there's a new classic now, authored yet again by Brendan Gregg, former Solaris kernel engineer at Sun and now Lead Performance Engineer at Joyent. Systems Performance: Enterprise and the Cloud is a modern, very comprehensive guide to general system performance principles and practices, as well as a highly detailed reference for specific UNIX and Linux observability tools used to examine and diagnose operating system behaviour.  It provides thorough definitions of terms, explains performance diagnostic Best Practices and "Worst Practices" (called "anti-methods"), and covers key observability tools including DTrace, SystemTap, and all the traditional UNIX utilities like vmstat, ps, iostat, and many others. The book focuses on operating system performance principles and expands on these with respect to Linux (Ubuntu, Fedora, and CentOS are cited), and to Solaris and its derivatives [1]; it is not directed at any one OS so it is extremely useful as a broad performance reference. The author goes beyond the intricacies of performance analysis and shows how to interpret and visualize statistical information gathered from the observability tools.  It's often difficult to extract understanding from voluminous rows of text output, and techniques are provided to assist with summarizing, visualizing, and interpreting the performance data. Gregg includes myriad useful references from the system performance literature, including a "Who's Who" of contributors to this great body of diagnostic tools and methods. This outstanding book should be required reading for UNIX and Linux system administrators as well as anyone charged with diagnosing OS performance issues.  Moreover, the book can easily serve as a textbook for a graduate level course in operating systems [2]. [1] Solaris 11, of course, and Joyent's SmartOS (developed from OpenSolaris) [2] Gregg has taught system performance seminars for many years; I have also taught such courses...this book would be perfect for the OS component of an advanced CS curriculum.

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  • What to do if I am working on a language that I don't like

    - by Sayem Ahmed
    Hi there, I really don't know if this is the right place to ask this question, but if it isn't, then I guess someone will notify. Anyway, I am working in a software development farm which is currently using PowerBuilder to develop a mid-size ERP solution. The work environment and company management are so great that it may be the best in the whole Bangladesh. Only problem is the technology that are currently being used, which is this PowerBuilder. Now I am a guy who tends to prefer modern development technologies, like DI containers, ORM, TDD, JQuery etc. PowerBuilder is a great tool too, but I couldn' like the application techniques used to build PB applications. These techniques are so inheritance-dependent that many a times these create a great deal of sufferings. I remember two days ago I had to change some processing logic in a core user object and as a result I had to test and re-test all the forms that the application have(apparently, there are almost 20 forms there, each of them with 3-4 kinds of functionalities). Also, learning PB is tough, because online material on this thing is very, very low. I can't afford to read all the documentation that PB provide because I have hard deadlines on the work that I have to do. Another thing with PB is that applications tend to rely on business logic that are implemented on databases which causes debugging to be a nightmare. As a result, I don't feel motivated enough to work in this IDE/System/Framework (or whatever) anymore. My productivity has greatly decreased, and I am not delivering quality code. I think I have the following options available to me - Remain in the current job, keep delivering worse code and let my productivity decrease day by day, taking salaries and bonuses but not delivering quality codes/doing my job the way I should, Search for a new job. At this point number 2 seems a good option, but there are also some issues. As I mentioned before, our management may be the best in the country. Our company owner is himself a software developer with 24 years of experience in software development. He is currently our Team Leader and System Analyst. He is by far the greatest manager and boss I have ever seen. He understands developer's mentality very well(as he IS himself a developer). He is also a great, kind and generous guy. Our company is only a start-up company with 10 developers. Among them, only 3-4 people knows about the business logic behind the ERP, and I am one of them. If I switch my current job, it may hamper the development of this product which I really don't want. I couldn't decide what to do in this situation, so I turned to the community for advice.

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  • Fraud Detection with the SQL Server Suite Part 2

    - by Dejan Sarka
    This is the second part of the fraud detection whitepaper. You can find the first part in my previous blog post about this topic. My Approach to Data Mining Projects It is impossible to evaluate the time and money needed for a complete fraud detection infrastructure in advance. Personally, I do not know the customer’s data in advance. I don’t know whether there is already an existing infrastructure, like a data warehouse, in place, or whether we would need to build one from scratch. Therefore, I always suggest to start with a proof-of-concept (POC) project. A POC takes something between 5 and 10 working days, and involves personnel from the customer’s site – either employees or outsourced consultants. The team should include a subject matter expert (SME) and at least one information technology (IT) expert. The SME must be familiar with both the domain in question as well as the meaning of data at hand, while the IT expert should be familiar with the structure of data, how to access it, and have some programming (preferably Transact-SQL) knowledge. With more than one IT expert the most time consuming work, namely data preparation and overview, can be completed sooner. I assume that the relevant data is already extracted and available at the very beginning of the POC project. If a customer wants to have their people involved in the project directly and requests the transfer of knowledge, the project begins with training. I strongly advise this approach as it offers the establishment of a common background for all people involved, the understanding of how the algorithms work and the understanding of how the results should be interpreted, a way of becoming familiar with the SQL Server suite, and more. Once the data has been extracted, the customer’s SME (i.e. the analyst), and the IT expert assigned to the project will learn how to prepare the data in an efficient manner. Together with me, knowledge and expertise allow us to focus immediately on the most interesting attributes and identify any additional, calculated, ones soon after. By employing our programming knowledge, we can, for example, prepare tens of derived variables, detect outliers, identify the relationships between pairs of input variables, and more, in only two or three days, depending on the quantity and the quality of input data. I favor the customer’s decision of assigning additional personnel to the project. For example, I actually prefer to work with two teams simultaneously. I demonstrate and explain the subject matter by applying techniques directly on the data managed by each team, and then both teams continue to work on the data overview and data preparation under our supervision. I explain to the teams what kind of results we expect, the reasons why they are needed, and how to achieve them. Afterwards we review and explain the results, and continue with new instructions, until we resolve all known problems. Simultaneously with the data preparation the data overview is performed. The logic behind this task is the same – again I show to the teams involved the expected results, how to achieve them and what they mean. This is also done in multiple cycles as is the case with data preparation, because, quite frankly, both tasks are completely interleaved. A specific objective of the data overview is of principal importance – it is represented by a simple star schema and a simple OLAP cube that will first of all simplify data discovery and interpretation of the results, and will also prove useful in the following tasks. The presence of the customer’s SME is the key to resolving possible issues with the actual meaning of the data. We can always replace the IT part of the team with another database developer; however, we cannot conduct this kind of a project without the customer’s SME. After the data preparation and when the data overview is available, we begin the scientific part of the project. I assist the team in developing a variety of models, and in interpreting the results. The results are presented graphically, in an intuitive way. While it is possible to interpret the results on the fly, a much more appropriate alternative is possible if the initial training was also performed, because it allows the customer’s personnel to interpret the results by themselves, with only some guidance from me. The models are evaluated immediately by using several different techniques. One of the techniques includes evaluation over time, where we use an OLAP cube. After evaluating the models, we select the most appropriate model to be deployed for a production test; this allows the team to understand the deployment process. There are many possibilities of deploying data mining models into production; at the POC stage, we select the one that can be completed quickly. Typically, this means that we add the mining model as an additional dimension to an existing DW or OLAP cube, or to the OLAP cube developed during the data overview phase. Finally, we spend some time presenting the results of the POC project to the stakeholders and managers. Even from a POC, the customer will receive lots of benefits, all at the sole risk of spending money and time for a single 5 to 10 day project: The customer learns the basic patterns of frauds and fraud detection The customer learns how to do the entire cycle with their own people, only relying on me for the most complex problems The customer’s analysts learn how to perform much more in-depth analyses than they ever thought possible The customer’s IT experts learn how to perform data extraction and preparation much more efficiently than they did before All of the attendees of this training learn how to use their own creativity to implement further improvements of the process and procedures, even after the solution has been deployed to production The POC output for a smaller company or for a subsidiary of a larger company can actually be considered a finished, production-ready solution It is possible to utilize the results of the POC project at subsidiary level, as a finished POC project for the entire enterprise Typically, the project results in several important “side effects” Improved data quality Improved employee job satisfaction, as they are able to proactively contribute to the central knowledge about fraud patterns in the organization Because eventually more minds get to be involved in the enterprise, the company should expect more and better fraud detection patterns After the POC project is completed as described above, the actual project would not need months of engagement from my side. This is possible due to our preference to transfer the knowledge onto the customer’s employees: typically, the customer will use the results of the POC project for some time, and only engage me again to complete the project, or to ask for additional expertise if the complexity of the problem increases significantly. I usually expect to perform the following tasks: Establish the final infrastructure to measure the efficiency of the deployed models Deploy the models in additional scenarios Through reports By including Data Mining Extensions (DMX) queries in OLTP applications to support real-time early warnings Include data mining models as dimensions in OLAP cubes, if this was not done already during the POC project Create smart ETL applications that divert suspicious data for immediate or later inspection I would also offer to investigate how the outcome could be transferred automatically to the central system; for instance, if the POC project was performed in a subsidiary whereas a central system is available as well Of course, for the actual project, I would repeat the data and model preparation as needed It is virtually impossible to tell in advance how much time the deployment would take, before we decide together with customer what exactly the deployment process should cover. Without considering the deployment part, and with the POC project conducted as suggested above (including the transfer of knowledge), the actual project should still only take additional 5 to 10 days. The approximate timeline for the POC project is, as follows: 1-2 days of training 2-3 days for data preparation and data overview 2 days for creating and evaluating the models 1 day for initial preparation of the continuous learning infrastructure 1 day for presentation of the results and discussion of further actions Quite frequently I receive the following question: are we going to find the best possible model during the POC project, or during the actual project? My answer is always quite simple: I do not know. Maybe, if we would spend just one hour more for data preparation, or create just one more model, we could get better patterns and predictions. However, we simply must stop somewhere, and the best possible way to do this, according to my experience, is to restrict the time spent on the project in advance, after an agreement with the customer. You must also never forget that, because we build the complete learning infrastructure and transfer the knowledge, the customer will be capable of doing further investigations independently and improve the models and predictions over time without the need for a constant engagement with me.

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  • SQL Server CTE Basics

    The CTE was introduced into standard SQL in order to simplify various classes of SQL Queries for which a derived table just wasn't suitable. For some reason, it can be difficult to grasp the techniques of using it. Well, that's before Rob Sheldon explained it all so clearly for us.

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  • The best Drupal and JavaScript developer?

    - by hakanito
    I've read a lot of JS articles and books by Nicholas Zakas and Addy Osmani, in my opinion evangelists in the field. But I am also a Drupal developer, and these guys are not. Many of the techniques they're talking about such as AMD and RequireJS are great, but it's hard to know how to integrate them when it comes to Drupal (and do it right, ofc). So my question is if there are any recognized developer/s out there with strong JavaScript AND Drupal experience?

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  • What is the way to understand someone else's giant uncommented spaghetti code? [closed]

    - by Anisha Kaul
    Possible Duplicate: I’ve inherited 200K lines of spaghetti code — what now? I have been recently handled a giant multithreaded program with no comments and have been asked to understand what it does, and then to improve it (if possible). Are there some techniques which should be followed when we need to understand someone else's code? OR do we straightaway start from the first function call and go on tracking next function calls? C++ (with multi-threading) on Linux

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  • Developing Essbase Applications de Cameron Lackpour, critique par Sébastien Roux

    Bonjour La rédaction de DVP a lu pour vous l'ouvrage suivant: Developing Essbase Applications - Advanced Techniques for Finance and IT Professionals de Dave Anderson, Joe Aultman, John Booth, Gary Crisci, Natalie Delemar, Dave Farnsworth, Michael Nader, Dan Pressman, Rob Salzmann, Tim Tow, Jake Turrell et Angela Wilcox, sous la direction de Cameron Lackpour paru aux Editions Auerbach Publications [IMG]http://images-eu.amazon.com/images/P/1466553308.01.LZZZZZZZ.jpg[/IMG] L'avez-vous lu ? Comptez-vous le lire bientô...

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  • Procedural, Semi-Procedural and Declarative Programming in SQL

    A lot of the time, the key to making SQL databases perform well is to take a break from the keyboard and rethink the way of approaching the problem; and rethinking in terms of a set-based declarative approach. Joe takes a simple discussion abut a problem with a UDF to illustrate the point that ingrained procedural reflexes can often prevent us from seeing simpler set-based techniques.

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  • A Community Cure for a String Splitting Headache

    - by Tony Davis
    A heartwarming tale of dogged perseverance and Community collaboration to solve some SQL Server string-related headaches. Michael J Swart posted a blog this week that had me smiling in recognition and agreement, describing how an inquisitive Developer or DBA deals with a problem. It's a three-step process, starting with discomfort and anxiety; a feeling that one doesn't know as much about one's chosen specialized subject as previously thought. It progresses through a phase of intense research and learning until finally one achieves breakthrough, blessed relief and renewed optimism. In this case, the discomfort was provoked by the mystery of massively high CPU when searching Unicode strings in SQL Server. Michael explored the problem via Stack Overflow, Google and Twitter #sqlhelp, finally leading to resolution and a blog post that shared what he learned. Perfect; except that sometimes you have to be prepared to share what you've learned so far, while still mired in the phase of nagging discomfort. A good recent example of this recently can be found on our own blogs. Despite being a loud advocate of the lightning fast T-SQL-based string splitting techniques, honed to near perfection over many years by Jeff Moden and others, Phil Factor retained a dogged conviction that, in theory, shredding element-based XML using XQuery ought to be even more efficient for splitting a string to create a table. After some careful testing, he found instead that the XML way performed and scaled miserably by comparison. Somewhat subdued, and with a nagging feeling that perhaps he was still missing "something", he posted his findings. What happened next was a joy to behold; the community jumped in to suggest subtle changes in approach, using an attribute-based rather than element-based XML list, and tweaking the XQuery shredding. The result was performance and scalability that surpassed all other techniques. I asked Phil how quickly he would have arrived at the real breakthrough on his own. His candid answer was "never". Both are great examples of the power of Community learning and the latter in particular the importance of being brave enough to parade one's ignorance. Perhaps Jeff Moden will accept the string-splitting gauntlet one more time. To quote the great man: you've just got to love this community! If you've an interesting tale to tell about being helped to a significant breakthrough for a problem by the community, I'd love to hear about it. Cheers, Tony.

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  • StateManagement Suggestions : A Beginners View

    This article takes you on short trip of State Management techniques used in ASP.NET...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Extend Oracle Sales Cloud with Oracle Platform as a Service

    - by Richard Lefebvre
    Use these Oracle guided-learning courses to learn how to extend Oracle Sales Cloud with Oracle Platform as a Service (PaaS) services. While this course is focused on using Oracle PaaS infrastructure services, many of the techniques presented are applicable to customers on Software as a Service (SaaS) environments. If you are a consultant embarking on an Oracle Fusion Applications SaaS implementation project or an Independent Solution Vendors (ISVs) looking to integrate a solution with Oracle Sales Cloud, this training is for you!

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  • London User Group Meetings this week (19th/20th May); 26th May-Agile Data Warehousing; 17th June-Kim

    - by tonyrogerson
    Got two user group meetings in London for you, we've also started the Cuppa Corner sessions - the first 3 are up on the site - A trip to First Normal Form, Lookup and Cache Transform in SSIS and Pipeline Limiter in SSIS - we are aiming for at least one per week. WhereScape are doing a breakfast meeting on Agile techniques to Data Warehousing and Kimberly Tripp and Paul Randal are over in June for a 1 day master class. Finally a 3 day performance and monitoring workshop on 22- 24th June in London...(read more)

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  • The Art of SEO Writing

    Website owners around the world have one thing they all want when it come to their respective websites: web traffic. And how do these website owners improve this? By using SEO techniques. And to do well in SEO, one must understand how to do quality SEO writing.

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  • Oracle University Nuovi corsi (Week 14)

    - by swalker
    Oracle University ha recentemente rilasciato i seguenti nuovi corsi in inglese: Database Oracle Data Modeling and Relational Database Design (4 days) Fusion Middleware Oracle Directory Services 11g: Administration (5 days) Oracle Unified Directory 11g: Services Deployment Essentials (2 days) Oracle GoldenGate 11g Management Pack: Overview (1 day) Business Intelligence & Datawarehousing Oracle Database 11g: Data Mining Techniques (2 days) Oracle Solaris Oracle Solaris 10 System Administration for HP-UX Administrators (5 days) E-Business Suite R12.x Oracle Time and Labor Fundamentals Per ulteriori informazioni e per conoscere le date dei corsi, contattate il vostro Oracle University team locale. Rimanete in contatto con Oracle University: LinkedIn OracleMix Twitter Facebook Google+

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  • Oiling the gears for the data dictionary

    Documenting the database is always a challenge, and there are many techniques you can use to help all the people on your team understand what all your tables are used for. David Poole brings us an easy way to implement a framework for documentation. The Future of SQL Server Monitoring "Being web-based, SQL Monitor 2.0 enables you to check on your servers from almost any location" Jonathan Allen.Try SQL Monitor now.

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  • How do you avoid being a "blowhard"?

    - by Conrad Frix
    When I'm passionate about something (particularly programming) I find it really easy come off like the guy Peter G. was talking about in Dealing with the “programming blowhard”. So what techniques do you use to 1) Identify when you are indeed a blowhard? 2) Communicate something "important" without seeming self important? Specific example help like When giving criticism ask "have you considered what happens when XXX changes" instead of "never take dependencies on implementation details" When giving advice "showing with code is better than talking" or use a reference.

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  • Selectively Exposing Functionallity in .Net

    - by David V. Corbin
    Any developer should be aware of the principles of encapsulation, cross-tier isolation, and cross-functional separation of concerns. However, it seems the few take the time to consider the adage of "minimal yet complete"1 when developing the software. Consider the exposure of "business objects" to the user interface. Some common situations occur: Accessing a given element requires a compound set of calls that do not "make sense" to the User Interface. More information than absolutely required is exposed to the user interface It would be much cleaner if a custom interface was provided that exposed exactly (and only) the information that is required by the consumer. Achieving this using conventional techniques would require the creation (and maintenance!) of custom classes to filter and transpose the information into the ideal format. Determining the ROI on this approach can be very difficult to ascertain, and as a result it is often ignored completely. There is another approach, which is largely made practical by virtual of the Action and Func delegates. From a callers point of view, the following two samples can be used interchangeably:     interface ISomeInterface     {         void SampleMethod1(string param);         string SamepleMethod2(string param);     }       class ISomeInterface     {         public Action<string> SampleMethod1 {get; }         public Func<string,string> SamepleMethod2 {get; }     }   The capabilities this simple changes enable are significant (and remember it does not cange the syntax at the call site): The delegates can be initialized to directly call the proper method of any target class. The delegates can be dynamically updated based on the current state. The "interface" can NOT be cast to the concrete class (which often exposes more functionallity). This patterns By limiting the interface to the exact functionallity required, the reduced surface area will typically result in lower development, testing and maintenance costs. We are currently in the process of posting a project on CodePlex which illustrates this (and many other) techniques which have proven helpful in creating robust yet flexible solutions that are highly efficient2 and maintainable. This post will be updated as soon as the project is published. 1) Credit: Scott  Meyers, Effective C++, Addison-Wesley 1992 2) For those who read my previous post on performance it should be noted that the use of delegates is on the same order of magnitude (actually a tiny amount faster) as conventional interfaces.

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