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  • jQuery validator and a custom rule that uses AJAX

    - by thatweblook
    Hi, I read your reply regarding the jQuery validator where you outline a method to check a username against a value in a database. Ive tried implementing this method but no matter what is returned from the PHP file I always get the message that the username is already taken. Here is ths custom method... $.validator.addMethod("uniqueUserName", function(value, element) { $.ajax({ type: "POST", url: "php/get_save_status.php", data: "checkUsername="+value, dataType:"html", success: function(msg) { // if the user exists, it returns a string "true" if(msg == "true") return false; // already exists return true; // username is free to use } })}, "Username is Already Taken"); And here is the validate code... username: { required: true, uniqueUserName: true }, Is there a specific way i am supposed to return the message from php. Thanks A

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  • A new tool in beta: Conflict Alert

    - by Alex Davies
    You know that manual merges are a real pain? Well, I’ve just released a Visual Studio extension that makes manual merges a thing of the past. No source control system can automatically merge two edits to the same line of code. Conflict Alert solves this by warning you that you are heading down a path that will cause a manual merge later down the line. You choose whether you want to carry on, or talk to your teammate and find out what they are doing. Have you ever warned your teammates that you are doing a big refactor, and that they should ‘keep out of class X’? Conflict Alert tells them for you automatically by highlighting the sections of code that you have edited.   It doesn’t need to connect to your source control system, so it works no matter which you use. Its a first release, and I hope it is useful. Any feedback would be gratefully received. Grab a teammate and try it now.

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  • Metrics - A little knowledge can be a dangerous thing (or 'Why you're not clever enough to interpret metrics data')

    - by Jason Crease
    At RedGate Software, I work on a .NET obfuscator  called SmartAssembly.  Various features of it use a database to store various things (exception reports, name-mappings, etc.) The user is given the option of using either a SQL-Server database (which requires them to have Microsoft SQL Server), or a Microsoft Access MDB file (which requires nothing). MDB is the default option, but power-users soon switch to using a SQL Server database because it offers better performance and data-sharing. In the fashionable spirit of optimization and metrics, an obvious product-management question is 'Which is the most popular? SQL Server or MDB?' We've collected data about this fact, using our 'Feature-Usage-Reporting' technology (available as part of SmartAssembly) and more recently our 'Application Metrics' technology: Parameter Number of users % of total users Number of sessions Number of usages SQL Server 28 19.0 8115 8115 MDB 114 77.6 1449 1449 (As a disclaimer, please note than SmartAssembly has far more than 132 users . This data is just a selection of one build) So, it would appear that SQL-Server is used by fewer users, but more often. Great. But here's why these numbers are useless to me: Only the original developers understand the data What does a single 'usage' of 'MDB' mean? Does this happen once per run? Once per option change? On clicking the 'Obfuscate Now' button? When running the command-line version or just from the UI version? Each question could skew the data 10-fold either way, and the answers only known by the developer that instrumented the application in the first place. In other words, only the original developer can interpret the data - product-managers cannot interpret the data unaided. Most of the data is from uninterested users About half of people who download and run a free-trial from the internet quit it almost immediately. Only a small fraction use it sufficiently to make informed choices. Since the MDB option is the default one, we don't know how many of those 114 were people CHOOSING to use the MDB, or how many were JUST HAPPENING to use this MDB default for their 20-second trial. This is a problem we see across all our metrics: Are people are using X because it's the default or are they using X because they want to use X? We need to segment the data further - asking what percentage of each percentage meet our criteria for an 'established user' or 'informed user'. You end up spending hours writing sophisticated and dubious SQL queries to segment the data further. Not fun. You can't find out why they used this feature Metrics can answer the when and what, but not the why. Why did people use feature X? If you're anything like me, you often click on random buttons in unfamiliar applications just to explore the feature-set. If we listened uncritically to metrics at RedGate, we would eliminate the most-important and more-complex features which people actually buy the software for, leaving just big buttons on the main page and the About-Box. "Ah, that's interesting!" rather than "Ah, that's actionable!" People do love data. Did you know you eat 1201 chickens in a lifetime? But just 4 cows? Interesting, but useless. Often metrics give you a nice number: '5.8% of users have 3 or more monitors' . But unless the statistic is both SUPRISING and ACTIONABLE, it's useless. Most metrics are collected, reviewed with lots of cooing. and then forgotten. Unless a piece-of-data could change things, it's useless collecting it. People get obsessed with significance levels The first things that lots of people do with this data is do a t-test to get a significance level ("Hey! We know with 99.64% confidence that people prefer SQL Server to MDBs!") Believe me: other causes of error/misinterpretation in your data are FAR more significant than your t-test could ever comprehend. Confirmation bias prevents objectivity If the data appears to match our instinct, we feel satisfied and move on. If it doesn't, we suspect the data and dig deeper, plummeting down a rabbit-hole of segmentation and filtering until we give-up and move-on. Data is only useful if it can change our preconceptions. Do you trust this dodgy data more than your own understanding, knowledge and intelligence?  I don't. There's always multiple plausible ways to interpret/action any data Let's say we segment the above data, and get this data: Post-trial users (i.e. those using a paid version after the 14-day free-trial is over): Parameter Number of users % of total users Number of sessions Number of usages SQL Server 13 9.0 1115 1115 MDB 5 4.2 449 449 Trial users: Parameter Number of users % of total users Number of sessions Number of usages SQL Server 15 10.0 7000 7000 MDB 114 77.6 1000 1000 How do you interpret this data? It's one of: Mostly SQL Server users buy our software. People who can't afford SQL Server tend to be unable to afford or unwilling to buy our software. Therefore, ditch MDB-support. Our MDB support is so poor and buggy that our massive MDB user-base doesn't buy it.  Therefore, spend loads of money improving it, and think about ditching SQL-Server support. People 'graduate' naturally from MDB to SQL Server as they use the software more. Things are fine the way they are. We're marketing the tool wrong. The large number of MDB users represent uninformed downloaders. Tell marketing to aggressively target SQL Server users. To choose an interpretation you need to segment again. And again. And again, and again. Opting-out is correlated with feature-usage Metrics tends to be opt-in. This skews the data even further. Between 5% and 30% of people choose to opt-in to metrics (often called 'customer improvement program' or something like that). Casual trial-users who are uninterested in your product or company are less likely to opt-in. This group is probably also likely to be MDB users. How much does this skew your data by? Who knows? It's not all doom and gloom. There are some things metrics can answer well. Environment facts. How many people have 3 monitors? Have Windows 7? Have .NET 4 installed? Have Japanese Windows? Minor optimizations.  Is the text-box big enough for average user-input? Performance data. How long does our app take to start? How many databases does the average user have on their server? As you can see, questions about who-the-user-is rather than what-the-user-does are easier to answer and action. Conclusion Use SmartAssembly. If not for the metrics (called 'Feature-Usage-Reporting'), then at least for the obfuscation/error-reporting. Data raises more questions than it answers. Questions about environment are the easiest to answer.

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  • Showplan Operator of the week - Assert

    As part of his mission to explain the Query Optimiser in practical terms, Fabiano attempts the feat of describing, one week at a time, all the major Showplan Operators used by SQL Server's Query Optimiser to build the Query Plan. He starts with Assert

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  • Data Model Dissonance

    - by Tony Davis
    So often at the start of the development of database applications, there is a premature rush to the keyboard. Unless, before we get there, we’ve mapped out and agreed the three data models, the Conceptual, the Logical and the Physical, then the inevitable refactoring will dog development work. It pays to get the data models sorted out up-front, however ‘agile’ you profess to be. The hardest model to get right, the most misunderstood, and the one most neglected by the various modeling tools, is the conceptual data model, and yet it is critical to all that follows. The conceptual model distils what the business understands about itself, and the way it operates. It represents the business rules that govern the required data, its constraints and its properties. The conceptual model uses the terminology of the business and defines the most important entities and their inter-relationships. Don’t assume that the organization’s understanding of these business rules is consistent or accurate. Too often, one department has a subtly different understanding of what an entity means and what it stores, from another. If our conceptual data model fails to resolve such inconsistencies, it will reduce data quality. If we don’t collect and measure the raw data in a consistent way across the whole business, how can we hope to perform meaningful aggregation? The conceptual data model has more to do with business than technology, and as such, developers often regard it as a worthy but rather arcane ceremony like saluting the flag or only eating fish on Friday. However, the consequences of getting it wrong have a direct and painful impact on many aspects of the project. If you adopt a silo-based (a.k.a. Domain driven) approach to development), you are still likely to suffer by starting with an incomplete knowledge of the domain. Even when you have surmounted these problems so that the data entities accurately reflect the business domain that the application represents, there are likely to be dire consequences from abandoning the goal of a shared, enterprise-wide understanding of the business. In reading this, you may recall experiences of the consequence of getting the conceptual data model wrong. I believe that Phil Factor, for example, witnessed the abandonment of a multi-million dollar banking project due to an inadequate conceptual analysis of how the bank defined a ‘customer’. We’d love to hear of any examples you know of development projects poleaxed by errors in the conceptual data model. Cheers, Tony

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  • Exploring In-memory OLTP Engine (Hekaton) in SQL Server 2014 CTP1

    The continuing drop in the price of memory has made fast in-memory OLTP increasingly viable. SQL Server 2014 allows you to migrate the most-used tables in an existing database to memory-optimised 'Hekaton' technology, but how you balance between disk tables and in-memory tables for optimum performance requires judgement and experiment. What is this technology, and how can you exploit it? Rob Garrison explains.

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  • Defining .NET Components with Namespaces

    A .NET software component is a compiled set of classes that provide a programmable interface that is used by consumer applications for a service. As a component is no more than a logical grouping of classes, what then is the best way to define the boundaries of a component within the .NET framework? How should the classes inter-operate? Patrick Smacchia, the lead developer of NDepend, discusses the issues and comes up with a solution.

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  • Improving Comparison Operators and Window Functions

    It is dangerous to assume that your data is sound. SQL already has intrinsic ways to cope with missing, or unknown data in its comparison predicate operators, or Theta operators. Can SQL be more effective in the way it deals with data quality? Joe Celko describes how the SQL Standard could soon evolve to deal with data in ways that allow aggregation and windowing in cases where the data quality is less than perfect

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  • background image disappears when position relative used in firefox

    - by toomanyairmiles
    So I'm trying to add a badge to the top right corner of a site I'm doing some work on. z-index works to float the object above the page content but each time i try to use position relative the background image disappears only position absolute shows the image. I don't really want to use absolute as the image needs to be positioned on the right hand side of the sites menu bar not the right hand side of the viewport. Any thoughts or advice appreciated <div class="badge-box"> <a href="http://www.google.com" class="badge">Book Now!</a> </div> <div id="header"> <a href="index.php"><img src="images/pixel.gif" width="378" height="31" alt="Welcome to Gwynfryn Farm Cottages" /></a> </div> <div id="main-menu"> <div> <a href="/">Home</a> <a href="/cottages.php">Our Cottages</a> <a href="/gwynfryn.php">Bed &amp; Breakfast</a> <a href="/rates.php">Price Guide</a> <a href="/llanbedr.php">Location &amp; Local Attractions</a> <a href="/news.php">News &amp; Special Offers</a> <a href="/contact.php">Contact Us</a> </div> </div> .badge-box { width: 1030px; margin-left: auto; margin-right: auto; border: 0px solid red; } .badge { background: url(../images/badge.png) 0px 0px no-repeat; width: 148px; height: 148px; text-indent: -10000px; position: relative; z-index: 999; } #header { width: 960px; height: 40px; margin-left:auto; margin-right:auto; margin-top:20px; padding: 20px 0px 0px 20px; background: #58564f url(../images/header-top-background.png); } #main-menu { width: 980px; margin-left: auto; margin-right: auto; height: 35px; /*background: red;*/ background: #58564f url(../images/header-bottom-background.png); font-family: Georgia, "Times New Roman", Times, serif; } #main-menu div { width: 776px; height: 35px; margin-left: auto; margin-right: auto; background: blue; } #main-menu div a { display: block; float: left; padding: 5px 10px 0px 10px; height: 30px; color: #FFFFFF; font-size: 1.2em; text-align: center; background: green; } #main-menu div a:hover { background-color: #333333; }

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  • Are your personal insecurities screwing up your internal communications?

    - by Lucy Boyes
    I do some internal comms as part of my job. Quite a lot of it involves talking to people about stuff. I’m spending the next couple of weeks talking to lots of people about internal comms itself, because we haven’t done a lot of audience/user feedback gathering, and it turns out that if you talk to people about how they feel and what they think, you get some pretty interesting insights (and an idea of what to do next that isn’t just based on guesswork and generalising from self). Three things keep coming up from talking to people about what we suck at  in terms of internal comms. And, as far as I can tell, they’re all examples where personal insecurity on the part of the person doing the communicating makes the experience much worse for the people on the receiving end. 1. Spending time telling people how you’re going to do something, not what you’re doing and why Imagine you’ve got to give an update to a lot of people who don’t work in your area or department but do have an interest in what you’re doing (either because they want to know because they’re curious or because they need to know because it’s going to affect their work too). You don’t want to look bad at your job. You want to make them think you’ve got it covered – ideally because you do*. And you want to reassure them that there’s lots of exciting work going on in your area to make [insert thing of choice] happen to [insert thing of choice] so that [insert group of people] will be happy. That’s great! You’re doing a good job and you want to tell people about it. This is good comms stuff right here. However, you’re slightly afraid you might secretly be stupid or lazy or incompetent. And you’re exponentially more afraid that the people you’re talking to might think you’re stupid or lazy or incompetent. Or pointless. Or not-adding-value. Or whatever the thing that’s the worst possible thing to be in your company is. So you open by mentioning all the stuff you’re going to do, spending five minutes or so making sure that everyone knows that you’re DOING lots of STUFF. And the you talk for the rest of the time about HOW you’re going to do the stuff, because that way everyone will know that you’ve thought about this really hard and done tons of planning and had lots of great ideas about process and that you’ve got this one down. That’s the stuff you’ve got to say, right? To prove you’re not fundamentally worthless as a human being? Well, maybe. But probably not. See, the people who need to know how you’re going to do the stuff are the people doing the stuff. And those are the people in your area who you’ve (hopefully-please-for-the-love-of-everything-holy) already talked to in depth about how you’re going to do the thing (because else how could they help do it?). They are the only people who need to know the how**. It’s the difference between strategy and tactics. The people outside of your bubble of stuff-doing need to know the strategy – what it is that you’re doing, why, where you’re going with it, etc. The people on the ground with you need the strategy and the tactics, because else they won’t know how to do the stuff. But the outside people don’t really need the tactics at all. Don’t bother with the how unless your audience needs it. They probably don’t. It might make you feel better about yourself, but it’s much more likely that Bob and Jane are thinking about how long this meeting has gone on for already than how personally impressive and definitely-not-an-idiot you are for knowing how you’re going to do some work. Feeling marginally better about yourself (but, let’s face it, still insecure as heck) is not worth the cost, which in this case is the alienation of your audience. 2. Talking for too long about stuff This is kinda the same problem as the previous problem, only much less specific, and I’ve more or less covered why it’s bad already. Basic motivation: to make people think you’re not an idiot. What you do: talk for a very long time about what you’re doing so as to make it sound like you know what you’re doing and lots about it. What your audience wants: the shortest meaningful update. Some of this is a kill your darlings problem – the stuff you’re doing that seems really nifty to you seems really nifty to you, and thus you want to share it with everyone to show that you’re a smart person who thinks up nifty things to do. The downside to this is that it’s mostly only interesting to you – if other people don’t need to know, they likely also don’t care. Think about how you feel when someone is talking a lot to you about a lot of stuff that they’re doing which is at best tangentially interesting and/or relevant. You’re probably not thinking that they’re really smart and clearly know what they’re doing (unless they’re talking a lot and being really engaging about it, which is not the same as talking a lot). You’re probably thinking about something totally unrelated to the thing they’re talking about. Or the fact that you’re bored. You might even – and this is the opposite of what they’re hoping to achieve by talking a lot about stuff – be thinking they’re kind of an idiot. There’s another huge advantage to paring down what you’re trying to say to the barest possible points – it clarifies your thinking. The lightning talk format, as well as other formats which limit the time and/or number of slides you have to say a thing, are really good for doing this. It’s incredibly likely that your audience in this case (the people who need to know some things about your thing but not all the things about your thing) will get everything they need to know from five minutes of you talking about it, especially if trying to condense ALL THE THINGS into a five-minute talk has helped you get clear in your own mind what you’re doing, what you’re trying to say about what you’re doing and why you’re doing it. The bonus of this is that by being clear in your thoughts and in what you say, and in not taking up lots of people’s time to tell them stuff they don’t really need to know, you actually come across as much, much smarter than the person who talks for half an hour or more about things that are semi-relevant at best. 3. Waiting until you’ve got every detail sorted before announcing a big change to the people affected by it This is the worst crime on the list. It’s also human nature. Announcing uncertainty – that something important is going to happen (big reorganisation, product getting canned, etc.) but you’re not quite sure what or when or how yet – is scary. There are risks to it. Uncertainty makes people anxious. It might even paralyse them. You can’t run a business while you’re figuring out what to do if you’ve paralysed everyone with fear over what the future might bring. And you’re scared that they might think you’re not the right person to be in charge of [thing] if you don’t even know what you’re doing with it. Best not to say anything until you know exactly what’s going to happen and you can reassure them all, right? Nope. The people who are going to be affected by whatever it is that you don’t quite know all the details of yet aren’t stupid***. You wouldn’t have hired them if they were. They know something’s up because you’ve got your guilty face on and you keep pulling people into meeting rooms and looking vaguely worried. Here’s the deal: it’s a lot less stressful for everyone (including you) if you’re up front from the beginning. We took this approach during a recent company-wide reorganisation and got really positive feedback. People would much, much rather be told that something is going to happen but you’re not entirely sure what it is yet than have you wait until it’s all fixed up and then fait accompli the heck out of them. They will tell you this themselves if you ask them. And here’s why: by waiting until you know exactly what’s going on to communicate, you remove any agency that the people that the thing is going to happen to might otherwise have had. I know you’re scared that they might get scared – and that’s natural and kind of admirable – but it’s also patronising and infantilising. Ask someone whether they’d rather work on a project which has an openly uncertain future from the beginning, or one where everything’s great until it gets shut down with no forewarning, and very few people are going to tell you they’d prefer the latter. Uncertainty is humanising. It’s you admitting that you don’t have all the answers, which is great, because no one does. It allows you to be consultative – you can actually ask other people what they think and how they feel and what they’d like to do and what they think you should do, and they’ll thank you for it and feel listened to and respected as people and colleagues. Which is a really good reason to start talking to them about what’s going on as soon as you know something’s going on yourself. All of the above assumes you actually care about talking to the people who work with you and for you, and that you’d like to do the right thing by them. If that’s not the case, you can cheerfully disregard the advice here, but if it is, you might want to think about the ways above – and the inevitable countless other ways – that making internal communication about you and not about your audience could actually be doing the people you’re trying to communicate with a huge disservice. So take a deep breath and talk. For five minutes or so. About the important things. Not the other things. As soon as you possibly can. And you’ll be fine.   *Of course you do. You’re good at your job. Don’t worry. **This might not always be true, but it is most of the time. Other people who need to know the how will either be people who you’ve already identified as needing-to-know and thus part of the same set as the people in you’re area you’ve already discussed this with, or else they’ll ask you. But don’t bring this stuff up unless someone asks for it, because most of the people in the audience really don’t care and you’re wasting their time. ***I mean, they might be. But let’s give them the benefit of the doubt and assume they’re not.

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  • How do I set up FirePHP version 1.0?

    - by jay
    I love FirePHP and I've been using it for a while, but they've put out this massive upgrade and I'm completely flummoxed trying to get it to work. I think I'm copying the "Quick Start" code (kind of guessing at whatever changes are necessary for my server configuration), but for some reason, FirePHP's "primary" function, FirePHP::to() isn't doing anything. Can anyone please help me figure out what I'm doing wrong? Thanks. <?php define('INSIGHT_IPS', '*'); define('INSIGHT_AUTHKEYS', '290AA9215205F24E5104F48D61B60FFC'); define('INSIGHT_PATHS', __DIR__); define('INSIGHT_SERVER_PATH', '/doc_root/hello_firephp2.php'); set_include_path(get_include_path . ":/home8/jayharri/php/FirePHP/lib"); // path to FirePHP library require_once('FirePHP/Init.php'); $inpector = FirePHP::to('page'); var_dump($inspector); $console = $inspector->console(); $console->log('hello firephp'); ?> Output: NULL Fatal error: Call to a member function console() on a non-object in /home8/jayharri/public_html/if/doc_root/hello_firephp2.php on line 14

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  • Know your Data Lineage

    - by Simon Elliston Ball
    An academic paper without the footnotes isn’t an academic paper. Journalists wouldn’t base a news article on facts that they can’t verify. So why would anyone publish reports without being able to say where the data has come from and be confident of its quality, in other words, without knowing its lineage. (sometimes referred to as ‘provenance’ or ‘pedigree’) The number and variety of data sources, both traditional and new, increases inexorably. Data comes clean or dirty, processed or raw, unimpeachable or entirely fabricated. On its journey to our report, from its source, the data can travel through a network of interconnected pipes, passing through numerous distinct systems, each managed by different people. At each point along the pipeline, it can be changed, filtered, aggregated and combined. When the data finally emerges, how can we be sure that it is right? How can we be certain that no part of the data collection was based on incorrect assumptions, that key data points haven’t been left out, or that the sources are good? Even when we’re using data science to give us an approximate or probable answer, we cannot have any confidence in the results without confidence in the data from which it came. You need to know what has been done to your data, where it came from, and who is responsible for each stage of the analysis. This information represents your data lineage; it is your stack-trace. If you’re an analyst, suspicious of a number, it tells you why the number is there and how it got there. If you’re a developer, working on a pipeline, it provides the context you need to track down the bug. If you’re a manager, or an auditor, it lets you know the right things are being done. Lineage tracking is part of good data governance. Most audit and lineage systems require you to buy into their whole structure. If you are using Hadoop for your data storage and processing, then tools like Falcon allow you to track lineage, as long as you are using Falcon to write and run the pipeline. It can mean learning a new way of running your jobs (or using some sort of proxy), and even a distinct way of writing your queries. Other Hadoop tools provide a lot of operational and audit information, spread throughout the many logs produced by Hive, Sqoop, MapReduce and all the various moving parts that make up the eco-system. To get a full picture of what’s going on in your Hadoop system you need to capture both Falcon lineage and the data-exhaust of other tools that Falcon can’t orchestrate. However, the problem is bigger even that that. Often, Hadoop is just one piece in a larger processing workflow. The next step of the challenge is how you bind together the lineage metadata describing what happened before and after Hadoop, where ‘after’ could be  a data analysis environment like R, an application, or even directly into an end-user tool such as Tableau or Excel. One possibility is to push as much as you can of your key analytics into Hadoop, but would you give up the power, and familiarity of your existing tools in return for a reliable way of tracking lineage? Lineage and auditing should work consistently, automatically and quietly, allowing users to access their data with any tool they require to use. The real solution, therefore, is to create a consistent method by which to bring lineage data from these data various disparate sources into the data analysis platform that you use, rather than being forced to use the tool that manages the pipeline for the lineage and a different tool for the data analysis. The key is to keep your logs, keep your audit data, from every source, bring them together and use the data analysis tools to trace the paths from raw data to the answer that data analysis provides.

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  • Unteachable Disaster Recovery Techniques

    There are some skills which are extensions of your instincts, and which you can only learn though years of experience. Matt Simmons has this brought home by the fact that he was recently minutes away from a data-loss disaster, and he doesn't quite know how he prevented it.

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  • A TDD Journey: 1-Trials and Tribulations

    Test-Driven Development (TDD) has a misleading name, because the objective is to design and specify that the system you are developing behaves in the ways that the customer expects, and to prove that it does so for the lifetime of the system. It isn't an intuitive way of coding but by automating the specifications of a system, we end up with tests and documentation as a by-product. Michael Sorens starts an introduction to TDD that is more of a journey in six parts:

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  • What Counts For a DBA: Fitness

    - by Louis Davidson
    If you know me, you can probably guess that physical exercise is not really my thing. There was a time in my past when it a larger part of my life, but even then never in the same sort of passionate way as a number of our SQL friends.  For me, I find that mental exercise satisfies what I believe to be the same inner need that drives people to run farther than I like to drive on most Saturday mornings, and it is certainly just as addictive. Mental fitness shares many common traits with physical fitness, especially the need to attain it through repetitive training. I only wish that mental training burned off a bacon cheeseburger in the same manner as does jogging around a dewy park on Saturday morning. In physical training, there are at least two goals, the first of which is to be physically able to do a task. The second is to train the brain to perform the task without thinking too hard about it. No matter how long it has been since you last rode a bike, you will be almost certainly be able to hop on and start riding without thinking about the process of pedaling or balancing. If you’ve never ridden a bike, you could be a physics professor /Olympic athlete and still crash the first few times you try, even though you are as strong as an ox and your knowledge of the physics of bicycle riding makes the concept child’s play. For programming tasks, the process is very similar. As a DBA, you will come to know intuitively how to backup, optimize, and secure database systems. As a data programmer, you will work to instinctively use the clauses of Transact-SQL DML so that, when you need to group data three ways (and not four), you will know to use the GROUP BY clause with GROUPING SETS without resorting to a search engine.  You have the skill. Making it naturally then requires repetition and experience is the primary requirement, not just simply learning about a topic. The hardest part of being really good at something is this difference between knowledge and skill. I have recently taken several informative training classes with Kimball University on data warehousing and ETL. Now I have a lot more knowledge about designing data warehouses than before. I have also done a good bit of data warehouse designing of late and have started to improve to some level of proficiency with the theory. Yet, for all of this head knowledge, it is still a struggle to take what I have learned and apply it to the designs I am working on.  Data warehousing is still a task that is not yet deeply ingrained in my brain muscle memory. On the other hand, relational database design is something that no matter how much or how little I may get to do it, I am comfortable doing it. I have done it as a profession now for well over a decade, I teach classes on it, and I also have done (and continue to do) a lot of mental training beyond the work day. Sometimes the training is just basic education, some reading blogs and attending sessions at PASS events.  My best training comes from spending time working on other people’s design issues in forums (though not nearly as much as I would like to lately). Working through other people’s problems is a great way to exercise your brain on problems with which you’re not immediately familiar. The final bit of exercise I find useful for cultivating mental fitness for a data professional is also probably the nerdiest thing that I will ever suggest you do.  Akin to running in place, the idea is to work through designs in your head. I have designed more than one database system that would revolutionize grocery store operations, sales at my local Target store, the ordering process at Amazon, and ways to improve Disney World operations to get me through a line faster (some of which they are starting to implement without any of my help.) Never are the designs truly fleshed out, but enough to work through structures and processes.  On “paper”, I have designed database systems to catalog things as trivial as my Lego creations, rental car companies and my audio and video collections. Once I get the database designed mentally, sometimes I will create the database, add some data (often using Red-Gate’s Data Generator), and write a few queries to see if a concept was realistic, but I will rarely fully flesh out the database since I have no desire to do any user interface programming anymore.  The mental training allows me to keep in practice for when the time comes to do the work I love the most for real…even if I have been spending most of my work time lately building data warehouses.  If you are really strong of mind and body, perhaps you can mix a mental run with a physical run; though don’t run off of a cliff while contemplating how you might design a database to catalog the trees on a mountain…that would be contradictory to the purpose of both types of exercise.

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  • Software Tuned to Humanity

    - by Phil Factor
    I learned a great deal from a cynical old programmer who once told me that the ideal length of time for a compiler to do its work was the same time it took to roll a cigarette. For development work, this is oh so true. After intently looking at the editing window for an hour or so, it was a relief to look up, stretch, focus the eyes on something else, and roll the possibly-metaphorical cigarette. This was software tuned to humanity. Likewise, a user’s perception of the “ideal” time that an application will take to move from frame to frame, to retrieve information, or to process their input has remained remarkably static for about thirty years, at around 200 ms. Anything else appears, and always has, to be either fast or slow. This could explain why commercial applications, unlike games, simulations and communications, aren’t noticeably faster now than they were when I started programming in the Seventies. Sure, they do a great deal more, but the SLAs that I negotiated in the 1980s for application performance are very similar to what they are nowadays. To prove to myself that this wasn’t just some rose-tinted misperception on my part, I cranked up a Z80-based Jonos CP/M machine (1985) in the roof-space. Within 20 seconds from cold, it had loaded Wordstar and I was ready to write. OK, I got it wrong: some things were faster 30 years ago. Sure, I’d now have had all sorts of animations, wizzy graphics, and other comforting features, but it seems a pity that we have used all that extra CPU and memory to increase the scope of what we develop, and the graphical prettiness, but not to speed the processes needed to complete a business procedure. Never mind the weight, the response time’s great! To achieve 200 ms response times on a Z80, or similar, performance considerations influenced everything one did as a developer. If it meant writing an entire application in assembly code, applying every smart algorithm, and shortcut imaginable to get the application to perform to spec, then so be it. As a result, I’m a dyed-in-the-wool performance freak and find it difficult to change my habits. Conversely, many developers now seem to feel quite differently. While all will acknowledge that performance is important, it’s no longer the virtue is once was, and other factors such as user-experience now take precedence. Am I wrong? If not, then perhaps we need a new school of development technique to rival Agile, dedicated once again to producing applications that smoke the rear wheels rather than pootle elegantly to the shops; that forgo skeuomorphism, cute animation, or architectural elegance in favor of the smell of hot rubber. I struggle to name an application I use that is truly notable for its blistering performance, and would dearly love one to do my everyday work – just as long as it doesn’t go faster than my brain.

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  • Celko's SQL Stumper: Eggs in one Basket

    Joe Celko returns with another stumper to celebrate Easter. Unsurprisingly, this involves eggs. More surprising is the nature of the puzzle: This time, the puzzle is one of designing a database rather than a query. DDL as well as the DML.

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  • Test-driven Database Development – Why Bother?

    Test-Driven Development is a practice that can bring many benefits, including better design, and less-buggy code, but is it relevant to database development, where the process of development tends to me much more interactive, and the culture more test-oriented? Greg reviews the support for TDD for Databases, and suggests that it is worth giving it a try for the range of advantages it can bring to team-working.

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  • A Knights Tale

    - by Phil Factor
    There are so many lessons to be learned from the story of Knight Capital losing nearly half a billion dollars as a result of a deployment gone wrong. The Knight Capital Group (KCG N) was an American global financial services firm engaging in market making, electronic execution, and institutional sales and trading. According to the recent order (File No.3.15570) against Knight Capital by U.S. Securities and Exchange Commission?, Knight had, for many years used some software which broke up incoming “parent” orders into smaller “child” orders that were then transmitted to various exchanges or trading venues for execution. A tracking ‘cumulative quantity’ function counted the number of ‘child’ orders and stopped the process once the total of child orders matched the ‘parent’ and so the parent order had been completed. Back in the mists of time, some code had been added to it  which was excuted if a particular flag was set. It was called ‘power peg’ and seems to have had a similar design and purpose, but, one guesses, would have shared the same tracking function. This code had been abandoned in 2003, but never deleted. In 2005, The tracking function was moved to an earlier point in the main process. It would seem from the account that, from that point, had that flag ever been set, the old ‘Power Peg’ would have been executed like Godzilla bursting from the ice, making child orders without limit without any tracking function. It wasn’t, presumably because the software that set the flag was removed. In 2012, nearly a decade after ‘Power Peg’ was abandoned, Knight prepared a new module to their software to cope with the imminent Retail Liquidity Program (RLP) for the New York Stock Exchange. By this time, the flag had remained unused and someone made the fateful decision to reuse it, and replace the old ‘power peg’ code with this new RLP code. Had the two actions been done together in a single automated deployment, and the new deployment tested, all would have been well. It wasn’t. To quote… “Beginning on July 27, 2012, Knight deployed the new RLP code in SMARS in stages by placing it on a limited number of servers in SMARS on successive days. During the deployment of the new code, however, one of Knight’s technicians did not copy the new code to one of the eight SMARS computer servers. Knight did not have a second technician review this deployment and no one at Knight realized that the Power Peg code had not been removed from the eighth server, nor the new RLP code added. Knight had no written procedures that required such a review.” (para 15) “On August 1, Knight received orders from broker-dealers whose customers were eligible to participate in the RLP. The seven servers that received the new code processed these orders correctly. However, orders sent with the repurposed flag to the eighth server triggered the defective Power Peg code still present on that server. As a result, this server began sending child orders to certain trading centers for execution. Because the cumulative quantity function had been moved, this server continuously sent child orders, in rapid sequence, for each incoming parent order without regard to the number of share executions Knight had already received from trading centers. Although one part of Knight’s order handling system recognized that the parent orders had been filled, this information was not communicated to SMARS.” (para 16) SMARS routed millions of orders into the market over a 45-minute period, and obtained over 4 million executions in 154 stocks for more than 397 million shares. By the time that Knight stopped sending the orders, Knight had assumed a net long position in 80 stocks of approximately $3.5 billion and a net short position in 74 stocks of approximately $3.15 billion. Knight’s shares dropped more than 20% after traders saw extreme volume spikes in a number of stocks, including preferred shares of Wells Fargo (JWF) and semiconductor company Spansion (CODE). Both stocks, which see roughly 100,000 trade per day, had changed hands more than 4 million times by late morning. Ultimately, Knight lost over $460 million from this wild 45 minutes of trading. Obviously, I’m interested in all this because, at one time, I used to write trading systems for the City of London. Obviously, the US SEC is in a far better position than any of us to work out the failings of Knight’s IT department, and the report makes for painful reading. I can’t help observing, though, that even with the breathtaking mistakes all along the way, that a robust automated deployment process that was ‘all-or-nothing’, and tested from soup to nuts would have prevented the disaster. The report reads like a Greek Tragedy. All the way along one wants to shout ‘No! not that way!’ and ‘Aargh! Don’t do it!’. As the tragedy unfolds, the audience weeps for the players, trapped by a cruel fate. All application development and deployment requires defense in depth. All IT goes wrong occasionally, but if there is a culture of defensive programming throughout, the consequences are usually containable. For financial systems, these defenses are required by statute, and ignored only by the foolish. Knight’s mistakes weren’t made by just one hapless sysadmin, but were progressive errors by an  IT culture spanning at least ten years.  One can spell these out, but I think they’re obvious. One can only hope that the industry studies what happened in detail, learns from the mistakes, and draws the right conclusions.

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  • Antenna Aligner Part 7: Connecting the dots

    - by Chris George
    The app is basically ready, so I eagerly started to sort out creating the application entry in iTunes Connect. It's mostly intuitive actually, although I did have to create yet another icon for iTunes sized 512x512 pixels, damn lucky I did the original graphics as vector! It took me longer to write the application description than anything else, I'm so not a tech author! I didn't like the way you have to 'make up' an SKU (Stock Keeping Unit) number. I have to do some googling to find out that it really doesn't matter what it is! It should be more obvious what to do from the actual website itself. That aside, the rest of it was actually fairly straightforward. As well as the details of the application, iPhone and iPad screenshots were also required. This posed somewhat of a problem. The iPhone ones were easy (as I have one!), but I do not (yet) own an iPad . So I thought I'd leave the iPad screenshots out for now. Once the application details were sorted, I moved onto the rights and pricing. At the start of the project I had made the decision that I wouldn't charge any more than the lowest amount £0.59. I believe there is a market for this, but as my first foray into app development I didn't want to take the mick. I did realise, however, that I had built my app with a developer certificate and provisioning profile. This was fairly quickly corrected, and again Nomad made this very easy to switch over to the distribution certificate and provisioning profile. With a sense of excitement I cracked open iTunes connect and clicked the upload button ... ...slight snag... . when the Nomad project was started, Apple allowed uploads of these binaries via iTunes Connect. But this is no longer possible, the only upload path is via the Application Loader available from the Apple Developer program. This itself has one limitation, it only runs on a mac! D'OH!!!  Actually my language was somewhat more colourful when this fact came to light. After picking my laptop up off the floor and putting it back together... ok only joking, but I did nearly throw it out of frustration!... I started to consider the options; I briefly entertained the idea of buying a cheap mac from ebay... no, that defeats the whole object of what I'm doing, plus my wife wouldn't be impressed there are some guys out there in the interweb who will upload your app for a small fee...but I don't really like the idea of giving some faceless email address my apple developer login details, as well as my app binary! find some willing friend with a mac who would kindly let me use it... obviously this is the only sensible option. In the meantime, I informed the Nomad team about this slight 'issue' and they are currently investigating possible solutions...

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  • Obscure SPUtility.SendMail Behavior When Manually Passing in Mail Headers

    - by Damon
    There are two ways to send mail in SharePoint: you can either use the mail components from the System.Net namespace, or you can send email using SharePoint's SPUtility.SendMail method.  One of the benefits of the SPUtility.SendMail method is that it uses the mail configuration from SharePoint, so you can manage settings in Central Administration instead of having to go through and modify your web.config file.  SPUtility.SendMail can get the job done, but it's defiantly not as developer friendly as the components from the System.Net namespace.  If you want to CC someone on an email, for example, you do NOT have a nice CC parameter - you have to manually add the CC mail header and pass it into the SPUtility.SendMail method.  I had to do this the other day, and ran into a really obscure issue. If you do NOT pass the headers into the method then SharePoint sends the email using the From Address configured in the Outgoing Mail settings in Central Admin.  If you pass headers into the method, but do not include the from header, then SharePoint sends the mail using the email address of the current user. This can be an issue if your mail server is setup to reject an email from an invalid email address or an email address that is not on your domain.  The way to fix this issue is to always pass in the from header.  If you want to use the configured From address, then you can do the following: SPWebApplication webApp = SPWebApplication.Lookup(new Uri(SPContext.Current.Site.Url)); StringDictionary headers = new StringDictionary(); headers.Add("from", webApp.OutboundMailSenderAddress);

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  • Documentation and Test Assertions in Databases

    - by Phil Factor
    When I first worked with Sybase/SQL Server, we thought our databases were impressively large but they were, by today’s standards, pathetically small. We had one script to build the whole database. Every script I ever read was richly annotated; it was more like reading a document. Every table had a comment block, and every line would be commented too. At the end of each routine (e.g. procedure) was a quick integration test, or series of test assertions, to check that nothing in the build was broken. We simply ran the build script, stored in the Version Control System, and it pulled everything together in a logical sequence that not only created the database objects but pulled in the static data. This worked fine at the scale we had. The advantage was that one could, by reading the source code, reach a rapid understanding of how the database worked and how one could interface with it. The problem was that it was a system that meant that only one developer at the time could work on the database. It was very easy for a developer to execute accidentally the entire build script rather than the selected section on which he or she was working, thereby cleansing the database of everyone else’s work-in-progress and data. It soon became the fashion to work at the object level, so that programmers could check out individual views, tables, functions, constraints and rules and work on them independently. It was then that I noticed the trend to generate the source for the VCS retrospectively from the development server. Tables were worst affected. You can, of course, add or delete a table’s columns and constraints retrospectively, which means that the existing source no longer represents the current object. If, after your development work, you generate the source from the live table, then you get no block or line comments, and the source script is sprinkled with silly square-brackets and other confetti, thereby rendering it visually indigestible. Routines, too, were affected. In our system, every routine had a directly attached string of unit-tests. A retro-generated routine has no unit-tests or test assertions. Yes, one can still commit our test code to the VCS but it’s a separate module and teams end up running the whole suite of tests for every individual change, rather than just the tests for that routine, which doesn’t scale for database testing. With Extended properties, one can get the best of both worlds, and even use them to put blame, praise or annotations into your VCS. It requires a lot of work, though, particularly the script to generate the table. The problem is that there are no conventional names beyond ‘MS_Description’ for the special use of extended properties. This makes it difficult to do splendid things such ensuring the integrity of the build by running a suite of tests that are actually stored in extended properties within the database and therefore the VCS. We have lost the readability of database source code over the years, and largely jettisoned the use of test assertions as part of the database build. This is not unexpected in view of the increasing complexity of the structure of databases and number of programmers working on them. There must, surely, be a way of getting them back, but I sometimes wonder if I’m one of very few who miss them.

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  • Getting the right results with bcp and DTS with multiple versions of SQL Server installed.

    - by fatherjack
    I was using SSIS for the first time on an instance the other day and came across this error when I executed a package Package migration from version 3 to version 2 failed with error 0xC001700A. The version number in the package is not valid. The version number cannot be greater than current version number. This was a pain and wasn't something that I was expecting, however, the error message made sense - the package was being executed by the wrong version of the executable. Not impossible to...(read more)

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