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  • Harnessing PowerShell's String Comparison and List-Filtering Features

    When you are first learning PowerShell, it often seems to be an 'Alice through the looking-glass' world. Just the simple process of comparing and selecting strings can seem strangely obtuse. Michael turns the looking-glass into wonderland with his wall-chart of the PowerShell string-comparison operators and syntax The Future of SQL Server MonitoringMonitor wherever, whenever with Red Gate's SQL Monitor. See it live in action now.

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  • Exposing PageRank

    Does PageRank matter? More than a few self proclaimed SEO experts say NO, but common sense dictates that it does, even though some low PageRank (PR) sites with just the correct combination of keywords outperform higher PR sites in Search Engine Results Pages (SERPS). When we externally compare sites for PageRank, we're comparing Toolbar PageRank which doesn't necessarily match Google's internal page rank.

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  • What would you take into account when you were asked to compare software? [closed]

    - by mstaessen
    For my master's thesis, I am asked to make a comparative study of frameworks for cross-platform mobile development. I want to eliminate the chances of having missed something in my comparison. This is why I want to ask what YOU would value (most) when comparing such frameworks (Like for instance PhoneGap and Appcelerator Titanium). Performance, capabilities and licensing are kind of obvious, but can you think of others?

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  • Learn Less, Do more! Is that true with PHP or ASP.NET?

    - by mallieem saleie
    When comparing PHP and ASP.NET, I find that in ASP.NET with Visual Studio you can do things quickly with help of the IDE and the available controls. However, they say that it does not take much time to learn PHP as in asp.net. I want to reach to a point where I can understand which one will I learn quickly? Which one will help me in producing more results (I mean more web applications) if I learned both in 3 months time.

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  • What are the difference between: agent, actor, dataflow based programming?

    - by inf3rno
    What are the difference between the following terms? agent-based programming agent-based programming with microagents actor-based programming actor-based programming with lightweight actors dataflow based programming It is hard to find comparing articles and they are very similar. Afaik they have different constraints and they are implemented on a different abstraction level, but I need some reassurance...

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  • Do Outbound Links Hold Search Engine Power?

    Now, I do not know if this applies to just when the link points to pages on your own site or any outbound links, but time and time again I see before me the evidence that this could just be the case. Last night I was comparing 2 of my own websites. The first, with Page Rank 3 and lots of SEO work against the second, Page Rank 0 and ignored.

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  • Examples of different architecture methodologies

    - by Lane
    Is there a resource or site which illustrates building the same application (desktop or web) using several different contrasting architectures? Such as MVP versus MVVM versus MVC, etc. It would be very helpful to see how they look side-by-side using real-world code instead of comparing written theory to written theory. I've often found that something can be described well in a book, but when you go to implement it, the subtleties and weaknesses of the theory become readily apparent.

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  • C#/.NET Little Wonders: The Nullable static class

    - by James Michael Hare
    Once again, in this series of posts I look at the parts of the .NET Framework that may seem trivial, but can help improve your code by making it easier to write and maintain. The index of all my past little wonders posts can be found here. Today we’re going to look at an interesting Little Wonder that can be used to mitigate what could be considered a Little Pitfall.  The Little Wonder we’ll be examining is the System.Nullable static class.  No, not the System.Nullable<T> class, but a static helper class that has one useful method in particular that we will examine… but first, let’s look at the Little Pitfall that makes this wonder so useful. Little Pitfall: Comparing nullable value types using <, >, <=, >= Examine this piece of code, without examining it too deeply, what’s your gut reaction as to the result? 1: int? x = null; 2:  3: if (x < 100) 4: { 5: Console.WriteLine("True, {0} is less than 100.", 6: x.HasValue ? x.ToString() : "null"); 7: } 8: else 9: { 10: Console.WriteLine("False, {0} is NOT less than 100.", 11: x.HasValue ? x.ToString() : "null"); 12: } Your gut would be to say true right?  It would seem to make sense that a null integer is less than the integer constant 100.  But the result is actually false!  The null value is not less than 100 according to the less-than operator. It looks even more outrageous when you consider this also evaluates to false: 1: int? x = null; 2:  3: if (x < int.MaxValue) 4: { 5: // ... 6: } So, are we saying that null is less than every valid int value?  If that were true, null should be less than int.MinValue, right?  Well… no: 1: int? x = null; 2:  3: // um... hold on here, x is NOT less than min value? 4: if (x < int.MinValue) 5: { 6: // ... 7: } So what’s going on here?  If we use greater than instead of less than, we see the same little dilemma: 1: int? x = null; 2:  3: // once again, null is not greater than anything either... 4: if (x > int.MinValue) 5: { 6: // ... 7: } It turns out that four of the comparison operators (<, <=, >, >=) are designed to return false anytime at least one of the arguments is null when comparing System.Nullable wrapped types that expose the comparison operators (short, int, float, double, DateTime, TimeSpan, etc.).  What’s even odder is that even though the two equality operators (== and !=) work correctly, >= and <= have the same issue as < and > and return false if both System.Nullable wrapped operator comparable types are null! 1: DateTime? x = null; 2: DateTime? y = null; 3:  4: if (x <= y) 5: { 6: Console.WriteLine("You'd think this is true, since both are null, but it's not."); 7: } 8: else 9: { 10: Console.WriteLine("It's false because <=, <, >, >= don't work on null."); 11: } To make matters even more confusing, take for example your usual check to see if something is less than, greater to, or equal: 1: int? x = null; 2: int? y = 100; 3:  4: if (x < y) 5: { 6: Console.WriteLine("X is less than Y"); 7: } 8: else if (x > y) 9: { 10: Console.WriteLine("X is greater than Y"); 11: } 12: else 13: { 14: // We fall into the "equals" assumption, but clearly null != 100! 15: Console.WriteLine("X is equal to Y"); 16: } Yes, this code outputs “X is equal to Y” because both the less-than and greater-than operators return false when a Nullable wrapped operator comparable type is null.  This violates a lot of our assumptions because we assume is something is not less than something, and it’s not greater than something, it must be equal.  So keep in mind, that the only two comparison operators that work on Nullable wrapped types where at least one is null are the equals (==) and not equals (!=) operators: 1: int? x = null; 2: int? y = 100; 3:  4: if (x == y) 5: { 6: Console.WriteLine("False, x is null, y is not."); 7: } 8:  9: if (x != y) 10: { 11: Console.WriteLine("True, x is null, y is not."); 12: } Solution: The Nullable static class So we’ve seen that <, <=, >, and >= have some interesting and perhaps unexpected behaviors that can trip up a novice developer who isn’t expecting the kinks that System.Nullable<T> types with comparison operators can throw.  How can we easily mitigate this? Well, obviously, you could do null checks before each check, but that starts to get ugly: 1: if (x.HasValue) 2: { 3: if (y.HasValue) 4: { 5: if (x < y) 6: { 7: Console.WriteLine("x < y"); 8: } 9: else if (x > y) 10: { 11: Console.WriteLine("x > y"); 12: } 13: else 14: { 15: Console.WriteLine("x == y"); 16: } 17: } 18: else 19: { 20: Console.WriteLine("x > y because y is null and x isn't"); 21: } 22: } 23: else if (y.HasValue) 24: { 25: Console.WriteLine("x < y because x is null and y isn't"); 26: } 27: else 28: { 29: Console.WriteLine("x == y because both are null"); 30: } Yes, we could probably simplify this logic a bit, but it’s still horrendous!  So what do we do if we want to consider null less than everything and be able to properly compare Nullable<T> wrapped value types? The key is the System.Nullable static class.  This class is a companion class to the System.Nullable<T> class and allows you to use a few helper methods for Nullable<T> wrapped types, including a static Compare<T>() method of the. What’s so big about the static Compare<T>() method?  It implements an IComparer compatible comparison on Nullable<T> types.  Why do we care?  Well, if you look at the MSDN description for how IComparer works, you’ll read: Comparing null with any type is allowed and does not generate an exception when using IComparable. When sorting, null is considered to be less than any other object. This is what we probably want!  We want null to be less than everything!  So now we can change our logic to use the Nullable.Compare<T>() static method: 1: int? x = null; 2: int? y = 100; 3:  4: if (Nullable.Compare(x, y) < 0) 5: { 6: // Yes! x is null, y is not, so x is less than y according to Compare(). 7: Console.WriteLine("x < y"); 8: } 9: else if (Nullable.Compare(x, y) > 0) 10: { 11: Console.WriteLine("x > y"); 12: } 13: else 14: { 15: Console.WriteLine("x == y"); 16: } Summary So, when doing math comparisons between two numeric values where one of them may be a null Nullable<T>, consider using the System.Nullable.Compare<T>() method instead of the comparison operators.  It will treat null less than any value, and will avoid logic consistency problems when relying on < returning false to indicate >= is true and so on. Tweet   Technorati Tags: C#,C-Sharp,.NET,Little Wonders,Little Pitfalls,Nulalble

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  • SQL SERVER – How to Compare the Schema of Two Databases with Schema Compare

    - by Pinal Dave
    Earlier I wrote about An Efficiency Tool to Compare and Synchronize SQL Server Databases and it was very much well received. Since the blog post I have received quite a many question that just like data how we can also compare schema and synchronize it. If you think about comparing the schema manually, it is almost impossible to do so. Table Schema has been just one of the concept but if you really want the all the schema of the database (triggers, views, stored procedure and everything else) it is just impossible task. If you are developer or database administrator who works in the production environment than you know that there are so many different occasions when we have to compare schema of the database. Before deploying any changes to the production server, I personally like to make note of the every single schema change and document it so in case of any issue , I can always go back and refer my documentation. As discussed earlier it is absolutely impossible to do this task without the help of third party tools. I personally use Devart Schema Compare for this task. This is an extremely easy tool. Let us see how it works. First I have two different databases – a) AdventureWorks2012 and b) AdventureWorks2012-V1. There are total three changes between these databases. Here is the list of the same. One of the table has additional column One of the table have new index One of the stored procedure is changed Now let see how dbForge Schema Compare works in this scenario. First open dbForge Schema Compare studio. Click on New Schema Comparison. It will bring you to following screen where we have to configure the database needed to configure. I have selected AdventureWorks2012 and AdventureWorks-V1 databases. In the next screen we can verify various options but for this demonstration we will keep it as it is. We will not change anything in schema mapping screen as in our case it is not required but generically if you are comparing across schema you may need this. This is the most important screen as on this screen we select which kind of object we want to compare. You can see the options which are available to select. The screen lets you select the objects from SQL Server 2000 to SQL Server 2012. Once you click on compare in previous screen it will bring you to this screen, which will essentially display the comparative difference between two of the databases which we had selected in earlier screen. As mentioned above there are three different changes in the database and the same has been listed over here. Two of the changes belongs to the tables and one changes belong to the procedure. Let us click each of them one by one to see what is the difference between them. In very first option we can see that there is an additional column in another database which did not exist earlier. In this example we can see that AdventureWorks2012 database have an additional index. Following example is very interesting as in this case, we have changed the definition of the stored procedure and the result pan contains the same. dbForget Schema Compare very effectively identify the changes in schema and lists them neatly to developers. Here is one more screen. This software not only compares the schema but also provides the options to update or drop them as per the choice. I think this is brilliant option. Well, I have been using schema compare for quite a while and have found it very useful. Here are few of the things which dbForge Schema Compare can do for developers and DBAs. Compare and synchronize SQL Server database schemas Compare schemas of live database and SQL Server backup Generate comparison reports in Excel and HTML formats Eliminate mistakes in schema changes propagation across environments Track production database changes and customizations Automate migration of schema changes using command line interface I suggest that you try out dbForge Schema Compare and let me know what you think of this product. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL

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  • The enterprise vendor con - connecting SSD's using SATA 2 (3Gbits) thus limiting there performance

    - by tonyrogerson
    When comparing SSD against Hard drive performance it really makes me cross when folk think comparing an array of SSD running on 3GBits/sec to hard drives running on 6GBits/second is somehow valid. In a paper from DELL (http://www.dell.com/downloads/global/products/pvaul/en/PowerEdge-PowerVaultH800-CacheCade-final.pdf) on increasing database performance using the DELL PERC H800 with Solid State Drives they compare four SSD drives connected at 3Gbits/sec against ten 10Krpm drives connected at 6Gbits [Tony slaps forehead while shouting DOH!]. It is true in the case of hard drives it probably doesn’t make much difference 3Gbit or 6Gbit because SAS and SATA are both end to end protocols rather than shared bus architecture like SCSI, so the hard drive doesn’t share bandwidth and probably can’t get near the 600MiBytes/second throughput that 6Gbit gives unless you are doing contiguous reads, in my own tests on a single 15Krpm SAS disk using IOMeter (8 worker threads, queue depth of 16 with a stripe size of 64KiB, an 8KiB transfer size on a drive formatted with an allocation size of 8KiB for a 100% sequential read test) I only get 347MiBytes per second sustained throughput at an average latency of 2.87ms per IO equating to 44.5K IOps, ok, if that was 3GBits it would be less – around 280MiBytes per second, oh, but wait a minute [...fingers tap desk] You’ll struggle to find in the commodity space an SSD that doesn’t have the SATA 3 (6GBits) interface, SSD’s are fast not only low latency and high IOps but they also offer a very large sustained transfer rate, consider the OCZ Agility 3 it so happens that in my masters dissertation I did the same test but on a difference box, I got 374MiBytes per second at an average latency of 2.67ms per IO equating to 47.9K IOps – cost of an 240GB Agility 3 is £174.24 (http://www.scan.co.uk/products/240gb-ocz-agility-3-ssd-25-sata-6gb-s-sandforce-2281-read-525mb-s-write-500mb-s-85k-iops), but that same drive set in a box connected with SATA 2 (3Gbits) would only yield around 280MiBytes per second thus losing almost 100MiBytes per second throughput and a ton of IOps too. So why the hell are “enterprise” vendors still only connecting SSD’s at 3GBits? Well, my conspiracy states that they have no interest in you moving to SSD because they’ll lose so much money, the argument that they use SATA 2 doesn’t wash, SATA 3 has been out for some time now and all the commodity stuff you buy uses it now. Consider the cost, not in terms of price per GB but price per IOps, SSD absolutely thrash Hard Drives on that, it was true that the opposite was also true that Hard Drives thrashed SSD’s on price per GB, but is that true now, I’m not so sure – a 300GByte 2.5” 15Krpm SAS drive costs £329.76 ex VAT (http://www.scan.co.uk/products/300gb-seagate-st9300653ss-savvio-15k3-25-hdd-sas-6gb-s-15000rpm-64mb-cache-27ms) which equates to £1.09 per GB compared to a 480GB OCZ Agility 3 costing £422.10 ex VAT (http://www.scan.co.uk/products/480gb-ocz-agility-3-ssd-25-sata-6gb-s-sandforce-2281-read-525mb-s-write-410mb-s-30k-iops) which equates to £0.88 per GB. Ok, I compared an “enterprise” hard drive with a “commodity” SSD, ok, so things get a little more complicated here, most “enterprise” SSD’s are SLC and most commodity are MLC, SLC gives more performance and wear, I’ll talk about that another day. For now though, don’t get sucked in by vendor marketing, SATA 2 (3Gbit) just doesn’t cut it, SSD need 6Gbit to breath and even that SSD’s are pushing. Alas, SSD’s are connected using SATA so all the controllers I’ve seen thus far from HP and DELL only do SATA 2 – deliberate? Well, I’ll let you decide on that one.

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  • Countdown of Top 10 Reasons to Never Ever Use a Pie Chart

    - by Tony Wolfram
      Pie charts are evil. They represent much of what is wrong with the poor design of many websites and software applications. They're also innefective, misleading, and innacurate. Using a pie chart as your graph of choice to visually display important statistics and information demonstrates either a lack of knowledge, laziness, or poor design skills. Figure 1: A floating, tilted, 3D pie chart with shadow trying (poorly)to show usage statistics within a graphics application.   Of course, pie charts in and of themselves are not evil. This blog is really about designers making poor decisions for all the wrong reasons. In order for a pie chart to appear on a web page, somebody chose it over the other alternatives, and probably thought they were doing the right thing. They weren't. Using a pie chart is almost always a bad design decision. Figure 2: Pie Chart from an Oracle Reports User Guide   A pie chart does not do the job of effectively displaying information in an elegant visual form.  Being circular, they use up too much space while not allowing their labels to line up. Bar charts, line charts, and tables do a much better job. Expert designers, statisticians, and business analysts have documented their many failings, and strongly urge software and report designers not to use them. It's obvious to them that the pie chart has too many inherent defects to ever be used effectively. Figure 3: Demonstration of how comparing data between multiple pie charts is difficult.   Yet pie charts are still used frequently in today's software applications, financial reports, and websites, often on the opening page as a symbol of how the data inside is represented. In an attempt to get a flashy colorful graphic to break up boring text, designers will often settle for a pie chart that looks like pac man, a colored spinning wheel, or a 3D floating alien space ship.     Figure 4: Best use of a pie chart I've found yet.   Why is the pie chart so popular? Through its constant use and iconic representation as the classic chart, the idea persists that it must be a good choice, since everyone else is still using it. Like a virus or an urban legend, no amount of vaccine or debunking will slow down the use of pie charts, which seem to be resistant to logic and common sense. Even the new iPad from Apple showcases the pie chart as one of its options.     Figure 5: Screen shot of new iPad showcasing pie charts. Regardless of the futility in trying to rid the planet of this often used poor design choice, I now present to you my top 10 reasons why you should never, ever user a pie chart again.    Number 10 - Pie Charts Just Don't Work When Comparing Data Number 9 - You Have A Better Option: The Sorted Horizontal Bar Chart Number 8 - The Pie Chart is Always Round Number 7 - Some Genius Will Make It 3D Number 6 - Legends and Labels are Hard to Align and Read Number 5 - Nobody Has Ever Made a Critical Decision Using a Pie Chart Number 4 - It Doesn't Scale Well to More Than 2 Items Number 3 - A Pie Chart Causes Distortions and Errors Number 2 - Everyone Else Uses Them: Debunking the "Urban Legend" of Pie Charts Number 1 - Pie Charts Make You Look Stupid and Lazy  

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  • Two Candidates + One Job = Two Different Outcomes

    - by david.talamelli
    Recruiters have always headhunted (sidenote: I do not like this word, in general I think the type of people who use the phrase “headhunting” are the ones who are trying to sound more important than what they likely are). Any serious Recruiter engages in direct recruiting activity, it is part and parcel of the business it is not something unique. With the uptake in Social Media the past 4-5 years, we have seen an increase in the number of Recruiters proactively reaching out to people about job opportunities. We have also seen this activity increase across all levels of hire, from help desk roles to C-Level Executives. While getting approached about a role can be a nice boost to a person’s ego, do not let it give you an inflated sense of entitlement. It is The way that people handle themselves during these calls and subsequent interviews will have a large impact on their potential to land that job. Last week I spoke to two very different candidates, both about the same position and both with very different outcomes. On paper, Candidate #1 looked fantastic; they ticked many of the boxes that we were looking for. The person is working at global IT company and working in a similar role as the one we were hiring for but not in as senior as the role we had. This role would have been the perfect step to getting involved in more complex work for the person. Candidate #2 had less polished IT experience, ticked some of the boxes we were looking for and on paper in comparison to Candidate #1 was not as close a fit as Candidate #1 was. It seemed like I was comparing apples and oranges. After speaking to both candidates it turns out I was comparing apples and oranges except the person better suited for our role was not the one I was expecting it would be. The first candidate on paper looked great – they had the experience we were looking for and appeared to be just right for the role, but after talking to them, they gave me the impression that they thought the world owed them. The impression I was left with was that they did not equate success with hard work, they seemed more interested in “what is in it for me”. Rather than having a proper conversation with me, I was often cut off and asked to hurry it up when explaining our business, what we are doing, etc... . This person seemed more interested in the job title and money than how rather than think about ways to make the role successful. Candidate #2 who had limited experience, made up for any perceived lack of experience and them some with a demonstrated motivation to succeed and do the things needed to make that happen. Candidate #2 made a great first impression, they did not seem afraid of hard work and demonstrated a “team player” attitude. In talking to them they kept me engaged, listened and asked thoughtful questions that made me think this is the type of person who creates their own luck and who would thrive in a place like Oracle. Skills, capabilities, experience and a good resume can certainly get your foot in the door, but the wrong attitude or approach to work can close those opportunities just as easily. On the other hand, hard work, effort and a genuine work ethic may help open those doors that would otherwise closed for you. A resume with all the credentials gets you in the front door but that is just the beginning of the process. It is not how we start the race that is important, it’s how things end that matter most.

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  • Consumer Oriented Search In Oracle Endeca Information Discovery - Part 2

    - by Bob Zurek
    As discussed in my last blog posting on this topic, Information Discovery, a core capability of the Oracle Endeca Information Discovery solution enables businesses to search, discover and navigate through a wide variety of big data including structured, unstructured and semi-structured data. With search as a core advanced capabilities of our product it is important to understand some of the key differences and capabilities in the underlying data store of Oracle Endeca Information Discovery and that is our Endeca Server. In the last post on this subject, we talked about Exploratory Search capabilities along with support for cascading relevance. Additional search capabilities in the Endeca Server, which differentiate from simple keyword based "search boxes" in other Information Discovery products also include: The Endeca Server Supports Set Search.  The Endeca Server is organized around set retrieval, which means that it looks at groups of results (all the documents that match a search), as well as the relationship of each individual result to the set. Other approaches only compute the relevance of a document by comparing the document to the search query – not by comparing the document to all the others. For example, a search for “U.S.” in another approach might match to the title of a document and get a high ranking. But what if it were a collection of government documents in which “U.S.” appeared in many titles, making that clue less meaningful? A set analysis would reveal this and be used to adjust relevance accordingly. The Endeca Server Supports Second-Order Relvance. Unlike simple search interfaces in traditional BI tools, which provide limited relevance ranking, such as a list of results based on key word matching, Endeca enables users to determine the most salient terms to divide up the result. Determining this second-order relevance is the key to providing effective guidance. Support for Queries and Filters. Search is the most common query type, but hardly complete, and users need to express a wide range of queries. Oracle Endeca Information Discovery also includes navigation, interactive visualizations, analytics, range filters, geospatial filters, and other query types that are more commonly associated with BI tools. Unlike other approaches, these queries operate across structured, semi-structured and unstructured content stored in the Endeca Server. Furthermore, this set is easily extensible because the core engine allows for pluggable features to be added. Like a search engine, queries are answered with a results list, ranked to put the most likely matches first. Unlike “black box” relevance solutions, which generalize one strategy for everyone, we believe that optimal relevance strategies vary across domains. Therefore, it provides line-of-business owners with a set of relevance modules that let them tune the best results based on their content. The Endeca Server query result sets are summarized, which gives users guidance on how to refine and explore further. Summaries include Guided Navigation® (a form of faceted search), maps, charts, graphs, tag clouds, concept clusters, and clarification dialogs. Users don’t explicitly ask for these summaries; Oracle Endeca Information Discovery analytic applications provide the right ones, based on configurable controls and rules. For example, the analytic application might guide a procurement agent filtering for in-stock parts by visualizing the results on a map and calculating their average fulfillment time. Furthermore, the user can interact with summaries and filters without resorting to writing complex SQL queries. The user can simply just click to add filters. Within Oracle Endeca Information Discovery, all parts of the summaries are clickable and searchable. We are living in a search driven society where business users really seem to enjoy entering information into a search box. We do this everyday as consumers and therefore, we have gotten used to looking for that box. However, the key to getting the right results is to guide that user in a way that provides additional Discovery, beyond what they may have anticipated. This is why these important and advanced features of search inside the Endeca Server have been so important. They have helped to guide our great customers to success. 

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  • Fastest way to remove non-numeric characters from a VARCHAR in SQL Server

    - by Dan Herbert
    I'm writing an import utility that is using phone numbers as a unique key within the import. I need to check that the phone number does not already exist in my DB. The problem is that phone numbers in the DB could have things like dashes and parenthesis and possibly other things. I wrote a function to remove these things, the problem is that it is slow and with thousands of records in my DB and thousands of records to import at once, this process can be unacceptably slow. I've already made the phone number column an index. I tried using the script from this post: http://stackoverflow.com/questions/52315/t-sql-trim-nbsp-and-other-non-alphanumeric-characters But that didn't speed it up any. Is there a faster way to remove non-numeric characters? Something that can perform well when 10,000 to 100,000 records have to be compared. Whatever is done needs to perform fast. Update Given what people responded with, I think I'm going to have to clean the fields before I run the import utility. To answer the question of what I'm writing the import utility in, it is a C# app. I'm comparing BIGINT to BIGINT now, with no need to alter DB data and I'm still taking a performance hit with a very small set of data (about 2000 records). Could comparing BIGINT to BIGINT be slowing things down? I've optimized the code side of my app as much as I can (removed regexes, removed unneccessary DB calls). Although I can't isolate SQL as the source of the problem anymore, I still feel like it is.

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  • What's the recommended implemenation for hashing OLE Variants?

    - by Barry Kelly
    OLE Variants, as used by older versions of Visual Basic and pervasively in COM Automation, can store lots of different types: basic types like integers and floats, more complicated types like strings and arrays, and all the way up to IDispatch implementations and pointers in the form of ByRef variants. Variants are also weakly typed: they convert the value to another type without warning depending on which operator you apply and what the current types are of the values passed to the operator. For example, comparing two variants, one containing the integer 1 and another containing the string "1", for equality will return True. So assuming that I'm working with variants at the underlying data level (e.g. VARIANT in C++ or TVarData in Delphi - i.e. the big union of different possible values), how should I hash variants consistently so that they obey the right rules? Rules: Variants that hash unequally should compare as unequal, both in sorting and direct equality Variants that compare as equal for both sorting and direct equality should hash as equal It's OK if I have to use different sorting and direct comparison rules in order to make the hashing fit. The way I'm currently working is I'm normalizing the variants to strings (if they fit), and treating them as strings, otherwise I'm working with the variant data as if it was an opaque blob, and hashing and comparing its raw bytes. That has some limitations, of course: numbers 1..10 sort as [1, 10, 2, ... 9] etc. This is mildly annoying, but it is consistent and it is very little work. However, I do wonder if there is an accepted practice for this problem.

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  • Objective-C: fetchManagedObjectsForEntity problem

    - by Meko
    Hi.I am trying to get value from CoreData entity name Person with predicate and then comparing with new data in dictionary.But it it returns every time 0 .And it creates about 5 person with same name. NSPredicate *predicate = [NSPredicate predicateWithFormat:@"userName == %@",[flickr usernameForUserID:@"owner"]]; peopleList = (NSMutableArray *)[flickr fetchManagedObjectsForEntity:@"Person" withPredicate:predicate]; NSEnumerator *enumerator = [peopleList objectEnumerator]; Person *person; BOOL exists = FALSE; while (person = [enumerator nextObject]) { NSLog(@" Person is: %@ ", person.userName); NSLog(@"Person ID IS %@",person.userID); NSLog(@"Dict ID is %@",[dict objectForKey:@"owner"]); if([person.userID isEqualToString:[dict objectForKey:@"owner"]]) { exists = TRUE; NSLog(@"-- Person Exists : %@--", person.userName); [newPhoto setPerson:person]; } } Here peopleList returns 0 and the enumerator also 0 and it does not use if and not comparing.In my entity I have Person and Photo entities.In Person I have userName and userID attributes and also one-to many relationship with Photo entity. I think problem in predicate but i cant figure out it .

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  • Comparable and Comparator contract with regards to null

    - by polygenelubricants
    Comparable contract specifies that e.compareTo(null) must throw NullPointerException. From the API: Note that null is not an instance of any class, and e.compareTo(null) should throw a NullPointerException even though e.equals(null) returns false. On the other hand, Comparator API mentions nothing about what needs to happen when comparing null. Consider the following attempt of a generic method that takes a Comparable, and return a Comparator for it that puts null as the minimum element. static <T extends Comparable<? super T>> Comparator<T> nullComparableComparator() { return new Comparator<T>() { @Override public int compare(T el1, T el2) { return el1 == null ? -1 : el2 == null ? +1 : el1.compareTo(el2); } }; } This allows us to do the following: List<Integer> numbers = new ArrayList<Integer>( Arrays.asList(3, 2, 1, null, null, 0) ); Comparator<Integer> numbersComp = nullComparableComparator(); Collections.sort(numbers, numbersComp); System.out.println(numbers); // "[null, null, 0, 1, 2, 3]" List<String> names = new ArrayList<String>( Arrays.asList("Bob", null, "Alice", "Carol") ); Comparator<String> namesComp = nullComparableComparator(); Collections.sort(names, namesComp); System.out.println(names); // "[null, Alice, Bob, Carol]" So the questions are: Is this an acceptable use of a Comparator, or is it violating an unwritten rule regarding comparing null and throwing NullPointerException? Is it ever a good idea to even have to sort a List containing null elements, or is that a sure sign of a design error?

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  • Understanding CSRF - Simple Question

    - by byronh
    I know this might make me seem like an idiot, I've read everything there is to read about CSRF and I still don't understand how using a 'challenge token' would add any sort of prevention. Please help me clarify the basic concept, none of the articles and posts here on SO I read seemed to really explicitly state what value you're comparing with what. From OWASP: In general, developers need only generate this token once for the current session. After initial generation of this token, the value is stored in the session and is utilized for each subsequent request until the session expires. If I understand the process correctly, this is what happens. I log in at http://example.com and a session/cookie is created containing this random token. Then, every form includes a hidden input also containing this random value from the session which is compared with the session/cookie upon form submission. But what does that accomplish? Aren't you just taking session data, putting it in the page, and then comparing it with the exact same session data? Seems like circular reasoning. These articles keep talking about following the "same-origin policy" but that makes no sense, because all CSRF attacks ARE of the same origin as the user, just tricking the user into doing actions he/she didn't intend. Is there any alternative other than appending the token to every single URL as a query string? Seems very ugly and impractical, and makes bookmarking harder for the user.

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  • What's the recommended implementation for hashing OLE Variants?

    - by Barry Kelly
    OLE Variants, as used by older versions of Visual Basic and pervasively in COM Automation, can store lots of different types: basic types like integers and floats, more complicated types like strings and arrays, and all the way up to IDispatch implementations and pointers in the form of ByRef variants. Variants are also weakly typed: they convert the value to another type without warning depending on which operator you apply and what the current types are of the values passed to the operator. For example, comparing two variants, one containing the integer 1 and another containing the string "1", for equality will return True. So assuming that I'm working with variants at the underlying data level (e.g. VARIANT in C++ or TVarData in Delphi - i.e. the big union of different possible values), how should I hash variants consistently so that they obey the right rules? Rules: Variants that hash unequally should compare as unequal, both in sorting and direct equality Variants that compare as equal for both sorting and direct equality should hash as equal It's OK if I have to use different sorting and direct comparison rules in order to make the hashing fit. The way I'm currently working is I'm normalizing the variants to strings (if they fit), and treating them as strings, otherwise I'm working with the variant data as if it was an opaque blob, and hashing and comparing its raw bytes. That has some limitations, of course: numbers 1..10 sort as [1, 10, 2, ... 9] etc. This is mildly annoying, but it is consistent and it is very little work. However, I do wonder if there is an accepted practice for this problem.

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  • Good way to identify similar images?

    - by Nick
    I've developed a simple and fast algorithm in PHP to compare images for similarity. Its fast (~40 per second for 800x600 images) to hash and a unoptimised search algorithm can go through 3,000 images in 22 mins comparing each one against the others (3/sec). The basic overview is you get a image, rescale it to 8x8 and then convert those pixels for HSV. The Hue, Saturation and Value are then truncated to 4 bits and it becomes one big hex string. Comparing images basically walks along two strings, and then adds the differences it finds. If the total number is below 64 then its the same image. Different images are usually around 600 - 800. Below 20 and extremely similar. Are there any improvements upon this model I can use? I havent looked at how relevant the different components (hue, saturation and value) are to the comparison. Hue is probably quite important but the others? To speed up searches I could probably split the 4 bits from each part in half, and put the most significant bits first so if they fail the check then the lsb doesnt need to be checked at all. I dont know a efficient way to store bits like that yet still allow them to be searched and compared easily. I've been using a dataset of 3,000 photos (mostly unique) and there havent been any false positives. Its completely immune to resizes and fairly resistant to brightness and contrast changes.

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  • Load some data from database and hide it somewhere in a web page

    - by kwokwai
    Hi all, I am trying to load some data (which may be up to a few thousands words) from the database, and store the data somewhere in a html web page for comparing the data input by users. I am thinking to load the data to a Textarea under Div tag and hide the the data: <Div id="reference" style="Display:none;"> <textarea rows="2" cols="20" id="database"> html, htm, php, asp, jsp, aspx, ctp, thtml, xml, xsl... </textarea> </Div> <table border=0 width="100%"> <tr> <td>Username</td> <td> <div id="username"> <input type="text" name="data" id="data"> </div> </td> </tr> </table> <script> $(document).ready(function(){ //comparing the data loaded from database with the user's input if($("#data").val()==$("#database").val()) {alert("error");} }); </script> I am not sure if this is the best way to do it, so could you give me some advice and suggest your methods please.

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  • Efficient and accurate way to compact and compare Python lists?

    - by daveslab
    Hi folks, I'm trying to a somewhat sophisticated diff between individual rows in two CSV files. I need to ensure that a row from one file does not appear in the other file, but I am given no guarantee of the order of the rows in either file. As a starting point, I've been trying to compare the hashes of the string representations of the rows (i.e. Python lists). For example: import csv hashes = [] for row in csv.reader(open('old.csv','rb')): hashes.append( hash(str(row)) ) for row in csv.reader(open('new.csv','rb')): if hash(str(row)) not in hashes: print 'Not found' But this is failing miserably. I am constrained by artificially imposed memory limits that I cannot change, and thusly I went with the hashes instead of storing and comparing the lists directly. Some of the files I am comparing can be hundreds of megabytes in size. Any ideas for a way to accurately compress Python lists so that they can be compared in terms of simple equality to other lists? I.e. a hashing system that actually works? Bonus points: why didn't the above method work?

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