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Development Team Blog

  1. Configuring HTTP Compression for DataFlex WebApps

    A standard feature of the Internet Information Server is HTTP compression. This module is available to optimize the performance of web applications by compressing HTTP responses that are sent to the client. The goal is to decrease the size of the responses to allow faster network transmission. Of course this has the side effect that the CPU usage increases on the server (and on the client). So we are trading CPU usage against bandwidth here. This means that HTTP compression doesn't always make your ...

    Updated 17-Feb-2014 at 03:26 AM by Harm Wibier

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  2. Diagnosing Studio and compile time performance problems

    by , 22-Mar-2010 at 08:00 AM (Development Team Blog)
    When it comes to performance working in the Studio as a developer, as opposed to running the application, there are generally two performance critical areas. The first one is the Studio Parser, which is the foundation for CodeSense, Visual Modeling, Go-To-Definition and more. The second performance critical area is when compiling. Unnecessarily long and slow compile times can make for a very frustrating experience working with the Visual DataFlex Studio.

    Sometimes you may not even ...

    Updated 17-Mar-2010 at 05:25 PM by Sonny Falk

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  3. Arrays & Structs in-depth Part VI

    by , 25-Sep-2009 at 08:00 AM (Development Team Blog)
    In [URL="http://support.dataaccess.com/forums/blog.php?b=39"]Part V[/URL] we realized that there's a very common mistake one can make when working with array properties and trying to write code designed after the old Array class interface, which can cause performance issues. When making changes to array properties, and you're concerned about performance, the key thing is to coalesce/combine all changes into one transaction. Remember that a [I]Get[/I] property is always super-fast. There's ...
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  4. Arrays & Structs in-depth Part V

    by , 23-Sep-2009 at 08:00 AM (Development Team Blog)
    In [URL="http://support.dataaccess.com/forums/blog.php?b=36"]Part IV[/URL] we discovered that passing very large arrays around via parameters and return values is usually very fast thanks to the built-in copy-on-write optimization. We also discovered that if you modify the array, you incur a copy operation and lose the benefit of the copy-on-write optimization. It may come as no surprise then that the fewer copy operations you perform, the better performance you get.

    Up ...
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