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It is possible to import C functions directly for use within the kdb process by dynamically loading modules. Below we will look at an example of compiling, importing and executing C functions on windows for kdb 3.0+.We will be adding two functions myavg, mysum which providemoving average and moving sum functions respectively. Yes, kdb does already mavg but read till the end and I think you will find the performance comparison interesting. The Interfacing Kdb with C and Extending with C page on the code KX website documents the C API extensively, we will give details for the core parts used in our example but you will want to read those pages thoroughly at a later stage. Download Example C Code Example of kdb C DLL Compilation Compiling a C DLL on Windows The steps to compile and load a C DLL are as follows: Download kdb C example code. It contains the following files: The latest version of header files provided by kx. k.h and and q.lib for windows 64. mymoving.c - C code that defines our actual functions mymoving.def - Declares the functions we will be providing Compile the code using comprun.bat this requires MS Visual Studio 2010 installed It uses "C:\Program Files (x86)\Microsoft Visual Studio 10.0\VC\vcvarsall.bat" amd64 to set the required environment variables for our compilation. Runs the command line compiler: cl /LD /DKXVER=3 mymoving.c mymoving.def q.lib Launch q running the script load-functions.q so that our DLL functions are loaded and defined. Now within q we can call our mytop, myavg functions. comprun.bat mymoving.c Loading a module load-functions.q In this q script we import functions from our DLL and assign them to variable names: mymoving is the name of our DLL which is in the current directory, you could place this in c:/q/w64 or specify a full path. 2: is the kdb function for loading native code. The right hand side e.g. (`mysum;2) specifies a function that exists and the number of arguments it accepts. Executing our C Code As you can see we get the same results using either our own function or kdb's builtin mavg. However our function is 46x quicker (users on linux report a much smaller 3x speed difference). There are a number of reasons why this is (nulls and partitioned data) but that's a topic for another post. If your having problems compiling or want advice either contact us or ask in our forums. We also provide kdb consulting services and have particular expertise in writing kdb+tick subscribers and feedhandlers. Related Tutorials

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Home › Forums › kdb+ › How to download attachments from *.eml file Posted by on April 5, 2023 at 12:00 am How to download attachments from *.eml file using kdb code? 4 Replies Kdb+ can parse binary files as nicely shown at the recent KX meetup by formats can get complicated though so this can be a lot of work.If I wanted to do this task quickly I would either:a) Use a system call to a command line tool to extract the files on disk and then read them in from there.Writing them to current directory or using mktemp command to write in /var/tmpb) Wrap some exiting python code using EmbedPy to extract the email and attachments to JSON and read in to kdb+ this way.Similar to how I did for XML with discussions on the topic in Python world:(Note: I have not tested these for functionality or safety) Hi KPC,Looking at an example .eml file here. If you wanted to parse the attachments purely in KDB/Q without the use of Python libs (although I suggest using Python libs) I’d suggest something along the lines of:read0 the *.eml file. Depending on the contents and if you want to interpret new lines literally or not you may find “c”$read1 a more appropriate solutionUse regex to locate the contents of the attachment, content type and encoding type (from the example looks to default to b64)Decode the body of the attachment – for b64 decoding in KDB/Q it looks like this is a solutionb64Decode:{c:sum x=”=”;neg[c]_”c”$raze 256 vs’64 sv’0N 4#.Q.b6?x}?Post-process the data further into Q objects if it’s suitable. E.g. if the filetype is a json you may want to utilise the .j.k json deserialiser for QThe solution provided should be the preferred solution with embedPy. Adding to this there is a PyPi

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What is Kona?Kona is the open-source implementation of the k3 programming language. k is a synthesis of APL and LISP. Although many of the capabilities come from APL, the fundamental data construct is quite different. In APL the construct is a multi-dimensional matrix-like array, where the dimension of the array can range from 0 to some maximum (often 9). In k, like LISP, the fundamental data construct is a list. Also, like LISP, the k language is ASCII-based, so you don't need a special keyboard.For many people, k was the preferred APL dialect. When it was available, it tended to be popular with investment bankers, the performance obsessed, and analysts dealing with lots of data. It is a demanding language.k was originally designed by Arthur Whitney and Kx Systems. Praise for k should be taken to refer to Kx's k. Kx sells a popular database called KDB+. People can and do create networked trading platforms in hours. If your business needs production support, you can evaluate KDB+ prior to purchasing from Kx, or possibly speak with Kx consulting partner First Derivatives. The 32-bit version of KDB+ is available for free.Kx's KDB+ uses the Q language, and is built on top of k4. Kx used to sell a database called KDB, which used the KSQL language, and was built on top of k3. Earlier, Kx sold k2 as its primary product. Before k2, UBS had a 5-year exclusive license to k1. To the confusion of all, these terms are used interchangeably. Kx's k3, k2 and k1 are basically no longer available. While you get k4 with KDB+, k4 is proprietary to Kx and no documentation is available. Kona is a reimplementation that targets k3 (which stopped being available about 20 years ago). Kona is unaffiliated with Kx.To get perspective on the various incarnations see note on the unusual style of C code: It attempts to replicate the style of Arthur Whitney. A striking original example is contained in file There are 2 versions of the buddy memory allocation system. The first is in 11 lines written by Whitney. The second is in well documented traditional C (almost 750 lines).Mailing Listskona-user is about using the Kona programming language.kona-dev is about developing the Kona language itself.InstallationWindowsYou can find an executable version of Kona here.Download k.exe. Use Windows "Explorer" to move k.exe from the "Download" directory to another directory ... or not. Double click

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Arrowkdb IntroductionThis interface allows kdb+ to users read and write Apache Arrow data stored in:Apache Parquet file formatArrow IPC record batch file formatArrow IPC record batch stream formatThis is part of the Fusion for kdb+ interface collection.New to kdb+ ?Kdb+ is the world's fastest time-series database, optimized for ingesting, analyzing and storing massive amounts of structured data. To get started with kdb+, please visit for downloads and developer information. For general information, visit to Apache Arrow?Apache Arrow is a software development platform for building high performance applications that process and transport large data sets. It is designed to both improve the performance of analytical algorithms and the efficiency of moving data from one system (or programming language to another).A critical component of Apache Arrow is its in-memory columnar format, a standardized, language-agnostic specification for representing structured, table-like datasets in-memory. This data format has a rich data type system (included nested data types) designed to support the needs of analytic database systems, data frame libraries, and more.What is the difference between Apache Arrow and Apache Parquet?Parquet is a storage format designed for maximum space efficiency, using advanced compression and encoding techniques. It is ideal when wanting to minimize disk usage while storing gigabytes of data, or perhaps more. This efficiency comes at the cost of relatively expensive reading into memory, as Parquet data cannot be directly operated on but must be decoded in large chunks.Conversely, Arrow is an in-memory format meant for direct and efficient use for computational purposes. Arrow data is not compressed but laid out in natural format for the CPU, so that data can be accessed at arbitrary places at full speed. Therefore, Arrow and Parquet complement each other with Arrow being used as the in-memory data structure for deserializing Parquet data.InstallationRequirementskdb+ ≥ 3.5 64-bit (Linux/MacOS/Windows)Apache Arrow ≥ 9.0.0 (or ≥ 6.0.0 if building arrowkdb from source)C++14 or laterCMake ≥ 3.1.3⚠️ If using the packaged version of arrowkdb you should install version 9.0.0 of Apache ArrowThird-party library installationLinuxFollow the instructions here to install libarrow-dev and libparquet-dev from Apache's APT or Yum repositories.Note: If using the packaged version of arrowkdb you should install version 9.0.0 of both:sudo apt install -y -V libarrow-dev=9.0.0-1sudo apt install -y -V libparquet-dev=9.0.0-1macOSFollow the instructions here to install apache-arrow using Homebrew.WindowsOn Windows it is necessary to build Arrow from source. Full details are provided here but the basic steps are as follows.From a Visual Studio command prompt, clone the Arrow source from github: git clone cd arrow">C:\Git> git clone cd arrowSwitch to the 9.0.0 tag: git checkout refs/tags/apache-arrow-9.0.0 --C:\Git> cd cpp">C:\Git\arrow> git checkout refs/tags/apache-arrow-9.0.0 --C:\Git> cd cppCreate an install directory and set an environment variable to this directory (substituting the correct absolute path as appropriate). This environment variable is used again later when building arrowkdb: mkdir installC:\Git\arrow\cpp> set ARROW_INSTALL=C:\Git\arrow\cpp\install">C:\Git\arrow\cpp> mkdir installC:\Git\arrow\cpp> set ARROW_INSTALL=C:\Git\arrow\cpp\installCreate the CMake build directory and generate the build files (this will default to using the Visual Studio CMake generator when run from a VS command prompt): mkdir buildC:\Git\arrow\cpp> cd buildC:\Git\arrow\cpp\build> cmake ... Kuiz KDB - Kuiz Klik Dengan Bijak - KDB - KDB! - KDB: Match Up! - CARI PADANAN KDB - KDB - Padankan KDB - KDB Maze - Kuiz KDB - CROSSWORD PUZZLE KDB