Multidimensional data is important for maps, because you are always interested in things within a range defined in two or three dimensions (though mddf can do N dimensions). Many popular methods of storing map data are not memory efficient, and you must load the entire dataset into RAM or a specialized heavy database engine before it can be used. mddf arranges data more sensibly, so it's actually possible to seek into the file, reading only a small segment, and pull out a collection of nearby points. This means map programs could load fast, work with massive maps and run on tiny devices.There is nothing in mddf that is specifically about maps, but that is the use case that motivates this work.
multi-dimensional database proximity nearest neighbors kd-tree b-tree kdb bkdQ interfacing with Node.js. Supports decompression. Can deserialize all q data types (including guid) to JavaScript. Can serialize all JavaScript data types to q. q has more data types than JavaScript. Therefore you need to know how types are converted.
kdb qlang q kx kdb+ kdb+tick interfacingOpenTick is a fast tick database for financial timeseries data, built on FoundationDB with simplified SQL layer. You need to use Go >=1.11 which has module support.
foundationdb kdb tick-data time-series-database sql cassandra-database market-dataAllows the kdb+ interpreter to manipulate Python objects and call Python functions. Part of the Fusion for kdb+ interface collection. Please direct any questions to ai@kx.com.
q kdbYou are welcome to download and use this code according to the terms of the licence. Instead, download code and subject it to the version control and regression testing you use for your application.
kdb kdb-tickPyQ brings the Python programming language to the kdb+ database. Part of the Fusion for kdb+ interface collection. It allows developers to integrate Python and q codes seamlessly in one application. This is achieved by bringing the Python and q interpreters into the same process so that code written in either of the languages operates on the same data. In PyQ, Python and q objects live in the same memory space and share the same data.
kdb databasePoetiq is a backtesting and algorithmic trading engine built in kdb+/Q. For testing and simulation use the buildhdb.q script to create a HDB equitysim with simulated equity data.
q kdb algorithmic-trading trading-simulator trading-platform backtester tradingqfactom is a kdb+ wrapper library designed to interact with the Factom blockchain via the factomd client (factomd) and wallet (factom-walletd) REST APIs. The library allows records, in the form of kdb+ tables, lists etc, to be easily secured on the Factom blockchain through the use of simple q function. Entries made to Factom chains can serve as a Proof of Existence, enabling cryptographically secure audit trails to be constructed. Data stored on existing Factom chains, like those used to hold Stock market prices, can also be easily extracted and coverted to kdb+ table format, see example. Combining the speed and scalability of kdb+, with the security and scalability of Factom, enables millions of records to be secured quickly and safely.
kdb factom factom-blockchain qfactom bitcoin anchoring immutability factoids bitcoin-blockchain kdb-library chain scalability iot iot-device securing factom-walletd factomd entrycreditsSource files for "Fun Q: A Functional Introduction to Machine Learning in Q"
kdb q machine-learningq-mode is a major mode for editing q (the language written by Kx Systems) in Emacs. If you load ess-mode, it will attempt to associate the .q extension with S-mode. To stop this, add the following lines to your initialization file.
kdb q emacsClone this project and start q with either of the following commands to see q load and analyze either 'trade and sales' or 'best bid and offer' data. All six data sets are downloaded, but only one is loaded. Change the file saved in variable f to load a different data set.
kdb q quantitative-financeThis project contains the source files for "Q Tips: Fast, Scalable and Maintainable Kdb+". Q Tips can be purchased on Amazon. A Kindle version is also available. Books may be purchased in quantity and/or special sales by contacting the publisher, Vector Sigma. Read a review by Yang Guo published by Vector Magazine.
kdb qPlease make sure you use the csv files inside the cvs_files/ directory and point to the right path inside your q code.
quantitative-trading neural-networks deep-learning random-forest support-vector-machines kdb kxkdb is a small pluggable IRC Bot framework utilizing the circuits Python Application Framework. kdb was one of the first "test" applications written in circuits and is still maintained and kept up-to-date with new features and changes in circuits.
kdb irc bot circuits pluginskdb+ bindings for Rust. Originally forked from and substantially based on the Krust cargo package by adwhit via robsmith11. These bindings enable Rust to be used as inside Q to add additional functionality. More generally they also enable Rust to communicate with kdb+ in a memory-safe way.
database kdb ffi-bindings
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