Search results
Results from the WOW.Com Content Network
The speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development. Big data is often available in real-time. Compared to small data, big data is produced more continually. Two kinds of velocity related to big data are the frequency of generation and the frequency of handling ...
Paimon: unified lake storage to build dynamic tables for both stream and batch processing with big data compute engines, supporting high-speed data ingestion and real-time data query; Pegasus: distributed key-value storage system which is designed to be simple, horizontally scalable, strongly consistent and high-performance
Massive Online Analysis (MOA): a real-time big data stream mining with concept drift tool in the Java programming language. MEPX: cross-platform tool for regression and classification problems based on a Genetic Programming variant. mlpack: a collection of ready-to-use machine learning algorithms written in the C++ language.
This is a comprehensive list of volunteer computing projects, which are a type of distributed computing where volunteers donate computing time to specific causes. The donated computing power comes from idle CPUs and GPUs in personal computers, video game consoles, [1] and Android devices.
Project Euler (named after Leonhard Euler) is a website dedicated to a series of computational problems intended to be solved with computer programs. [ 1 ] [ 2 ] The project attracts graduates and students interested in mathematics and computer programming .
The data is collected by crowdsourcing. In a new project OpenSeaMap collect shallow water depths worldwide for making bathimetric charts. OpenSignal is a project to independently map cell phone carrier coverage and performance. All data is collected from a smartphone application that has been downloaded over 3.5m times worldwide.
In 1966, Scientific American featured Project MAC in the September thematic issue devoted to computer science, [5] that was later published in book form. At the time, the system was described as having approximately 100 TTY terminals, mostly on campus but with a few in private homes. Only 30 users could be logged in at the same time.
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...