These graphics were updated on Aug. 20 to reflect the new maps passed by the Texas House. Texas Republicans adopted a redrawn congressional map that they hope will result in a gain of five seats in ...

Abstract: In this paper, we discuss security issues relating to inadequate authentication in MapReduce applications. We examine MapReduce applications deployed in the cloud, as this environment ...

This project implements a simple MapReduce algorithm in Rust. It reads a set of strings and counts the occurrences of each word, demonstrating basic parallel processing using threads.

Deep learning (DL) techniques, more specifically Convolutional Neural Networks (CNNs), have become increasingly popular in advancing the field of data science and have had great successes in a wide ...

This repository contains an implementation of a map-reduce job for Hazelcast, created as part of a Distributed Systems course @ ITBA. The code is designed to facilitate distributed processing of large ...

Reporting and analysis drives businesses in making the best possible decisions. The source of all these decisions is the data. There are two types of data: structured and unstructured. Most recently, ...

In this presentation, Markus Deshon describes MapReduce, a programming model for processing large data sets with a parallel, distributed algorithm. In this presentation, Markus Deshon describes ...

In this video, the Rafael Coss, manager Big Data Enablement for IBM describes how MapReduce works in plain English. MapReduce is a framework for processing embarrassingly parallel problems across huge ...