TITLE: SU(PE)RREAL Director: Li-Qun Zhao SuperReal is about the manipulation of the mass information in the Big Data Era. Due to the development of multi-media technologies, everyone has submerged in the data ocean. Data could be generated by anything surround us. Instead of generating forms and effects, the key of SuperReal is, how we can parameterize the

Realtime Data Management Platform

The next level of this prototype will stand upon three primary pillars: 1. Simulation environment: How to create an easy to assemble & reproducible simulation environment using minimal hardware to create engagement models for our audience? ShopNext v2.0 will be about real people generating real events using real objects! 2. Reusability: How to ensure the nod

Node.js Levenshtein distance, efficient for big data.

This group project of 4 members is delivered as part of my Masters in Big Data Science (MSc BDS) Program Module named “Digital Media and Social Network” in Queen Mary University of London (QMUL), London, United Kingdom. This project covers the network analysis covering 4 different problem statements and use cases using python NetworkX package, Gephi network

hadoop-projects IBM stock project Get IBM stock dataset Clean the dataset Load dataset on the HDFS Build MapReduce program Process/ Analyse result Hadoop set up Run single node Hadoop cluster /usr/local/Celler/hadoop Check : https://www.slideshare.net/SunilkumarMohanty3/install-apache-hadoop-on-mac-os-sierra-76275019 http://zhongyaonan.com/hadoop-tutorial

Applied spatial statistics to spatio-temporal big data to identify statistically significant spatial hot spots on a 4-node cluster. (Java, Hadoop Distributed File System (HDFS), Apache Spark)

A demonstration of the implementation of a distributed columnar NoSQL key-value pair based datastore for big data. With support for multiple nodes, node management, centralized control, replica management and fault tolerance..

Configured Hadoop in multi-cluster node in AWS cloud; analyzed the 22 years of Airline data i.e 130 million flight records (implemented in MapReduce) and found interesting facts on category wise performance, the probability of airline being on schedule, most common reason for cancellation

Datasets of cognitive adhoc network with pairs of senders-receivers nodes. The data can be used for generating empirical models for spectrum awareness in networks and also for validating analytical models. The system model is as define in https://ieeexplore.ieee.org/document/8249073/

Graph databases are widely used for big data problems and scenarios which are really hard to be presented using relational database. How to represent and be able to query time-varying graph database has been the major challenge in implementing graph databases. In this project, we designed, implemented and tested an improved time-varying data structure for ne

Eleven thousand years ago with the emergence of the system of bartering the first men and women started exchanging goods.Back then people would only trade with other people within their tribe that they knew and trusted ,but as years went by and the population started growing exponentially it became harder and harder to personally know and trust everyone more

Repositório para o trabalho de Arquitetura de Software para Big Data

A collection of scripts to gather data about nodes on a mesh

A virtual HyperLogLog is a highly compact virtual maximum likelihood Sketch for counting big network data for Node.js

In this course, you’ll use Python to refactor an existing application that was originally built using Node.js. The app, called Just Tech News, is a website where users can post, upvote, and comment on links to news articles. Instead of using Node.js as the back-end language and Handlebars.js as the templating engine, you’ll use Python to create the app and t

MapReduce is a programming model that involves two steps. The first, the map step, takes an input set I and groups it into N equivalence classes I0, I1, I2, ..., IN-1. I can be thought of as a set of tuples <key, data>, and the function map maps I into the equivalence classes based on the value of key. In the second reduce step, the equivalence classes are p

Profit with JavaScript is a project-driven course of JavaScript language along with its related libraries and technologies . This course is specifically designed for people who want through the development and programming applications, web-based, etc. earn the income . In addition, this course perfectly suits beginners and designed all the necessary skills t

BigData Visualization with Spark Node.JS and MongoDB

stock data pipeline, Kafka+Cassandra+Spark+Node.js