Results 21 to 30 of about 9,135 (230)

On the Computational Complexity of MapReduce [PDF]

, 2015
In this paper we study MapReduce computations from a complexity-theoretic perspective. First, we formulate a uniform version of the MRC model of Karloff et al. (2010). We then show that the class of regular languages, and moreover all of sublogarithmic space, lies in constant round MRC. This result also applies to the MPC model of Andoni et al. (2014).
Fish, Benjamin, Kun, Jeremy, Lelkes, Ádám, Reyzin, Lev, Turán, György   +4 more
openaire   +4 more sources

Real-world evidence in the cloud: Tutorial on developing an end-to-end data and analytics pipeline using Amazon Web Services resources. [PDF]

Clin Transl Sci
Abstract In the rapidly evolving landscape of healthcare and drug development, the ability to efficiently collect, process, and analyze large volumes of real‐world data (RWD) is critical for advancing drug development. This article provides a blueprint for establishing an end‐to‐end data and analytics pipeline in a cloud‐based environment. The pipeline
Anderson W, Bhatnagar R, Scollick K, Schito M, Walls R, Podichetty JT.   +5 more
europepmc   +2 more sources

Oppositional Cuckoo Search Optimization based Clustering with Classification Model for Big Data Analytics in Healthcare Environment

Journal of Applied Science and Engineering, 2022
Big data in healthcare defines a massive quantity of healthcare data accumulated from massive sources like electronic health records (EHR), medical imaging, genomic sequence, pharmacological research, wearable, medical gadgets, etc.
T. Gayathri, D. Lalitha Bhaskari
doaj   +1 more source

REST-MapReduce: An Integrated Interface but Differentiated Service

Journal of Applied Mathematics, 2014
With the fast deployment of cloud computing, MapReduce architectures are becoming the major technologies for mobile cloud computing. The concept of MapReduce was first introduced as a novel programming model and implementation for a large set of ...
Jong-Hyuk Park, Hwa-Young Jeong, Young-Sik Jeong, Min Choi   +3 more
doaj   +1 more source

XRepo 2.0: a Big Data Information System for Education in Prognostics and Health Management

International Journal of Prognostics and Health Management, 2021
Within Industry 4.0, Prognostics and Health Management (PHM) holds great potential due to its ability to bring deep insights into the current state of manufacturing equipment.
Nestor Romero, Rafael Medrano, Kelly Garces, David Sanchez-Londono, Giacomo Barbieri   +4 more
doaj   +1 more source

Social content matching in MapReduce [PDF]

Proceedings of the VLDB Endowment, 2011
Matching problems are ubiquitous. They occur in economic markets, labor markets, internet advertising, and elsewhere. In this paper we focus on an application of matching for social media. Our goal is to distribute content from information suppliers to information consumers.
Gionis A., Sozio M., De Francisci M. G.
openaire   +6 more sources

On using MapReduce to scale algorithms for Big Data analytics: a case study

Journal of Big Data, 2019
Introduction Many data analytics algorithms are originally designed for in-memory data. Parallel and distributed computing is a natural first remedy to scale these algorithms to “Big algorithms” for large-scale data.
Phongphun Kijsanayothin, Gantaphon Chalumporn, Rattikorn Hewett   +2 more
doaj   +1 more source

Comparative Study Parallel Join Algorithms for MapReduce environment

Труды Института системного программирования РАН, 2018
There are the following techniques that are used to analyze massive amounts of data: MapReduce paradigm, parallel DBMSs, column-wise store, and various combinations of these approaches. We focus in a MapReduce environment.
A. Yu. Pigul
doaj   +1 more source

On the Design of Resilient Multicloud MapReduce [PDF]

IEEE Cloud Computing, 2017
MapReduce is a popular distributed data-processing system for analyzing big data in cloud environments. This platform is often used for critical data processing, e.g., in the context of scientific or financial simulation. Unfortunately, there is accumulating evidence of severe problems - including arbitrary faults and cloud outages - affecting the ...
Costa, Pedro A. R. S., Ramos, Fernando M. V., Correia, Miguel   +2 more
openaire   +3 more sources

Adaptive MapReduce Similarity Joins [PDF]

Proceedings of the 5th ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond, 2018
Similarity joins are a fundamental database operation. Given data sets S and R, the goal of a similarity join is to find all points x in S and y in R with distance at most r. Recent research has investigated how locality-sensitive hashing (LSH) can be used for similarity join, and in particular two recent lines of work have made exciting progress on ...
McCauley, Samuel, Silvestri, Francesco
openaire   +5 more sources