Results 71 to 80 of about 41,447 (233)
Task failure resilience technique for improving the performance of MapReduce in Hadoop
ETRI Journal, 2020 MapReduce is a framework that can process huge datasets in parallel and distributed computing environments. However, a single machine failure during the runtime of MapReduce tasks can increase completion time by 50%.
Kavitha C, Anita X
doaj +1 more source
Empirical Analysis of Recent Advances, Characteristics and Challenges of Big Data [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2019 Here in this study, we provide an empirical analysis of recent advances, characteristic and challenges of big data. Initially, we acquaint the readers with the general background, history, and characteristics of big data including volume, velocity, value
Burhanullah Khattak +5 more
doaj +1 more source
Big data technologies in e-learning
Открытое образование (Москва), 2018 Recently, e-learning around the world is rapidly developing, and the main problem is to provide the students with quality educational information on time.
Gyulara A. Mamedova +2 more
doaj +1 more source
Slicing and Dictionaries: A New Approach to Medical Big Data
iMetaMed, Volume 1, Issue 1, September 2025.We present SliceDB, a dual‐dimensional data partitioning framework that optimizes healthcare data access through strategic row‐wise and column‐wise slicing coupled with semantic dictionaries, enabling efficient querying of massive clinical datasets on standard computing resources without specialized database expertise.
Jing Zhang +3 more
wiley +1 more source
Research on Advanced Streaming Processing on Apache Spark
International Journal of Industrial Engineering and Production Research, 2021 The Today’s digital world computations are tremendously difficult and always demands for essential requirements to significantly process and store enormous size of datasets for wide variety of applications.
A.K.V.K Sasikanthr +4 more
doaj
MOON: MapReduce On Opportunistic eNvironments [PDF]
, 2009 —MapReduce offers a flexible programming model for processing and generating large data sets on dedicated resources, where only a small fraction of such resources are every unavailable at any given time.
Archuleta, Jeremy +5 more
core +1 more source
On data skewness, stragglers, and MapReduce progress indicators
, 2015 We tackle the problem of predicting the performance of MapReduce applications, designing accurate progress indicators that keep programmers informed on the percentage of completed computation time during the execution of a job.
Chambers J. M. +7 more
core +1 more source
Accounting &Finance, Volume 65, Issue 3, Page 2649-2664, September 2025.ABSTRACT Using survey research, we investigate accountants' self‐rated knowledge of a variety of digital technologies (DTs). We find that accountants' self‐rated knowledge of established DTs is almost in line with IES2 requirements, but their self‐rated knowledge of emerging DTs is significantly below IES2 requirements. Of greater concern, we find that
Richard Busulwa +3 more
wiley +1 more source
MapReduce is Good Enough? If All You Have is a Hammer, Throw Away Everything That's Not a Nail! [PDF]
, 2012 Hadoop is currently the large-scale data analysis "hammer" of choice, but there exist classes of algorithms that aren't "nails", in the sense that they are not particularly amenable to the MapReduce programming model.
Lin, Jimmy
core +1 more source
OS-Assisted Task Preemption for Hadoop
, 2014 This work introduces a new task preemption primitive for Hadoop, that allows tasks to be suspended and resumed exploiting existing memory management mechanisms readily available in modern operating systems. Our technique fills the gap that exists between
Dell'Amico, Matteo +2 more
core +1 more source