Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sheriffo Ceesay"'
Autor:
Sheriffo Ceesay, 薛瑞夫
101
Moving Towards Pure ANSI SQL in NoSQL The main focus of this master’s thesis is to narrow down the user friendly gap between the newly more distributed data processing platforms (HBase,Cassandra, MapReduce e.t.c) and the traditional less d
Moving Towards Pure ANSI SQL in NoSQL The main focus of this master’s thesis is to narrow down the user friendly gap between the newly more distributed data processing platforms (HBase,Cassandra, MapReduce e.t.c) and the traditional less d
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/94005727847322522131
Publikováno v:
Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f7643484ee688039994aa1d89f502ab
https://doi.org/10.1145/3492323.3495624
https://doi.org/10.1145/3492323.3495624
Publikováno v:
2021 IEEE/ACM 8th International Conference on Big Data Computing, Applications and Technologies (BDCAT '21).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::432780f98ebb3facd7d82a2645d55fbc
https://doi.org/10.1145/3492324.3494159
https://doi.org/10.1145/3492324.3494159
Publikováno v:
IEEE BigData
Funding: ABC project (Adaptive Brokerage for the Cloud) funded by UK EPSRC EP/R010528/1. Modern cluster management systems have been evolving to cope with running and managing diverse cloud applications on heterogeneous computing clusters. Consequent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4244c8871168a0189e81278451e4c5e8
https://doi.org/10.1109/bigdata50022.2020.9377802
https://doi.org/10.1109/bigdata50022.2020.9377802
Publikováno v:
CloudCom
Understanding and predicting the performance of big data applications running in the cloud or on-premises could help minimise the overall cost of operations and provide opportunities in efforts to identify performance bottlenecks. The complexity of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c62641596c0bad456723d974d06bc6c8
Publikováno v:
IEEE BigData
The recent boom of big data, coupled with the challenges of its processing and storage gave rise to the development of distributed data processing and storage paradigms like MapReduce, Spark, and NoSQL databases. With the advent of cloud computing, p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2e7ebb6ad5e76a2cc52808a40f4941d
Autor:
Akgün, Özgür, Hariri, Youssef Al, Alabidi, Laila, Andrei, Oana, Belikov, Evgenij, Bernard, Elvis, Sheriffo Ceesay, Chantler, Mike, Chen-Burger, Jessica, Cram, Laura, Crescimanna, Vincenzo, Dearden, Monica, Falconer, Ruth, Muyao Fan, Azimeh Gharavi, Gkatzia, Dimitra, Gray, Alasdair, Henderson, Tristan, Higgs, Matthew, Hill, Robin, Lawson, Alistair, Hans-Wolfgang Loidl, Lones, Michael, Maidarti, Mila, Martin, Tom, Methven, Thomas, Moshfeghi, Yashar, Ntarmos, Nikos, Padilla, Stefano, Pan, Jeff, Pernet, Cyril, Rosales, Andrea, Sanusi, Usman, Simpson, Ian, Zervogianni, Vanessa, Yajie Zhu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc7682169d9416678380d6f92fc979dc