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pro vyhledávání: '"John Poelman"'
Autor:
John Poelman, Emily May Curtin
Publikováno v:
Encyclopedia of Big Data Technologies ISBN: 9783319639628
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::718c9dc3a41ee96b53bc08a007a88af3
https://doi.org/10.1007/978-3-319-63962-8_300-1
https://doi.org/10.1007/978-3-319-63962-8_300-1
Autor:
Chinmayi Narasimhadevara, Tilmann Rabl, Meikel Poess, Seetha Lakshmi, John Poelman, Patrick Nguyen, Paul Cao, Bhaskar Gowda
Publikováno v:
Performance Evaluation and Benchmarking. Traditional-Big Data-Interest of Things
Performance Evaluation and Benchmarking. Traditional-Big Data-Interest of Things ISBN: 9783319543338
TPCTC
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Performance Evaluation and Benchmarking. Traditional-Big Data-Interest of Things
Performance Evaluation and Benchmarking. Traditional-Big Data-Interest of Things ISBN: 9783319543338
TPCTC
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Performance Evaluation and Benchmarking. Traditional-Big Data-Interest of Things
With the increased adoption of Hadoop-based big data systems for the analysis of large volume and variety of data, an effective and common benchmark for big data deployments is needed. There have been a number of proposals from industry and academia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61e82a4e408767774c343b6c89a570a8
Autor:
Tilmann Rabl, Todor Ivanov, Anna Queralt, John Poelman, Jeffrey Buell, Meikel Poess, Nicolas Poggi
Publikováno v:
Performance Evaluation and Benchmarking: Traditional to Big Data to Internet of Things ISBN: 9783319314082
TPCTC
TPCTC
The field of Big Data and related technologies is rapidly evolving. Consequently, many benchmarks are emerging, driven by academia and industry alike. As these benchmarks are emphasizing different aspects of Big Data and, in many cases, covering diff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c532e24b8664b89999bc4d4dd987557e
https://doi.org/10.1007/978-3-319-31409-9_9
https://doi.org/10.1007/978-3-319-31409-9_9
Autor:
Thomas O. Bodner, Alexander Alexandrov, Berni Schiefer, Volker Markl, John Poelman, Stephan Ewen
Publikováno v:
Proceedings of the 1st Workshop on Architectures and Systems for Big Data.
The need for efficient data generation for the purposes of testing and benchmarking newly developed massively-parallel data processing systems has increased with the emergence of Big Data problems. As synthetic data model specifications evolve over t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76f2f7e2fd81332244dcbd7e23de9ed1
https://doi.org/10.1145/2377978.2377983
https://doi.org/10.1145/2377978.2377983