Data Lake Query Processing
Data Lake Query Processing is a computational framework that enables the direct execution of analytical queries over heterogeneous, schema-on-read data stored in a data lake, distinguishing itself from traditional database query processing by supporting schema flexibility, data variety, and on-demand parsing at query time.
26
Publications
1.1K
Citations
112
Authors
49
Institutions
Publications per year
2017–2026
21
Parents
26
Rihan Hai, Sandra Geisler, Christoph Quix · 2016 · 211 citations
Finding Related Tables in Data Lakes for Interactive Data Science
Yi Zhang, Zachary G. Ives · 2020 · 94 citations · Full text
Personal Data Lake with Data Gravity Pull
Coral Walker, Hassan Alrehamy · 2015 · 89 citations
Amin Beheshti, Boualem Benatallah, Reza Nouri et al. · Proceedings of the VLDB Endowment · 2018 · 87 citations
1–5 of 26
112
2
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 112
49

UNSW Sydney
Sydney, Australia
2 h-index
9 publications
711 citations
RWTH Aachen University
Aachen, Germany
2 h-index
3 publications
443 citations
University of Bonn
Bonn, Germany
2 h-index
6 publications
90 citations
Fraunhofer Institute for Intelligent Analysis and Information Systems
Sankt Augustin, Germany
2 h-index
2 publications
30 citations

Silesian University of Technology
Gliwice, Poland
2 h-index
5 publications
184 citations
Cardiff University
Cardiff, United Kingdom
2 h-index
4 publications
202 citations

University of Rostock
Rostock, Germany
1 h-index
1 publications
16 citations
Microsoft (United States)
Redmond, United States
1 h-index
7 publications
140 citations
1–8 of 49
PVLDB · 6 publications · 200 citations
6
h-index
TOG · 1 publications · 13 citations
1
h-index
Conference · 1 publications · 33 citations
1
h-index
1 publications · 20 citations
1
h-index
Conference · 1 publications · 20 citations
1
h-index
1–5