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

Authors

112

  1. SA
    Sören Auer

    University of Bonn, Germany

    2 publications · 30 citations

    2

    h-index

  2. CW
    Coral Walker

    Cardiff University, United Kingdom

    2 publications · 101 citations

    2

    h-index

  3. BB
    Boualem Benatallah

    UNSW Sydney, Australia

    2 publications · 162 citations

    2

    h-index

  4. DM
    Dariusz Mrozek

    Silesian University of Technology, Poland

    2 publications · 68 citations

    2

    h-index

  5. CQ
    Christoph Quix

    RWTH Aachen University, Germany

    2 publications · 232 citations

    2

    h-index

1–5 of 112

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 6 publications · 200 citations

    6

    h-index

  2. ACM Transactions on Graphics

    TOG · 1 publications · 13 citations

    1

    h-index

  3. 1

    h-index

  4. IEEE Access

    1 publications · 20 citations

    1

    h-index

  5. International Conference on Management of Data

    Conference · 1 publications · 20 citations

    1

    h-index

1–5