Parallel Query Processing

Parallel Query Processing is a method in database systems that enables the simultaneous execution of query operations across multiple processors or nodes to improve performance and scalability by dividing and distributing query tasks.

501

Publications

25.8K

Citations

1.3K

Authors

367

Institutions

Publications per year

2017–2026

71

Authors

1.3K

  1. DJ
    David J. DeWitt

    University of Wisconsin–Madison, United States

    18 publications · 1.8K citations

    15

    h-index

  2. PV
    Patrick Valduriez

    Institut national de recherche en sciences et technologies du numérique, France

    13 publications · 823 citations

    12

    h-index

  3. GG
    Goetz Graefe

    Hewlett-Packard (United States), United States

    10 publications · 1.4K citations

    10

    h-index

  4. DS
    Dan Suciu

    University of Washington, United States

    10 publications · 648 citations

    10

    h-index

  5. PK
    Paraschos Koutris

    University of Washington, United States

    9 publications · 575 citations

    9

    h-index

1–5 of 1.3K

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 42 publications · 2.4K citations

    27

    h-index

  2. ACM SIGMOD Record

    19 publications · 693 citations

    14

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 14 publications · 1.5K citations

    12

    h-index

  4. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 11 publications · 217 citations

    11

    h-index

  5. ACM Transactions on Database Systems

    TODS · 10 publications · 545 citations

    10

    h-index

1–5