Heuristic Query Optimization

Heuristic Query Optimization is a query optimization strategy that applies rule-based heuristics to transform relational algebra expressions into equivalent but more efficient forms by pruning the search space of possible execution plans according to predefined cost-saving patterns.

54

Publications

8.3K

Citations

131

Authors

59

Institutions

Publications per year

2017–2026

4

Variants

Rule-based Query Optimization

Authors

131

  1. SS
    S. Sudarshan

    Indian Institute of Technology Bombay, India

    5 publications · 164 citations

    5

    h-index

  2. TU
    Tolga Urhan

    University of Maryland, College Park, United States

    3 publications · 309 citations

    3

    h-index

  3. KS
    Kyuseok Shim

    Korea Advanced Institute of Science and Technology, South Korea

    2 publications · 148 citations

    2

    h-index

  4. PJ
    Peter J. Stuckey

    The University of Melbourne, Australia

    2 publications · 117 citations

    2

    h-index

  5. KA
    Kenneth A. Ross

    Columbia University, United States

    2 publications · 108 citations

    2

    h-index

1–5 of 131

Venues

  1. ACM SIGMOD Record

    6 publications · 1.7K citations

    6

    h-index

  2. ACM Transactions on Database Systems

    TODS · 2 publications · 106 citations

    2

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 79 citations

    2

    h-index

  4. Information Systems

    2 publications · 34 citations

    2

    h-index

  5. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 129 citations

    2

    h-index

1–5