Concepedia

Join Method Selection

Join Method Selection is a query optimization technique that determines the most efficient algorithm for combining relational data during join operations, distinguished by its focus on evaluating and choosing among alternative execution strategies such as nested loop, hash, or sort-merge joins based on cost metrics and data characteristics.

4

Publications

245

Citations

8

Authors

2

Institutions

Publications per year

2017–2026

1

Parents

Publications

4

1–4 of 4

Authors

8

  1. MJ
    Michael J. Carey

    University of Wisconsin–Madison, United States

    2 publications · 197 citations

    2

    h-index

  2. TJ
    Tobin J. Lehman

    IBM Research - Almaden, United States

    2 publications · 197 citations

    2

    h-index

  3. SW
    Siqi Wei

    Southwest University, China

    1 publications · 20 citations

    1

    h-index

  4. YZ
    Yi Zhao

    Guangdong Medical College, China

    1 publications · 20 citations

    1

    h-index

  5. JD
    Jaeyoung Do

    Microsoft (United States), United States

    1 publications · 28 citations

    1

    h-index

1–5 of 8

Institutions

2

  1. University of Wisconsin–Madison

    Madison, United States

    3 h-index

    6 publications

    450 citations

  2. Nanjing University of Science and Technology

    Nanjing, China

    1 h-index

    4 publications

    80 citations

1–2 of 2

Venues

  1. Library & Information Science Research

    1 publications · 20 citations

    1

    h-index

  2. ACM SIGMOD Record

    1 publications · 106 citations

    1

    h-index

1–2