Aggregation Processing

Aggregation Processing is a query processing operation that computes summary values over grouped data sets by applying aggregate functions such as sum, count, average, minimum, or maximum to derive scalar results from collections of input tuples.

57

Publications

3.8K

Citations

143

Authors

60

Institutions

Publications per year

2017–2026

10

Variants

Aggregate Processing

Authors

143

  1. PJ
    Peter J. Haas

    IBM Research - Almaden, United States

    3 publications · 1.2K citations

    3

    h-index

  2. JM
    Joseph M. Hellerstein

    University of California, Berkeley, United States

    2 publications · 1.2K citations

    2

    h-index

  3. GÖ
    Gültekin Özsoyoğlu

    Case Western Reserve University, United States

    2 publications · 175 citations

    2

    h-index

  4. CG
    César Galindo-Legaria

    Microsoft (United States), United States

    2 publications · 121 citations

    2

    h-index

  5. ID
    Ivan Dychka

    National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine

    2 publications · 26 citations

    2

    h-index

1–5 of 143

Venues

  1. ACM SIGMOD Record

    4 publications · 379 citations

    4

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 3 publications · 111 citations

    3

    h-index

  3. European Journal of Operational Research

    1 publications · 48 citations

    1

    h-index

  4. International Conference on Data Engineering

    Conference · 1 publications · 20 citations

    1

    h-index

  5. Theoretical Computer Science

    1 publications · 144 citations

    1

    h-index

1–5