DBScholar

Back to papers

Bitvector-aware Query Optimization for Decision Support Queries

Summary: Bitvector filtering speeds decision-support queries; naive optimization explodes the plan space, but for star/snowflake/right-deep queries the optimal plan comes from a linear set. A linear-candidate join-order algorithm, implemented as a DBMS-X transformation, yields 22–64% CPU savings overall and up to 100× on some queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6046
Venue
SIGMOD
Year
2020
Pagerank
6.4803828e-05
Overall Rank
4,849 | 66.74%
DOI
10.1145/3318464.3389769

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{ding_sigmod20,
        title = {{Bitvector-aware Query Optimization for Decision Support Queries}},
        author = {Ding, Bailu and Chaudhuri, Surajit and Narasayya, Vivek},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3389769},
        url = {https://dl.acm.org/doi/10.1145/3318464.3389769},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 12 of 12 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers