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)
Incoming Non-self Citations Over Time
Authors
- 1. Bailu Ding (Microsoft)
- 2. Surajit Chaudhuri (Microsoft)
- 3. Vivek Narasayya (Microsoft)
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}
}
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