Database Paper Browser

Back to papers

The Case for Deep Query Optimisation

Summary: Proposes Deep Query Optimisation (DQO): decompose physical operators into fine-grained subcomponents to enumerate sub-plans offline/at query time, enabling deeper plan search than shallow QO. Defines MAVs and the Algorithmic View Selection Problem (AVSP), evaluates DQO on hash-based grouping, and sketches a research agenda. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
366
Venue
CIDR
Year
2020
Pagerank
4.7201897e-05
Overall Rank
7,470 | 48.04%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 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