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Progressive Optimization in a Shared-Nothing Parallel Database

Summary: Progressive optimization extends to shared-nothing parallel DBs; cardinality monitoring triggers re-optimization. Key contributions: voting-based triggers, MV reuse, and parallel checkpointing with fast inter-node communication; up to 22x OLAP speedups. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3902
Venue
SIGMOD
Year
2007
Pagerank
4.5717277e-05
Overall Rank
8,165 | 43.20%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
4,261 Parallelizing Query Optimization 2008 VLDB 6.31244e-05
5,014 Dynamically Optimizing Queries over Large Scale Data Platforms 2014 SIGMOD 5.7586174e-05
7,126 Debunking the Myth of Join Ordering: Toward Robust SQL Analytics 2025 SIGMOD 4.8232367e-05
7,465 Non-Invasive Progressive Optimization for In-Memory Databases 2016 VLDB 4.7228742e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

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