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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
3964
Venue
SIGMOD
Year
2007
Pagerank
5.4949524e-05
Overall Rank
8,064 | 44.68%
DOI
10.1145/1247480.1247569

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{han_sigmod07,
        title = {{Progressive Optimization in a Shared-Nothing Parallel Database}},
        author = {Han, Wook-Shin and Ng, Jack and Markl, Volker and Kache, Holger and Kandil, Mokhtar},
        series = {{SIGMOD} '07},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1247480.1247569},
        url = {https://dl.acm.org/doi/10.1145/1247480.1247569},
        year = {2007}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
3,726 Parallelizing Query Optimization 2008 VLDB 7.1697834e-05
4,481 Dynamically Optimizing Queries over Large Scale Data Platforms 2014 SIGMOD 6.6754521e-05
5,529 Debunking the Myth of Join Ordering: Toward Robust SQL Analytics 2025 SIGMOD 6.18591e-05
7,366 Non-Invasive Progressive Optimization for In-Memory Databases 2016 VLDB 5.6322753e-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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