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POP/FED: Progressive Query Optimization for Federated Queries in DB2

Summary: POP/FED extends progressive optimization for federated queries addressing stale statistics that mislead plan choice. Enables risk-controlled iterative reoptimizations with redundancy elimination and eager statistics; demonstrated on DB2 with POPMonitor. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9402
Venue
VLDB
Year
2006
Pagerank
5.2360942e-05
Overall Rank
6,049 | 57.92%
DOI
-

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

Rank Cited Paper Year Venue Pagerank
182 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00036962631
650 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.00018659177
1,059 Answering Complex SQL Queries Using Automatic Summary Tables 2000 SIGMOD 0.00014382575
5,025 Automated Statistics Collection in DB2 UDB 2004 VLDB 5.7533741e-05
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