Eddies: continuously adaptive query processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Rate-based query optimization for streaming information sources
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Adaptive Query Processing: A Survey
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
Conquest: CONcurrent QUEries over Space and Time
ISD '99 Selected Papers from the International Workshop on Integrated Spatial Databases, Digital Inages and GIS
Dynamic plan migration for continuous queries over data streams
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Toward a progress indicator for database queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Self-monitoring query execution for adaptive query processing
Data & Knowledge Engineering
Increasing the Accuracy and Coverage of SQL Progress Indicators
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Adaptive workload allocation in query processing in autonomous heterogeneous environments
Distributed and Parallel Databases
A Vision for Next Generation Query Processors and an Associated Research Agenda
Globe '09 Proceedings of the 2nd International Conference on Data Management in Grid and Peer-to-Peer Systems
Efficient load balancing in partitioned queries under random perturbations
ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special section on formal methods in pervasive computing, pervasive adaptation, and self-adaptive systems: Models and algorithms
Towards window stream queries over continuous phenomena
Proceedings of the 4th ACM SIGSPATIAL International Workshop on GeoStreaming
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Very long-running queries in database systems are not uncommon in non-traditional application domains such as image processing or data warehousing analysis. Query optimization, therefore, is important. However, estimates of the query characteristics before query exe- cution are usually inaccurate. Further, system configuration and resource availability may change during long evaluation period. As a result, queries are often evaluated with sub-optimal plan configurations. To remedy this situation, we have designed a novel approach to re-optimize suboptimal query plan configurations on- the- y with Conquest | an extensible and distributed query processing system. A dynamic optimizer considers reconfiguration cost as well as execution cost in determining the best query plan configuration. Experimental results are presented.