Publication | Closed Access
Distributed query processing optimization objectives
17
Citations
8
References
2003
Year
Unknown Venue
Cluster ComputingCost MeasuresEngineeringDatabase BenchmarkingInformation RetrievalData ScienceManagementPerformance TuningBig DataParallel ComputingData ManagementParallel DatabaseNetwork FlowsDistributed SystemsComputer ScienceDistributed Query ProcessingParallel Data ManagementQuery OptimizationPerformance ScalabilityRelational QueriesDollar CostOptimization ObjectivesResource Optimization
The authors examine objectives, or measures of cost, which can be used in optimizing queries in a distributed database (DDB). They include the delay and dollar cost due to the network data transfer, CPU processing or a combination of both, and cost measures in terms of the size of partial results. These measures are used in distributed query processing modeling on a testbed of queries to examine the effect of choosing one measure of cost in optimizing strategies on their cost expressed in other measures and the cost of strategies generated by a two-phased approach. Results indicate that best strategies are generated when optimization considers cost measured in terms of both CPU processing and a network data transfer. They also confirm that the two-phased optimization yields close to optimal strategies.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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