Publication | Closed Access
Parallelism and its price
23
Citations
16
References
1995
Year
Cluster ComputingEngineeringDatabase ScalabilityMarket DesignParallel AlgorithmsDatabase BenchmarkingData ScienceParallel Complexity TheoryManagementCommunication CostsParallel ComputingData ManagementParallel DatabaseDistributed SystemsComputer ScienceDistributed Query ProcessingParallel ExecutionParallel Data ManagementRelational QueriesParallel ProcessingParallel Performance EvaluationParallel ProgrammingNonstop Sql/mpData-level Parallelism
We describe the use of parallel execution techniques and measure the price of parallel execution in NonStop SQL/MP, a commercial parallel database system from Tandem Computers. Non-Stop SQL uses intra-operator parallelism to parallelize joins, groupings and scans. Parallel execution consists of starting up several processes and communicating data between them. Our measurements show (a) Startup costs are negligible when processes are reused rather than created afresh (b) Communication costs are significant — they may exceed the costs of operators such as scan, grouping or join. We also show two counter-examples to the common intuition that parallel execution reduces response time at the expense of increased work — parallel execution may reduce work or may increase response time depending on communication costs.
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