2014 · 37 citations · 38 references
ComputingComputer ScienceComputer SystemsDatabasesFault-tolerant ComputingFault-tolerant SystemsDatabase ManagementQuery ManagementQuery OptimizationQuery ProcessingQuery ExecutionSkew Mitigation
As the size and complexity of analytic data processing systems continue to grow, the effort required to mitigate faults and performance skew has also risen. However, in some environments we have encountered, users prefer to continue query execution even in the presence of failures (e.g., the unavailability of certain data sources), and receive a "partial" answer to their query. We explore ways to characterize and classify these partial results, and describe an analytical framework that allows the system to perform coarse to fine-grained analysis to determine the semantics of a partial result. We propose that if the system is equipped with such a framework, in some cases it is better to return and explain partial results than to attempt to avoid them.
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