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Benchmarking Query Execution Robustness

机译:基准化查询执行的鲁棒性

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Benchmarks that focus on running queries on a well-tuned database system ignore a long-standing problem: adverse runtime conditions can cause database system performance to vary widely and unexpectedly. When the query execution engine does not exhibit resilience to these adverse conditions, addressing the resultant performance problems can contribute significantly to the total cost of ownership for a database system in over-provisioning, lost efficiency, and increased human administrative costs. For example, focused human effort may be needed to manually invoke workload management actions or fine-tune the optimization of specific queries.rnWe believe a benchmark is needed to measure query execution robustness, that is, how adverse or unexpected conditions impact the performance of a database system. We offer a preliminary analysis of barriers to query execution robustness and propose some metrics for quantifying the impact of those barriers. We present and analyze results from preliminary tests on four real database systems and discuss how these results could be used to increase the robustness of query processing in each case. Finally, we outline how our efforts could be expanded into a benchmark to quantify query execution robustness.
机译:专注于在经过良好调整的数据库系统上运行查询的基准忽略了一个长期存在的问题:不利的运行时条件可能导致数据库系统性能发生很大的变化,且出乎意料。当查询执行引擎没有表现出对这些不利条件的适应力时,解决由此产生的性能问题可能会大大增加数据库系统的总体拥有成本,从而导致过度配置,效率降低和人工管理成本增加。例如,可能需要集中精力来手动调用工作负载管理操作或微调特定查询的优化。rn我们认为需要一个基准来衡量查询执行的健壮性,即不利或意外情况如何影响查询性能。数据库系统。我们对查询执行健壮性的障碍进行了初步分析,并提出了一些量化这些障碍影响的指标。我们介绍并分析了在四个真实数据库系统上进行的初步测试的结果,并讨论了在每种情况下如何使用这些结果来提高查询处理的鲁棒性。最后,我们概述了如何将我们的工作扩展到基准以量化查询执行的鲁棒性。

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