Identifying Robust Plans Through Plan Diagram Reduction
Identifying Robust Plans through Plan Diagram Reduction ∗ Harish D. Pooja N. Darera Jayant R. Haritsa Database Systems Lab, SERC/CSA Indian Institute of Science, Bangalore 560012, INDIA ABSTRACT tary and conceptually different approach, which we consider in this Estimates of predicate selectivities by database query optimizers paper, is to identify robust plans that are relatively less sensitive to often differ significantly from those actually encountered during such selectivity errors. In a nutshell, to “aim for resistance, rather query execution, leading to poor plan choices and inflated response than cure”, by identifying plans that provide comparatively good times. In this paper, we investigate mitigating this problem by performance over large regions of the selectivity space. Such plan replacing selectivity error-sensitive plan choices with alternative choices are especially important for industrial workloads where plans that provide robust performance. Our approach is based on global stability is as much a concern as local optimality [18]. the recent observation that even the complex and dense “plan di- Over the last decade, a variety of strategies have been proposed agrams” associated with industrial-strength optimizers can be ef- to identify robust plans, including the Least Expected Cost [6, 8], ficiently reduced to “anorexic” equivalents featuring only a few Robust Cardinality Estimation [2] and Rio [3, 4] approaches. These plans, without materially impacting query processing quality. techniques provide novel and elegant formulations (summarized in Extensive experimentation with a rich set of TPC-H and TPC- Section 6), but have to contend with the following issues: DS-based query templates in a variety of database environments Firstly, they are intrusive requiring, to varying degrees, modifi- indicate that plan diagram reduction typically retains plans that are cations to the optimizer engine.
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