Trade-Offs In Static And Dynamic Evaluation Of Hierarchical Queries
PODS'20: PROCEEDINGS OF THE 39TH ACM SIGMOD-SIGACT-SIGAI SYMPOSIUM ON PRINCIPLES OF DATABASE SYSTEMS(2020)
摘要
We investigate trade-offs in static and dynamic evaluation of hierarchical queries with arbitrary free variables. In the static setting, the trade-off is between the time to partially compute the query result and the delay needed to enumerate its tuples. In the dynamic setting, we additionally consider the time needed to update the query result under single-tuple inserts or deletes to the database.Our approach observes the degree of values in the database and uses different computation and maintenance strategies for high-degree (heavy) and low-degree (light) values. For the latter it partially computes the result, while for the former it computes enough information to allow for on-the-fly enumeration.The main result of this work defines the preprocessing time, the update time, and the enumeration delay as functions of the light/heavy threshold. By conveniently choosing this threshold, our approach recovers a number of prior results when restricted to hierarchical queries.For a restricted class of hierarchical queries, our approach can achieve worst-case optimal update time and enumeration delay conditioned on the Online Matrix-Vector Multiplication Conjecture.
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关键词
adaptive query evaluation,hierarchical queries,incremental view maintenance,sublinear enumeration delay,sublinear update time
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