PANDA: Query Evaluation in Submodular Width
CoRR(2024)
摘要
In recent years, several information-theoretic upper bounds have been
introduced on the output size and evaluation cost of database join queries.
These bounds vary in their power depending on both the type of statistics on
input relations and the query plans that they support. This motivated the
search for algorithms that can compute the output of a join query in times that
are bounded by the corresponding information-theoretic bounds. In this paper,
we describe "PANDA", an algorithm that takes a Shannon-inequality that
underlies the bound, and translates each proof step into an algorithmic step
corresponding to some database operation. PANDA computes a full join query in
time given by the largest output size, and computes a Boolean query in time
given by the submodular width. It represents a significant simplification of
the original version in [ANS17].
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