PANDA: Query Evaluation in Submodular Width

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].