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arXiv · 2010.08694

Aggregated Deletion Propagation for Counting Conjunctive Query Answers

Xiao Hu·Shouzhuo Sun·Shweta Patwa·Debmalya Panigrahi·Sudeepa Roy
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Abstract

We investigate the computational complexity of minimizing the source side-effect in order to remove a given number of tuples from the output of a conjunctive query. This is a variant of the well-studied {\em deletion propagation} problem, the difference being that we are interested in removing the smallest subset of input tuples to remove a given number of output tuples} while deletion propagation focuses on removing a specific output tuple. We call this the {\em Aggregated Deletion Propagation} problem. We completely characterize the poly-time solvability of this problem for arbitrary conjunctive queries without self-joins. This includes a poly-time algorithm to decide solvability, as well as an exact structural characterization of NP-hard instances. We also provide a practical algorithm for this problem (a heuristic for NP-hard instances) and evaluate its experimental performance on real and synthetic datasets.

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Xiao Hu, Shouzhuo Sun, Shweta Patwa, Debmalya Panigrahi, Sudeepa Roy. 2020-10-17. Aggregated Deletion Propagation for Counting Conjunctive Query Answers. https://arxiv.org/abs/2010.08694

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