Approximate Aggregate Queries Under Additive Inequalities
Approximate Aggregate Queries Under Additive Inequalities
复制标题
加性不等式下的近似聚合查询
DOI:
10.1137/1.9781611976489.7
复制
发表时间:
2021
期刊:
影响因子:
--
通讯作者:
Samadian, A.
中科院分区:
文献类型:
--
作者:
Abo-Khamis, M.;Im, S.;Moseley, B.;Pruhs, K.;Samadian, A.
We consider the problem of evaluating certain types of functional aggregation queries on relational data subject to additive inequalities. Such aggregation queries, with a smallish number of additive inequalities, arise naturally/commonly in many applications, particularly in learning applications. We give a relatively complete categorization of the computational complexity of such problems. We first show that the problem is NP-hard, even in the case of one additive inequality. Thus we turn to approximating the query. Our main result is an efficient algorithm for approximating, with arbitrarily small relative error, many natural aggregation queries with one additive inequality. We give examples of natural queries that can be efficiently solved using this algorithm. In contrast, we show that the situation with two additive inequalities is quite different, by showing that it is NP-hard to evaluate simple aggregation queries, with two additive inequalities, with any bounded relative error.
DOI:
--
发表时间:
2017
期刊:
International Conference on Database Theory
影响因子:
--
作者:
Mahmoud Abo Khamis;H. Ngo;Dan Olteanu;Dan Suciu
通讯作者:
Dan Suciu
DOI:
--
发表时间:
2019-01
期刊:
--
影响因子:
--
作者:
A. Burkov
通讯作者:
A. Burkov
影响因子:
0.5
作者:
Paraschos Koutris;Tova Milo;Sudeepa Roy;Dan Suciu
通讯作者:
Dan Suciu