@inproceedings{dutt2017leveraging,
author = {Dutt, Anshuman and Narasayya, Vivek and Chaudhuri, Surajit},
title = {Leveraging Re-costing for Online Optimization of Parameterized Queries with Guarantees},
booktitle = {International Conference on Management of Data (SIGMOD)},
year = {2017},
month = {May},
abstract = {Parametric query optimization (PQO) deals with the problem of finding and reusing a relatively small number of plans that can achieve good plan quality across multiple instances of a parameterized query. An ideal solution to PQO would process query instances "online" and ensure (a) tight, bounded cost sub-optimality for each instance, (b) low optimization overheads, and (c) only a small number of plans need to be stored. Existing solutions to online PQO however, fall short on at least one of the above metrics. We propose a plan re-costing based approach that enables us to perform well on all three metrics. We empirically show the effectiveness of our technique on industry benchmark and real-world query workloads with our modified version of the Microsoft SQL Server query optimizer.},
publisher = {ACM},
url = {http://approjects.co.za/?big=en-us/research/publication/leveraging-re-costing-online-optimization-parameterized-queries-guarantees/},
edition = {International Conference on Management of Data (SIGMOD)},
}